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Ethics statement | The studies involving human participants were reviewed and approved by the institutional review board of Myongji Hospital (2021-05-009). The patients/participants provided their written informed consent to participate in this study. | PMC10361252 | ||
Author contributions | JJ | YJ and SYL conceived this study and wrote the draft. YJ, SYL, HH, JL MK, YC, SC, SL, and JJ collected and analyzed data. S-CP helped the data analysis. YJ and SYL revised the manuscript. All authors contributed to the articles and approved the submitted version. | PMC10361252 | |
Funding | DISEASE | This Study was supported by the Newhorizon grant of Myongji Hospital (2013-07-01) and by a fund from the Korea Centers for Disease Control and Prevention (2023-ER1003-00). | PMC10361252 | |
Conflict of interest | The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. | PMC10361252 | ||
Publisher’s note | All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | PMC10361252 | ||
Supplementary material | The Supplementary material for this article can be found online at: Click here for additional data file.Click here for additional data file. | PMC10361252 | ||
References | PMC10361252 | |||
1. Introduction | Background: The purpose of this study was to assess the effects of protein and carbohydrate supplementation, with and without creatine, on occupational performance in firefighters. Methods: Using a randomized, double-blind approach, thirty male firefighters (age: 34.4 ± 8.4 yrs., height: 1.82 ± 0.07 m; weight: 88.6 ± 12.5 kg; BF%: 17.2 ± 5.8%) were randomized to receive either (A.) 25 g of whey protein isolate + 25 g of carbohydrate powder (ProCarb group); or (B.) ProCarb + 5 g of creatine (Creatine group) in a double-blind fashion over a period of 21–26 days (depending on shift rotations) to evaluate the impact of supplementation on occupation-specific performance. At baseline and following supplementation, firefighters completed a battery of tests. These tests included an aerobic speed test on an air-braked cycle ergometer followed by the hose carry, body drag, stair climb, and Keiser sled hammer for time. Results: No significant differences in measures of performance were observed at baseline (Firefighters are viewed as tactical athletes due to the physically demanding nature of the occupation and the specialized activities they routinely complete. Firefighters repeatedly perform high-intensity functional tasks at varying intervals, and are often exposed to high-temperature environments and environmental hazards, which places a high degree of physiological and thermoregulatory strain on the body [A recent position stand outlined the importance of adequate energy and macronutrient intakes to meet the activity demands of tactical athletes [Creatine may be another nutrient of interest for tactical populations because of its well-supported ergogenic benefits and minimal reported side effects across the literature [Previous work has examined the effects of adding creatine to whey protein and carbohydrates on training adaptations in resistance-trained individuals with mixed findings [ | PMC10745745 | ||
2. Materials and Methods | PMC10745745 | |||
2.1. Study Design | In a randomized, parallel-group, double-blind fashion, active-duty firefighters were randomly assigned to ingest (A) whey protein isolate + carbohydrate (ProCarb Group); or (B) whey protein isolate + carbohydrate + creatine monohydrate (Creatine Group) for a 21–26-day supplementation period (the ClinicalTrials.gov Identifier is: NCT06172543). A CONSORT diagram is presented in | PMC10745745 | ||
2.2. Participants | musculoskeletal or neurological condition | Thirty active-duty male structural firefighters were enrolled (age: 34.4 ± 8.4 yrs., height: 1.82 ± 0.07 m; weight: 88.6 ± 12.5 kg; BF%: 17.2 ± 5.8%) in the current study. Inclusion criteria included being between the ages of 18–55 years of age and medically cleared for field duty. Exclusion criteria included a current musculoskeletal or neurological condition that would prohibit the completion of performance testing. A 4-week washout period was implemented for anyone who reported current use of supplemental protein and creatine. All participants signed an institutionally approved informed consent form in accordance with the University of Wisconsin La Crosse’s Institutional Review Board (Approved on: 2 June 2023; IRB# 23-KE-137) and Human Subject Research Guidelines. | PMC10745745 | |
2.3. Procedures | PMC10745745 | |||
2.3.1. Anthropometrics | During baseline testing, height and weight were recorded using a stadiometer and portable scale, followed by a body composition assessment using a portable multi-frequency bioelectrical impedance analyzer (H2ON, InBody Inc., Cerritos, CA, USA). | PMC10745745 | ||
2.3.2. Performance Testing | STRUCK | Participants then completed a maximal effort, 3.5 km time trial on an air-braked cycle ergometer (Assault Bike, Assault Fitness Products, Carlsbad, CA, USA). Firefighters were instructed to complete the time trial as fast as possible. Time to completion (s) was recorded. On a separate day (within 48 h of the time trial), firefighters completed a battery of occupation-specific firefighter tasks. These tasks included a hose carry, body drag, stair climb, and forcible entry (Keiser sled hammer) for time. For the hose carry, firefighters advanced a 30.48 m section of a charged 4.45 cm hose line over a distance of 30.5 m in a straight line before flowing water for 2 s. Rescue (body drag) consisted of firefighters being instructed to grasp a mannequin (mass 50 kg, height: 180 cm) underneath the shoulders using a “seatbelt” grip and dragging the mannequin 30.5 m backward. Stair climb consisted of climbing four flights of stairs and returning to the bottom as quickly as possible. In the forcible entry, firefighters struck a simulated forcible entry chopping device (Keiser FORCE Machine, Keiser Co., Fresno, CA, USA) using a 3.6 kg sledgehammer until completed. Thirty seconds of rest was provided between each task to allow for standardized time for set up and preparation. The total time to complete each task was recorded in addition to the total completion time for all tasks summed together. All testing was completed in non-protective gear attire and without a self-contained breathing apparatus. | PMC10745745 | |
2.3.3. Dietary Supplementation | Participants were assigned to ingest a single serving daily of either (A) a 25 g dose of whey protein isolate + 25 g dose of carbohydrate powder (ProCarb); or (B) a 25 g dose of whey protein isolate + 25 g dose of carbohydrate powder (+5 g dose of creatine monohydrate) (Creatine) for a ~24-day period (average supplementation duration was 23 ± 2 days; minimum days = 21, maximum days = 26). All supplements were provided to participants in powder form and were of similar texture, bitterness, appearance, and sweetness. All supplements were weighed and blinded by research personnel not involved in testing. The groups were instructed to ingest the supplements daily, within one hour after exercise on training days, and on non-training days first thing in the morning (immediately upon waking). The whey protein isolate and maltodextrin were provided by Argopur Dairy Cooperative (La Crosse, WI, USA) and the creatine was sourced from 1st Phorm, LLC (St. Louis, MO, USA). | PMC10745745 | ||
3. Statistical Analysis | EVENT | All analyses were completed using the Statistical Package for the Social Sciences (v26; SPSS Inc., Chicago, IL, USA). Primary outcome measures for this investigation were time to completion for the firefighter-specific tasks and time trial. A 2 × 2 mixed factorial (group × time) ANOVA with repeated measures on time was used to determine any statistically significant differences for time and group main effects and group × time interaction effects. All data are presented as means ± standard deviations. In the event of a significant interaction effect, we conducted a follow-up analysis by calculating delta values (“change scores”) between pre-and post-testing and performed an independent samples | PMC10745745 | |
4. Results | No significant differences in measures of performance were observed at baseline (Independent sample There was a main effect for time observed for the time trial ( | PMC10745745 | ||
5. Discussion | ±, irritation, gastrointestinal distress | ADVERSE EFFECTS, FIRE, FLUID RETENTION | The primary aim of the current study was to examine the effects of adding creatine to protein and carbohydrate supplementation over a period of 3 weeks on changes in occupational performance in firefighters. The study’s main findings were that providing a daily protein and carbohydrate supplement to the diet over a three week period improved select measures of occupational performance in firefighters. Specifically, improvements in completion times for rescue, stair climb, overall time to completion for all tasks, and time trial performance were observed post testing. Further, the addition of creatine led to greater improvements in time to completion for the rescue and forcible entry tasks, compared to protein and carbohydrate supplementation alone. This study is the first of its kind to report on the ergogenic benefits of providing firefighters with dietary ingredients purported to enhance occupational-specific performance outcomes.Because of the physical demands of their occupation, it is recommended that tactical populations adhere to specialized dietary recommendations designed to meet their activity levels and fitness-related training goals [The addition of creatine was found to further improve select measures of performance for the firefighters included in the current study. Several of the occupational tasks completed in the current study can be characterized as short-duration bouts of maximal effort. Specifically, average completion times for the tasks completed in the current study were 9–30 s in