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Acknowledgments | The authors thank all the participants in the study. The authors also thank all research nurses and physicians at the sites, as well as Ingela Johansson, Gosia Smolinska and Claudia Matzke for skillful laboratory work. The authors are grateful to Dr. Joachim Davidsson (Department of Radiology, Linköping University Hospital, Linköping, Sweden) for skillful performance of the needle-guided lymph node injections and instructions to other centers. | PMC9933867 | ||
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. | PMC9933867 | ||
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. | PMC9933867 | ||
Supplementary material | The Supplementary Material for this article can be found online at: Click here for additional data file. | PMC9933867 | ||
References | PMC9933867 | |||
Subject terms | Artificial intelligence (AI) has been developed for echocardiographyThe impact of artificial intelligence in cardiac function assessment is evaluated by a blinded, randomized non-inferiority trial of artificial intelligence versus sonographer initial assessment of the left ventricular ejection fraction. | PMC10115627 | ||
Main | DISEASE | Accurate quantification of cardiac function is necessary for disease diagnosis, risk stratification and assessment of treatment responseClinical practice guidelines recommend when assessing LVEF based on cardiac imaging—most commonly echocardiography—that the measurements should be performed repeatedly over multiple cardiac cycles to improve precision and account for arrhythmic or haemodynamic sources of variationExtending from tremendous progress in the field of AI over the past decade | PMC10115627 | |
Cohort characteristics | We enroled 3,769 transthoracic echocardiogram studies originally performed at an academic medical centre between 1 June 2019 and 8 August 2019; these studies were prospectively re-evaluated by 25 cardiac sonographers (mean of 14.1 years of practice) and 10 cardiologists (mean of 12.7 years of practice). In total, 3,495 studies from 3,035 patients were able to be annotated by sonographers using Simpson’s method of disc calculation of LVEF, and 274 studies were excluded for being of insufficient image quality to contour the left ventricle (Fig. Demographic and imaging study characteristicsA4C, apical-4-chamber; EF, ejection fraction. | PMC10115627 | ||
Assessment of blinding | BANG | After completing each study, cardiologists were asked to predict the agent of initial interpretation. Cardiologists correctly predicted the method of initial assessment for 1,130 (32.3%) studies, incorrectly guessed for 845 (24.2%) studies and were unsure whether initial assessment was provided by AI or sonographers for 1,520 (43.4%) studies. The Bang’s blinding index, a metric of blinding in which 0 is perfect blinding and −1 or 1 is perfectly unblinding, was used to assess the trial | PMC10115627 | |
Consort diagram. | Screening, randomization and follow-up. | PMC10115627 | ||
Secondary safety outcome | SECONDARY | The secondary safety outcome of substantial difference between final cardiologist-adjudicated LVEF compared with the previously clinically reported LVEF occurred in 871 (50.1%) studies in the AI group compared with 957 (54.5%) studies in the sonographer group (difference of −4.5%, 95% confidence interval: −7.8% to −1.2%, | PMC10115627 | |
Other outcomes and subgroup analyses | The reduction in the primary end point with the AI group was consistent across all major subgroups (Table | PMC10115627 | ||
Comparison of AI versus sonographer guidance on cardiologist assessment and difference between final versus previous cardiologist assessments. | Dots represent individual studies and lines represent the lines of best fit. MAD, mean absolute difference.We additionally assessed the frequency of changes from initial to final assessment crossing a clinically meaningful threshold (that is, LVEF of 35% for consideration of implantable defibrillator therapy) post-hoc. In the AI group, 22 of 1,740 (1.3%) studies crossed the 35% threshold between initial and final cardiologist assessments. In the sonographer group, 54 of 1,755 (3.1%) studies crossed the threshold between initial and final assessments (Subgroup analysis | PMC10115627 | ||
Discussion | In this trial of board-certified cardiologists adjudicating clinical transthoracic echocardiographic exams, AI-guided initial evaluation of LVEF was found to be non-inferior and even superior to sonographer-guided initial evaluation. After blinded review of AI versus sonographer-guided LVEF assessment, cardiologists were less likely to substantially change the LVEF assessment for their final report with initial AI assessment. Furthermore, the AI-guided assessment took less time for cardiologists to overread and was more consistent with cardiologist assessment from the previous clinical report. Although not the first trial of AI technology in clinical cardiologyIn addition to prospectively evaluating the impact of AI in a clinical trial, our study represents the largest test–retest assessment of clinician variability in assessing LVEF to date. The degree of human variability between repeated LVEF assessments in our study is consistent with previous studiesNotwithstanding tremendous interest in AI technologies, there have been few prospective trials evaluating their efficacy and effect on clinician assessments. Important clinical trials of AI technology have already shown the efficaciousness of AI in cardiologyTo enable effective blinding, we implemented a single cardiac cycle annotation workflow representative of many real-world high-volume echocardiography laboratories. Despite this framework, there was a small signal for cardiologists to be more likely to be correct than incorrect in guessing the agent of initial assessment. However, the blinding index is within the range typically described as good blinding, and regardless of whether the cardiologist thought the initial agent was AI, sonographer or uncertain, the results trended towards improved performance in the AI arm. Our findings of non-inferiority and even superiority of initial AI assessment are encouraging given that AI assessment reduces the time and effort required of the tedious manual processing that is typically required by routine clinical workflows. Given these promising results, further developments of AI could eventually facilitate additional workflows that are required for conducting comprehensive cardiac assessments in routine clinical practice and in accordance with guideline recommendationsSeveral limitations of our trial should be mentioned. First, our study was single centre, reflecting the demographics and clinical practices of a particular population. Nevertheless, the AI model was trained on example images from another centre and the clinical trial was performed as prospective external validation, suggesting generalizability of the AI techniques and workflow. Second, the study was not powered