Tag: nevin manimala

PLoS One. 2025 Jul 3;20(7):e0327537. doi: 10.1371/journal.pone.0327537. eCollection 2025.

ABSTRACT

Identifying critically ill patients who are likely to improve their respiratory physiology following RBC transfusion is dynamic and difficult. Current decision tools are over-reliant on hemoglobin transfusion thresholds, without considering respiratory measures that may reflect physiologic effects of anemia and functional responses to RBC transfusion. Further, routine clinical measures to determine transfusion efficacy beyond hemoglobin increment are lacking to identify patients as responders or non-responders. We present a two-center retrospective cohort study aiming to determine a potential biomarker to assess the physiologic response of RBC transfusion for non-traumatic ICU patients. The study was performed with 13,274 eligible patients at the first center. Another 3,757 from the second center were used as a validation population. We introduced a comparative analysis of two respiratory measures, SpO2 and SpO2/FiO2 (SF) ratio, in addition to hemoglobin, to assess individual patient responses to RBC transfusion. A statistical study was performed to compare these markers before and after the transfusion interval. Based on quantitative statistical analyses, we found SF ratio to be a more effective biomarker than hemoglobin alone for revealing RBC transfusion efficacy. There existed an inverse correlation between pre-transfusion SF and transfusion efficacy. The results were consistent across both centers, revealing generalizability. With the SF data from both the centers, we also developed a random forest-based regression model that significantly evaluated the level of transfusion effectiveness (p < 0.001).

PMID:40608780 | DOI:10.1371/journal.pone.0327537

Anal Chem. 2025 Jul 3. doi: 10.1021/acs.analchem.5c01672. Online ahead of print.

ABSTRACT

We present a comprehensive map of the metabolomics research landscape, synthesizing insights from over 80,000 publications. Using PubMedBERT, we transformed abstracts into 768-dimensional embeddings that capture the nuanced thematic structure of the field. Dimensionality reduction with t-SNE revealed distinct clusters corresponding to key domains, such as analytical chemistry, plant biology, pharmacology, and clinical diagnostics. In addition, a neural topic modeling pipeline refined with GPT-4o mini reclassified the corpus into 20 distinct topics─ranging from “Plant Stress Response Mechanisms” and “NMR Spectroscopy Innovations” to “COVID-19 Metabolomic and Immune Responses.” Temporal analyses further highlight trends including the rise of deep learning methods post-2015 and a continued focus on biomarker discovery. Integration of metadata such as publication statistics and sample sizes provides additional context to these evolving research dynamics. An interactive web application (https://metascape.streamlit.app/) enables the dynamic exploration of these insights. Overall, this study offers a robust framework for literature synthesis that empowers researchers, clinicians, and policymakers to identify emerging research trajectories and address critical challenges in metabolomics while also sharing our perspectives on key trends shaping the field.

PMID:40608399 | DOI:10.1021/acs.analchem.5c01672

Epilepsia Open. 2025 Jul 3. doi: 10.1002/epi4.70072. Online ahead of print.

ABSTRACT

OBJECTIVE: The gut microbiota (GM) plays a role in epilepsy development via the microbiota-gut-brain axis. However, its relationship with various epilepsy subtypes and its mediating role through immune cells remain unclear. Thus, identifying the GM linked to specific epilepsy subtypes and investigating immune mechanisms to predict epilepsy risk, tailor treatments, and monitor outcomes are crucial.

METHODS: We performed a two-sample Mendelian randomization (MR) study focused on the relationships between different epilepsy subtypes associated with the GM and the mediating role of immune cells between different epilepsy subtypes and the GM. Genome-wide association analysis summary statistics of 412 GM species (GCST90027446-GCST90027857) and 731 immune cell phenotypes (GCST90001391-GCST90002121), along with summary statistics of different subtypes of epilepsy, were used in a publicly available genome-wide association analysis. Significantly associated single-nucleotide polymorphism (SNP) loci were extracted as instrumental variables according to preset thresholds, with an inverse variance weighted (IVW) model being the main model. Additionally, MR-Egger regression, weighted median, weighted, and simple models were also used for analysis.

