title stringlengths 1 1.19k | keywords stringlengths 0 668 | concept stringlengths 0 909 | paragraph stringlengths 0 61.8k | PMID stringlengths 10 11 |
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2. Materials and Methods | PMC10608521 | |||
2.1. Study Design and Subjects | obesity, Obesity | OBESITY, PEDIATRIC OBESITY, OBESITY, DISEASE | We conducted a cross-sectional comparative study that was a branch of a randomized clinical trial where the main objective was to evaluate several physical activity interventions in pediatric patients with obesity who were included in a multidisciplinary lifestyle change intervention program.Children and adolescents ag... | PMC10608521 |
2.2. Measurements | PMC10608521 | |||
2.2.1. Anthropometry | CREST | The measurements were performed by trained pediatricians and nutritionists after a standardization procedure. Total body weight was measured relative to participants dressed in light clothes, and a mechanical column scale was used (to the nearest 0.1 kg); standing height was measured using a standard stadiometer board ... | PMC10608521 | |
2.2.2. Biochemical Evaluation | INSULIN SENSITIVITY | After 12 h of fasting, a venous blood sample was obtained to measure alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-Chol), low-density lipoprotein cholesterol (LDL-Chol), and triglycerides (Tg) usin... | PMC10608521 | |
2.2.3. Evaluation of Liver Steatosis and Fibrosis | steatosis, Liver steatosis, hepatic abnormalities, fibrosis | STEATOSIS, LIVER STEATOSIS, FIBROSIS | Liver steatosis and fibrosis were estimated using transient elastography (Fibros canThree groups were categorized according to hepatic abnormalities evaluated using Fibroscan: non-MASLD (children without steatosis and fibrosis), MASLD (children with steatosis and without fibrosis), and MASLD + fibrosis (children with s... | PMC10608521 |
2.2.4. Targeted Metabolomic Determinations | AC18OH | A targeted metabolome analysis was carried out, including glucose, free carnitine, acylcarnitines (AC2, AC3, AC4, AC5, AC5:1, AC6, AC8, AC8:1, AC10, AC10:1, AC10:2, AC12, AC12:1, AC14, AC14:1, AC14:2, AC14OH, AC16, AC16:1, AC16:1OH, AC16OH, AC18, AC18:1, AC18:1OH, AC18:2, and AC18OH), arginosuccinate (ASA), and 12 L-am... | PMC10608521 | |
2.3. Statistical Analysis | fibrosis | REGRESSION, FIBROSIS | To describe the studied population, the mean and standard deviations (SD) were estimated for continuous variables, and proportions and frequencies were calculated for categorical variables. To evaluate the differences between groups (non-MASLD, MASLD, and MASLD + fibrosis), ANOVA and exact Fisher tests were performed, ... | PMC10608521 |
3. Results | fibrosis | EARLY PUBERTY, FIBROSIS | A total of 79 children and adolescents were included in the study; of them, 52.7% were female with a mean age of 11.74 ± 2.52 years. For males, the mean age was 10.66 ± 1.71. Of the total sample, 39% were classified as prepubertal, 32.4% belonged to the early puberty group, and 28.4% belonged to advanced puberty. There... | PMC10608521 |
3.1. Metabolic Phenotypes According to the Progression of MASLD | PMC10608521 | |||
3.1.1. Non-MASLD and MASLD | The hierarchical heatmap ( | PMC10608521 | ||
3.1.2. Non-MASLD and MASLD + Fibrosis | The hierarchical heatmap ( | PMC10608521 | ||
3.1.3. MASLD and MASLD + Fibrosis | fibrosis | FIBROSIS | Once the phenotypes for MASLD and MASLD + fibrosis were established, we aimed to identify the differences between MASLD and MASLD + fibrosis. The heatmap showed that children with MASLD + fibrosis had higher concentrations of methionine, leucine, glycine, alanine, proline, arginine, phenylalanine, ornithine, citrulline... | PMC10608521 |
4. Discussion | obesity, MASLD (hepatic steatosis, fibrosis, hepatic and muscle glucose, hepatic abnormalities, hepatic damage, steatosis | OBESITY, FIBROSIS, PATHOPHYSIOLOGY, REMISSION, HEPATIC STEATOSIS, HEPATIC DAMAGE, REGRESSION, HEPATIC FIBROSIS, STEATOSIS | In the present study, we described the metabolomic phenotypes associated with two stages of MASLD progression (MASLD (hepatic steatosis) and MASLD + fibrosis (hepatic steatosis + fibrosis)) in Mexican children with obesity compared to those with obesity but without MASLD. According to logistic regression models, MASLD ... | PMC10608521 |