duration, with the exception of the time trial which lasted ~340 s in duration. We previously reported that this type of firefighter circuit elicits mean heart rate values of 86.8 ± 6.3% of age-predicted max heart rates, with peak values reaching 98.9 ± 5.6% of maximum heart rate [It is unknown why improvements in some performance parameters have been observed while others have reported null findings within the same population across the literature, including what was found in the current study. Variations in training age, physical fitness status, and familiarity with performance tasks may influence outcomes following creatine supplementation. Furthermore, despite the term tactical population being used to characterize military personnel, firefighters, police, and first responders, the heterogeneity of the individuals across these sub-groups, along with the differences in job activities or daily physical activity levels, may preclude the generalizability of findings across all tactical populations. Therefore, it is important for future research to isolate each sub-group to examine the efficacy of various dietary interventions on performance outcomes that are specific to that population and, subsequently, the occupational demands. Even within the fire service, there are well-known differences in the occupational demands of wildland versus structural firefighting because of the contrast in how fire suppression is handled, along with the environmental demands.Importantly, with the exception of an increase in body mass, which can commonly be attributed to increased fluid retention and increases in fat-free mass, none of the studies reported adverse effects, which is an important indication of the safety of creatine supplementation for this population. In the current study, two participants from the creatine group and one from the ProCarb group reported mild gastrointestinal distress during the supplementation period that resolved on its own, even with continuation of the assigned supplement. It is possible the artificial flavoring agents used in the manufacturing of the supplement caused mild irritation; however, it is difficult to definitively identify the primary causality. This study is not without limitations. For example, this study did not include a true control group in the current design. Additionally, due to the field-based nature of this study, there were no intramuscular measurements of metabolites, so changes in phosphocreatine and total creatine content were not assessed. Lastly, due to the varying schedules of the firefighters, a standardized diet and training program were not imposed throughout the duration of this study. Thus, future research involving firefighters should consider strategies to minimize the potentially confounding factors. | PMC10745745 |
6. Conclusions | The addition of supplemental protein and carbohydrates to the diet of career firefighters throughout a three-week period improves occupational performance in specific areas of high-intensity activities. Furthermore, the addition of creatine within the protein and carbohydrate supplementation leads to greater improvements in specific tests when compared to protein and carbohydrates alone. These findings provide preliminary evidence supporting the benefits of targeted dietary strategies for occupational performance benefits in firefighters. | PMC10745745 | ||
Author Contributions | Conceptualization, K.E., J.L., C.M.K., A.M. and A.R.J.; methodology, K.E., J.L., C.M.K., A.M. and A.R.J.; formal analysis, J.L. and A.R.J.; investigation, K.E., J.L., S.J.J., W.C.D., T.A., C.M.K., A.M. and A.R.J.; data curation, K.E., J.L., S.J.J., W.C.D., T.A., C.M.K., A.M. and A.R.J.; writing—original draft preparation, K.E., C.M., J.L. and A.R.J.; writing—review and editing, K.E., J.L., S.J.J., W.C.D., T.A., C.M.K., A.M. and A.R.J.; data curation, K.E., C.M., J.L., S.J.J., W.C.D., T.A., C.M.K., A.M. and A.R.J.; supervision, K.E., J.L. and A.R.J.; funding acquisition, K.E., J.L., W.C.D., C.M.K. and A.R.J. All authors have read and agreed to the published version of the manuscript. | PMC10745745 | ||
Institutional Review Board Statement | The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of The University of Wisconsin-La Crosse (Approved on 2 June 2023; IRB# 23-KE-137). | PMC10745745 | ||
Informed Consent Statement | Written informed consent was obtained from all subjects involved in the study. | PMC10745745 | ||
Data Availability Statement | Data are available upon request. | PMC10745745 | ||
Conflicts of Interest | A.R.J. and C.M.K. serve on the scientific advisory board for Alzchem. A.R.J. and C.M.K. have consulted with and received external funding from companies who sell certain dietary ingredients, and have received remuneration from companies for delivering scientific presentations at conferences. A.R.J. and C.M.K. also write for online and other media outlets on topics related to exercise and nutrition. The remaining authors declare no conflicts of interest. The companies had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. | PMC10745745 | ||
References | CONSORT diagram.Percent changes in individual occupational performance tasks. * Denotes significance at Changes in 3.5 km cycling time trial performance.Summary of time to completion for measures of occupational performance across each group.* Denotes significance at | PMC10745745 | ||
Introduction | stroke, Atrial Fibrillation, AF | ATRIAL FIBRILLATION, STROKE, RECRUITMENT, ATRIAL FIBRILLATION (AF) | Atrial fibrillation (AF) is associated with a fivefold increased risk of stroke. Oral anticoagulation reduces the risk of stroke, but AF is elusive. A machine learning algorithm (Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF)) developed to predict incident AF within 6 months using data in primary care electronic health records (EHRs) could be used to guide AF screening. The objectives of the FIND-AF pilot study are to determine yields of AF during ECG monitoring across AF risk estimates and establish rates of recruitment and protocol adherence in a remote AF screening pathway. | PMC10546147 |
Methods and analysis | SECONDARY, RECRUITMENT | The FIND-AF Pilot is an interventional, non-randomised, single-arm, open-label study that will recruit 1955 participants aged 30 years or older, without a history of AF and eligible for oral anticoagulation, identified as higher risk and lower risk by the FIND-AF risk score from their primary care EHRs, to a period of remote ECG monitoring with a Zenicor-ECG device. The primary outcome is AF diagnosis during ECG monitoring, and secondary outcomes include recruitment rates, withdrawal rates, adherence to ECG monitoring and prescription of oral anticoagulation to participants diagnosed with AF during ECG monitoring. | PMC10546147 | |
Ethics and dissemination | WEST | The study has ethical approval (the North West—Greater Manchester South Research Ethics Committee reference 23/NW/0180). Findings will be announced at relevant conferences and published in peer-reviewed journals in line with the Funder’s open access policy. | PMC10546147 | |
WHAT IS ALREADY KNOWN ON THIS TOPIC | stroke | STROKE, ATRIAL FIBRILLATION (AF) | Population screening for atrial fibrillation (AF) guided by age or stroke risk with ECG monitoring increases AF detection rates compared with routine care and is associated with increased prescription of oral anticoagulation. However, yields of newly detected AF are low, which limits clinical effectiveness and cost-effectiveness. | PMC10546147 |
WHAT THIS STUDY ADDS | Atrial Fibrillation | ATRIAL FIBRILLATION | The Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF) pilot study investigates the use of a machine learning AF risk prediction algorithm (FIND-AF) in UK primary care electronic health records (EHRs) to guide a remote AF screening pathway, and will provide data on the yield that can be achieved with ECG monitoring across risk estimates. | PMC10546147 |
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY | FIND-AF is applicable at scale in primary care EHRs. If the study demonstrates that higher predicted AF risk is associated with a high yield of AF detection on ECG monitoring, it has the potential to efficiently guide targeted early detection of AF in the community. | PMC10546147 | ||
Introduction | stroke, Atrial Fibrillation, cardiac arrhythmia | ATRIAL FIBRILLATION (AF), STROKE, RECRUITMENT, CARDIAC ARRHYTHMIA, ATRIAL FIBRILLATION | Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide and confers a fivefold increased risk of stroke.Systematic population screening for AF guided by age with or without the presence of additional stroke risk factors with a non-invasive ECG devices has been shown to be feasible, increase detection rates for AF compared with routine care, and increase initiation of oral anticoagulation. However, yields of new AF diagnosed are low at between 2.6% and 5.3%.A targeted screening approach towards a reliably identified subpopulation at higher risk of AF may be more effective and cost-effective. Guiding AF screening by predicted AF risk based on artificial intelligence analysis of ECGs in sinus rhythm has been demonstrated to improve yield of new AF,A previous randomised clinical trial (RCT) of intermittent non-invasive ECG monitoring compared with routine care for individuals identified as higher risk by an EHR-based risk prediction algorithm (PuLSE-AI) did not find a higher yield of AF detection from ECG monitoring.The Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF) machine learning algorithm was developed and validated in routinely collected EHRs from over two million UK patients for prediction of incident AF within the next 6 months. It demonstrates an area under the receiver operating characteristic (AUROC) of 0.824 (95% CI 0.814 to 0.834), with robust prediction performance across both sexes and different ethnic groups.FIND-AF was developed and validated in retrospective cohorts of patients where AF was diagnosed during routine care. The objectives of the FIND-AF pilot study are to determine yields of AF during non-invasive ECG monitoring across AF risk estimates and to establish recruitment and protocol adherence rates for a remote AF screening intervention. | PMC10546147 |
