Nevin Manimala

Adv Sci (Weinh). 2026 Apr 2:e20738. doi: 10.1002/advs.202520738. Online ahead of print.

ABSTRACT

We demonstrate that the primary factor determining the external quantum efficiency (EQE) of InGaN-based micro-scale light-emitting diodes (µLEDs) depends on their internal state. A comparative photoluminescence (PL) study shows that the lateral diffusion length of carriers in InGaN red µLEDs is significantly shorter than in InGaN blue µLEDs, primarily due to inhomogeneity in the bulk material. This results in an insignificant change in PL intensity regardless of sidewall conditions. Additionally, examinations of EQE and peak wavelength across various epitaxial designs and sidewall conditions reveal that sidewall-surface recombination does not significantly impact EQE in InGaN red µLEDs. Meanwhile, the peak wavelength, which represents the radiative recombination rate given by the quantum well design of InGaN red µLEDs, is found to dominantly influence the EQE of InGaN red µLEDs. Furthermore, statistical analysis based on the relative standard deviation indicates that the peak wavelength is one of the primary determinants of EQE in InGaN red µLEDs. These findings suggest that addressing internal state is crucial for optimizing EQE of µLEDs.

PMID:41926672 | DOI:10.1002/advs.202520738

Int J Audiol. 2026 Apr 2:1-13. doi: 10.1080/14992027.2026.2650507. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to evaluate the effectiveness of the integrated digit-in-noise test (iDIN), which uses digit sequences of varying lengths as test materials, in assessing speech-in-noise recognition among non-native Cantonese speakers with normal hearing.

DESIGN: A cross-sectional observational study was conducted involving native Mandarin speakers with Cantonese as a second language. Participants completed Cantonese and Mandarin versions of iDIN and the Cantonese Speech in Noise Test (HINT). In the iDIN, only the 2-, 3-, and 5-digit forward recall, as well as the 3-digit backward recall conditions, were administered. Data on language experience, proficiency, and exposure were collected through questionnaires.

STUDY SAMPLE: Forty-seven participants (mean age 29.13 years) with normal hearing and Cantonese as a second language were recruited in Hong Kong. All had varying durations of Cantonese exposure, from <1 year to over 10 years.

RESULTS: Statistically significant differences were observed between Cantonese and Mandarin speech reception thresholds (SRTs) for the 3-digit, 5-digit forward recall, and 3-digit backward recall conditions, but not for the 2-digit forward recall. Longer Cantonese exposure correlated with improved (lower) SRTs in Cantonese iDIN, with performance becoming comparable to native speakers after ∼2 years of exposure.

CONCLUSIONS: iDIN may have potential as a tool for assessing speech-in-noise recognition in non-native Cantonese speakers with normal hearing, particularly after two years of exposure, though further validation in clinical populations is needed.

PMID:41926650 | DOI:10.1080/14992027.2026.2650507

J Med Internet Res. 2026 Apr 2;28:e76432. doi: 10.2196/76432.

ABSTRACT

BACKGROUND: Digital biomarkers are increasingly being used to support depression assessment by providing objective, continuous, and real-time physiological and behavioral data. However, most existing studies have focused on individual biomarkers, such as sleep or cardiac parameters, while integrative evaluations that capture the multidimensional nature of depression remain limited.

OBJECTIVE: This systematic review evaluated digital biomarkers for depression and synthesized evidence on differences between individuals with depression and controls.

METHODS: Eligible studies included observational or interventional studies examining digital biomarkers for depression with validated outcome measures. We searched major international and Korean databases, including MEDLINE, PsycINFO, CINAHL, IEEE Xplore, Web of Science, Cochrane Library, KISS, RISS, KMbase, and KoreaMed, from inception to December 28, 2025. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool and the Scottish Intercollegiate Guidelines Network checklist. Meta-analyses were conducted using random-effects models with the Hartung-Knapp-Sidik-Jonkman method, and other outcomes were narratively summarized.

