Tag: nevin manimala

JMIR AI. 2026 Feb 17;5:e75064. doi: 10.2196/75064.

ABSTRACT

BACKGROUND: The impact of surgical complications is substantial and multifaceted, affecting patients and their families, surgeons, and health care systems. Despite the remarkable progress in artificial intelligence (AI), there remains a notable gap in the prospective implementation of AI models in surgery that use real-time data to support decision-making and enable proactive intervention to reduce the risk of surgical complications.

OBJECTIVE: This scoping review aims to assess and analyze the adoption and use of AI models for preventing surgical complications. Furthermore, this review aims to identify barriers and facilitators for implementation at the bedside.

METHODS: Following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, we conducted a literature search using IEEE Xplore, Scopus, Web of Science, MEDLINE, ProQuest, PubMed, ABI, Embase, Epistemonikos, CINAHL, and Cochrane registries. The inclusion criteria included empirical, peer-reviewed studies published in English between January 2013 and January 2025, involving AI models for preventing surgical complications (surgical site infections, and heart and lung complications or stroke) in real-world settings. Exclusions included retrospective algorithm-only validations, nonempirical research (eg, editorials or protocols), and non-English studies. Study characteristics and AI model development details were extracted, along with performance statistics (eg, sensitivity and area under the receiver operating characteristic curve). We then used thematic analysis to synthesize findings related to AI models, prediction outputs, and validation methods. Studies were grouped into three main themes: (1) duration of hypotension, (2) risk for complications, and (3) decision support tool.

RESULTS: Of the 275 identified records, 19 were included. The included models frequently demonstrated strong technical accuracy with high sensitivity and area under the receiver operating characteristic curve, particularly among studies evaluating decision support tools. However, only a few models were adopted routinely in clinical practice. Two studies evaluated the clinicians’ perceptions regarding the use of AI models, reporting predominantly positive assessments of their usefulness.

CONCLUSIONS: Overall, AI models hold potential to predict and prevent surgical complications as the validation studies demonstrated high accuracy. However, implementation in routine practice remains limited by usability barriers, workflow misalignment, trust concerns, and financial and ethical constraints. The evidence included in this scoping review was limited by the heterogeneity in study design and the predominance of small-scale feasibility studies, particularly for hypotension prediction. Future research should prioritize prospectively validated models that use other physiologic features and address clinicians’ concerns regarding generalizability and adoption.

PMID:41701931 | DOI:10.2196/75064

JMIR Public Health Surveill. 2026 Feb 17;12:e85904. doi: 10.2196/85904.

ABSTRACT

BACKGROUND: As communication technology advances and the digital divide grows, a deeper understanding of the influence of different information sources on vaccine uptake by generations can inform targeted public health interventions in times of future crisis. While the COVID-19 pandemic highlighted the role of media sources on the decision to receive vaccines, no studies have focused on the impact of the type and number of information sources in a population-based sample in California.

OBJECTIVE: In this study, we examined associations between Californians’ self-reported most relied upon COVID-19 information sources, categorized by type and measured as a count, and their COVID-19 vaccination status using data collected from the 2022 California Health Interview Survey. To address differences in information preferences and vaccine uptake by age, we also tested for potential effect modification of the relationship between relied upon COVID-19 information sources and vaccination status by generational membership (eg, Generation Z, millennials, Generation X, baby boomers, and Silent Generation).

METHODS: We conducted a secondary analysis of cross-sectional data from the 2022 California Health Interview Survey. Vaccine status (any or none) was modeled as a function of information sources (or count) controlling for important sociodemographic and health confounding variables. Interaction terms of information sources (or count) by generational status were added to the models to test effect modification, and if significant, the models were stratified by generation. All analysis was survey-weighted to account for the complex survey sampling design.

RESULTS: Compared to relying on traditional news media for COVID-19 information, relying on word of mouth (odds ratio [OR] 0.6), social media (OR 0.62), and doctors (OR 0.41) for COVID-19 information was associated with lower odds of being vaccinated for COVID-19. A dose-response relationship was identified, with each additional information source associated with 9% higher odds of being vaccinated for COVID-19. In stratified models, social media, compared to traditional news media, was associated with lower odds of vaccination for Generation X, baby boomers, and the Silent Generation.