to assess long-term outcomes based on differences in LVEF assessment. Although the results were consistent across subgroups, further analyses are needed to evaluate the impact of video selection, frame selection and intra-provider variability. Third, this trial used previously acquired echocardiogram studies, and although prospectively evaluated by sonographers and cardiologists, there can be bias when a different sonographer than the scanning sonographer interprets the images. Last, consistent with findings from most AI studies, we found model performance improvement scales with the number of training examples. Thus, we anticipate that future studies could improve on the AI performance that we observed in the current study by implementing AI models developed based on an even greater number of training examples derived from a broad and diverse cohort of patients. Of note, this clinical trial utilized an AI model entirely trained from an independent site, representing external validation of the model. Effective deployment of AI models in cardiology clinical practice will require additional regulatory oversight, adoption and appropriate use by clinicians, and functional integration with clinical systems, all of which need to be carefully considered and further studied.In summary, we found that an AI-guided workflow for the initial assessment of cardiac function in echocardiography was non-inferior and even superior to the initial assessment by the sonographer. Cardiologists required less time, substantially changed the initial assessment less frequently and were more consistent with previous clinical assessments by the cardiologist when using an AI-guided workflow. This finding was consistent across subgroups of different demographic and imaging characteristics. In the context of an ongoing need for precision phenotyping, our trial results suggest that AI tools can improve efficacy as well as efficiency in assessing cardiac function. Next steps include studying the effect of AI guidance on cardiac function assessment across multiple centres. | PMC10115627 | ||
Methods | PMC10115627 | |||
Study design and oversight | Cardiologists with board certification in echocardiography were assigned to read independent transthoracic echocardiogram studies randomized to initial assessment by AI versus sonographer. Imaging studies were initially acquired and interpreted clinically by a board-certified cardiologist between 1 June 2019 and 8 August 2019 at Cedars-Sinai Medical Center. Studies were randomly sampled within the time range without regard to patient identity, so that multiple studies from the same patient would be randomized and assessed independently. Sonographers were asked to use their standard clinical practice to annotate the left ventricle for either single-plane or biplane method-of-discs calculation of LVEFEligible studies were randomly assigned, in a 1:1 ratio, to initial assessment by AI or sonographer and presented to the cardiologists in the standard clinical reporting workflow and software (Siemens Syngo Dynamics VA40D) for adjusting the LV annotation and calculating EF. Although the AI model could annotate every single frame and cardiac cycle, to facilitate blinding, one representative cardiac cycle was annotated and presented to the cardiologist in the AI group. To preserve blinding, the same proportion of single-plane-annotated and biplane-annotated studies was generated for the AI group as the sonographer group.The trial was designed as a blinded, randomized non-inferiority trial with a prespecified margin of difference by academic study investigators without industry sponsorship or representation in trial design. Approval by the Cedars-Sinai Medical Center Institutional Review Board was obtained before the start of the study. All reading echocardiographers gave informed consent and were excluded from the data analysis. The last author prepared the first draft of the manuscript. The first and last authors had full access to the data. All the authors vouch for the accuracy and completeness of the data and analyses and for the fidelity of the study to the protocol. This study satisfies the requirements set forth by the CONSORT-AI and SPIRIT-AI reporting guidelines | PMC10115627 | ||
Model design and clinical integration | The architecture and design of the AI model have been previously describedFor both sonographers and cardiologists, the entire study (most often between 60 and 120 videos) was shown in the standard clinical reporting software. The study was shown without any annotations to the sonographer, who chose the apical-4-chamber and apical-2-chamber videos and traced the endocardium to assess LVEF. For the cardiologist, the study was shown with one set of annotations (provided by either AI or the sonographer) and can adjust the endocardium to change the reported LVEF (example video 1). Standard method of discs evaluation of the left ventricle, either biplane or single plane depending on sonographer input, was used to calculate LVEF. | PMC10115627 | ||
Outcomes assessment | SECONDARY | The primary outcome was the change in LVEF between the initial assessment by AI or sonographer and the final cardiologist assessment. The primary outcome was evaluated both as the proportion of studies with substantial change and the mean absolute difference between initial and final assessments. Substantial change was defined as greater than 5% change in LVEF between initial and final assessments. The analysis was performed as randomized and there was no crossover between the two groups.The duration of time for contouring and adjustment by the sonographer and cardiologist was tracked and compared between the sonographer and AI arms. To assess blinding, cardiologists were asked to predict whether the initial interpretation was by AI, sonographer or unable to tell for each study. A key secondary safety end point was change in final cardiologist-adjudicated LVEF compared with the previous cardiologist-reported LVEF. An additional secondary end point includes the proportion of studies with no change in LVEF between initial and final interpretations. | PMC10115627 | |
Statistical analysis | SECONDARY | The trial was designed to test for non-inferiority, with a secondary objective of testing for superiority with respect to the primary end point. Non-inferiority is shown if the lower limit of the 95% confidence interval for the between-group difference in the primary end point was less than 5% (less than the natural variation of test–retest variability in the blinded human assessment of LVEF) | PMC10115627 | |
Reporting summary | Further information on research design is available in the | PMC10115627 | ||
Online content | Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-05947-3. | PMC10115627 | ||
Supplementary information | The online version contains supplementary material available at 10.1038/s41586-023-05947-3. | PMC10115627 | ||