RESULTS: The search yielded 39,617 records, of which 132 studies involving 57,852 participants met the inclusion criteria. These studies encompassed various digital biomarkers, including sleep, physical activity, cardiac measures, smartphone-derived data, speech, GPS data, and circadian rhythms. A meta-analysis of 22 studies (6947 participants) revealed that individuals with depression had significantly longer sleep onset latency (5 studies; n=292; +4.75 min, 95% CI 2.46-7.04; P=.005; 95% prediction interval [PI] 0.01-10.27) and time in bed (3 studies; n=236; +31.81 min, 95% CI 18.22-45.39; P=.01; 95% PI 2.28-55.16). Physical activity counts were also significantly lower (5 studies; n=462; standardized mean difference -0.71, 95% CI -1.33 to -0.09; P=.03; 95% PI -2.18 to 0.71). Although individuals with depression showed a lower sleep efficiency, higher mean heart rate, and lower SD of normal-to-normal intervals, these differences were not statistically significant. Other digital markers yielded inconsistent results. Overall, these findings indicate that no single digital biomarker sufficiently captures depression-related changes. Instead, the results support the superiority of personalized, multimodal approaches. However, the generalizability of these findings is limited by the lack of standardized data collection protocols and high clinical heterogeneity across studies, as reflected in wide PIs.

CONCLUSIONS: Certain digital biomarkers, particularly sleep onset latency and physical activity counts, showed consistent average differences between the depression and control groups. However, wide PIs indicate substantial variability across settings, suggesting that no single marker is sufficient for reliable detection. This study advances the field by providing a comprehensive meta-analysis of multidimensional digital biomarkers, establishing a quantitative foundation for objective depression screening and monitoring. These findings support the use of personalized, multimodal digital phenotyping approaches and highlight the need for standardized, clinically interpretable frameworks for real-world depression monitoring.

PMID:41926632 | DOI:10.2196/76432

J Wound Care. 2026 Apr;35(Sup4a):S28-S36. doi: 10.12968/jowc.2025.0340. Epub 2026 Apr 2.

ABSTRACT

OBJECTIVE: To determine the composite cut-off value and diagnostic accuracy of C-reactive protein (CRP) for diabetic foot osteomyelitis (DFO).

METHOD: A retrospective study of patients was combined with a meta-analysis. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity and area under the curve (AUC) were calculated via forest plots and summary receiver operating characteristic curves. A composite cut-off model was developed using R 4.4.3 (R Foundation for Statistical Computing, Austria).

RESULTS: The experimental cohort comprised 265 patients (204 with DFO and 61 without). The meta-analysis comprised 12 studies, including a total of 1828 patients. The retrospective cohort demonstrated that CRP achieved an AUC of 0.63 (95% confidence interval (CI): 0.55, 0.71) for diagnosing DFO, with an optimal cut-off value of 9.57mg/l (sensitivity 74%, specificity 53%). Meta-analysis revealed pooled sensitivity of 74% (63-83%) and specificity of 73% (65-79%) (AUC=0.79; 95%CI: 0.75, 0.82). The composite model suggested a CRP cut-off of 15.20mg/l (sensitivity 80%, specificity 53%).

CONCLUSION: In this study, CRP demonstrated moderate diagnostic utility for DFO and could function as a screening adjunct.

PMID:41926570 | DOI:10.12968/jowc.2025.0340

J Cardiovasc Pharmacol. 2026 Apr 1;87(4):209-218. doi: 10.1097/FJC.0000000000001801.

ABSTRACT

Aspirin (ASA) is the cornerstone of the acute coronary syndrome primary and secondary prevention. Still, its role is debated in some high bleeding risk patients or cases that underwent second-generation drug-eluting stents with a better scaffold. This study compared the efficacy and safety of aspirin-free versus aspirin-based strategies in patients with ACS undergoing PCI. We systematically searched PubMed, Embase, Scopus, and ScienceDirect for studies comparing aspirin-based versus aspirin-free strategies in patients with ACS undergoing PCI. Pooled relative risk (RR) with 95% CI was calculated using a fixed effects model or a random effects model if heterogeneity was present. Significance was set at P < 0.05. Thirty studies including 207,938 patients (N = 104,062 in the ASA arm, and 103,876 in the ASA-free arm) were included in this study. There was a statistically significant reduction in risk of all-cause mortality [RR 0.93, 95% CI, 0.87-0.99, P-value = 0.024, I2 = 0%], BARC 2-5 [RR = 0.68, 95% CI, 0.58-0.81, P-value = <0.01, I2 = 0%], BARC 3 or 5 [RR= 0.71, 95% CI, 0.60-0.82, P-value= <0.01, I2 = 0%], TIMI major bleeding [RR = 0.66, 95% CI, 0.50-0.86, P-value= 0.02, I2 = 0%], TIMI minor or major bleeding [RR= 0.61, 95% CI, 0.52-0.72, P-value= <0.01, I2 = 0%], and ISTH major bleeding with aspirin-free strategy [RR= 0.52, 95% CI, 0.42-0.64, P-value= <0.001, I2= 0%]. Other secondary outcomes showed statistically nonsignificant results. The aspirin-free strategy showed lower all-cause mortality and bleeding, supporting its efficacy and safety in high bleeding risk patients.