RESULTS: MR analyses revealed the relationships of the GM and immune cells with diverse epilepsy subtypes, with no statistically significant effect of different epilepsy subtypes on the GM after correction for multiple testing via the false discovery rate (FDR) approach. Notably, one bacterial species, Gordonibacter pamelaeae, with an uncorrected low p-value (OR: 1.0136, 95% CI: 1.0048-1.0225, p = 0.0025), was positively related to childhood absence epilepsy (CAE). Among immune cells, CD4+ ACs (OR: 1.0152, 95% CI: 1.0067-1.0238, p = 0.0005) were strongly related to CAE. Additionally, mediated effect analysis revealed that seven types of GM mediate the effects of eight immune cells on epilepsy, with Bacteroides caccae mediating CD33br HLA DR+ CD14dim AC cells producing the greatest effect on generalized epilepsy.

SIGNIFICANCE: The above results demonstrate the close association between specific GM and specific immune cells in epilepsy and can be used to inform the treatment of different epilepsy subtypes by modulating the GM and immune cells.

PLAIN LANGUAGE SUMMARY: This study investigated the relationships between the gut microbiota and different epilepsy subtypes and the mediating role of immune cells. These findings emphasize that there is a close association between specific gut microbiota and specific immune cells in epilepsy and that they can be used to inform the treatment of different epilepsy subtypes by modulating the gut microbiota and immune cells.

PMID:40608392 | DOI:10.1002/epi4.70072

JAMA Netw Open. 2025 Jul 1;8(7):e2518906. doi: 10.1001/jamanetworkopen.2025.18906.

ABSTRACT

IMPORTANCE: Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin-stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring approaches that produce more reliable and consistent readouts is important.

OBJECTIVE: To evaluate the analytical and clinical validity of a machine learning algorithm for TIL quantification in melanoma compared with traditional pathologist-read methods.

DESIGN, SETTING, AND PARTICIPANTS: This multioperator, global, multi-institutional prognostic study compared TIL scoring reproducibility between traditional pathologist-read methods and an artificial intelligence (AI)-driven approach. The study was conducted using retrospective cohorts of patients with melanoma between January 2022 and June 2023 across 45 institutions, with tissue evaluated by participants from academic, clinical, and research institutions. Participants were selected to ensure diverse expertise and professional backgrounds.

MAIN OUTCOMES AND MEASURES: Intraclass correlation coefficient (ICC) values were calculated for the manual and AI-assisted arms using log-transformed data. Kendall W values were calculated for Clark scores (brisk = 3, nonbrisk = 2, and sparse = 1). Reliabilities of ICC and W values were classified as moderate (0.40-0.60), good (0.61-0.80), or excellent (>0.80). AI TIL measurements were dichotomized using the 16.6 and median cutoffs. Univariable and multivariable Cox regression analyses assessed the prognostic value of TIL scores adjusted for clinicopathologic variables.

RESULTS: There were 111 patients with melanoma in the independent testing cohort (median [range] age at diagnosis, 61.0 [25.0-87.0] years; 56 [50.5%] male) who contributed melanoma whole tissue sections. A total of 98 participants evaluated TILs on 60 hematoxylin and eosin-stained melanoma tissue sections. All 40 participants in the manual arm were pathologists, while the AI-assisted arm included 11 pathologists and 47 nonpathologists (scientists). The AI algorithm demonstrated superior reproducibility, with ICCs higher than 0.90 for all machine learning TIL variables, significantly outperforming manual assessments (ICC, 0.61 for AI-derived stromal TILs vs Kendall W, 0.44 for manual Clark TIL scoring). AI-based TIL scores showed prognostic associations with patient outcomes (n = 111) using the median cutoff approach with a hazard ratio (HR) of 0.45 (95% CI, 0.26-0.80; P = .005), and using the cutoff of 16.6, with an HR of 0.56 (95% CI, 0.32-0.98; P = .04).

CONCLUSIONS AND RELEVANCE: In this prognostic study of TIL quantification in melanoma, the AI algorithm demonstrated superior reproducibility and prognostic associations compared with traditional methods. Although the retrospective nature of the cohorts limits demonstration of clinical utility, the publicly available dataset and open-source AI tool offer a foundation for future validation and integration into melanoma management.