Acknowledgements | No external funding was obtained for this study. We thank the Cedars-Sinai Medical Center Enterprise Information Systems Enterprise Imaging team for their support with clinical integration and deployment. | PMC10115627 | ||
Author contributions | B.H., S.C., J.Y.Z. and D.O. designed the clinical trial, study protocol and implementation of the AI model. B.H., G.D. and M.J. engineered technical design and clinical deployment. A.C.K., J.H.C., N.Y., C.P., T.S., J.E., N.A.B., J.W., K.J. and R.S. performed the blinded review of AI versus sonographer assessments. B.H., S.C., J.Y.Z. and D.O. wrote the manuscript with feedback from all authors. | PMC10115627 | ||
Peer review | PMC10115627 | |||
Data availability | The AI model was trained using echocardiogram videos from Stanford Healthcare following Stanford IRB protocol 43721 with waiver of individual consent. A set of de-identified Stanford Healthcare echocardiogram videos is publicly available at EchoNet-Dynamic ( | PMC10115627 | ||
Code availability | The code for the AI model is available at GitHub ( | PMC10115627 | ||
Competing interests | Stanford University is in the process of applying for a patent application covering video-based deep learning models for assessing cardiac function that lists B.H., J.Y.Z. and D.O. as inventors | PMC10115627 | ||
References | PMC10115627 | |||
Purpose | The purpose of this study was to investigate the potential of a doubled semitendinosus (ST) and a single gracilis tendon (GT) lateral meniscus autograft to restore the knee joint kinematics and tibiofemoral contact after total lateral meniscectomy (LMM). | PMC10276070 | ||
Methods | knee joints | Fourteen human knee joints were tested intact, after LMM and after ST and GT meniscus autograft treatment under an axial load of 200 N during full range of motion (0°–120°) and four randomised loading situations: without external moments, external rotation, valgus stress and a combination of external rotation and valgus stress using a knee joint simulator. Non-parametric statistical analyses were performed on joint kinematics and on the tibiofemoral contact mechanics. | PMC10276070 | |
Results | knee joints | LMM led to significant rotational instability of the knee joints ( | PMC10276070 | |
Conclusion | The doubled ST lateral meniscus autograft improved the knee joint kinematics significantly and restored the tibiofemoral contact mechanics almost comparable to the native situation. Thus, from a biomechanical point of view, ST meniscus autografts might be a potential treatment alternative for patients who are indicated for meniscus allograft transplantation. | PMC10276070 | ||
Supplementary Information | The online version contains supplementary material available at 10.1007/s00167-022-07300-z. | PMC10276070 | ||
Keywords | Open Access funding enabled and organized by Projekt DEAL. | PMC10276070 | ||
Introduction | Meniscal injuries are among the most common injuries within the knee joint [ | PMC10276070 | ||
Materials and methods | knee joints | Following IRB approval (No. 37/20; University of Ulm), fourteen non-osteoarthritic fresh frozen cadaveric knees (11 males, 3 females; all left knees; median age 57 years, range 28–64 years; Science Care, Phoenix, AZ, USA) were thawed at room temperature and both the gracilis tendon (GT) and ST were harvested following a standard clinical protocol [Schematic representation of Initially the knee joints were tested it the native state (Nat, Fig. | PMC10276070 | |
Biomechanical testing | An established knee joint loading simulator [ | PMC10276070 | ||
Statistical analysis | On the basis of a comparable study [ | PMC10276070 | ||
Results | PMC10276070 | |||
Joint kinematics | varus-valgus | Compared to the native condition, the other knee joint conditions (LMM, GT, ST) did not affect the varus-valgus rotation, except for the LMM state at 90° flexion (Box plots (minimum, maximum, median, 25th and 75th percentile values) of | PMC10276070 | |
Lateral tibiofemoral contact mechanics | In the native knee joint, the lateral CPMinimum, median and maximum peak contact pressure (CPStatistically different to bold numbers within one loading condition and the according flexion angleNon-parametric statistical analyses: Minimum, median and maximum mean contact pressure (CPStatistically different to bold numbers within one loading condition and the according flexion angleNon-parametric statistical analyses: Minimum, median and maximum contact area (CA) values in mmStatistically different to bold numbers within one loading condition and the according flexion angleNon-parametric statistical analyses: | PMC10276070 | ||
Discussion | knee flexion [A | The most important finding of this biomechanical in vitro study is that the ST meniscus autograft was able to significantly improve both the joint kinematics and the tibiofemoral contact parameters after LMM. To the best of the authors’ knowledge, this is the first study investigating the kinematic knee joint changes and the impact on lateral tibiofemoral contact mechanics after total LMM and total meniscus replacement by a single-bundle GT and doubled ST autografts, which were surgically applied in the manner of a meniscus allograft transplant. The most important kinematic finding of the present study was that the LMM-induced rotational instability of the knee joint which was seen during the application of no external moments and during the application of 1 Nm valgus could be restored by the application of the doubled ST meniscus autograft, whereas application of the GT autograft indicated only a positive trend. With respect to the detrimental impact of the LMM on the lateral tibiofemoral contact mechanics, again, the ST autograft was able to restore the CPIn addition to the ACL, the posterior horn of the lateral meniscus is a main rotation stabiliser of the knee joint, particularly during deep knee flexion [A recent review on the impact of different test setups and meniscal states on the tibiofemoral contact pressure indicated a major impact of the applied axial load on the CPRepresentative peak contact pressure (CPSeveral limitations must be considered when interpreting the results of the present study. First, the inherent in vitro study design only reflects time zero evaluations and cannot account for in vivo changes postoperatively after an autograft implantation procedure. On the basis of recent clinical results utilising the same autografting procedure [In the context of clinical applicability, the present biomechanical results need to be interpreted with care, because both, remodelling and failure mechanisms cannot be investigated by such an in vitro study. However, small animal [ | PMC10276070 | |
Conclusion | The doubled ST lateral meniscus autograft improved the knee joint kinematics significantly and restored the tibiofemoral contact mechanics almost comparable to the native situation. Thus, from a biomechanical point of view, ST meniscus autografts might be a potential treatment alternative for patients who are indicated for meniscus allograft transplantation.