PMID:41926558 | DOI:10.1097/FJC.0000000000001801

Crit Care Explor. 2026 Apr 2;8(4):e1393. doi: 10.1097/CCE.0000000000001393. eCollection 2026 Apr 1.

ABSTRACT

IMPORTANCE: Accurate prediction of intubation in critically ill patients could enable interventions that improve patient outcomes. However, the performance of intensive care physicians compared with machine learning (ML) models remains unknown.

OBJECTIVES: To investigate intensive care physicians’ ability to predict the need for intubation within 24 hours and compare their performance against an established ML model, Vent.io.

DESIGN, SETTING, AND PARTICIPANTS: This prospective observational study in two ICUs surveyed intensivists to test their ability to predict the need for intubation of adult patients under their care. Physician predictions of intubation were then compared with predictions from Vent.io.

MAIN OUTCOMES AND MEASURES: Primary metrics include prediction sensitivity, specificity, and descriptive statistics for both physicians and ML model. Generalized linear mixed models investigated the fixed effect of the predictor (physician vs. Vent.io) on both sensitivity and specificity while accounting for the random effects from different physicians. Similar modeling was used to investigate the relationship between physician confidence and correctness.

RESULTS: Overall, physicians were quite confident in their predictions of intubation with a median score of 8 (on a 0-10 point scale, with 0 being not at all confident and 10 being extremely confident) out of the 302 surveys administered. Sensitivity was 0.190 and 0.714 for physicians and Vent.io, respectively. Specificity was 0.960 and 0.673 for physicians and Vent.io, respectively. Generalized linear mixed modeling showed that physician confidence was associated with greater odds of correctly predicting intubation outcome (odds ratio [OR] 1.49; 95% CI, 1.22-1.84; p < 0.001). Vent.io had significantly greater odds of being correct when patients required intubation compared with physicians (OR 18.68; 95% CI, 1.87-186.31; p = 0.013). However, intensive care physicians outperformed Vent.io at correctly predicting when patients did not require intubation (OR 24.80; 95% CI, 13.22-46.52; p < 0.001).

CONCLUSIONS AND RELEVANCE: Although predictive performance compared with human experts is promising, Vent.io needs real-time testing in a randomized clinical trial to determine if its deployment can improve clinical outcomes.

PMID:41926168 | DOI:10.1097/CCE.0000000000001393

J Glob Health. 2026 Apr 3;16:04099. doi: 10.7189/jogh.16.04099.

ABSTRACT

BACKGROUND: The incidence and overuse of caesarean section, an adverse pregnancy outcome closely associated with pregnancy complications, is markedly high globally. However, previous research has predominantly examined individual complications in isolation, leaving a need for a comprehensive evaluation of multimorbidity patterns. We aimed to explore the associations between caesarean sections and adverse pregnancy outcomes in a Chinese population.

METHODS: We retrieved data from the National Maternal Near Miss Surveillance System in Jilin Province in China from 2021 to 2023. We summarised them using descriptive statistics and used the Rao-Scott χ² test to compare the differences between spontaneous labour and caesarean section. Then, we used latent class analysis (LCA) to cluster pregnancy complications and logistic regression to examine their association with modes of delivery.