5. Conclusions | obesity, metabolic alterations | OBESITY, PATHOLOGY, DYSFUNCTION | According to our findings, MASLD phenotype changes as this dysfunction progresses, involving a switch in amino acid use. The assessment of ALT, proline, alanine, and Matsuda Index could be considered as metabolic signatures of MASLD in children living with obesity. However, more studies are necessary to broaden the kno... | PMC10608521 |
Author Contributions | N.G.-N.: Conceptualization, methodology, investigation, data curation, writing—original preparation, review and editing, visualization, project administration, and funding acquisition. K.P.-E.: Investigation, data curation, and project administration. I.O.-G.: Formal analysis, writing—original preparation, and review a... | PMC10608521 | ||
Institutional Review Board Statement | The study was approved by the Hospital General de Mexico’s Research, Ethics and Biosafety for Human Research Committees (Number DI/17/311/03/028; Approval date: 19 April 2017), was conducted in accordance with the 1975 and 2013 Declaration of Helsinki, and adhered to the Good Clinical Practice Guidelines issued by the ... | PMC10608521 | ||
Informed Consent Statement | Informed consent was obtained from all subjects involved in the study. | PMC10608521 | ||
Data Availability Statement | The data presented in this study are available upon request from the corresponding author. | PMC10608521 | ||
Conflicts of Interest | The authors declare no conflict of interest. | PMC10608521 | ||
References | fibrosis | REGRESSION, FIBROSIS | Serum metabolite and biochemical profile in children with MASLD. (Serum metabolite and biochemical profile in children with MASLD + fibrosis. (Serum metabolite and biochemical profile in children with MASLD. (Demographic, clinical, biochemical, and metabolomic characteristics of children enrolled in the study.The Evalu... | PMC10608521 |
Key summary points | PMC10169200 | |||
Aim | Does a multicomponent agility training improves handgrip strength (maximum force and rate of force development) in healthy older adults and what is the link between handgrip strength dimensions and agility in healthy older adults? | PMC10169200 | ||
Findings | Neither maximum handgrip strength nor rate of force development of handgrip strength in healthy older adults is influenced by a 1-year multicomponent agility training. However, maximum handgrip strength and rate of force development are associated with agility performance measured via the agility challenge for the elde... | PMC10169200 | ||
Message | Handgrip strength is not influenced by multicomponent agility training but could serve as an indicator for agility performance in older adults. | PMC10169200 | ||
Purpose | Handgrip strength is considered as important indicator for general fitness in older adults. However, it does not notably reflect adaptations from whole-body training but may reflect adaptions of multicomponent exercise training. These approaches seem to be more functional and related to relevant daily tasks. Effects of... | PMC10169200 | ||
Methods | Healthy older adults ( | PMC10169200 | ||
Results | Neither maximum handgrip strength (F | PMC10169200 | ||
Conclusion | A 1-year multicomponent agility training does not affect handgrip strength in healthy older adults. However, handgrip strength (F | PMC10169200 | ||
Keywords | Open Access funding enabled and organized by Projekt DEAL. | PMC10169200 | ||
Introduction | sarcopenia | DISEASES, SARCOPENIA | Measuring maximum isometric handgrip strength is common in the field of gerontology as it is considered as an important vitality surrogate for general fitness, cognitive status, frailty and sarcopenia in older adults [The effect of general exercise training and physical activity on handgrip strength is merely small to ... | PMC10169200 |
Method | The present study is a two-armed randomized controlled intervention trial over 1 year. All participants were informed about the procedures and provided informed written consent. The study is in accordance with the Declaration of Helsinki, and received ethical approval of the German Sport University (no. 31/2018). Anthr... | PMC10169200 | ||
Intervention | IG took part in multicomponent agility training (strength, coordination, start-stop movements and change of directions, dual task and decision-making tasks) twice a week on non-consecutive days for 1 year. The total training volume was around 90 sessions and adherence of the participants ranged between 56 and 91% (mean... | PMC10169200 | ||
Measurements | PMC10169200 | |||