| PMC10276070 | ||
Supplementary Information | Below is the link to the electronic supplementary material.Supplementary file1 (XLSX 35 KB)Supplementary file2 (XLSX 35 KB)Supplementary file3 (XLSX 27 KB)Supplementary file4 (XLSX 34 KB)Supplementary file5 (XLSX 34 KB)Supplementary file6 (PDF 529 KB)Supplementary file7 (DOCX 21 KB)Supplementary file8 (DOCX 21 KB) | PMC10276070 | ||
Acknowledgements | The authors acknowledge Patrizia Horny from the Institute of Orthopaedic Research and Biomechanics Ulm for her art design support. | PMC10276070 | ||
Author contributions | AMS | JL and TK performed the specimen preparation and the surgical interventions. AMS, JL and TK performed the joint simulator tests. JS performed the equilibration and calibration of the pressure sensors. JS performed the data extraction and conducted the statistical analyses. AMS drafted the manuscript. AI, HR and TK supported with expert knowledge and helped in drafting the manuscript. AMS and TK conceived the study. All authors read and approved the final manuscript. | PMC10276070 | |
Funding | Open Access funding enabled and organized by Projekt DEAL. This study was funded by the Deutsche Arthrose-Hilfe e.V. (P507). | PMC10276070 | ||
Data availability | All data generated or analysed during this study are included in this published article (and its supplementary information files). | PMC10276070 | ||
Declarations | PMC10276070 | |||
Conflict of interest | The authors declare that they have no competing interests. | PMC10276070 | ||
Ethical approval | The study design was approved by the institutional review board of the University of Ulm under reference number 37/20. | PMC10276070 | ||
Informed consent | No informed consent was required for this study. | PMC10276070 | ||
References | PMC10276070 | |||
ABSTRACT | PMC9924963 | |||
Purpose | metabolic syndrome, SB | METABOLIC SYNDROME, INSULIN SENSITIVITY | This study aimed to investigate whether a reduction in daily sedentary behavior (SB) improves insulin sensitivity in adults with metabolic syndrome in 6 months, without adding intentional exercise training. | PMC9924963 |
Methods | overweight and metabolic syndrome | Sixty-four sedentary inactive middle-age adults with overweight and metabolic syndrome (mean (SD) age, 58 (7) yr; mean (SD) body mass index, 31.6 (4.3) kg·m | PMC9924963 | |
Results | SB decreased by 40 (95% confidence interval, 17–65) min·d | PMC9924963 | ||
Conclusions | weight loss | ADIPOSITY, INSULIN SENSITIVITY | An intervention aimed at reducing daily SB resulted in slightly decreased fasting insulin, but had no effects on insulin sensitivity or body adiposity. However, as the change in insulin sensitivity associated with the changes in SB and body mass, multifaceted interventions targeting to weight loss are likely to be beneficial in improving whole-body insulin sensitivity. | PMC9924963 |
Key Words | SB, MetS, premature death, cluster of metabolic disorders, metabolic disorders | DISORDER, METABOLIC SYNDROME, CARDIOVASCULAR DISEASES, INSULIN RESISTANCE, METABOLIC DISORDERS, INSULIN RESISTANCE, TYPE 2 DIABETES | The associations between measured sedentary behavior (SB) and metabolic disorders as well as premature death are well established (Metabolic syndrome (MetS) is a lifestyle-related cluster of metabolic disorders that are associated with a sedentary lifestyle and a positive energy balance and can lead to type 2 diabetes and cardiovascular diseases (Insulin resistance is a gradually developing disorder and one of the early manifestations of type 2 diabetes, which can effectively be counteracted by exercise (The amount of SB can be reduced by different behavioral strategies. Previously, counseling interventions have been able to reduce daily SB by 24–91 min·dA weakness in the previously reported long-term interventions (i.e., interventions lasting for more than 3 months) is that the PA and SB of the study participants have been measured with devices only for approximately 5–10 d before and at the end of the intervention, and not during the whole follow-up (The purpose of this randomized controlled trial was to investigate whether replacing 1 h of daily SB with standing or PA, without adding exercise, would improve whole-body insulin-stimulated glucose uptake (GU) measured by HEC, body composition, and MetS status in sedentary inactive adults with MetS during 6 months. Previously, we have reported that after 3 months, the increases in plasma insulin, insulin resistance index, and glycated hemoglobin (HbA | PMC9924963 |
MATERIALS AND METHODS | This study was a randomized controlled trial in free-living conditions. The study was conducted at the Turku PET Centre, Turku, Finland, between April 2017 and March 2020 according to good clinical practice and the Declaration of Helsinki. The participants gave their informed consent before entering the study. The study was approved by the Ethics Committee of the Hospital District of Southwestern Finland (16/1810/2017). The study is registered at | PMC9924963 | ||
Study participants | The participants were recruited from the local community by newspaper advertisements and bulletin leaflets. The inclusion criteria for choosing the participants were as follows: age of 40–65 yr, body mass index (BMI) of 25–40 kg·m | PMC9924963 | ||
Anthropometric and metabolic measurements | MetS, fat-free mass | BLOOD, CREST | HEC was performed as previously described by Sjöros et al. (Venous blood samples were drawn after at least 10 h of fasting and analyzed at the Turku University Hospital Laboratory. Plasma insulin was determined by electrochemiluminescence immunoassay (Cobas 8000 e801; Roche Diagnostics GmbH, Mannheim, Germany). Plasma glucose was determined by enzymatic reference method with hexokinase GLUC3 and plasma triglycerides and HDL cholesterol by enzymatic colorimetric tests (Cobas 8000 c702; Roche Diagnostics GmbH). HbABody mass, body fat, and fat-free mass (FFM) were measured by air displacement plethysmography (Cosmed USA, Concord, CA) after at least 4 h of fasting. Body height was measured with a wall-mounted stadiometer. Waist circumference in 0.1 cm was measured with a flexible measuring tape midline between the iliac crest and the lowest rib, repeated twice or until the same measure was obtained twice. One researcher did all the waist circumference measurements. Blood pressure was measured with a digital blood pressure monitor (Apteq AE701f; Rossmax International Ltd, Taipei, Taiwan) in a seated position after at least 5 min of sitting. The mean of two to three measurements was used as the outcome measure. MetS score was calculated as the sum of | PMC9924963 |