PMID:40608341 | DOI:10.1001/jamanetworkopen.2025.18906

JAMA Netw Open. 2025 Jul 1;8(7):e2518960. doi: 10.1001/jamanetworkopen.2025.18960.

ABSTRACT

IMPORTANCE: Secure firearm storage is a key strategy for firearm injury prevention. Understanding trends in firearm storage behaviors over time is critical for developing tailored interventions.

OBJECTIVE: To characterize trends in household firearm storage from 2013 to 2022 in Washington State and to assess time-varying associations between demographic groups and secure storage.

DESIGN, SETTING, AND PARTICIPANTS: This survey study with repeated cross-sectional measures used data from the Behavioral Risk Factor Surveillance System, a state-based survey of adults (aged ≥18 years) living in Washington State that was conducted by telephone and included questions regarding firearm storage in the 2013, 2015, 2016, 2018, 2020, or 2022 cycles. Data were analyzed from August 2024 through April 2025.

EXPOSURES: Demographic variables including sex, age, rurality (urban vs small town or rural), veteran status, and the presence of children in the home.

MAIN OUTCOMES AND MEASURES: The primary outcome was the percentage of adults who reported secure firearm storage (all household firearms stored unloaded and locked). Logistic regression models that included each of the selected demographic variables, year, and interactions between them were used to estimate time-varying associations, with weighted percentages used to account for complex survey design and to be representative of the adult population of Washington State.

RESULTS: A total of 77 275 survey respondents (mean [SD] age, 46.7 [18.9] years) in Washington State were included in the analysis. Of these, 51.7% (95% CI, 51.2%-52.1%) were female. The percentage of adults reporting household firearm presence was 35.7% (95% CI, 34.4%-37.0%) in 2013 and 33.3% (95% CI, 32.5%-34.1%) in 2022. Among households with firearms (n = 27 721), secure storage was reported among 34.9% (95% CI, 32.8%-37.1%) in 2013 and 48.8% (95% CI, 47.2%-50.3%) in 2022. The odds of secure storage significantly increased per year overall (odds ratio [OR], 1.07; 95% CI, 1.06-1.08), and among nearly all subgroups: males (OR, 1.08; 95% CI, 1.07-1.10), females (OR, 1.06; 95% CI, 1.04-1.08), veterans (OR, 1.09; 95% CI, 1.07-1.10), nonveterans (OR, 1.07; 95% CI, 1.05-1.08), those with children (1.08; 95% CI, 1.06-1.10), and those without (OR, 1.07; 95% CI, 1.06-1.08). The odds increased in urban areas (OR, 1.07; 95% CI, 1.05-1.08) and suburban areas or large towns (OR, 1.08; 95% CI, 1.05-1.10) but not in small towns or rural areas (OR, 1.01; 95% CI, 0.97-1.06).

CONCLUSIONS AND RELEVANCE: In this survey study of Washington State adults, the percentage of adults reporting secure storage of household firearms increased from 2013 to 2022, but differences persisted across demographic groups. These findings underscore the need for more tailored interventions to address these disparities.

PMID:40608340 | DOI:10.1001/jamanetworkopen.2025.18960

JAMA Netw Open. 2025 Jul 1;8(7):e2518967. doi: 10.1001/jamanetworkopen.2025.18967.

ABSTRACT

IMPORTANCE: Goal-concordant care (GCC) is recognized as the highest quality of care and most important outcome measure for serious illness research, yet practical methods for measuring it are lacking.

OBJECTIVE: To measure GCC using clinical notes in patients’ medical records.

DESIGN, SETTING, AND PARTICIPANTS: This longitudinal cohort study involved a retrospective medical record review in 3 urban hospitals in a single health system. Participants included adults with a hospital encounter of 3 or more days between April 1 and July 31, 2019, and 50% or higher predicted 6-month mortality risk. Data abstraction occurred from July 2021 through June 2022.

EXPOSURE: Acute care hospitalization and a 50% or higher predicted 6-month mortality risk.