CONCLUSIONS: Health information preferences, especially for traditional news media, are associated with COVID-19 vaccine uptake, and the information sources differ by generation. These findings provide information for stakeholders interested in vaccine hesitancy, health informatics, messaging strategies, health literacy, and future health information outreach programs during epidemics or pandemics. Dissemination of public health information should include multiple information sources to reach all individual preferences across different generations.

PMID:41701926 | DOI:10.2196/85904

JMIR Res Protoc. 2026 Feb 17;15:e84176. doi: 10.2196/84176.

ABSTRACT

BACKGROUND: Climate change-induced international migration has the potential to negatively impact the health and well-being of displaced populations. Pregnancy often serves as a point of entry into the health care system for migrant women; however, these women often face reduced access to maternal health care services compared to nonmigrants. In the context of climate-related international migration, these disparities may be further exacerbated, increasing the risk of maternal morbidity and adverse perinatal outcomes. While the intersections between climate change, migration, and health are increasingly acknowledged, literature specifically focused on international climate-related migrant women-particularly during the perinatal period-remains limited and dispersed. Thus, there is a growing need for research and synthesized data on climate change, population movements, and the perinatal health care needs of childbearing women.

OBJECTIVE: The aim of this study is to examine and describe the scope and nature of available evidence on maternal health and care for international climate-related migrant women, from pregnancy through the postpartum period.

METHODS: We will conduct a scoping review following the Joanna Briggs Institute methodology. A tailored search strategy using key terms related to climate change, migration, women, and perinatal health care will be applied to four databases-Embase, CINAHL, PsycINFO, and Ovid MEDLINE-without restriction on publication date. Relevant gray literature sources will also be searched and considered for inclusion. Only literature published in English, French, Portuguese, or Spanish will be included. Two reviewers will independently screen full-text records based on predefined inclusion criteria and extract the relevant data.

RESULTS: A total of 741 studies were screened from 1113 records. Results summarizing perinatal health outcomes and needs, care experiences, barriers faced by international climate-related migrant women, and recommendations will be reported using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 flow diagram. We anticipate finalizing the manuscript for this work in 2026.

CONCLUSIONS: Considering vulnerability factors related to migration status is essential to improving access to integrated perinatal health care and reducing health inequities among immigrant women. This review will provide valuable insights to tailor interventions to the social and cultural needs of climate-affected migrant women during the perinatal period.

PMID:41701925 | DOI:10.2196/84176

Phlebology. 2026 Feb 17:2683555261424388. doi: 10.1177/02683555261424388. Online ahead of print.

ABSTRACT

ObjectiveTo compare the clinical efficacy of two postoperative compression methods at 48 h after endovenous radiofrequency ablation (RFA) of the great saphenous vein on complications, quality of life, return-to-work time, and patient satisfaction.MethodsIn this prospective, single-center randomized controlled trial, 210 patients with duplex ultrasound-confirmed great saphenous vein incompetence (C2-C5) underwent RFA and were randomized to receive either elastic stockings (study group) or multilayer bandage compression (control group) for 48 h postoperatively. Primary outcomes included postoperative complications assessed at 2 h, 1 day, 2 days, 7 days, and 1 month. Secondary outcomes included pain (VAS), quality of life (CIVIQ-14), venous clinical severity score (VCSS), satisfaction (10-point scale), and time to return to normal work. Follow-up rates were 98% at 7 days and 96% at 1 month.ResultsMinor but statistically significant differences were observed in complications such as pain, ecchymosis, edema, and itching between groups. The study group returned to work sooner (2.11 ± 1.19 days) than the control group (4.39 ± 2.55 days, p < 0.01). Patient satisfaction at 1 month and changes in CIVIQ-14 and VCSS scores showed no significant between-group differences.ConclusionElastic stockings worn for 48 h after RFA provided certain advantages over multilayer bandage compression, particularly in reducing early postoperative complications and shortening time to return to work.

PMID:41701921 | DOI:10.1177/02683555261424388

J Am Soc Mass Spectrom. 2026 Feb 17. doi: 10.1021/jasms.5c00372. Online ahead of print.