Accelerometry | APE | SB and PA were measured during waking hours through the whole intervention with a hip-worn triaxial accelerometer (Movesense; Suunto, Vantaa, Finland) with embedded measurement and analysis algorithms (ExSed; UKK Institute, Tampere, Finland). The baseline SB and PA were measured for 4 wk at the screening phase with a hip-worn triaxial accelerometer (UKKAM30; UKK-institute, Tampere, Finland). The collected accelerometer data were analyzed in 6-s epochs using validated mean amplitude deviation (MAD) and angle for posture estimation (APE) methods. The epoch-wise MAD values were converted to metabolic equivalents (METs) (3.5 mL·kgThe body posture was determined with the APE method only for the epochs, which had a MET value lower than 1.5 (The step detection algorithm splits the measured acceleration into vertical and horizontal components. The vertical component is band-pass filtered (1–4 Hz), and positive values are integrated. When the integral value exceeds the specified limit, a step is detected (A period was classified as nonwear time, if the acceleration of each three measurement axes remained within 187.5-m | PMC9924963 | |
Intervention | After the baseline measurements, the participants were randomly allocated by a statistician to the INT and CONT groups using random permuted blocks with 1:1 allocation ratio and block size of 44, performed separately for men and women.The participants in the INT group received a 1-h tailored personal counseling session with a physiotherapist, where they were instructed to reduce their SB by 1 h·dThe CONT participants were instructed to maintain their habitual PA and SB during the intervention and received the mobile application and accelerometer. The goals for SB and PA in the application were set according to the baseline accelerometer measurements. Both groups were instructed not to alter their diet during the intervention, and this was assessed by 4-d food diaries before and at the end of the intervention. The mean daily energy intake was calculated with computerized software (AivoDiet 2.2.0.1; Aivo, Turku, Finland). The duration of the intervention was 5–6 months, after which all measurements done at the baseline were repeated. | PMC9924963 | ||
Statistical methods | The sample size was determined according to the following power calculations: Based on the earlier finding that GU was increased by 2.4 μmol·kg | PMC9924963 | ||
Additional analyses | We ran additional analyses by dividing the participants into two groups according to the changes in measured SB as a proportion of the daily wear time of the accelerometer. The participants who reduced their daily SB by at least three percentage points compared with the baseline (that equals about a 27-min reduction in SB with 15-h wear time) were defined as “more active” ( | PMC9924963 | ||
RESULTS | In total, 263 individuals volunteered, of which 155 participated in the screening measurements and 64 participants were included (Fig. S1, Supplemental Digital Content, Study flow diagram, Study participant characteristics at the baseline.Unless otherwise stated, the results are presented as mean (SD). The differences between groups were tested with DBP, diastolic blood pressure; fP-Glucose, fasting plasma glucose; fP-Insulin, fasting plasma insulin; HR, resting heart rate; MetS score, sum score of waist circumference, mean blood pressure, fasting plasma glucose, insulin, and the HDL/triglyceride ratio; M-value, whole-body GU in HEC; Q1, first quartile; Q3, third quartile; SBP, systolic blood pressure. | PMC9924963 | ||
Accelerometry | The mean (SD) duration of the intervention was 171 (36) d. Accelerometer data of 56 participants were successfully collected during the intervention with a median (Q1, Q3) duration of 117 (74, 142) d. The data collection of eight participants failed, one because of discontinued participation in the study and seven because of technical errors. During the intervention, SB decreased by approximately 40 min·dAccelerometer-measured PA and SB of the intervention (MVPA increased in the INT group by 20 min·dThe duration of the intervention period was split into quartiles, and data collection succeeded as follows: first quartile, Accelerometer-measured PA and SB of the intervention ( | PMC9924963 | ||
Anthropometric and metabolic outcomes | MetS | INSULIN SENSITIVITY | Body mass, BMI, and waist circumference decreased similarly in both groups (Fig. Anthropometric results of the intervention (Metabolic results of the intervention (Energy intake of the intervention (The change in insulin sensitivity was inversely associated with the changes in MetS score, BMI, body mass, fasting glucose, and SB percentage (Table Pearson correlation coefficients between the changes in different metabolic, cardiovascular, and PA markers (post–pre Δ values) during the intervention.Δ, the change from preintervention to postintervention measurements in metabolic and cardiovascular outcomes, and from screening to intervention in accelerometry outcomes; fInsulin, fasting plasma insulin, fGlucose, fasting plasma glucose; LPA, LPA measured by accelerometry; MetS score, MetS severity score (sum of waist circumference, mean blood pressure, fasting plasma glucose, insulin, and HDL/triglyceride-ratio); M-value, whole-body insulin-stimulated GU measured by HEC; MVPA, MVPA measured by accelerometry; SB, SB measured by accelerometry; WC, waist circumference.*Significant at the level of **Significant at the level of | PMC9924963 |
Additional analyses | INSULIN SENSITIVITY | When the participants were divided into two groups according to the changes in accelerometer-measured SB, insulin sensitivity increased in the more active group compared with the continuously sedentary group (Fig. Whole-body insulin-stimulated GU (M-value) measured by HEC in more active (accelerometer-measured SB decreased by at least 3 percentage points during intervention compared with screening, | PMC9924963 | |
DISCUSSION | In this study, a tailored intervention aimed to reduce SB by 1 h·d | PMC9924963 | ||
Insulin resistance | tissue damage, hyperinsulinemia | INSULIN RESISTANCE, HYPERINSULINEMIA | Insulin resistance is currently considered a protective mechanism against hyperglycemia-induced hyperinsulinemia in plasma and subsequent hyperglycemia-induced tissue damage ( | PMC9924963 |
Behavior change | This intervention was successful in reducing SB, but the mean change during the intervention (40 min·dThe intervention aimed at replacing SB with standing and nonexercise PA, but during the whole 6-month intervention, the participants were able to sustain only the increase in MVPA (consisting mainly of moderate-intensity PA), whereas during the first 3 months, the mean durations of LPA and standing also increased, as previously reported ( | PMC9924963 | ||