Methods and analysis | PMC10546147 | |||
Study design | This publication describes V2.0 of the FIND-AF pilot study protocol, dated 7 September 2023. The FIND-AF pilot study is an interventional, non-randomised, single-arm, open-label study in UK primary care. | PMC10546147 | ||
Study population | ATRIAL FLUTTER | The study will enrol 1955 participants aged ≥30 years with a primary care EHR at general practices in the National Institute of Health and Care Research (NIHR) Clinical Research Network Yorkshire and Humber region, who do not have known AF or atrial flutter, and are eligible for oral anticoagulation.Individuals aged ≥30 years are included because this age group were included in the development of the FIND-AF algorithm. | PMC10546147 | |
Inclusion and exclusion criteria | PMC10546147 | |||
Inclusion criteria | Age at enrolment ≥30 years.Men with CHA | PMC10546147 | ||
Exclusion criteria | atrial fibrillation | ATRIAL FIBRILLATION, ATRIAL FLUTTER | Known diagnosis of atrial fibrillation or atrial flutter.Currently receiving anticoagulation.On the palliative care register.Unable to give written informed consent for participation in the study.Unable to adhere to the study requirements.The eligible population will have their AF risk estimated using FIND-AF.Study invitations will be sent to a random sample of eligible participants in each risk category in batches until the target sample size is reached. As participants are enrolled in the study, the number of invitations for each risk category will be adjusted in the subsequent batches (Batch enrolment, study intervention, follow-up procedures. GP, general practitioner. | PMC10546147 |
Enrolment method | ATRIAL FIBRILLATION | Eligible participants will be identified by the primary care team via an electronic search of general practice data (Remote consent with eligibility based on information recorded in electronic health records. EHRs, electronic health records; FIND-AF, Future Innovations in Novel Detection of Atrial Fibrillation; GP, general practitioner.All invitations to targeted screening will occur on site by members of the primary care site team. The invitation process consists of a text message followed by an information pack in the post including a participant information sheet, consent form, data protection leaflet and free-post return envelope ( | PMC10546147 | |
Intervention | EVENT | All participants will undergo non-invasive ECG monitoring (The Zenicor database has an algorithm that classifies and tags each ECG trace as ‘no tag’, ‘possible AF’ or ‘poor quality’. The algorithm has been tested in 80 149 ECGs and the negative predictive value for ECGs classified as normal is 99.9%.Once ECG monitoring reports have been reviewed, a standardised results letter will be sent to the participant and the general practitioner (GP). Results letters will be sent for all participants, irrespective of whether AF is diagnosed or not. The management of AF will be at the discretion of the GP, allowing doctor and participant to discuss the management strategy, including anticoagulation, independently and in line with how new cases of AF diagnosed in the community are managed in routine clinical practice. A diagnosis of AF does not require immediate action, but if there is a finding meeting the criteria for an emergent event per current clinical practice standards according to the National Institute for Health and Care Excellence, participants and appropriate clinicians will be notified. Actions will be taken following the same procedures as the established clinical workflow. | PMC10546147 | |
Baseline characteristics | Baseline participant characteristics will be drawn from their primary care EHRs ( | PMC10546147 | ||
Participant baseline characteristics | PMC10546147 | |||
Participant characteristics | Age.Sex.Ethnicity. | PMC10546147 | ||
Medical history | Hypertension, Stroke/transient | DIABETES MELLITUS, CORONARY ARTERY DISEASE, HYPERTENSION, HEART FAILURE, CHRONIC KIDNEY DISEASE, VALVULAR HEART DISEASE | Coronary artery disease.Chronic kidney disease.Heart failure.Hypertension.Diabetes mellitus.Stroke/transient ischaemic attack.Valvular heart disease.CHA | PMC10546147 |
Medications | Aspirin.ACE inhibitor or angiotensin receptor blocker.Beta blocker.Oral anticoagulant.Statin. | PMC10546147 | ||
Outcomes | arrhythmias | ARRHYTHMIAS | The primary outcome will be a new diagnosis of AF defined as at least one episode of completely irregular rhythm with no organised or regular atrial activity and a duration of 30 s on one-lead ECG during the Zenicor monitoring period.Secondary outcomes include:Number (%) of people who consent to participate compared with number of people who are invited.Characteristics of those who consent to participate and do not consent to participate.Number (%) of people who consent to participate but subsequently withdraw consent or decline ECG monitoring.Characteristics of those who participate and those that withdraw.Of those who conduct ECG monitoring, the number (%) of participants who record less than 50% of the stipulated amount of ECG recordings.Of those who conduct ECG monitoring, the day of first detection of AF.Number (%) of participants who are diagnosed with other arrhythmias during ECG monitoring in participants.Number (%) of participants who are diagnosed with AF during ECG monitoring who then receive a prescription of oral anticoagulation within 6 months.Number (%) of diagnoses of AF during routine practice outside of ECG monitoring (presence of an AF diagnostic code in their primary care EHR at 6 months after enrolment). | PMC10546147 |
Sample size | Assuming 1.5% of the participants in the lower risk group have newly diagnosed AF, | PMC10546147 | ||
Statistical analysis | We will calculate the incidence rate ratio of AF detection during ECG monitoring between higher predicted AF risk and lower predicted AF risk participants, using the threshold from the original development and validation paper. | PMC10546147 | ||
Patient and public involvement | The FIND-AF patient and public involvement group co-designed the study and co-drafted the consent forms and participant information sheets. Importantly, they designed the multimodal invitation (text followed by letter) to screening as they concluded that the usual invitation approach, a letter alone, may lead to poorer participation from people of minority ethnicities and lower socioeconomic classifications. | PMC10546147 | ||
Limitations | The FIND-AF pilot is not an RCT. The Zenicor-ECG device is the only AF detection device that will be used in the study. Other studies have used a skin patch that can monitor the ECG rhythm continuously, for between 14 and 30 days. | PMC10546147 | ||
Ethics and dissemination | WEST | The study will be performed in compliance with the articles of the Declaration of Helsinki (revised in October 2013). The study was approved by the North West—Greater Manchester South Research Ethics Committee, and the study was approved by the Health research Authority (IRAS project ID: 318197), and registered on ClinicalTrials.gov (NCT05898165). Study results will be disseminated at relevant conferences and published in peer-reviewed journals. Authorship will be decided according to ICMJE guidelines as to qualifying contributions, and the primary results manuscript jointly drafted by the co-chief investigators and the trial methodologists before circulating to remaining coauthors. | PMC10546147 | |
Data availability statement | Data are available on reasonable request. | PMC10546147 | ||
Ethics statements | PMC10546147 | |||
Patient consent for publication | Not applicable. | PMC10546147 | ||
Ethics approval | WEST | This study involves human participants and the study has ethical approval (the North West—Greater Manchester South Research Ethics Committee reference 23/NW/0180). Participants gave informed consent to participate in the study before taking part. | PMC10546147 | |
References | PMC10546147 | |||
1. Introduction | ’ movements | The popularity of competitive sports, particularly football, has grown in tandem with cultural and economic advancements [This paragraph compiles several studies examining the effects of functional training on the strength and performance of football players. A study focused on the high-intensity tactical training program employed by the United States Marine Corps, which shares similarities with high-intensity functional training, and its growing popularity among military personnel. The authors also assessed the benefits and drawbacks of high-intensity functional training for the military [Despite the available research, there is a dearth of studies investigating the specific relationship between functional training and football players. Machine learning algorithms have demonstrated proficiency in recognizing human and athletic movements. While functional training has shown the potential to enhance athletes’ strength, there is a limited body of evidence specifically focused on the impact of functional training on the strength of football players. Furthermore, the imbalanced nature of sample data for feature extraction during changes in athletes’ actions presents a challenge in the recognition task. Further investigation is warranted in this area to provide a comprehensive understanding of the effects of functional training on the strength and performance of football players.In this work, the movements of football players are identified using machine learning techniques to investigate the effectiveness of strength training in football. A total of 116 young participants aged 8 to 13, engaged in football team training, were randomly selected. Both groups undergo 24 training sessions, with the experimental group receiving an additional 15–20 minutes of functional strength training after each session. Machine learning algorithms are employed to recognize the distinct postures adopted by football players during training. Specifically, a BPNN is utilized to analyze the kicking motion of the players. By comparing images of the players’ movements using the BPNN, incorporating factors such as speed, sensitivity, and strength as input vectors, the output result measures the similarity between the players’ kicking action and the standard action. This approach aims to enhance training efficiency. Subsequently, the experimental scores of the kicking motions for both the experimental and control groups are compared against the standard movements. The findings of this work offer a valuable theoretical foundation for the development of training programs for football players, with the potential to enhance training efficiency and overall performance. | PMC10275424 | |
