Nevin Manimala

BMC Med. 2025 May 28;23(1):305. doi: 10.1186/s12916-025-04139-2.

ABSTRACT

BACKGROUND: While the protective role of body mass index (BMI) in bone mass has been well-documented, the divergent associations between BMI and estimated bone mineral density (eBMD), attributed to its highly heterogeneous nature, remain insufficiently understood.

METHODS: Leveraging the hitherto largest genome-wide summary statistics, we conducted a two-sample Mendelian randomization (MR) to re-evaluate the effect of genetically predicted BMI on eBMD. Then, MR-Clust was applied to examine the potential presence of distinct causal pathways underlying the BMI-eBMD link. Utilizing tissue-partitioned MR, we estimated the distinct effects of separated tissue-specific subcomponents of BMI on eBMD, further supplemented by multivariable MR of body composition phenotypes on eBMD.

RESULTS: We reconfirmed the significant positive association between genetically predicted BMI and eBMD (β_IVW = 0.13, P value = 1.28 × 10^-34). Potential distinct causal pathways contributing to the observed total effect were identified by MR-Clust, with some exerting a protective effect while others leading to its deterioration. Tissue-partitioned MR suggested a marginally independent protective association between skeletal muscle-tissue instrumented BMI and eBMD (β_IVW = 0.14, P value = 4.98 × 10^-2) after accounting for adipose-tissue instrumented BMI, which was supported by the independent association between genetically predicted lean mass and eBMD after accounting for other body composition phenotypes.

CONCLUSIONS: Our results shed preliminary insights into the intricate relationship between obesity and bone mass, highlighting divergent causal pathways underlying the association between BMI and eBMD. Our findings emphasize the potential importance of precision obesity management over merely a general indicator as BMI in future public health strategies for osteoporosis prevention.

PMID:40437494 | DOI:10.1186/s12916-025-04139-2

BMC Oral Health. 2025 May 28;25(1):821. doi: 10.1186/s12903-025-06193-x.

ABSTRACT

BACKGROUND: Forensic dentistry is crucial in human identification, with dental age estimation being a key component of this process. The deposition of secondary dentin over an individual’s lifetime, along with the resulting changes in tooth anatomy, serves as an important factor in age estimation. The objective of this study was to develop regression equations for estimating age in adults based on linear measurements and ratios obtained from axial, sagittal, and coronal planes of the maxillary central incisors in the Iraqi subpopulation using cone beam computed tomography (CBCT).

METHODS: In this retrospective cross-sectional study, Multiplanar measurements of 400 maxillary central incisors from subjects ranging in age from 18 to 84 years were taken for a sample of 200 CBCTs. The data were analyzed using independent Student’s t-test, Mann-Whitney test, and Spearman’s and Pearson’s correlation coefficients to determine the strength of correlations. Multiple regression analysis was performed to predict age, and a p-value of ≤ 0.05 was considered statistically significant.

RESULTS: The age range of the participants was 18-84 years. The results revealed a statistically significant difference in age between male and female samples (p = 0.018). Consequently, separate age estimation equations were developed for each sex. In males, the equation derived from multiplanar linear measurements demonstrated a standard error of estimate (SEE) of ± 10.84 years, with a coefficient of determination (R²) of 0.49. In contrast, the equation for females, based on multiplanar measurements, yielded a SEE of ± 11.11 years and an R² value of 0.393.

CONCLUSIONS: Based on the findings of this study, dental morphometric measurement of maxillary central incisors using CBCT was found to be an acceptable method for age estimation especially for identification of unknow human remains. Horizontal measurements improve the accuracy of age estimate equations.

PMID:40437491 | DOI:10.1186/s12903-025-06193-x

BMC Health Serv Res. 2025 May 28;25(1):767. doi: 10.1186/s12913-025-12922-3.

ABSTRACT

BACKGROUND: While allied health plays a central role in healthcare, workforce challenges are straining the sector. Challenges are shaped by population changes, emerging models of care, and educational limitations, and were exacerbated by COVID-19. This study aimed to identify drivers of recruitment and retention for allied health clinicians in an Australian metropolitan setting. Identifying and addressing these factors is essential to the design and implementation of tailored, evidence-informed workforce strategy and policy.

METHODS: This cross-sectional, online survey explored workplace attraction, job seeking behaviours, and workplace perceptions. 29 Likert-scale statements informed by the existing literature examined factors influencing allied health retention. Allied health employees from a single Australian metropolitan health network were invited to participate. Descriptive statistics, logistic regression, and deductive content analysis were undertaken.