Effectiveness of replacing SB with PA in daily activities | overweight | INSULIN SENSITIVITY | Even if the amount of MVPA and step count significantly increased, the intervention was unable to enhance whole-body insulin sensitivity measured by HEC. The (nearly total) lack of VPA may be the reason that MVPA was not effective in improving insulin sensitivity in this study. It is possible that VPA rather than moderate PA is needed to gain health benefits in adults with overweight ( | PMC9924963 |
Methodological consideration | In some studies, metabolic markers or physical functioning have modestly improved even if no changes in device-measured SB were detected at the end of the intervention ( | PMC9924963 | ||
Strengths and limitations | weight loss | INSULIN SENSITIVITY | Key strengths of this study are the randomized controlled trial design, gold standard method for measuring whole-body insulin sensitivity, and the 6-month assessment of SB and PA by accelerometry. A limitation was that because of the nature of the intervention, blinding of the participants was not possible. Moreover, the food diaries were collected only twice, during 4 consecutive days (including one weekend day) before and at the end of the intervention. Detailed instructions were given and the diaries were checked with a portion picture booklet during a study visit to assure reliable reporting, but there is a risk for underreporting or altered dietary habits during data collection. According to the food diaries, energy intake did not change significantly in either group. However, the change in energy intake was correlated to the changes in body mass, BMI, and fasting plasma glucose. This may indicate that some participants (who either did or did not change their SB) possibly changed their diet, and this could have led to a weight loss or gain during the intervention, and also contributed to the plasma glucose levels. | PMC9924963 |
Clinical implications | Insulin sensitivity is a multifactorial phenomenon, and therefore, multifactorial lifestyle interventions with sufficient support and follow-up strategies can be expected to be successful ( | PMC9924963 | ||
CONCLUSIONS | MetS | INSULIN SENSITIVITY | Reducing 40 min of daily SB mainly by adding nonexercise PA seems not to be enough to improve whole-body insulin sensitivity in adults with MetS in 6 months, although it minimally decreased fasting insulin. Instead, multifaceted approaches with sustained changes in SB and PA behaviors including exercise and a healthy diet are more likely to be beneficial in the long term. | PMC9924963 |
Supplementary Material | PMC9924963 | |||
SUPPLEMENTARY MATERIAL | Diabetes | DIABETES | The authors thank the staff in the Turku PET Centre, University of Turku, and the laboratory personnel in the Turku University Hospital Laboratory for their proficient assistance in conducting the study. This study was conducted within the Centre of Excellence in Cardiovascular and Metabolic Research, supported by the Academy of Finland, the University of Turku, Turku University Hospital, and Åbo Akademi University.Dr. Knuuti received consultancy fees from GE Healthcare and AstraZeneca and speaker fees from GE Healthcare, Bayer, Lundbeck, Boehringer-Ingelheim, and Merck, outside of the submitted work. The other authors report no conflicts of interest in this work. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.Author contributions: I. H. A. H., K. K. K., J. K., T. V., and T. S. contributed to the conception and design of research; T. S., M. K., S. L., T. G., and N. H. performed the experiments; H. V.-Y., T. S., N. H., and E. L. analyzed the data; T. S. drafted the manuscript. All authors edited and revised the manuscript. All authors approved the final version of the manuscript.The study was financially supported by the Finnish Cultural Foundation, the Juho Vainio Foundation, Academy of Finland, the Hospital District of Southwest Finland, the Yrjö Jahnsson Foundation, the Turku University Foundation, Diabetestutkimussäätiö (the Finnish Diabetes Research Foundation), and TYKS-foundation.Data sharing: Data are available upon reasonable request from the corresponding author.Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site ( | PMC9924963 |
REFERENCES | PMC9924963 | |||
1. Introduction | hypoxia, FiOAltitude/hypoxic, infections, injuries | HYPOXIC, HYPOXIA, INFECTIONS | The aim of this study was to evaluate the effects of D-aspartic acid (DAA) supplementation during a simulated altitude protocol on the hormonal and hematological responses in athletes. We hypothesized that DAA supplementation would contribute to an increase in the luteinizing hormone (LH), free, and testosterone and a greater increase in hematological variables. Sixteen male boxers participated; they were randomly assigned to an experimental group (DAA) or a control group (C) and underwent 14 days of supplementation, 6 g/day of DAA. Both DAA and C participants were exposed to normobaric hypoxia (FiOAltitude/hypoxic training has been used for many years to improve exercise capacity in athletes. A number of concepts have been developed for using hypoxic conditions to improve performance in various sports. Popular methods include the live high–train low (LH–TL) protocol, where athletes live in hypoxic conditions at moderate altitudes (2000–2500 m above sea level, or a.s.l.) for 10–12 h a day (chiefly in the evening and at night) and train in normoxia, with normal oxygen availability [The improvement in hematological variables expected from the use of LH–TL depends on many factors, including the duration of exposure to hypoxia and the intensity of the hypoxic stimulus, body iron stores in athletes, injuries and infections, and the anabolic–catabolic balance in the body [Testosterone (T) has been proven to stimulate the hematopoietic system by increasing erythropoietin synthesis and secretion, acting on erythroid cells in the bone marrow, improving iron absorption and transport, stimulating iron incorporation into erythrocytes, increasing hemoglobin synthesis, prolonging erythrocyte survival time, and increasing 2,3-diphosphoglycerate (2,3-DPG) levels in red blood cells [One legal substance being considered as an ergogenic aid to support T production is D-aspartic acid (DAA). D-aspartic acid (DAA) is a natural amino acid found in many tissues (including the brain, nervous system, endocrine glands, liver, ovaries, and testes), where it acts as a signaling factor [So far, few human studies have investigated the effects of DAA supplementation on T levels, and their findings have been inconsistent. Some studies showed that ingesting 3 g/day of DAA for a period of 14–28 days had no effect on blood levels of total and/or free testosterone (T and fT) in trained men [To date, the scientific literature lacks sufficient reports on the use of DAA to promote hematological adaptations during altitude/hypoxic training in athletes. Hence, the present study aims to address this specific issue. Based on the above research results and theoretical underpinnings, this study investigated the following hypotheses: (1) DAA supplementation of 6 g/day would contribute to an increase in the blood concentration of LH, free testosterone (fT), and T in the participants; and (2) DAA supplementation during the LH–TL protocol results in a greater increase in the changes in hematological variables induced by hypoxic exposure. | PMC10780457 |