ABSTRACT

Untargeted tandem mass spectrometry (MS/MS)-based metabolomics enable broad characterization of small molecules in complex samples, yet the majority of spectra in a typical experiment remain unannotated, limiting biological interpretation. Reference data-driven (RDD) metabolomics addresses this gap by contextualizing spectra through comparison to curated, metadata-annotated reference data sets, allowing inference of spectrum origins without requiring exact structural identification. Here, we present an open-source RDD metabolomics platform comprising a user-friendly web application and a Python software package that performs RDD analyses directly from molecular networking outputs generated by GNPS. The tools support visualization and statistical analysis of RDD results, including interactive bar plots, heat maps, principal component analysis, and Sankey diagrams. We illustrate the approach using a hierarchical reference data set of 3500 food items to derive dietary patterns from stool metabolomics data of omnivore and vegan participants. The analysis reveals clear dietary group separation, demonstrating how RDD metabolomics can extract biologically meaningful patterns from otherwise unannotated spectra. Thus, the RDD metabolomics platform removes technical barriers for the metabolomics community to adopting RDD analysis, with the functionality freely available at https://github.com/bittremieuxlab/gnps-rdd and https://gnps-rdd.bittremieuxlab.org/.

PMID:41701920 | DOI:10.1021/jasms.5c00372

Natl Health Stat Report. 2025 Sep 30;(219):1. doi: 10.15620/cdc/174622.

ABSTRACT

OBJECTIVE: This report examines selected measures of healthcare use among teenagers ages 12-17 by parent- or self-report. Agreement between parent-reported and teen self-reported data is also evaluated.

METHODS: The percentage of teenagers with doctor visits, wellness visits, having a usual place of care, having a personal doctor or nurse, and having time alone with a doctor were estimated using teen-reported data from the National Health Interview Survey-Teen collected from July 2021 through December 2023. These estimates were compared with parent-reported estimates from the same time period using data from the National Health Interview Survey. Cohen’s kappa and prevalence-adjusted, bias-adjusted kappa (PABAK) values were used to evaluate agreement between parent and teen responses.

RESULTS: Across all measures, parents reported higher healthcare use for their teenagers than teenagers reported for themselves (for example, 91.4% of parents reported a doctor’s visit in the last 12 months compared with 83.0% of teenagers). Cohen’s kappa values across measures showed fair to slight agreement, with PABAK values showing slightly higher agreement, ranging from slight to substantial. Percentage agreement patterns were most often driven by both parent and teenager affirming healthcare use indicators, except for having time alone with a doctor, which was driven slightly more by the parent and teenager both reporting the teenager had not received this service. Disagreement patterns were driven by parents affirming services the teenager did not; disagreement was highest for having a personal doctor or nurse and time alone with a doctor.

PMID:41701917 | DOI:10.15620/cdc/174622

Natl Health Stat Report. 2025 Dec 16;(220):1. doi: 10.15620/cdc/174626.

ABSTRACT

BACKGROUND: Since 1972, low-density lipoprotein cholesterol (LDL-C) has been calculated by the Friedewald equation, which estimates very low-density lipoprotein cholesterol as triglycerides divided by 5 and is accurate only for triglycerides <400 mg/dL. The Martin equation, published in 2013 (for triglycerides <400 mg/dL), replaced 5 with a factor varying over an array of non-high-density lipoprotein cholesterol and triglyceride levels. This array was extended in 2021 for triglycerides 400-<800 mg/dL. In 2020, the Sampson equation, accurate for triglycerides <800 mg/dL, was developed using multiple least squares regression. This report compares LDL-C as calculated by the Friedewald, Martin, and Sampson equations in a nationally representative sample of adults with triglycerides <400 mg/dL across the distribution of clinical cut points for LDL-C (<70 mg/dL, 70-<100 mg/dL, 100-<160 mg/dL, 160-<190 mg/dL, and ≥190 mg/dL) to assess the impact of equation choice on national estimates.

METHODS: Using data on 4,461 adults in the 2015-2018 National Health and Nutrition Examination Survey, classification agreement into the LDL-C categories used for clinical management across the three equations was assessed using kappa statistics for men and women overall and by demographic subgroups. A sensitivity analysis assessed classification agreement between the Martin and Sampson equations for adults with triglycerides <800 mg/dL.

RESULTS: During 2015-2018, 9.8%-10.0% of adults age 20 and older had LDL-C levels <70 mg/dL (Friedewald: 10.0%, Martin: 9.8%, Sampson: 9.8%). Less than 3% had LDL-C >190 mg/dL (Friedewald: 2.3%, Martin: 2.4%, Sampson: 2.6%). Very good agreement between the equations was seen in all subgroups (kappa >0.8).

CONCLUSIONS: The three equations for LDL-C produce similar U.S. population-level percent distributions for adults age 20 and older across LDL-C categories.