RESULTS: 42.6% (n = 593) of those invited participated in the survey, with 45.7% (n = 271) of participants having been with the organisation for six or more years. 35% (n = 197) of respondents to a question about intention to leave agreed that they aimed to leave their current role within six months. Variables associated with intention to leave were not feeling a sense of satisfaction with their role (odds ratio [OR] 1.51, 95% CI 1.22-1.85), not being recognised and rewarded by the team manager (OR 1.37, 95% CI 1.12-1.67), not working in the preferred clinical area (OR 1.56; 95% CI 1.25-1.95), and feeling burned out by the job (OR 1.44; 95% CI 1.16-1.78). Qualitative findings support the centrality of aspects of the job (job characteristics), the organisational context (rewards offered; climate; organisational support) and person-context interface (peer/group relations; work-life conflict) to attraction, retention, and attrition in roles.

CONCLUSION: This study identifies factors affecting recruitment, retention, and attrition of allied health professionals in a metropolitan setting. Findings are impacted by the personal and professional effects of the COVID-19 pandemic response. Results provide a baseline upon which the impact of interventions can be measured, while informing the prioritisation and design of tailored workforce strategies. Further, findings may inform local policy responses to improve the allied health workforce and ensure excellent care for the community.

PMID:40437489 | DOI:10.1186/s12913-025-12922-3

BMC Med. 2025 May 28;23(1):311. doi: 10.1186/s12916-025-04154-3.

ABSTRACT

BACKGROUND: Insulin resistance (IR) is a precursor to metabolic syndrome. Weekend catch-up sleep (WCS) is practiced to compensate for insufficient weekday sleep, but its impact on IR remains unclear. This study investigated associations between WCS and severe IR risk.

METHODS: Data from 1,903 adults participating in the National Health and Nutrition Examination Survey 2017-2020 were analyzed. IR was assessed using the Homeostatic Model Assessment for IR (HOMA-IR) and Metabolic Score for IR (METS-IR), with severe IR defined as the highest quartile. WCS was calculated by subtracting weekday sleep duration from weekend sleep duration and was categorized into five groups. Weighted logistic regression and restricted cubic spline analyses were performed to examine associations between WCS patterns and severe IR risk. Percentages reported were weighted to account for sampling design and population distribution.

RESULTS: The majority of participants were under 60 yrs (75.2%, n = 1,344) and had a body mass index below 30 kg/m² (59.2%, n = 1,082). Slightly more than half of the participants were female (51.3%, n = 990). A U-shaped relationship between WCS duration and severe IR risk was observed, with the lowest risk at approximately 0.7-1.0 h of WCS. Short WCS durations (0 < WCS ≤ 1 h) were associated with a significantly reduced risk of severe IR as defined by HOMA-IR (OR = 0.63, 95% CI: 0.41-0.97, P = 0.037) compared to stable sleep pattern (WCS = 0). Long WCS durations (WCS ≥ 2 h) were associated with an increased risk of severe IR as defined by METS-IR (OR = 1.88, 95% CI: 1.13-3.14, P = 0.018). Sensitivity analyses showed that the reduction in severe IR risk associated with short WCS durations was more significant in individuals with weekday sleep durations of seven hours or less.

CONCLUSIONS: WCS duration exhibits a U-shaped association with severe IR risk, with approximately 0.7-1.0 h of WCS linked to the lowest risk. Both insufficient and excessive WCS are associated with increased severe IR risk, emphasizing the importance of optimal sleep patterns for metabolic health.

PMID:40437485 | DOI:10.1186/s12916-025-04154-3

Burns. 2025 May 27;51(6):107530. doi: 10.1016/j.burns.2025.107530. Online ahead of print.

ABSTRACT

AIM: The aim of this study was to translate the Itch Man Scale into Turkish and validate it for use in assessing itching in pediatric burn patients.

METHODS: This language adaptation and psychometric testing was conducted in two stages. In the first stage, the Itch Man Scale was translated into Turkish by expert translators-and back translated into English-and the content validity was assessed by subject-matter experts. In the second stage, the scale was administered twice within 30 minutes to 102 pediatric patients with burns to evaluate the test-retest reliability. The Visual Analog Scale and 5-D Itch Scale were also administered once to the same group to assess convergent validity.

RESULTS: Statistically significant positive correlations were found between the Itch Man Scale and both the Visual Analog Scale (r = 0.767, p < 0.001) and the 5-D Itch Scale (r = 0.665, p < 0.001). The test-retest intraclass correlation coefficient (ICC) was 0.915.

CONCLUSION: The Itch Man Scale is a reliable and valid instrument for Turkish pediatric burn patients and is therefore recommended for use in assessing itching in such patients in Türkiye.

PMID:40435536 | DOI:10.1016/j.burns.2025.107530

JMIR Aging. 2025 May 28;8:e66610. doi: 10.2196/66610.