2. Materials and Methods | PMC10780457 | |||
2.1. Study Participants | This study involved 16 young men (aged 18 to 25 years) participating in competitive, Olympic-style boxing. The inclusion criteria required a minimum of a six-month washout period from previous altitude/hypoxic training and baseline blood testosterone levels within the age-specific reference range.The participants were randomly assigned to the experimental group (DAA) and the control group (C) and underwent 14 days of supplementation. The DAA group (n = 8; age = 20.6 ± 2.1 years; height = 177.5 ± 1.7 cm; body mass = 75.1 ± 8.1 kg; % body fat = 10.5 ± 2.3; VOAll participants had current valid medical examinations confirming they were in good health and could practice sports. Before commencing this study, all participants were informed about the purpose and course of this study and provided their written consent to participate. The athletes were also informed that they could withdraw from this study at any time without needing to provide a reason. Additionally, participants declared that for at least one month before testing, they had not taken any medications or dietary supplements. This study was approved by the ethics committee of the Institute of Sport—National Research Institute in Warsaw (No. KEBN-22-73-KP, 2 November 2022). | PMC10780457 | ||
2.2. Study Design | hypoxia | HYPOXIA | The experiment consisted of four study series (S1 to S4). S1 involved baseline tests before the start of supplementation and LH–TL training. S2 took place after the fourth day of supplementation and after the first night of exposure to hypoxia. S3 was conducted after the ninth day of supplementation and after the sixth night of the LH–TL protocol. Finally, S4 was performed immediately after the last night of the LH–TL protocol and the last day of supplementation. The study design is shown in During each study series, venous blood samples (10 mL) collected from the basilic vein were obtained from the participants in the morning (7.30 a.m.) under fasting conditions. Two samples of venous blood were then collected at each time point on the 5th, 10th, and 15th day of the experiment, always after an active rest day. Of each pair of samples, one was drawn using an ethylenediaminetetraacetic (EDTA) tube (for morphology analysis); the other was drawn using an anti-coagulant tube and processed for serum for the other biochemical assays (T, fT, C, and LH). Creatine kinase (CK) activity was determined immediately after blood collection (Piccolo Express Chemistry Analyzer, Abaxis, Union City, CA, USA). After 30 min, blood samples were centrifuged at 1500× | PMC10780457 |
2.3. DAA Supplementation | hypoxia | HYPOXIA | During this study, the participants in the DAA group took 6 g/day of DAA in the form of gelatin capsules for 14 days. The dose was divided into equal portions and administered twice a day at similar intervals. In turn, participants in the C group received a placebo (cellulose) in identical gelatin capsules, with the dose similarly divided into two equal portions. Participants were not aware of which substance they were ingesting. Supplementation began four days before the first exposure to hypoxia and continued throughout the whole of the LH–TL training period. D-aspartic acid (DAA) dose and supplementation time were selected based on the methodologies of previous studies regarding the ergogenic effects of DAA [ | PMC10780457 |
2.4. LH–TL Protocol and Conditioning Training | hypoxia | HYPOXIA | During this study, both DAA and C participants were subjected to continuous hypoxia for 10–12 h a day over a period of 11 days. In the rooms where the participants stayed in the evening and at night, the fraction of inspired oxygen (FiOThe training program consisted of two basic microcycles (weeks) with progressively increasing loads, which were equal in both groups ( | PMC10780457 |
2.5. Diet during the Experiment | dehydration | DEHYDRATION | As mentioned above, throughout the experiment, all athletes lived at the same accommodation and followed the same training schedule, sleeping time, and diet. During the experiments, the participants consumed a controlled mixed diet (50% CHO, 20% Fat, 30% Pro). Daily energy intake was set at 3500–4000 kcal (depending on the day), and the protein dose varied from 1.6 to 1.8 g/kg of body mass. During the experiment, the athletes consumed an isotonic sports drink or plain water. The dehydration level was assessed using Osmocheck calibrated in mOsm/kg H | PMC10780457 |
2.6. Statistical Analysis | The results of the experiment were analyzed using StatSoft Statistica 13.0 software. The results are presented as arithmetic means (x) with standard deviations (SD). The Lilliefors test was used to demonstrate the consistency of the results with normal distribution. The intergroup differences between consecutive research series were determined using a two-way ANOVA (group and training) with repeated measures. The significance of differences between individual research series (differences between series of testing) in the study groups was calculated using Tukey’s post hoc test. The area under the curve (AUC) for T and fT levels was calculated using the trapezoid method. Significant differences for AUC values between groups were determined using the one-way analysis of variance (ANOVA). The significance of differences between the study groups was calculated based on the post hoc Tukey’s test. The relationships between AUC for T and fT levels and changes in selected hematological variables were analyzed using the Pearson’s correlation coefficient. Statistical significance was set at | PMC10780457 | ||
3. Results | PMC10780457 | |||
3.1. Hormonal Response | The analysis of variance (ANOVA) showed no statistically significant group × training interactions for changes in resting values of T, fT, C, or LH following DAA supplementation compared to the control group. However, ANOVA revealed a statistically significant effect of training on changes in T levels (F = 12.572, | PMC10780457 | ||
3.2. Hematological Response | The statistical analysis showed no significant group × training interactions for changes in resting values of red blood cell count (RBC), hemoglobin concentration (HGB), hematocrit (HCT), or blood reticulocyte percentage (Ret) following DAA supplementation compared to the control group ( | PMC10780457 | ||