2. Method | PMC10275424 | |||
2.1 Research subject | A total of 116 students within the age range of 8 to 13, who are actively engaged in football training, are selected as participants for this work. These students are randomly assigned to either the experimental group (consisting of 60 students) or the control group (comprising 56 students). Over the course of this work, both groups undergo a series of twenty-four training sessions, with each group following its own specific curriculum. Prior to participating in this work, the minors involve, along with their respective guardians, provided informed consent by signing a consent form, thereby indicating their willingness to take part in the experiment. | PMC10275424 | ||
2.2 Research methods | ’ movements | Literature review: This work incorporates a comprehensive analysis of existing research to gain insights into the perspectives of other scholars regarding machine learning for recognizing athletes’ movements. By examining previous studies, this work aims to establish a theoretical foundation and evaluate the reliability and validity of this work.Expert interview: The design of student courses is based on a scientific approach that involves input from both football coaches and experts in functional strength training. By incorporating the knowledge and expertise of these professionals, the course design ensures that the selected indicators are representative of the overall training process.Experiment: The participants in the experimental group engage in functional strength training sessions following each regular course, while the control group does not receive such training. This experimental setup enables the investigation of whether functional strength training has a positive impact on the development of speed and strength in football players. By comparing the outcomes between the two groups, valuable insights can be obtained regarding the benefits of functional strength training. | PMC10275424 | |
2.3 Content of functional strength training | muscle hypertrophy | BENDING, CONTRACTION, BEND | Functional strength training is a training approach that aims to improve the overall muscular contraction strength and efficiency of individuals, taking into account their specific characteristics and needs. Unlike traditional training methods that focus on isolated muscle development for specific movements, functional strength training emphasizes a balanced approach. It encompasses a range of exercises that target opposing movements such as pushing and pulling, as well as exercises that address different areas of the body, such as the hips and knees. The primary goal of functional strength training is to enhance the ability to engage a greater number of muscle fibers rather than solely focusing on muscle hypertrophy. This approach leverages the body’s elasticity to generate explosive power. By promoting the activation of multiple muscle groups and optimizing neural coordination, functional strength training contributes to the improvement of maximum strength and power output. The concept of functional training seeks to establish a standardized training method that can benefit athletes across various sports. It recognizes the importance of the body’s kinematic chain and aims to enhance overall coordination and functional performance. Through the incorporation of functional strength training, individuals can unlock their full potential and achieve improved physical capabilities in sports and other activities of daily life.The functional strength training program utilized here includes the following exercises:1. Supine leg lifting with feet clamping a football:This exercise aims to target and strengthen the rectus abdominis and iliopsoas muscles. Participants lie on their backs, gripping a football with their feet to prevent it from rolling away. The exercise involves lifting the leg quickly and lowering it slowly while simultaneously lifting the hands and head off the ground. Each round consists of two sets, with each set comprising ten repetitions of leg lifts and drops.2. Supine hip turning with knees clamping a football:This drill focuses on enhancing the hip flexors and iliopsoas muscles. Participants lie on their back with arms extended to the sides. They bend their knees to a 90-degree angle while gripping a solid ball between their knees. The exercise involves twisting the hips from left to right while maintaining steady breathing and engaging the abdominal muscles. Each participant performs two sets of 15 repetitions for each movement.3. Single-sided plank:The aim of this exercise is to target multiple muscle groups, including the latissimus dorsi, erector spinae, gluteus maximus, deltoid muscle, rectus abdominis, and abdominal oblique muscles. Participants start in a prone position and bend their left elbow joint to support their body weight, while simultaneously raising their right arm forward. During the training, the participants straighten their left leg to support the ground and lift the front of their right foot. It is important to maintain steady breathing throughout the entire training process, keep the back tightened, and avoid any shaking of the raised arm and leg. Each set consists of 15 repetitions, and participants perform two sets of training.4. Single leg squat:The objective of this exercise is to target the hip muscles and quadriceps of the players. Participants begin by assuming a standing posture with their weight on the right foot, maintaining balance. They then extend the left leg backward, placing the right hand behind the ears. The exercise involves squatting down, touching the right foot with the left hand, and standing back up. It is crucial to avoid bending over during the squatting movement. Participants should perform two sets of training, with each set comprising 15 repetitions.5. Supine leg swinging with feet clamping a football:The purpose of this exercise is to target the players’ rectus abdominis and iliopsoas muscles. Participants lie on their backs with their feet clamped around a football to prevent it from dropping during training. Using the waist as the axis, they swing their legs from left to right, with their hands placed on both sides of the body to maintain balance. The upward swing should be swift, while the downward swing should be done leisurely. Each set consists of 10 repetitions, and participants perform two sets of training.6. Supine head leg crunches with feet clamping a football:This exercise focuses on exercising the players’ rectus abdominis and iliopsoas muscles. Participants lie on their backs with their feet pinned to the football, lifting their legs, curling their abdominals, and raising their hands. They slightly raise their head and lift their legs straight off the ground. Each set comprises 15 repetitions, and participants perform two sets of training.These exercises have been incorporated into the functional strength training program to specifically target and strengthen the rectus abdominis and iliopsoas muscles of the football players. Participants can enhance their core stability, abdominal strength, and overall lower body muscular endurance by including supine leg swinging and supine head leg crunches with feet clamping a football. | PMC10275424 |
2.4 Experimental teaching methods | AIDS | Over the course of one month, specifically from July 2019 to August 2019, the experimental group underwent regular training sessions from 9 a.m. to 11 a.m. daily, while the control group attended scheduled classes from 5 p.m. to 7 p.m. each day. Both groups implemented game-based learning strategies to ignite the students’ enthusiasm for football. The training primarily focused on application drills such as passing and dribbling, aiming to enhance the players’ skills in these areas.Following each training session, the experimental group participated in 15–20 minutes of functional strength training. Throughout the entire project, three coaches were involved, ensuring the elimination of potential instructor bias. There were no changes made to the training aids used by either the experimental or control groups during the duration of this work.Data were collected and analyzed using a machine learning-based posture identification technique, focusing on ten football players and their seven postures: inaction, walking, running, juggling, kicking, catching, and lifting the ball. Each motion was recorded fifty times, resulting in a total of 5000 samples. The participants assumed standard football positions based on their typical physical activity levels during the data collection process. | PMC10275424 | |
2.5 Test indicator selection | SENSITIVITY | The indicators examined in this work encompassed the player’s speed, sensitivity, and strength. To assess speed, the 10-meter and 30-meter sprints were employed as performance measures. Sensitivity was evaluated using the Illinois agility test and the 5*25-meter shuttle run. Lastly, strength was evaluated through throws and set kicking drills, which provided a measure of the players’ overall strength capabilities. | PMC10275424 | |