RESULTS: We included 85 446 pregnant women, of whom 53 916 (63.1%) had undergone caesarean sections and 31 530 (36.9%) had experience spontaneous labour. There were significant differences in terms of pregnancy complications between pregnant women who underwent spontaneous labour and those who had caesarean sections. We then clustered pregnancy complication symptoms into six classes using LCA and fitted three models. After adjusting for potential confounders, the incidence of caesarean sections was significantly higher in pregnant women with diabetes and hypothyroidism (odds ratio (OR) = 1.177; 95% confidence interval (CI) = 1.105-1.253), hyperthyroidism and kidney disease (OR = 2.078; 95% CI = 1.391-3.106), with hypertension and hypothyroidism (OR = 3.613; 95% CI = 3.217-4.058), and hypertension, diabetes, and anaemia (OR = 3.365; 95% CI = 2.997-3.779) when compared to pregnant women with a lower incidence of pregnancy complications.

CONCLUSIONS: Caesarean sections occur frequently among pregnant women in China and are significantly associated with specific pregnancy complication clusters, particularly those involving hypertension, diabetes, anaemia, and thyroid dysfunction. These findings suggest that women with multimorbidity profiles should receive enhanced antenatal surveillance and individualised delivery planning to optimise maternal outcomes.

PMID:41926167 | DOI:10.7189/jogh.16.04099

J Glob Health. 2026 Apr 3;16:04080. doi: 10.7189/jogh.16.04080.

ABSTRACT

BACKGROUND: Malaria is a preventable disease that causes serious illness and death. In 2022, it remained the leading cause of death among children under five years of age in Burkina Faso, despite significant intervention efforts over the past two decades. Research on the effects of interventions and climatic factors on malaria morbidity has expanded, but their effects on malaria mortality remain unclear. We aimed to estimate the effects of interventions and lagged climatic factors on malaria mortality among children under five years of age in northwest Burkina Faso. We further evaluated the role of climatic seasonality in patterns of malaria mortality.

METHODS: We investigated the seasonal patterns of malaria mortality among children under five years of age and their association with climatic factors, such as rainfall and land surface temperature (LST), using wavelet analysis on mortality data from the Nouna Health Demographic Surveillance System spanning 2002-2021. Furthermore, we assessed the effects of interventions, including coverage of insecticide-treated nets (ITNs) and artemisinin-based combination therapies (ACTs), on malaria mortality alongside climate effects using Bayesian negative binomial temporal models for the period 2013-2021.

RESULTS: The lag time in the effects of climatic factors varied over time. Malaria mortality, rainfall, and LST showed a 12-month seasonal cycle throughout the years, while LST also had a six-month cycle in specific years. Rainfall lagged by 1.5 to 2 months and LST by 1 to 1.5 months, depending on the seasonal cycle and year. Rainfall was positively associated with malaria mortality (mortality rate ratio (MRR) = 1.59; 95% Bayesian credible interval (BCI) = 1.18, 1.95), LST showed a decrease in mortality (MRR = 0.68; 95% BCI = 0.52, 0.86), and ITN was associated with a reduction in mortality (MRR = 0.59; 95% BCI = 0.42, 0.79); however, ACT was not statistically important.

CONCLUSIONS: We found that ITN was more effective in reducing malaria mortality than temperature, but rainfall had a greater opposing impact on increasing malaria mortality. The seasonal mortality pattern was more influenced by rainfall than by temperature. Varying climatic lag times highlight the need for adaptive strategies. Policymakers should focus on climate-informed planning, sustained ITN coverage, and reassessment of ACT strategies to further reduce malaria mortality.

PMID:41926164 | DOI:10.7189/jogh.16.04080

JMIR Med Educ. 2026 Apr 2;12:e87524. doi: 10.2196/87524.

ABSTRACT

BACKGROUND: Women and visible minorities (VMs) continue to face discrimination while working in health care. These instances of discrimination can range from those perpetrated by individuals, such as misidentification, to prejudices held by institutions, such as a lack of commitment to hiring VMs. Furthermore, many residents face unique experiences of discrimination due to the intersection of gender and race. Although numerous studies have been published on the experiences of physicians with discrimination, there is a limited literature specifically on the experiences of residents.

OBJECTIVE: This study aimed to explore and analyze the impact of gender and racial discrimination on medical residents during their residency training.