ABSTRACT

BACKGROUND: Mobile apps and peer support are known to effectively promote physical activity in older adults, which, in turn, improves physical function. Previously, we investigated the feasibility and impact of using digital peer-supported apps (DPSAs) to increase physical activity among older adults over a 3-month period. However, the long-term feasibility and impact on sustainable behavior change remain unknown.

OBJECTIVE: This study aims to evaluate the 12-month feasibility of the DPSA and to obtain preliminary estimates of its effects on physical activity and physical function among older Japanese adults.

METHODS: This nonrandomized controlled trial recruited older adults aged 65 years or older from 2 physical activity programs. Participants chose either the intervention (app program + exercise instruction) group or the control (exercise instruction only) group. Only those participants who had completed the 3-month intervention and wished to continue in the 12-month follow-up intervention study were included. DPSA feasibility was assessed using retention and adherence rates. Physical activity was assessed using accelerometers, capturing daily step count, light-intensity activity, moderate to vigorous intensity activity, and sedentary behavior. Physical function was evaluated using grip strength and the 30-second chair stand test (CS-30). Accelerometer measurements were collected every 3 months over 12 months (5 time points, including baseline), whereas physical function was measured at baseline, 3 months, and 12 months.

RESULTS: The follow-up study included 44 of 66 participants from the 3-month intervention study, with 26 participants in the intervention group and 18 participants in the control group. The 12-month retention rate for participants in the DPSA intervention group was 73% (19/26), whereas the retention rate among all 41 participants, including those who chose not to participate in the follow-up study, was 46% (19/41). The adherence rate was 85.9%. The average number of steps per day (95% CI) in the intervention group changed before and after DPSA use (P=.048). We observed an increase of 1736 (β=1736, 95% CI 232-3241) steps per day compared with baseline. No significant change was observed in the control group. There were significant within-group differences in CS-30 scores for both intervention (P<.001) and control (P=.03) groups over the 12-month period. Specifically, there was a significant change in CS-30 scores (95% CI) between the baseline and 12-month assessments for the intervention (β=6.5, 95% CI 3.8-9.1; P<.001) and control (β=3.8, 95% CI 0.6-7.1; P=.02) groups.

CONCLUSIONS: Participants with long-term DPSA use observed increases in average daily steps and CS-30 scores before and after DPSA use, although only a limited number of older adults had long-term access to the DPSA. Identifying ways to expand long-term DPSA use among older adults is necessary. Additionally, randomized controlled trials should be conducted to determine the long-term effects of DPSAs on physical activity and function in older adults.

PMID:40435519 | DOI:10.2196/66610

Cogn Emot. 2025 May 28:1-15. doi: 10.1080/02699931.2025.2508400. Online ahead of print.

ABSTRACT

This experiment aimed to test whether FutureMe, a VR-tool combining positive mental imagery and dual tasking, is efficacious in increasing willingness to exposure, and decreasing distress, emotionality, and vividness, of children’s autobiographical fears, compared to an active VR control condition. Additionally, the moderating role of emotion regulation difficulties was investigated. Children (N = 557; 53.9% boys), with a mean age of 10.14 years (SD = 1.90), were randomly allocated to either the FutureMe (n = 281) or control (n = 276) condition. Willingness to exposure, distress, emotionality, and vividness were measured at pre- and posttest on a VAS from 0 (not at all) to 100 (very much). Parents (n = 437) filled out the Difficulties in Emotion Regulation Scale-Parent Report, assessing their child’s emotion regulation difficulties. Willingness to exposure increased only in the FutureMe condition. Distress and emotionality decreased in both conditions. Vividness decreased only in the control condition. Emotion regulation difficulties moderated the pre-post change of distress and emotionality only within the control condition. This study shows that the FutureMe could improve children’s willingness to exposure, which in clinical practice could lead to less drop-out in anxiety therapy for children. More research is needed on the separate effects of dual tasking and positive mental imagery.

PMID:40435503 | DOI:10.1080/02699931.2025.2508400

PLoS One. 2025 May 28;20(5):e0324604. doi: 10.1371/journal.pone.0324604. eCollection 2025.