Handgrip strength (HGS) | Handgrip strength (FData were computed using the software IsoTest (version 2.0, meachTronic, Hamm, Germany). Measurements were conducted with a 100 Hz sample rate. Maximum handgrip strength measured in Newton is the highest force value participants could reach. Out of the three trials, the mean of the two best trials w... | PMC10169200 | ||
Agility challenge for the elderly (ACE) | As a functional and integrative test for neuromuscular and cardiocirculatory capacity, the ACE course was assessed. The detailed description of the course and its three segments (i) start-and-stop movements, (ii) change of direction and (iii) spatial orientation can be found elsewhere [ | PMC10169200 | ||
Statistical analysis | All data were checked for normal distribution using the Shapiro–Wilk-test. A mixed ANOVA (2 (group: IG vs. CG) × 2 (time: pre vs. post) was computed to analyse the time × group interaction effect of maximum handgrip strength and rate of force development. Post-hoc testing was done in case of a statistical significant i... | PMC10169200 | ||
Results | PMC10169200 | |||
Handgrip strength | PMC10169200 | |||
Rate of force development of handgrip strength | Repeated measurements ANOVA for handgrip strength RFD (see Table | PMC10169200 | ||
ACE course | Comparing pre (M = 50.7; SD = 6.8) and post (M = 46.3; SD = 5.0) measurement, participants were significantly faster in completing the course ( | PMC10169200 | ||
Correlation analysis | Spearman correlation for ACE and maximum handgrip strength (r(64) =− 0.367, Spearman correlation for time to complete ACE challenge (in seconds) and | PMC10169200 | ||
Author contributions | BKL performed parts of the measurement, did the statistical analysis and wrote the manuscript in consultation with LD. | PMC10169200 | ||
Funding | Open Access funding enabled and organized by Projekt DEAL. This research received no specific Grant from any funding agency in the public, commercial, or not-for-profit sectors. | PMC10169200 | ||
Data availability | All data analysed during this study are included in this article. Further enquiries can be directed to the corresponding author. | PMC10169200 | ||
Declarations | PMC10169200 | |||
Conflict of interest | All authors declare that they have no conflicts of interest. | PMC10169200 | ||
Ethical approval | All participants were informed about the procedures and provided written informed consent. The study is in accordance with the Declaration of Helsinki, and got an ethical approvement of the German Sport University (no. 31/2018). | PMC10169200 | ||
Informed consent | All participants were informed about the procedures and provided informed written consent. | PMC10169200 | ||
References | PMC10169200 | |||
Background | SKIN CONDITION, PERISTOMAL SKIN COMPLICATION | Peristomal skin complications (PSCs) pose a major challenge for people living with an ostomy. To avoid severe PSCs, it is important that people with an ostomy check their peristomal skin condition on a regular basis and seek professional help when needed. | PMC10734405 | |
Aim | To validate a new ostomy skin tool (OST 2.0) that will make regular assessment of the peristomal skin easier. | PMC10734405 | ||
Methods | Seventy subjects participating in a clinical trial were eligible for the analysis and data used for the validation. Item-level correlation with anchors, inter-item correlations, convergent validity of domains, test-retest reliability, anchor- and distribution-based methods for assessment of meaningful change were all p... | PMC10734405 | ||
Results | A final tool was established including six patient reported outcome items and automatic assessment of the discolored peristomal area. Follow-up with cognitive debriefing interviews assured that the concepts were considered relevant for people with an ostomy. | PMC10734405 | ||
Conclusion | COMPLICATIONS | The OST 2.0 demonstrated evidence supporting its reliability and validity as an outcome measure to capture both visible and non-visible peristomal skin complications. | PMC10734405 | |
Introduction | LEAKAGE, SKIN, COMPLICATION, SKIN CONDITION, LEAKAGE, COMPLICATIONS | A compromised skin barrier in the peristomal area can be detrimental to people living with an ostomy. Findings from a recent systematic literature review demonstrated that peristomal skin complications (PSCs) are the most frequent post-operative complication associated with creation of an ostomy (Leakage (ostomy output... | PMC10734405 | |