2.6 Football players’ posture recognition using machine learning | ’s hand gestures, ’ posture | Data on acceleration and angular velocity were collected from football players’ positions. Similarly, Eq (The data acquisition module captures three acceleration vectors and three angular velocity vectors. The vector sum of acceleration and angular velocity is computed using Eqs (Eq (The time-domain features extracted comprise a total of 16 dimensions of attitude parameters. These include:Acceleration sensors: x-axis, y-axis, z-axis, and the mean value of the acceleration vector sum.Angular velocity vector sensors: x-axis, y-axis, z-axis, and mean value of the angular velocity vector sum.Acceleration sensors: x-axis, y-axis, z-axis, and variance of the acceleration vector sum.Angular velocity vector sensors: x-axis, y-axis, z-axis, and variance of the angular velocity vector sum.These 16 dimensions provide valuable information about the attitude and movement characteristics of football players.Following feature extraction, a 32-dimensional feature parameter set is generated for football players’ posture recognition. However, to improve the recognition performance and efficiency of the classifier, it is important to filter out irrelevant or redundant feature parameters that are closely related to the football player’s hand gestures. This can be achieved by selecting relevant features to reduce the dimensionality of the data. In this work, the principal component analysis (PCA) method was employed for feature parameter selection after conducting experimental tests. PCA helps identify the most informative features and reduce the dimensionality of the dataset, thereby enhancing the accuracy and efficiency of football hand gesture recognition. | PMC10275424 | |
2.7 Acquisition of ball-kicking data of players | The deep learning (DL) method aligns with the concept of an artificial neural network (ANN), which serves as a machine learning architecture. The neural network, functioning as an algorithm, trains the weights connecting individual units within the network. Drawing inspiration from the workings of the human brain, ANN algorithms have the capacity to learn and adapt to new scenarios. In the human brain, input signals are received and processed through the nervous system, while external stimuli are sensed through neurons that convert electrical signals from nerve endings. DL-based neural networks are mathematical models that emulate the neural system of the human brain. These networks exhibit high fault tolerance, fast learning and self-adaptation rates, and the ability to approximate nonlinear functions. They can be effectively employed for tasks such as binary image recognition, prediction, and fuzzy control of binary images. The BPNN is an example of a three-layer feedforward neural network comprising the input, hidden, and output layers. The structure of the BPNN is illustrated in | PMC10275424 | ||
BPNN structure. | In the BPNN, each layer consists of n neurons, and there are connections between each layer. However, the neurons within a single layer are not interconnected. The BPNN algorithm involves two main processes: error backpropagation and forward information propagation [ | PMC10275424 | ||
Algorithm process of BPNN. | In the forward propagation process, the input object is divided into n input vectors. The weight coefficient is denoted as “In Eq (The domains of the mentioned functions are sets of real numbers, and their range is [0, 1]. After obtaining the outputs from all the hidden layers, the cross-entropy loss function is used to measure the discrepancy between the predicted values and the observed values, thus evaluating the predictive capability of the model. The loss function can be represented by Eq (In Eq (During the error backpropagation process, the gradient of the loss function is propagated backward from the output layer to the hidden layer, and the loss value is distributed to each layer of neurons. Through continuous iteration, the parameters between layers are updated to minimize the error between the actual output and the expected output values. This procedure enhances the robustness of the BPNN by adjusting the weights and thresholds associated with the smallest error [In Eqs (The selection of the number of nodes in the hidden layer is a challenging aspect of feature layer fusion based on BPNN. Currently, there is no standardized method for determining the number of nodes in the hidden layer, which directly affects the overall performance of the network. Therefore, careful consideration must be given to the selection of hidden layer nodes [In Eq (For this work, a dataset was collected by inviting twenty male football players who had different heights and weights to perform kicking actions. Among the players, one player stood out as being taller than the rest, and his kicking action data was used as the standard action. High-speed cameras were utilized to capture the kicking action data, with a frame rate of 25fps and a resolution of 1024×1280. The BPNN algorithm was employed to analyze the similarity between the kicking actions of young players and the standard action, providing valuable insights for their football training. | PMC10275424 | ||
2.8 Evaluation criteria for similarity of image features | HOT SPOT | The calculation of image feature similarity plays a crucial role in the accuracy of subsequent image retrieval. Different similarity measurement functions can yield diverse image retrieval results. In this work, the following similarity measurement function is utilized:(1) Euclidean Distance: Euclidean Distance is a widely used distance metric for comparing two points in three or more dimensions of space [In Eq ((2) Cosine Similarity: Cosine similarity utilizes the cosine value of the angle between two vectors in the vector space to quantify their dissimilarity [In football players’ joint point detection, a CNN is used to convolve the input images and generate confidence maps, also known as hot spot maps, for detecting the joint points. Multi-stage learning is employed, where each stage refines the learning and detection results of the previous stage, aiming to bring the final results closer to the target values. Let After detecting the joint points, it is necessary to connect them to form a complete human body model. However, if the connection is solely based on the confidence of the detection points, errors may occur when multiple points are involved. A local affinity domain method incorporates limb direction information into the predictions to address this issue, generating a two-dimensional (2D) vector code. Typically, the human body model can be represented as a simple connection of multiple joint points. After polynomial fitting of the body joint points in the x-axis and y-axis directions, the coefficients of the polynomial fitting are used as features for data analysis. PCA is then applied to perform data dimension reduction. PCA aims to reduce the dimensionality of the data by utilizing the eigenvectors of the sample covariance matrix. It constructs an orthogonal transformation that minimizes the mean square error (MSE). Through this transformation, the characteristics of the samples are decomposed into orthogonal components, revealing the fundamental components of the data information.In the data training phase, several steps are followed to prepare the data for classification using Support Vector Machines (SVMs). First, the average of the training data samples is calculated, and this average is subtracted from each training data point. Next, the covariance matrix and eigenvalues are computed. The dimension of the matrix is then reduced based on the contribution rate of the calculated eigenvectors. This reduction helps to eliminate redundant or less informative dimensions. Finally, the final training data is obtained by multiplying the difference between each training sample and the average data by the dimensionality reduction matrix. During the data testing phase, a similar process is applied. The average of the training data is subtracted from each testing data point, and the resulting difference is multiplied by the dimensionality reduction matrix.Once the data is prepared, it is fed into SVMs for classification and action recognition. SVMs are capable of handling nonlinear problems by using a kernel function to map the data into a higher-dimensional feature space (Hilbert space) where the problem becomes linearly separable. In this case, the Gaussian kernel function is typically used to transform the feature space, allowing the SVM training model to successfully recognize different actions. | PMC10275424 | |
2.9 Statistical methods | This work utilizes the Berkeley Multi-Channel Human Action Detection (MHAD) dataset to evaluate the effectiveness of the BPNN algorithm for action recognition. The MHAD dataset includes reference background and depth images, which are used to extract the first-layer feature vectors. The dataset consists of 11 different movements performed by a group of seven men and five women. Each movement is repeated five times, resulting in a total of 660 action sequences. The recording duration for the dataset is approximately 82 minutes. This dataset provides a valuable resource for training and evaluating the BPNN algorithm’s performance in action recognition tasks.The player training data is analyzed using IBM’s statistical software SPSS 26.0 (Statistical Product and Service Solutions 26.0), developed by IBM Corporation in New York, USA. In the analysis of the players’ basic situation, the data were presented using a percentile system. A single-factor analysis was conducted to examine the differences between different situations. In statistical analysis, a commonly used threshold for determining statistical significance is a p-value of less than 0.05. If the calculated p-value is less than 0.05, it indicates that the observed difference between the groups is statistically significant. In other words, there is a significant difference between the situations being compared. | PMC10275424 | ||