ABSTRACT

Current predictive methods for dam failures in reservoirs remain limited, indicating that the underlying mechanisms of such failures are not yet fully understood. To further elucidate the interrelationships among safety monitoring data in the reservoir area, this study established 36 monitoring cross-sections distributed across upper, middle, and lower slope zones. Each cross-section was instrumented with eight different types of monitoring devices. A total of 4,320 samples were collected (432 samples per instrument type), resulting in an overall dataset of 34,560 measurements. The monitoring data were sequentially analyzed using: (1) descriptive statistics, (2) Welch/Brown-Forsythe post hoc One-way analysis of variance (ANOVA), and (3) cluster analysis. The results demonstrate that: (1) Significant correlations exist among monitoring variables, with the strongest positive correlation observed between loading and lean (r = 0.40), while the strongest negative correlation occurred between sedimentation and stress (r = -0.39). (2) Cluster analysis of the eight monitoring variables revealed two distinct clusters: soil displacement, stress, and water-level formed one cluster, while the remaining variables comprised the second cluster. In summary, variations in monitoring data and their correlations resulted from water-level and environmental changes in the reservoir area, with spatial differences across monitoring types. A thorough investigation of these variations and their causes will enable accurate safety assessments of the reservoir area and support tailored response strategies for different locations.

PMID:40435450 | DOI:10.1371/journal.pone.0324604

PLoS One. 2025 May 28;20(5):e0324545. doi: 10.1371/journal.pone.0324545. eCollection 2025.

ABSTRACT

AIM: In the present study, we aimed to provide an epidemiological and descriptive overview of violence against healthcare workers in an Italian university hospital, presenting and characterizing the risk factors in the department where such events occur and to propose ways to prevent aggressive behaviors.

METHODS: We retrospectively analyzed violence against healthcare workers by patients and attendants at an Italian university hospital from 2020 to 2022. Aggressions were documented in anonymous incident reports collected by the hospital’s Clinical Risk Unit. The frequencies and percentages were calculated via a descriptive analysis. Chi-square tests were used to compare the wards with the most aggressions to other wards.

RESULTS: Of the 219 included cases, the aggressors were primarily male patients and the victims female nurses. Most of the aggressions occurred in the psychiatry and emergency department. Among the aggressors, 41.1%, had a psychiatric diagnosis or neurocognitive impairment. Over half the cases involved physical aggression. Compared to other wards, psychiatric wards showed an even distribution of aggressor gender, a higher proportion of male victims, fewer verbal aggressions, and less impact from environmental factors. Notably, female aggressor status (p < 0.001, OR = 8.687) and involvement in physical assaults (p < 0.001, OR = 15.236) were identified as independent risk factors associated with aggression in psychiatric settings.

CONCLUSION: Our findings align with the literature in that most of the incidents occurred in the psychiatry and emergency medicine departments and involved nurses. However, physical rather than verbal aggression predominated. Notable distribution, risk factor, and qualitative differences were observed between the psychiatric and non-psychiatric services, which warrants further investigation. Our results could be useful in implementing better prevention strategies based on the type of ward.

PMID:40435448 | DOI:10.1371/journal.pone.0324545

JCO Clin Cancer Inform. 2025 May;9:e2400324. doi: 10.1200/CCI-24-00324. Epub 2025 May 28.

ABSTRACT

PURPOSE: Recent advances in machine learning have led to the development of classifiers that predict molecular subtypes of acute lymphoblastic leukemia (ALL) using RNA-sequencing (RNA-seq) data. Although these models have shown promising results, they often lack robust performance guarantees. The aim of this study was three-fold: to quantify the uncertainty of these classifiers, to provide prediction sets that control the false-negative rate (FNR), and to perform implicit error reduction by transforming incorrect predictions into uncertain predictions.

METHODS: Conformal prediction (CP) is a distribution-agnostic framework for generating statistically calibrated prediction sets whose size reflects model uncertainty. In this study, we applied an extension called conformal risk control to three RNA-seq ALL subtype classifiers. Leveraging RNA-seq data from 1,227 patient samples taken at diagnosis, we developed a multiclass conformal predictor ALLCoP, which generates statistically guaranteed FNR-controlled prediction sets.

RESULTS: ALLCoP was able to create prediction sets with specified FNR tolerances ranging from 7.5% to 30%. In a validation cohort, ALLCoP successfully reduced the FNR of the ALLIUM RNA-seq ALL subtype classifier from 8.95% to 3.5%. For patients whose subtype was not previously known, the use of ALLCoP was able to reduce the occurrence of empty predictions from 37% to 17%. Notably, up to 34% of the multiple-class prediction sets included the PAX5alt subtype, suggesting that increased prediction set size may reflect secondary aberrations and biological complexity, contributing to classifier uncertainty. Finally, ALLCoP was validated on two additional RNA-seq ALL subtype classifiers, ALLSorts and ALLCatchR.

CONCLUSION: Our results highlight the potential of CP in enhancing the use of oncologic RNA-seq subtyping classifiers and also in uncovering additional molecular aberrations of potential clinical importance.

PMID:40435436 | DOI:10.1200/CCI-24-00324