MAIN OUTCOMES AND MEASURES: Pairs of clinicians independently reviewed clinical notes from admission through 6 months or death to classify the care received during each epoch between patients’ documented goals of care (GOC) discussions, into 1 of 4 categories: (1) comfort focused, (2) maintain or improve function, (3) life extension, or (4) unclear. The GOC discussions had been previously classified using the same 4 categories. The primary study outcome was GCC, defined as the alignment of classification of care received and GOC. Secondary outcomes included goal-discordant care, if GOC and care-received classifications were misaligned, and uncertain concordance, if either care received or GOC was classified as unclear or GOC were not documented. Interrater reliability for classification of care received was assessed using Cohen κ statistics.

RESULTS: Among 109 patients (53 female [49%]), the median (IQR) age was 70 (63-79) years. The most common serious illnesses were cardiac disease (76 patients [70%]), metastatic cancer (50 patients [45%]), and chronic kidney disease (42 patients [39%]). Interrater reliability for care-received classification was almost perfect (95% interrater agreement, Cohen κ = 0.92; 95% CI, 0.86-0.99). A total of 398 epochs of care were identified, 198 (50%) of which were classified as goal concordant. Of the remaining 200 epochs, 74 (19%) were classified as goal discordant and 126 (32%) of uncertain concordance. During at least 1 epoch of care over the 6-month follow-up, 85 patients (78%) received care of uncertain concordance and 43 (39%) received goal-discordant care.

CONCLUSIONS AND RELEVANCE: In this cohort study of seriously ill adults, GCC was measured using clinical notes alone. These findings can inform automated text-based classification methods to improve the efficiency and scalability of this method and facilitate pragmatic and reliable measurement of GCC in serious illness research and quality improvement efforts.

PMID:40608339 | DOI:10.1001/jamanetworkopen.2025.18967

JAMA Netw Open. 2025 Jul 1;8(7):e2518977. doi: 10.1001/jamanetworkopen.2025.18977.

ABSTRACT

IMPORTANCE: Primary care practitioners (PCPs) and staff in Veterans Health Administration (VHA) clinics with staffing shortages have reported higher rates of burnout that may be associated with higher workloads. Introducing PCPs through the Clinical Research Hub (CRH) virtual contingency staffing program into these clinics may help reduce burnout but may also disrupt workflows and increase burnout.

OBJECTIVE: To understand how rates of burnout among VHA PCPs and staff vary by staffing level and CRH program use.

DESIGN, SETTING, AND PARTICIPANTS: This survey study used annual, repeated, cross-sectional VHA employee survey data from fiscal years 2018 to 2022 to examine associations between staffing and burnout before and after implementation of the CRH program.

EXPOSURE: Clinical Research Hub virtual contingency PCP visits.

MAIN OUTCOME AND MEASURES: The main outcome was burnout as measured using multilevel, mixed-effects logistic regression to estimate the association between health care system-level PCP staffing and individual-level PCP and staff burnout before and after implementation of the CRH program. An interaction term was used to test the association between program use and burnout in health care systems with full and less-than-full PCP staffing, controlling for PCP, staff, and health care system characteristics. Estimated marginal means of burnout were calculated from model results.

RESULTS: Survey responses from 134 640 PCPs and staff (53% younger than 49 years; 70% female) in 139 VHA health care systems were analyzed. From fiscal years 2018 to 2022, 38% of PCPs and staff experienced burnout, and CRH visits ranged from a median of 0 to 127.6 (IQR, 76.7-237.4) visits per 1000 patients at the health care system level. In estimations derived from the full model, the probability of burnout was higher in clinics without full PCP staffing before program implementation (34.3% [95% CI, 33.4%-35.2%] without full staffing vs 36.5% [95% CI, 35.3%-37.8%] with full staffing) and in the lowest tertile of CRH visits (37.4% [95% CI, 36.4%-38.4%] without full staffing vs 40.2% [95% CI, 38.3%-42.1%] with full staffing). However, burnout did not differ by staffing at higher levels of CRH visits.

CONCLUSIONS AND RELEVANCE: In this survey study of VHA PCPs and staff, the association between low staffing and burnout was mitigated at higher levels of CRH program use, suggesting that contingency PCPs may alleviate high workload in short-staffed clinics.