3. Results | This section presents a comprehensive analysis of experiments conducted to validate the effectiveness of image processing technology based on DL in guiding football players during functional strength training. Each experiment result is thoroughly examined and discussed. The following subsections provide a clear overview of the findings:Section 3.1 presents the accuracy results of the BPNN algorithm for recognizing single movements in the MHAD dataset.Section 3.2 analyzes the statistical differences between the experimental and control football players in terms of movement speed, sensitivity, and strength test metrics. The focus is on highlighting the improvements observed in each testing metric within the experimental group.Section 3.3 compares the performance of the experimental and control football players in 10-meter sprints, 30-meter sprints, and fixed-point kicks. It examines and discusses the observed differences between the two groups.Section 3.4 illustrates the performance test results of the experimental hidden node within the BPNN framework. This analysis aims to evaluate the effectiveness and capabilities of the hidden node within the experimental setup.Section 3.5 provides a detailed analysis of the performance test results of the BPNN model. This examination sheds light on the model’s performance and effectiveness in the context of the experiments.Section 3.6 presents the performance test results of the experimental hidden node and highlights any observed differences in functional strength training between the experimental and control groups. | PMC10275424 | ||
Comparison of single-action recognition accuracy rate in MHAD dataset. | During the collection of sport posture data, participants perform specific football actions based on their exercise habits. These football postures consist of distinct upper limb actions and lower limb actions, which are recognized separately. As a result, separate classifiers are constructed for upper limb actions and lower limb actions. The recognition results of random forest classifiers, support vector machines, and Bayesian networks for upper and lower limb actions are presented in | PMC10275424 | ||
The recognition results of classifiers of random forest, support vector machine, and Bayesian network. | PMC10275424 | |||
Comparison of the results in the experimental group before and after the experiment (Note: * indicates that the difference is statistically significant). | The experimental group demonstrated significant improvements in various performance metrics after the experiment. Specifically, there was a substantial 1.6% improvement (P = 0.000 < 0.05) in the 10-meter running performance. The 30-meter run performance showed a 1.95% improvement (P = 0.000 < 0.05), and the Illinois run performance increased by 6.38% (P = 0.000 < 0.05). Additionally, the experimental group exhibited a 5.29% improvement (P = 0.000 < 0.05) in the 5x25m shuttle running performance and a 4.73% improvement (P = 0.000 < 0.05) in throwing performance. Notably, the kicking performance of the experimental group significantly increased by 49.73% (P = 0.000 < 0.05) as a result of the trial. | PMC10275424 | ||
Comparison of the results between the experimental and control groups(Note: * Indicates a significant difference). | There were no statistically significant differences (P > 0.05) observed in the performances of players who underwent functional strength training compared to those who did not, specifically in the 10-meter running, 30-meter running, and set kicking tests. The experimental group achieved an average score of 3.07 ± 0.23 in the 10-meter running test, while the control group scored 3.04 ± 0.23, and this difference was not statistically significant (P = 0.659). Similarly, in the 30-meter running test, the experimental group achieved a score of 7.05 ± 0.25, while the control group scored 6.90 ± 0.31, resulting in a non-statistically significant difference (P = 0.060). However, there was a statistically significant difference (P = 0.031) between the experimental group’s performance (22.88 ± 1.42) and the control group’s performance (23.63 ± 1.08) in the Illinois running tests. The 5x25 shuttle running tests also revealed a statistically significant difference (P = 0.033) between the experimental group’s performance (48.30 ± 2.56) and the control group’s performance (49.75 ± 2.37). Similarly, a statistically significant difference (P = 0.038) was found between the experimental group’s throwing test performance (6.64 ± 0.43) and the control group’s performance (6.42 ± 0.33). However, the difference in mean scores between the experimental and control groups in the overall test scores was not statistically significant (27.28 ± 2.28 and 26.82 ± 2.27, respectively), with a P value of 0.461. | PMC10275424 | ||
Simulation results of BPNN. | After 127 iterations, as depicted in | PMC10275424 | ||
3.6 Accuracy of kicking actions of football players | Figs | PMC10275424 | ||
The accuracy of kicking actions of players in the experimental group. | PMC10275424 | |||
The accuracy of kicking actions of players in the control group. | There are no significant differences observed between the experimental and control groups before and after the experiment, as both groups received similar action training. Prior to the experiment, the action accuracy of the players in the experimental group was 73.2%, while the control group achieved an accuracy of 74.3%. After the experiment, the experimental group demonstrated an accuracy of 83.4%, while the control group showed an accuracy of 84.1%. | PMC10275424 | ||
4. Discussion | The declining physical fitness of football players is a concerning trend in the current landscape. In light of this, the present work aims to investigate the impact of functional strength training on the physical capabilities of football players. By exploring the relationship between functional strength training and the physical fitness of football players, this research seeks to shed light on potential strategies for improving and maintaining their physical performance levels.The experimental findings provide evidence that functional strength training is effective in enhancing the strength and sensitivity of football players. The observed improvements in strength can be attributed to the training’s ability to target and strengthen the players’ core muscles. Functional strength training stimulates the core muscles, particularly when there are imbalances in other body parts, resulting in improved utilization of athletic abilities and increased core strength during exercises. This, in turn, contributes to improved overall performance. However, the immediate impact on speed is not as evident. This could be due to the fact that speed performance improvement is closely tied to specific speed training, which may not have been explicitly included in the functional strength training program. Both the experimental and control groups likely had similar speed training components, resulting in comparable speed outcomes after the experiment. It is worth noting that the athletes may have already possessed a higher level of speed quality prior to the experiment, which could explain the lack of significant differences in speed improvement between the two groups. Previous research has examined the effects of functional strength training in various contexts. For example, a study focusing on weightlifters aimed to improve snatch performance through functional strength (strength-strength-balance) training [In this work, the focus is on the analysis of kicking actions in football players. The analysis of football movement serves as a training aid, providing timely feedback to players when their kicking action deviates from the desired technique. Functional strength training has been a subject of investigation in relation to its impact on the effectiveness of football practice sessions. Previous research has explored the efficacy of functional strength training in injury prevention for adult male football players. The research has also examined the actual outcomes of implementing functional strength training when teaching football skills. The results have consistently demonstrated that functional strength training methods effectively enhance athletes’ abilities and performance, supporting its application in football training [This article investigates the relationship between functional strength training and physical ability in soccer players. However, it is critical to acknowledge the limitations of this work, including the exclusion of speed training and the lack of clear conclusions regarding speed performance. Therefore, future research should consider incorporating speed training and expanding the sample size to provide a more comprehensive understanding of the developed program’s impact on improving the physical fitness of soccer players. | PMC10275424 | ||
5. Conclusion | This work aims to investigate the relationship between functional strength training and speed and power in football players. The results indicate that functional strength training effectively increases strength and sensitivity in football players. However, this work did not find a significant correlation between functional strength training and players’ speed. These findings provide a theoretical basis for improving training methods and efficiency in teenage football players. However, there are limitations to consider. The small sample size used in this work may introduce potential biases and chance factors. Future research should expand the sample size to ensure more accurate results. Additionally, further investigation is needed to examine the impact of functional strength training on speed quality in football players. Exploring the link between motions and skills would also contribute to a more comprehensive understanding of the topic. | PMC10275424 | ||