PMID:41701902 | DOI:10.15620/cdc/174626

Can Urol Assoc J. 2026 Feb 13. doi: 10.5489/cuaj.9476. Online ahead of print.

ABSTRACT

INTRODUCTION: Automated segmentation using artificial intelligence (AI) has the potential to rapidly perform three-dimensional (3-D) segmentation of small renal masses (SRM). The objective of this study was to test for clinically and statistically significant differences in time spent segmenting, accuracy, and reliability when comparing manual and automated segmentation of computed tomography (CT) scans with SRM.

METHODS: Patients with a CT scan, SRM <4 cm, and renal neoplasm were identified through an institutional database. Of the 854 patients identified, 184 were excluded. Forty test cases were randomly selected. There were 630 cases for training (using nnU-Net) to which 488 cases from the KiTS23 open-source data set were added. Each of the test cases was segmented by a radiologist, a urologist, and the AI model. Time to segment and Dice coefficients were compared. Deidentified segmented CTs were provided to two independent radiologists who attempted to identify the segmentor and rated the acceptability of the segmented images on a five-point Likert scale.

RESULTS: There were 39 cases with complete timing data. The median time for the AI model to segment was one third of the radiologist’s (152.4 s, interquartile range [IQR] 120.9-177.8 vs. 450 s, IQR 318.8-551.2) and about one-fifth of the urologist’s (800.0 s, IQR 492.0-1538.0) (p<0.001). There was a high degree of inter-rater reliability (median Dice coefficients 0.86-0.90, p=0.09). The scoring radiologists were able to correctly identify the true segmentor in 61.6% of cases (p <0.001). The AI segmentations were scored highest among the three segmentors (median score 4.1/5, standard deviation [SD] 1.0) compared to 3.8 (SD 0.7) for the radiologist, and 3.3 (SD 0.7) for the urologist.

CONCLUSIONS: Automated segmentation of CT scans for patients with SRM was efficient, accurate, and acceptable in this study. This approach has the potential to greatly improve the clinical use of radiomics to assess medical images for these patients.

PMID:41701890 | DOI:10.5489/cuaj.9476

Nurs Educ Perspect. 2026 Mar-Apr 01;47(2):96-100. doi: 10.1097/01.NEP.0000000000001491. Epub 2026 Feb 16.

ABSTRACT

AIM: The study explored the relationship between self-care practices and resilience in baccalaureate nursing faculty before, during, and after the COVID-19 pandemic.

BACKGROUND: There is limited research on self-care and resilience in nurse faculty, yet certain factors have been determined to negatively impact work-life balance.

METHOD: A cross-sectional research survey collected quantitative data on demographics, self-care practices, and resilience. Surveys were sent to nurse faculty within a large statewide system (n = 312).

RESULTS: Before the pandemic, neither demographic characteristics nor self-care was significant predictors of resilience; during and after, however, there was a statistically significant relationship between self-care behaviors and resilience (p = .007, p = .018). Faculty reporting higher levels of self-care measured higher in resilience.

CONCLUSION: Encouraging self-care practices in nurse faculty can enhance resilience and potentially improve overall well-being. Further research on factors of influence would be of benefit.

PMID:41701857 | DOI:10.1097/01.NEP.0000000000001491

Nurs Educ Perspect. 2026 Mar-Apr 01;47(2):86-95. doi: 10.1097/01.NEP.0000000000001492. Epub 2026 Feb 16.

ABSTRACT

AIM: The aim of this study was to examine the relationships between work efforts and rewards with intention to leave and burnout among full-time nurse educators.

BACKGROUND: The nursing faculty shortage is a contributor to the nursing shortage. Poor balance between work efforts and rewards may contribute to intention to leave.

METHOD: A cross-sectional survey of US nurse faculty examined work efforts, rewards, burnout, and intention to leave. Structural equation modeling was used to evaluate the relationships among variables.

RESULTS: Among 588 participants, efforts and rewards both had significant effects on burnout. Burnout and rewards had significant effects on intention to leave. Relationships between efforts, rewards, and intention to leave were significantly mediated by burnout. Efforts, rewards, and burnout all had significant total effects on intention to leave.

CONCLUSION: Interrelationships linking effort, rewards, and burnout require thoughtful solutions focusing on balancing efforts and rewards while addressing dissatisfaction with the nursing faculty role.

PMID:41701856 | DOI:10.1097/01.NEP.0000000000001492