PMID:40608338 | DOI:10.1001/jamanetworkopen.2025.18977

JAMA Netw Open. 2025 Jul 1;8(7):e2519029. doi: 10.1001/jamanetworkopen.2025.19029.

ABSTRACT

IMPORTANCE: Hospital ratings including the US News & World Report’s Best Hospitals rankings and the Centers for Medicare & Medicaid Services’ (CMS’) Overall Hospital Quality Star Rating (Overall Star Rating) measure different outcomes and are weakly correlated. Therefore, methods for defining and measuring reliable excellence, defined as consistently great performance across all quality measures, are needed.

OBJECTIVE: To assess a measure of reliable excellence using the 45 quality measures reported in the Overall Star Ratings.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used hospital-level data from the 2023 and 2024 CMS Overall Star Ratings at all US hospitals with a 2023 and 2024 CMS Overall Star Rating.

EXPOSURES: The exposure was the CMS Overall Star Rating summary score, a continuous variable calculated from the weighted z scores of 45 quality measures used in the Overall Star Rating. A total of 100 000 simulations were run in which all US hospitals’ CMS Overall Star Rating summary scores were calculated through summation of z scores from randomly generated measure weights, as opposed to the existing weights used in the Overall Star Rating method.

MAIN OUTCOMES AND MEASURES: Reliable excellence, defined as achieving a 90th percentile (or better) CMS Overall Star Rating summary score on at least 50 000 of 100 000 simulations. The percentage of hospitals achieving reliable excellence was calculated both overall and stratified by CMS Ovearll Star Ratings.

RESULTS: There were 2700 hospitals in the analysis, with 335 5-star hospitals (12.4%), 727 4-star hospitals (26.9%), 799 3-star hospitals (29.6%), 572 2-star hospitals (21.2%), and 267 1-star hospitals (9.9%) in the 2024 CMS Overall Star Rating. A total of 244 of 2700 hospitals (9.0%) met the study definition of reliable excellence, whereas 1287 of 2700 hospitals (47.7%) achieved excellence in at least 1 simulation.

CONCLUSIONS AND RELEVANCE: This cross-sectional study of 2700 US hospitals found that only 244 hospitals (9.0%), including less than two-thirds of the CMS 5-star rated hospitals, were reliably excellent across 100 000 CMS Overall Star Rating scoring simulations using random measure weightings. These findings lend credence to the ubiquity of inconsistent greatness in health care quality and illuminate the need for methods to distinguish hospitals that provide reliably excellent care.

PMID:40608337 | DOI:10.1001/jamanetworkopen.2025.19029

JAMA Netw Open. 2025 Jul 1;8(7):e2519038. doi: 10.1001/jamanetworkopen.2025.19038.

ABSTRACT

IMPORTANCE: Real-time prescription benefit (RTPB) tools provide point-of-care information for clinicians at the time of prescribing and may reduce prescription costs for patients and payers.

OBJECTIVE: To assess trends in prescription use and spending among Medicare Advantage beneficiaries at a national health insurer during the first year of clinician access to an RTPB tool.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study used 2018 to 2020 administrative data from a national insurer to compare prescription fills for beneficiaries receiving prescriptions from clinicians at practices with an RTPB tool with fills prescribed by clinicians without access to the tool. Trends in prescription spending and fills in the year after practices adopted an RTPB tool (in March 2019) were measured using a difference-in-differences design. Data were analyzed from November 2022 to June 2024.

EXPOSURE: Access to an RTPB tool within a national electronic health record software vendor.

MAIN OUTCOMES AND MEASURES: The main outcomes were total prescription spending, beneficiary out-of-pocket spending, and number of prescription fills. Secondary outcomes included percentage of fills with the insurer-owned mail-order pharmacy, percentage of fills with a 90-day supply, and subgroup analyses in drug classes appearing most frequently in the RTPB tool and high-cost prescription drug classes.