Supporting information | (XLSX)Click here for additional data file. | PMC10275424 | ||
References | PMC10275424 | |||
1. Introduction | calcification, ossifications, shock, swelling, calcifications, pain, orthosis, atrophy, rupture | DEGENERATION, INFILTRATION, SHOCK, PROLIFERATION, INFLAMMATION, DISEASE, PLANTAR FASCIITIS, ATROPHY, CALCAR CALCANEI | Academic Editor: Stefano BrunelliThe prospective, simple randomized study assesses the effect of focused extracorporeal shock wave therapy (f-ESWT) on pain intensity and calcification size compared to the application of ultrasound physical therapy in treating patients with calcar calcanei. A total of 124 patients diagnosed with calcar calcanei were consecutively included in the study. The patients were divided into two groups: the experimental group (Calcar calcanei is one of the most frequent causes of foot pain in adults (15–20%) [Calcar calcanei is a disease manifested by the presence of calcification on the calcaneus. Histological analysis shows that the calcar calcanei consists of a core of mature lamellar bone and demonstrates evidence of degeneration and fibro-cartilaginous proliferation, along with one or more intramembranous, chondroid, and endochondral ossifications occurring at the surface [Its treatment is multimodal and may include the following: the application of anti-inflammatory drugs, physical therapy, surgical treatment, kinesiotherapy, and the use of an orthosis. Generally speaking, there is no proof of the efficiency of any particular method, apart from glucocorticoid infiltration, which is associated with possible atrophy of the tissue in the foot heel or rupture of the plantar fascia [Nowadays, in the literature, there is numerous evidence of the use of f-ESWT in the treatment of plantar fasciitis without or with (calcar calcanei) calcification. [The effect of the application of ultrasound therapy is twofold. The thermal effect manifests as a local increase in the temperature of the tissue located at the site of therapy application. The mechanical effect leads to micro-massage of the tissue being treated, resulting in increased permeability of cell membranes. This therapy has the effect of reducing swelling and tension in soft tissues, reducing pain and inflammation, and improving sensation.Research on the efficiency of safe physical therapy methods is an important current issue. Before introducing shock wave therapy into clinical practice, different forms of therapy were applied in treating calcifications. The application of different forms of therapy used thus far, including the local administration of corticosteroids, results in reduced swelling of the soft tissue of the heel and sole of the foot and reduced pain. Surgical removal of the calcification may lead to side effects in the soft tissue of the heel [Standard ultrasound therapy in calcar calcanei was the treatment of choice before introducing ESWT [The study aims to determine the effect of f-ESWT on pain intensity and the calcification size in calcar calcanei compared to the application of standard ultrasound therapy. | PMC9970705 |
2. Methods | The protocol applied in this study is based on the principles of the Helsinki Declaration. The study was approved by the Faculty of Medicine Ethics Committee of Belgrade University (No. 213). All of the patients involved in the study submitted written consent forms for inclusion in the study. The research was performed at the Clinic for Rehabilitation dr Miroslav Zotovic. The study was carried out between September 1, 2021, and September 31, 2022.The study included 124 consecutive patients. With the method of equal randomization, the patients were divided into two groups. The first group was designated as the experimental group and had 62 patients treated with f-ESWT. The second group was selected as the control group; it included 62 patients treated with standard ultrasound therapy. | PMC9970705 | ||
3. Criteria | carcinoma | CARCINOMA, SENSORY POLYNEUROPATHY, COAGULATION DISORDER, CALCAR CALCANEI, OSTEOPOROSIS | A total of 190 patients were considered for the study, of whom 124 fulfilled the criteria for inclusion. The primary criterion for including patients in the study was diagnostically confirmed painful calcar calcanei diagnosed with X-rays up to six months before. Patients with the following contraindications were excluded from the study: coagulation disorder, anticoagulant use, carcinoma, pregnancy, sensory polyneuropathy, osteoporosis, a pacemaker, acute conditions, lesions of the sole skin, and cortisone treatment up to six weeks before the initial treatment session. Statistical analysis was performed on an “intention to treat” basis, and dropout was not registered. | PMC9970705 |
4. The Procedure | orthosis, Shock, shock | SHOCKS, SHOCK, SHOCK | The shock wave therapy machine used was the Masterpuls MP 200, serial No: BS 2058, manufactured in 2011 by STORZ MEDICAL, Switzerland. Shock wave therapy was applied locally, on the heel of the foot, at the site of the calcar calcanei. The application was performed with a focused probe with the following parameters: 16 Hz frequency, 1,600 shocks, and a pressure of 1.6 bars. The patients lay prone, and a cylinder was placed under their lower leg so the heel would be completely relaxed and more accessible to the doctor performing the therapy. The f-ESWT was applied once a week for ten weeks.The patients in the control group underwent a series of ten physical ultrasound therapy treatments continuously every day. The machine applied was the SONOPULS 492 Enraf-Nonius. The application of standard ultrasound therapy was performed using the stable method, directly on the heel of the foot and the plantar fascia, for five minutes at an intensity ranging between 0.5 and 0.8 W/cm2. The patients were positioned in the same way as for shock wave therapy application. A licensed physician administered shock wave therapy. A licensed physical therapist administered standard ultrasound treatment to the patients in the control group according to the protocol defined by a physiatrist. None of the patients treated in either of the groups took any medication belonging to the group of analgesics or non-steroid antirheumatics, nor were they treated with corticosteroid drugs during the study. Additionally, none used an orthosis for their heel or applied any gels locally. | PMC9970705 |
5. Outcome Parameters | CIA, calcification, pain | CALCAR CALCANEI | The pain intensity was measured using the Visual Analog Scale (VAS) [The calcification size was measured in millimeters with X-ray diagnostics. Imaging the calcar calcanei was performed by applying the standard X-ray technique for the ankle, with the patient standing upright and the X-ray beam spread vertically. Thus, the images show all the elements of the ankle (distal tibia, talus, and calcaneus). The size and angle of each abnormality of the calcaneus, which was registered as a calcar calcanei, were measured. The measurement of the size of the calcar calcanei was performed via the calcaneal inclination angle (CIA), the lateral talocalcaneal angle (LTCA), the Böhler angle (BA), and the Gissane angle [All the results were statistically processed with the IBM SPSS Statistics 22 (SPSS Inc., Chicago, IL, USA) software package. | PMC9970705 |
5.1. Statistical Analysis | REGRESSION | Descriptive statistics were used to describe data. The continuous variables are presented by mean ± standard deviation, while the categorical variables are presented by count (percentage).The comparison between independent variables, which distributions were approximately the same as a normal distribution, we were done by the The relationship between variables for each group was analyzed separately by Pearson's correlations. The relationship between the two variables was analyzed by controlling the third variable using partial correlation. The partial correlation coefficient measures the strength of the linear relationship between two variables after entirely controlling for the effects of other variables. The logistic regression was performed for changes in a specific outcome.The level of statistical significance was set at a two-tailed alpha level of 0.05. RStudio (version 1.4.1106) was used for statistical analysis. | PMC9970705 | |
5.2. Results | Calcification, calcification, shock | CALCIFICATION, SHOCK, POLYNEUROPATHIES, REGRESSION, CALCAR CALCANEI | One hundred and ninety consecutive patients with diagnostically confirmed painful calcar calcanei were screened for eligibility criteria. One hundred and twenty-four patients fulfilled all eligibility criteria. Eighteen patients had sensory polyneuropathies, a lesion of the sole skin had ten participants, cortisone treatment up to six weeks before the initial treatment session had eight, eleven patients were medically unstable, and nineteen declined to participate in the clinical trial. The patients were divided by the method of equal randomization into two groups. The first group was designated as the experimental group and had 62 patients treated with shock wave therapy. The second group was selected as the control group; it included 62 patients treated with standard ultrasound therapy. Descriptive statistics of all outcomes for both groups are presented in The results of the analysis of comparisons between experimental and control groups are presented in The results of the ‘pre-post' therapy analysis are presented in Calcification and VAS change were calculated as subtraction, pretherapy, posttherapy, and VAS pretherapy and VAS posttherapy. The results of comparing changes in calcification and VAS, separately between the experimental and control groups are presented in Additionally, we observed the change in the VAS as greatly improved (> = 50), much improved (50 < ×< = 30), somewhat improved (30 < ×< = 10), about the same (10 < ×< = 1), and worse (>1). The change in VAS in both groups is presented in Additionally, we observed the change in the calcification as improved (>0), not improved (<=0)—the change of calcification in both groups presented in The logistic regression was done for calcification improvement, and the results are presented in The relationship between variables for each group was analyzed separately by Pearson's correlations. The results are shown in The analysis of the relationship between two variables, calcification changes and BMI, while controlling by the third variable, age, was done using the partial correlation. The partial correlation was statistically significant and positive with a small degree (The analysis of the relationship between two variables, calcification changes and age, while controlled by the third variable, BMI, was done using the partial correlation. The partial correlation was statistically significant and positive with a medium degree (The analysis of the relationship between two variables, calcification change and VAS change, but controlling a third variable (age, BMI, and therapy duration, separately) was done using the partial correlation. The partial correlation coefficient measures the strength of the linear relationship between two variables after entirely controlling for the effects of other variables. The results are presented in | PMC9970705 |