3.3. Training Loads and Changes in Blood Creatine Kinase (CK) Activity | TSS | The statistical analysis showed no significant differences in training load (TSS; 2038 ± 54—DAA group vs. 2068 ± 43—C group) in the study groups. Additionally, ANOVA showed no statistically significant group × training interactions for changes in CK activity in the blood during the experiment. However, ANOVA revealed a statistically significant effect of training on changes in CK activity (F = 24.268 | PMC10780457 | |
4. Discussion | hypoxia, fatigue | HYPOXIC, HYPOXIA | A high T blood concentration and a favorable T/C ratio are considered important factors influencing the effectiveness of altitude training [The results of our study showed that a 2-week DAA supplemental protocol (6 g per day) did not cause significant beneficial changes in blood testosterone (T, fT) concentration during LH–TL and did not affect the effectiveness of hypoxic exposure in terms of hematological changes in relation to the control group. We showed that in both groups, after the first night spent in hypoxic conditions (after 4 days of supplementation), there was an approx. 20% increase in T concentration in the blood. No significant changes in fT, LH, or C were noted. Changes in the T/C ratio were also observed. Initially, after 12 h of exposure to hypoxia (S2), there was a significant increase in T/C in the DAA group compared to the baseline studies. Notably, the changes in the C group had the same trend, but they were not statistically significant. The increase in the T/C ratio in the DAA group was temporary, and on the following days of the LH–TL protocol (S3 and S4), the T/C values no longer differed significantly from the baseline. In our opinion, the decrease in T/C values during S3 and S4 compared to the S2 measurement was due to the increasing fatigue of the subjects, as evidenced by significant changes in CK activity, as well as an increase in C concentration in the blood.The observed increase in T concentration in the blood during S2 was the effect of 12 h of hypoxic exposure of the subjects, not the effect of the introduced DAA supplementation. Recently, Oyedokun et al. [Our study results, indicating that DAA supplementation does not affect T or fT concentrations, are consistent with previous studies involving male athletes using various DAA doses (1.78 to 6 g per day) over different dosing periods (from 2 to 12 weeks) [As mentioned above, the ineffectiveness of DAA was previously explained by the autoregulatory control of the HPG axis, which may limit endogenous T production when it approaches or exceeds a certain individual threshold. The results of our study suggest that the autoregulatory control of the HPG axis depends on the strength of the stimulus. Our study found that after exposure to normobaric hypoxia, there was a significant increase in blood T concentration in the studied groups. The lack of change in T concentration after DAA supplementation, on the other hand, suggests that the stress caused by hypoxia seems to be a much stronger stimulus in this regard than the effect of DAA.The only potentially beneficial change observed in our study resulting from DAA supplementation appears to be a significantly higher T concentration (by 15% vs. baseline) after 6 nights of the LH–TL protocol (after 9 days of supplementation), despite the accumulation of training loads. In the control group, the T concentration at this time tended to return to baseline values. Additionally, in the control group, on the 5th and 10th days of the experiment, the level of fT in the blood reached values lower than the baseline. In the DAA group, on the other hand, despite increasing fatigue over the consecutive days of training, the fT did not change. However, further analysis of the area under the curve (AUC) for T and fT concentrations in the blood during the entire intervention period did not show significant differences between the DAA and control groups. These findings allow us to conclude that the applied DAA supplementation did not cause significant beneficial changes in blood testosterone concentration during the given LH–TL protocol. In our opinion, the observed changes in the rate of return of T and fT concentrations to baseline values during training are most likely the result of the different reactivity of the subjects to hypoxic conditions and the imposed training loads rather than the effect of DAA.As regards hematological changes, we observed a small but significant ( | PMC10780457 |
5. Study Limitations | hypoxia, ’ | HYPOXIA | To the best of our knowledge, our study is the first in which the effect of DAA supplementation was assessed in normobaric hypoxia during the LH–TL protocol. Our experiment, however, is not without certain limitations. Firstly, we did not measure the levels of the analyzed indicators immediately before the initial exposure to hypoxia. An additional point of measurement would have allowed for a precise determination of whether there was a change in blood T levels after 4 days of DAA supplementation and whether the rise in T levels during S2 was due to hypoxia alone or the combined influence of DAA and hypoxia. However, logistical constraints (related to the athletes’ arrival at the training camp) prevented us from taking measurements on that particular day. Secondly, it would have been advantageous to determine the concentrations of DAA and D-aspartate oxidase in the blood. Such data would enable us to understand if oral DAA supplementation significantly alters the levels of DAA and D-aspartate oxidase in the blood. Future research should also consider a longer DAA supplementation period prior to altitude training and possibly using a 3 g/day dosage, as there are some indications that a 6 g/day dosage may lead to reduced T and fT concentrations [ | PMC10780457 |
Author Contributions | Conceptualization: K.P. and M.C.; methodology: K.P., M.C. and R.G.; investigation: K.P., M.C. and R.G.; database collection: K.P., M.C. and A.Z.; statistical analysis: K.P. and M.C.; writing—original draft: K.P. and M.C.; writing—review and editing: K.P., M.C., A.Z. and R.G.; resources: K.P., M.C. and R.G.; funding acquisition: R.G. and A.Z. All authors contributed to manuscript’s revision. All authors have read and agreed to the published version of the manuscript. | PMC10780457 | ||
Institutional Review Board Statement | POLAND | This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Institute of Sport—National Research Institute in Warsaw, Poland (No. KEBN-22-73-KP, 2 November 2022). | PMC10780457 | |
Informed Consent Statement | Informed consent was obtained from all subjects involved in this study. | PMC10780457 | ||
Data Availability Statement | The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy. | PMC10780457 |
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