Materials & Methods | PMC10734405 | |||
Study design | COMPLICATION | Data for the psychometric validation study was obtained from a randomized controlled, open-label, comparative, cross-over, multicenter investigation (Clinical Trial ID: NCT04101318). This investigation was carried out in four countries including United Kingdom (UK), Germany, Italy, and Norway. Subjects were eligible fo... | PMC10734405 | |
Patient reported outcome (PRO) questionnaire | itching,, pain | The new OST 2.0 comprises a PRO questionnaire consisting of six items designed to assess the severity of PSCs (The remaining three items (Q4–Q6) assess symptoms of itching, pain, and burning (sensation symptoms). For each symptom, the corresponding item asks the subject to rate the severity of the symptom at its worst ... | PMC10734405 | |
Peristomal skin image analysis | Image analysis techniques were applied to pictures of peristomal skin taken by the subjects to quantify the total area of discolored skin. Specifically, this was an automated assessment using an algorithm based on artificial intelligence ( | PMC10734405 | ||
Decision tree model scoring | SKIN CONDITION, COMPLICATIONS | The PRO questionnaire and image analysis data were combined in a Decision Tree model to provide an overall score between the score 0–3 representing the severity level of skin complications for each patient. A composite score of 0 represents no treatment required peristomal skin condition and the score of 3 is represent... | PMC10734405 | |
Anchor measures | stoma, ’ | EROSION, COMPLICATIONS | For the psychometric evaluation, five anchor measures were included. After review of the literature for gold standard measures to use as anchor measures, it was deemed there were none that were appropriate for use. As such, new items were developed in line with US FDA guidance (For the PGIS anchor, subjects were initia... | PMC10734405 |
Psychometric validation | Data for the psychometric validation was derived from 70 eligible subjects participating in the clinical investigation (Clinical Trial ID: NCT04101318). Although the study was a cross-over design, only data from the first test period was used (Visit 1 and Visit 2) with exception of the subpopulation eligible for the te... | PMC10734405 | ||
Analysis | All analyses were pre-defined in a statistical analysis plan prior to conducting psychometric evaluation and conducted using SAS software (SAS Institute Inc. Cary, NC, USA). The psychometric evaluation was conducted in accordance with European Medicines Agency and US Food & Drug Administration (FDA) best practice guide... | PMC10734405 | ||
Item-level correlations with anchors | To evaluate the properties of the individual items, the relationships with anchor measures was explored. Specifically, correlations with the PGIS anchor were explored, and correlations were calculated using data collected at Visit 2, where the PRO data used was from the closest assessment to Visit 2 (provided this was ... | PMC10734405 | ||
Inter-item correlations | Inter-item correlations were used to explore the relationships among the PRO items. Inter-item correlations were determined using correlation coefficients appropriate for the variables in question between each pair of items at Visit 1. Due to the complexity and variety of the data of interest, using a single type of co... | PMC10734405 | ||
Convergent validity of domains | The convergent validity method was applied to evaluate the construct validity and correlation between the different measures ( | PMC10734405 | ||
Test-retest reliability | bleeding, ulcer, ’ | BLEEDING, ULCER | Test-retest reliability was used to evaluate the stability of the PIB score and the Decision Tree score in relation to the PGIS, PGIC, CGIS, and CGIC anchor. Moreover, the stability of the weeping, bleeding, and ulcer items were evaluated using the same four anchors. The test-retest reliability measured the degree to w... | PMC10734405 |
Known-groups analysis | stoma, ’ | COMPLICATIONS | The PIB score and the Decision Tree score were evaluated in patients who differed on variables hypothesized to influence the construct of interest. The magnitude of differences in scores characterized the degree to which the PIB score/Decision Tree score could distinguish among groups hypothesized a priori to be clinic... | PMC10734405 |