METHODS: This scoping review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. A health sciences librarian searched 5 databases: Ovid Medline(R) ALL, Embase (via Ovid), APA PsycInfo (via Ovid), CINAHL Plus with Full Text (via EBSCOhost), and Scopus. No study design, country, or date restrictions were applied. Studies that explored the impact of both gender and racial discrimination on residents during their residency training were included. Two reviewers conducted title and abstract screening, followed by full-text screening, and any discrepancies were resolved through group consensus. This study’s content was extracted using Microsoft Word to create tables for organizing and managing the information from the included studies.

RESULTS: After removing duplicates, the literature search revealed 2435 papers for title and abstract screening. A total of 340 papers were selected for full-text review, and ultimately, 26 papers met the inclusion criteria. Included papers were published between 1995 and 2024 in the United States (n=16), Canada (n=4), Australia and New Zealand (n=2), Saudi Arabia (n=1), Mexico (n=1), South Africa (n=1), and the United Kingdom (n=1). Our analysis revealed four themes: (1) forms of discrimination faced by VMs, (2) sources of discrimination, (3) ramifications of discrimination, and (4) ways for individuals and institutions to reduce gender and racial discrimination.

CONCLUSIONS: This scoping review identified that discrimination primarily manifests as microaggressions against residents and revealed the negative impact it continues to have on their careers. Raising awareness about these issues can help programs and institutions develop tailored solutions to tackle these problems and provide a safe, inclusive training environment for all residents.

PMID:41926156 | DOI:10.2196/87524

JMIR Form Res. 2026 Apr 2;10:e84947. doi: 10.2196/84947.

ABSTRACT

BACKGROUND: Nipah virus (NiV) infection is considered one of the deadliest infectious diseases, with a case fatality rate of approximately 71%. In Bangladesh, the primary risk factor for NiV infection is the consumption of raw date palm sap (DPS) contaminated with excreta from fruit bats (ie, members of the Pteropodidae family). Recently, the increasing use of social media among Bangladeshi youth has enabled business groups to widely advertise and sell raw DPS. This increased access, combined with young people perceiving consumption of raw DPS as an “adventurous event,” may facilitate an increase in incidences of NiV infection.

OBJECTIVE: We aimed to explore and document data from social media regarding raw DPS advertisements and consumption. Furthermore, we aimed to investigate the commercial distribution of raw DPS across the country.

METHODS: The data were accessed from common social media platforms used in Bangladesh, including Facebook and YouTube, between November 10, 2023, and January 31, 2024. We considered this period to capture public opinions, discussions, and reported incidents during the peak harvesting and consumption season of DPS. While DPS harvesting continues until March, early monitoring is essential for identifying the emerging concerns related to NiV transmission. Extracted variables were post dates and times, source locations, types of sources and posts, provider details (eg, sellers and gachis), post descriptions, user reactions, views, comments, and shares. Particular emphasis was placed on identifying the districts of both DPS suppliers and recipients. We used R version 4.3.2 and Stata version 15 for analyzing statistical data and QGIS for geographic data.

RESULTS: Of 556 social media posts, 361 (64.9%) were advertisements promoting raw DPS. Few DPS-related posts (n= 10, 1.8%) were associated with raising awareness about DPS consumption and NiV infection. In total, 473,724 people interacted with the social media posts. The identification of supplier and recipient districts revealed 14 source districts of raw DPS. The majority of raw DPS were distributed from Rajshahi, Naogaon, Rajbari, and Faridpur, which are among the most NiV-prone districts. During the data collection period, we observed an average of 996 (SD 377) liters of raw DPS sold per day from multiple gachhis (sap collectors) and sellers (vendors) in Rajshahi.

CONCLUSIONS: The marketing of raw DPS through digital media platforms has increased customer interest, as evidenced by the notably high level of public engagement observed on this topic within the Bangladeshi social media context. Distributing raw DPS using digital platforms is a marketing tool that significantly increases the availability of raw DPS to previously hard-to-reach markets and potentially increases individuals’ exposure to NiV infection. This study recommends a multidisciplinary approach, which incorporates context-specific public health investigations, policymaking, and digital media surveillance to address emerging public health concerns.

PMID:41926155 | DOI:10.2196/84947