6. Discussion | shock, calcification, pain | CALCAR CALCANEI, SIDE EFFECTS, SHOCK | The most prominent symptom of calcar calcanei is pain. In our study, none of the patients from either of the groups took any analgesics or nonsteroid antirheumatics. Analyzing the results obtained in treating the patients in the experimental and control groups, we received statistically similar data regarding the decrease in pain levels in patients. The application of f-ECWT in the experimental group of patients showed a demonstrable reduction in the calcification size and a decrease in pain. Patients from the control group treated with standard ultrasound therapy experienced a positive effect regarding pain intensity reduction. By analyzing the calcification size in millimeters, in patients of both tested groups, a result was obtained demonstrating the effect of f-ESWT on reducing the calcification. Correlation analyses did not show a connection between the size of calcification and pain, but some factors, such as BMI and the age of patients, moderate the therapeutic effects. The results show that the improvement in calcification size is more significant for the elderly and subjects with a higher BMI. There is no data in the literature on the moderating effect of other factors related to patient characteristics. Side effects of the application of shock wave therapy were not registered. Similarly, there were no registered side effects among the patients in the control group.Many studies confirm that the f-ESWT method is noninvasive, safe, and without severe contraindications for breaking up calcifications [The complete biological mechanism of shock wave therapy has yet to be precisely understood. It is believed that ESWT promotes healing through the process of mechano-transduction, acting as a mechanical stimulus [It is assumed that the application of f-ESWT induced changes at the cellular and molecular level, resulting in a reduction in the calcification size. An objective reduction in calcification size was also statistically proven in this study. | PMC9970705 |
7. Study Limitations | The result should be considered against a few limitations. The patients are not homogeneous in the duration of symptoms and have not been monitored for a long time. A limitation is the lack of determination of the sample size since the patients were determined consecutively. Also, many factors other than BMI that could influence the effects of therapy were not monitored. | PMC9970705 | ||
8. Conclusion | calcification, pain | In conclusion, both types of therapy applied in the study contributed to reducing pain intensity. The application of f-ESWT significantly reduced the calcification size compared with standard ultrasound therapy. | PMC9970705 | |
Data Availability | Data supporting the study results can be found in the medical data system of the Clinic for Rehabilitation dr Miroslav Zotovic. | PMC9970705 | ||
Conflicts of Interest | calcification | REGRESSION, RECRUITMENT | The authors have no conflict of interest to declare.Flow diagram of patient recruitment.Descriptive statistics of all outcomes in this study.The comparisons of outcomes with descriptive statistics (mean ± standard deviation), test statistics,
The ‘pre-post' analysis of VAS and calcification.
The analysis of change of calcification and VAS.
The distribution of VAS change.The distribution of calcification change.The logistic regression.The correlation coefficients for both groups, separately.The partial correlation analysis. | PMC9970705 |
Subject terms | OHE, transjugular intrahepatic portosystemic shunt | BLOOD, PORTAL HYPERTENSION, HEPATIC ENCEPHALOPATHY | We aim to develop a nomogram to predict overt hepatic encephalopathy (OHE) after transjugular intrahepatic portosystemic shunt (TIPS) in patients with portal hypertension, according to demographic/clinical indicators such as age, creatinine, blood ammonia, indocyanine green retention rate at 15 min (ICG-R15) and percentage of Portal pressure gradient (PPG) decline. In this retrospective study, 296 patients with portal hypertension who received elective TIPS in Beijing Shijitan Hospital from June 2018 to June 2020 were included. These patients were randomly divided into a training cohort (n = 207) and a validation cohort (n = 89). According to the occurrence of OHE, patients were assigned to OHE group and non-OHE group. Both univariate and multivariate analyses were performed to determine independent variables for predicting OHE after TIPS. Accordingly, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to compare the accuracy and superiority of a novel model with conventional Child–Pugh and MELD scoring model. Age (OR 1.036, 95% CI 1.002–1.070, p = 0.037), Creatinine (OR 1.011, 95% CI 1.003–1.019, p = 0.009), Blood ammonia (OR 1.025, 95% CI 1.006–1.044, p = 0.011), ICG-R15 (OR 1.030, 95% CI 1.009–1.052, p = 0.004) and Percentage decline in PPG (OR 1.068, 95% CI 1.029–1.109, p = 0.001) were independent risk factors for OHE after TIPS using multifactorial analysis. A nomogram was constructed using a well-fit calibration curve for each of these five covariates. When compared to Child–Pugh and MELD score, this new nomogram has a better predictive value (C-index = 0.828, 95% CI 0.761–0.896). Consistently, this finding was reproduceable in validation cohort and confirmed with DCA. A unique nomogram was developed to predict OHE after TIPS in patients with PHT, with a high prediction sensitivity and specificity performance than commonly applied scoring systems. | PMC10502141 |
Introduction | overt hepatic encephalopathy, OHE, cirrhosis, covert hepatic encephalopathy | WEST, CIRRHOSIS, PORTAL HYPERTENSION, INFLAMMATORY RESPONSE | After a long-term inflammatory response, the normal liver parenchyma is replaced by fibrotic tissues and regenerative nodules, which can subsequently progress to cirrhosis, and eventually lead to portal hypertension (PHT)According to clinical manifestations, HE can be divided into covert hepatic encephalopathy (CHE) and overt hepatic encephalopathy (OHE). In addition, HE may be categorized into grades 0 to 4 according to the West Haven grading criteria; of which, CHE includes grades 0 and 1, whereas OHE includes grades 2–4Presently, Child–Pugh and MELD scoring systems for predicting HE after TIPS are clinically available | PMC10502141 |
Materials and methods | PMC10502141 | |||
Patients | ascites, bleeding, cardiopulmonary insufficiency, varicose bleeding | ASCITES, BLEEDING, ENCEPHALOPATHY | In this retrospective study, 358 PHT patients who received elective TIPS at Beijing Shijitan Hospital from June 2018 to June 2020 were included. Among them, 62 patients were excluded due to incomplete data and loss to follow-up. The remaining 296 patients were randomly divided into a training cohort (n = 207) and a validation cohort (n = 89), All patients with esophagogastric variceal bleeding and refractory ascites had treatment failure after first-line treatment. This study was approved by the Institutional Review Board at Beijing Shijitan Hospital in accordance with the Declaration of Helsinki. All methods are performed in accordance with relevant guidelines and regulations.The inclusion criteria were as follows: (1) diagnosed with PHT; (2) treatment of varicose bleeding by beta-blockers or endoscopy failed; (3) patients with refractory ascites who do not respond to adequate doses of diuretics and sodium restriction; (4) with complete perioperative clinical data. The exclusion criteria were as follows: (1) diagnosed with preoperative HE; (2) previously treated with liver transplantation; (3) diagnosed with preoperative severe cardiopulmonary insufficiency or severe encephalopathy. | PMC10502141 |
Clinicopathological variables | ascites, OHE, cirrhosis, TIPS | ASCITES, LIVER DISEASES, CIRRHOSIS | Demographic and clinical data were collected, including age, sex, history of PHT and liver diseases. Imaging results from MRI contrast-enhanced, CT contrast-enhanced, and ultrasonography were analyzed to identify cirrhosis and ascites. TIPS perioperative tests were recorded, including complete blood count, renal function, serum electrolyte, plasma ammonia, liver function, prothrombin time, international normalized ratio and ICG-R15. The perioperative information on TIPS was recorded. In addition, the symptoms of OHE were evaluated by more than 2 experienced hepatologists according to the West-Haven criteria. | PMC10502141 |
Diagnosis and definitions | The MELD score | PMC10502141 |
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