Ability to detect change | The ability of a score to detect change over time was assessed using data from the measurement periods associated with Visit 1 and Visit 2 in the psychometric analysis population. To investigate the ability of the PIB score to detect change, subjects were grouped according to the PGIC anchor and categorized into ‘Impro... | PMC10734405 | ||
Anchor-based methods for assessing meaningful change | COMPLICATIONS | Anchor-based methods were conducted to establish the level of change which could be considered meaningful for the domains. For this analysis, both PIB weekly mean and PIB weekly maximum scores were assessed alongside the Decision Tree score. The anchor-based analyses were performed in the psychometric analysis populati... | PMC10734405 | |
Distribution-based methods for assessing meaningful change | A distribution-based approach was employed, and these methods consisted of computing the SD and the standard error of measurement (SEm) ( | PMC10734405 | ||
Results | PMC10734405 | |||
Sociodemographic profile | The psychometric analysis sample was comprised of a total of 70 subjects living with an ostomy. There was an even distribution between females (51%) and males (49%), and the population had a mean age of 55.3 years ( | PMC10734405 | ||
Sociodemographic profile of subjects. | The psychometric analysis population was comprised of 70 subjects living with an ostomy. Data shows distribution of samples according to gender, age, and type of ostomy. | PMC10734405 | ||
Item-level correlations with anchors | The severity items were correlated with the PGIS anchor. | PMC10734405 | ||
Item-level correlations. | bleeding | BLEEDING | The correlations of the six items were determined by calculating the relevant correlation coefficient based on the PGIS anchor (Based on the applied cut-off values, five out of six items demonstrated a moderate or strong correlation with the PGIS anchor. The item regarding bleeding (item 1) showed a 0.266 correlation c... | PMC10734405 |
Inter-item correlations | itching, pain | To explore how the items could be grouped into domains, the inter-item correlations were examined among the items assessing itching severity, pain severity, and burning severity (item 4, 5, and 6). As depicted in | PMC10734405 | |
Inter-item correlations for severity items. | bleeding, itching, pain | BLEEDING | The Pearson’s correlation coefficient was determined for the itching severity, pain severity, and burning severity items. The weeping, bleeding, and ulcer/sore items were also subject to inter-item correlation analysis. All correlation among those items were poor; thus, the weeping, bleeding, and ulcer/sore items were ... | PMC10734405 |
Convergent validity of domains | In addition to the composite outcome score of the OST 2.0, namely the Decision Tree score, the PIB domain was also taken through for further validation at the domain level. The PGIS and DET score were the two anchors used for assessing convergent validity of the two domains. When determining the polyserial correlation ... | PMC10734405 | ||
Convergent validity of domains. | The polyserial correlation coefficient was determined for correlation of the PIB score (weekly mean) and the PGIS anchor ( | PMC10734405 | ||
Test-retest reliability | The ICC can be interpreted as the correlation between repeatedly measured scores within subjects, where higher values indicate greater stability in scores. The test-retest reliability was investigated for the PIB score (weekly mean) and the Decision Tree score. The PIB score demonstrated good reliability when using the... | PMC10734405 | ||
Test-retest reliability of weekly mean domain scores between the two visits. | bleeding | BLEEDING | The test-retest reliability of the PIB score (weekly mean) and Decision Tree score were evaluated by calculating the intraclass correlation coefficient (ICC). Data is listed with 95% confidence intervals displayed in brackets. For the number of subjects, data is displayed as n (PIB score)/n (Decision Tree score). The f... | PMC10734405 |
Test-retest reliability of bleeding, weeping, and ulcers/sores items. | bleeding | BLEEDING | The test-retest reliability the bleeding, weeping, and ulcers/sores items were evaluated by calculating the intraclass correlation coefficient (ICC). Data is listed with 95% confidence intervals displayed in brackets. The number of subjects used for the analysis is displayed (n). The following cut-offs were applied: IC... | PMC10734405 |