RESULTS: The sample included 2 805 060 beneficiaries (mean [SD] age 70.9 [9.2] years; 56.7% female; 14.7% Black individuals; 80.5% White individuals), with mean (SD) monthly out-of-pocket costs of $29.1 ($90.4), total prescription costs of $213.2 ($1066.3), and 2.6 (2.1) prescription fills per month. After introduction of the RTPB tool, there was no change in prescription spending (estimated out-of-pocket spending change, 1.2% [95% CI, -0.7% to 3.0%]; estimated total prescription spending change, 0.5% [95% CI: -0.2% to 1.2%]) or number of prescription fills (estimated change, 0.01 [95% CI, -0.01 to 0.02]) among beneficiaries prescribed medication by clinicians at practices with the RTPB tool.

CONCLUSIONS AND RELEVANCE: In this cohort study of 2.8 million patients, simply providing clinicians access to a RTPB tool was not associated with the anticipated benefits to patients and payers in the first year the tool was released. Further research on how to design and deploy RTPB tools to maximize potential benefits is needed.

PMID:40608336 | DOI:10.1001/jamanetworkopen.2025.19038

JAMA Netw Open. 2025 Jul 1;8(7):e2521158. doi: 10.1001/jamanetworkopen.2025.21158.

ABSTRACT

IMPORTANCE: Umbilical cord blood-derived cells (UCBCs) are increasingly being evaluated for neuroprotective properties in perinatal brain injury.

OBJECTIVE: To report early neurodevelopmental outcomes of extremely preterm infants who received autologous UCBCs in the CORD-SaFe study.

DESIGN, SETTING, AND PARTICIPANTS: This study reports early follow-up on the preplanned secondary aims of a phase 1 safety and feasibility nonrandomized clinical trial conducted between May 2021 and November 2023, with early follow-up completed in August 2024. Participants were infants born at less than 28 weeks’ completed gestation who received autologous UCBCs in the CORD-SaFe study at Monash Children’s Hospital, Australia. A contemporaneous cohort of noninfused infants born during the study period was included for comparison. Data were analyzed from October to December 2024.

INTERVENTION: Autologous UCBC administered intravenously in the second postnatal week of life.

MAIN OUTCOMES AND MEASURES: Infants underwent brain magnetic resonance imaging to assess structure and injury (Kidokoro score) at term-equivalent age. Assessments at 52 to 54 weeks postmenstrual age included General Movements Assessment, Hammersmith Infant Neurological Examination score, and clinical examination to diagnose risk of cerebral palsy.

RESULTS: A total of 23 infants (median [IQR] gestation, 26 [25-27] weeks; median [IQR] birth weight, 748 [645-981] grams; 17 [73.9%] male) were administered UCBCs at a median (IQR) dose of 42.3 (31.1-63.2) million cells/kg. The contemporaneous cohort included 93 infants (median [IQR] gestation, 26 (24-27) weeks; median [IQR] birth weight, 769 [660-1017] grams; 39 [41.9%] male). Median (IQR) Kidokoro score was 2 (1-3) for the UCBCs group and 3 (2-5) for the contemporaneous cohort, with no statistically significant difference observed between the groups (adjusted median difference, 0 [95% CI, -1.78 to 1.78]). No infants in the UCBC group were assessed as high risk for cerebral palsy compared with 6 of 87 assessed infants (6.8%) in the contemporaneous group; however, the difference was not statistically significant (adjusted log odds, 0.31 [95% CI, -0.76 to 1.38]). No differences in Hammersmith Infant Neurological Examination score (adjusted log odds, -1.50 [95% CI, -5.78 to 2.78]) and absent fidgety movements (adjusted odds ratio, 0.24 [95% CI, 0.20 to 3.04]) were observed between groups.

CONCLUSIONS AND RELEVANCE: This phase 1 nonrandomized clinical trial assessing the safety and feasibility of autologous UCBCs in extremely preterm infants did not find significant differences in brain imaging parameters and early neurodevelopmental outcomes between the cell therapy and contemporaneous untreated groups. It was encouraging to note no infants who received UCBCs were assessed as high risk for cerebral palsy at 52 to 54 weeks postmenstrual age, and the absence of high risk for CP merits further study.

TRIAL REGISTRATION: ANZCTR.org.au Identifier: ACTRN12619001637134.

PMID:40608334 | DOI:10.1001/jamanetworkopen.2025.21158