Known-groups analysis | The known-groups analysis of the PIB score and the Decision Tree score was evaluated by comparing groups defined based on the PGIS anchor. When evaluating the differences in PIB mean scores between the three groups, Group 1 (reference) showed a mean score of 1.5, while group 2 and 3 demonstrated a mean score of 1.9 and... | PMC10734405 | ||
Known-groups analysis of the domain scores. | COMPLICATIONS | Known-groups analysis was investigated for the PIB score (weekly mean) and for the Decision Tree score. Subjects were divided into three groups depending on presence and severity of peristomal skin complications. Using the PGIS anchor, the between group effect sizes (ES) were estimated using the pooled standard deviati... | PMC10734405 | |
Ability to detect change | The ability of the PIB score to detect change was investigated by using the PGIC anchor to define change groups, while the ability of the Decision Tree score to detect change was evaluated by comparison with the CGIS anchor. The mean change score was assessed for the three groups of subjects. For the PIB score, the cha... | PMC10734405 | ||
Ability to detect change of domain scores. | The ability of the PIB score (weekly mean) to detect change was evaluated by use of the PGIC anchor, while the ability of the Decision Tree score to detect change was investigated by comparison with the CGIS anchor. Subjects were divided into three groups depending on their progression from Visit 1 to Visit 2. These gr... | PMC10734405 | ||
Anchor-based methods of score interpretation | To establish an estimate for a meaningful change in domain score, a correlation between the anchor and the change in domain scores of | PMC10734405 | ||
Meaningful change estimates for domain scores. | Meaningful change estimates for the PIB weekly mean and PIB weekly maximum domains were calculated using the PGIC anchor. For the Decision Tree score, the CGIS anchor was used instead. The correlation between the anchor and the change in domain score was determined by calculating polyserial correlation coefficient. Sub... | PMC10734405 | ||
Distribution-based methods of score interpretation | In addition to the anchor-based methods, distribution-based methods were also used to determine a meaningful change for the domain scores. These methods aimed to identify the smallest amount of change which exceeded measurement errors. Thus, the distribution-based estimates, in the form of 0.5 SD and the SEm, were calc... | PMC10734405 | ||
Distribution-based estimates for PIB weekly mean and PIB weekly maximum. |
The distribution-based estimates were determined for the PIB weekly mean and PIB weekly maximum domain. The estimates were 0.5 of the SD and the SEm.
standard deviationstandard error of measurementintraclass correlation coefficient | PMC10734405 | ||
Discussion | bleeding, itching, pain | BLEEDING | The OST 2.0 was designed to evaluate the severity of PSCs within the ostomy population, and the Decision Tree score offers a simple and evidence-based categorization of PSC severity (Despite the continuous development of improved ostomy devices, people living with an ostomy continue to experience challenges with PSCs (... | PMC10734405 |
Limitations | Despite the fact that the psychometric analysis sample was broad and representative of the end user population, the study did encompass some limitations. Specifically, the sample size for (70 subjects for the psychometric validation) could have been larger although similar sample sizes have been used for other tools PG... | PMC10734405 | ||
Conclusions | discolored peristomal skin | SKIN CONDITION | This study presents the psychometric validation of the OST 2.0 instrument. The evidence provided support that OST 2.0 is reliable and valid for assessing severity of PSCs. Unlike the OST, this new tool enables close monitoring and captures subjects with PSC even in the absence of discolored peristomal skin. The Decisio... | PMC10734405 |
Supplemental Information | PMC10734405 | |||
Patient questionnaire | Click here for additional data file. | PMC10734405 | ||
Study design | Click here for additional data file. | PMC10734405 | ||
Skin area visit 3 | Click here for additional data file. | PMC10734405 | ||
Skin Discolouration score | Click here for additional data file. | PMC10734405 |
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