Tag: nevin manimala

Seizure. 2025 May 21;130:92-99. doi: 10.1016/j.seizure.2025.05.014. Online ahead of print.

ABSTRACT

BACKGROUND: Anxiety is a prevalent psychiatric comorbidity in temporal lobe epilepsy (TLE), however, limited attention has been given to the dynamic characteristics of TLE coexisting with anxiety.The aim of this study was to examine abnormal resting-state Electroencephalography (EEG) microstate dynamics in TLE patients with anxiety disorders compared with TLE patients without anxiety disorders and healthy controls.

METHODS: Ninety participants in this study: 30 healthy controls (HC), 30 TLE patients with anxiety (PAS), and 30 TLE patients without anxiety (nPAS). The dynamic changes in the entire brain were detected using a 21-channel EEG for microstate analysis. This study comprehensively compared the mean duration, frequency of occurrence, time coverage, and transition probability of each microstate(A, B, C, D) among the three groups. Rigorous statistical methods were employed to ensure the robustness and validity of the research findings.

RESULTS: The results of EEG microstate analysis revealed that the occurrence frequency and time coverage of microstate B (visual network) in the PAS were significantly reduced compared to the nPAS. Compared to HC and nPAS groups, patients with PAS exhibited alterations in the probability of EEG microstate transitions: an increase in transitions from the microstate C (salience network) to the microstate A (auditory network), a decrease in transitions from the dorsal microstate C (salience network) and microstate D (attention network) to the microstate B (visual network). These changes suggest heightened overall network alertness, impaired attention-visual pathway function, and decreased stability of the attention network.

CONCLUSION: Our research reveals that anxiety disorders in individuals with temporal lobe epilepsy are characterized by heightened alertness, impaired attention-visual integration, and instability of the dorsal attention network. This highlights the significant impact of anxiety on brain network remodeling and cognitive control deficits. Changes in EEG microstate dynamics may serve as a novel biomarker for psychiatric complications associated with epilepsy.

PMID:40440857 | DOI:10.1016/j.seizure.2025.05.014

Sci Total Environ. 2025 May 28;985:179724. doi: 10.1016/j.scitotenv.2025.179724. Online ahead of print.

ABSTRACT

New Approach Methods (NAMs) encompass a wide range of data types; it is increasingly common to have highly multi-dimensional data (e.g., cellular, molecular and gene expression effects) on the same chemicals. In addition, chemical structure descriptors (for mono-constituent substances) or fractional composition (for complex substances) inform similarity hypotheses for read-across. Still, the utility of these multi-dimensional datasets for decision-making is difficult to ascertain. To address this challenge, we hypothesized that correlation and mediation analyses methods can be used to uncover significant and interpretable relationships in complex NAMs datasets. We used previously published data on 141 petroleum UVCBs (substances of unknown or variable composition, complex reaction products and biological materials) that included (i) characterization of the polycyclic aromatic compound (PAC) content, (ii) 42 bioactivity measurements from 12 human cell types, and (iii) transcriptomic data from 6 cell types. We explored the relationships among data types and determined how these data can be used for bioactivity-based prioritization. We found that PAC content was highly informative for bioactivity prediction, while the addition of transcriptomic data provided modest improvements. We then applied the statistical procedure of mediation analysis to uncover relationships among transcriptomics, PAC, and bioactivity. The strongest relationships appeared to be nearly completely mediated, and phenotypes with high transcriptomic mediation tended to have high correlation with PAC content. This study shows how a mediation analysis approach can be used to uncover relationships in multi-dimensional NAMs datasets and provides further insights into strategies for hazard prioritization using a combination of transcriptomic and bioactivity data.

PMID:40440850 | DOI:10.1016/j.scitotenv.2025.179724

Food Chem. 2025 May 24;488:144693. doi: 10.1016/j.foodchem.2025.144693. Online ahead of print.

ABSTRACT

Flavor deterioration during juice processing limits industrial-scale pomegranate juice (PJ) production. To evaluate the effects of thermal and non-thermal processing on PJ flavor, three samples-pasteurized (PS), high-temperature short-time treated (HTST), and ultrasound-treated (US)-were analyzed against a fresh control (FJ). Totally 144 volatiles were identified by the combination of GC-MS and GC × GC-TOF-MS. Among, 16 was screened out as key aroma-active compounds of different PJs through GC-olfactometry/aroma intensity and relative odor activity values analysis. Quantitative descriptive analysis revealed pronounced variations in cooked flavor intensity across thermally processed samples (PS, HTST), while US exhibited a sensory profile comparable to FJ. Partial least squares regression aligned with the sensory profile. Further OPLS-discriminant analysis identified 8 and 11 key markers differentiating FJ from processed PJs, and thermal (PS, HTST) from non-thermal (US) treated PJs, respectively. Precursor addition elucidated formation pathways of major off-flavor compounds (dimethyl sulfide, methanethiol) in processed PJs.

PMID:40440840 | DOI:10.1016/j.foodchem.2025.144693

Gigascience. 2025 Jan 6;14:giaf052. doi: 10.1093/gigascience/giaf052.

ABSTRACT

Unsupervised clustering is a powerful machine-learning technique widely used to analyze high-dimensional biological data. It plays a crucial role in uncovering patterns, structures, and inherent relationships within complex datasets without relying on predefined labels. In the context of biology, high-dimensional data may include transcriptomics, proteomics, and a variety of single-cell omics data. Most existing clustering algorithms operate directly in the high-dimensional space, and their performance may be negatively affected by the phenomenon known as the curse of dimensionality. Here, we show an alternative clustering approach that alleviates the curse by sequentially projecting high-dimensional data into a low-dimensional representation. We validated the effectiveness of our approach, named automated projection pursuit (APP), across various biological data modalities, including flow and mass cytometry data, scRNA-seq, multiplex imaging data, and T-cell receptor repertoire data. APP efficiently recapitulated experimentally validated cell-type definitions and revealed new biologically meaningful patterns.

PMID:40440093 | DOI:10.1093/gigascience/giaf052

Nord J Psychiatry. 2025 May 29:1-4. doi: 10.1080/08039488.2025.2511072. Online ahead of print.

ABSTRACT

OBJECTIVE: In October 2022, the psychiatric emergency service PAB (in Danish: Psykiatrisk Akutberedskab) in the Capital Region of Denmark expanded its operations from an off-hours service to a 24/7 operational model. The PAB offers telephone and outreach services for people with psychiatric emergencies on professional request. The aim of this study was to describe the activities and evaluate the perceived usefulness of PAB’s 24/7 model.

MATERIALS AND METHODS: This study utilized a quantitative research approach, with data collection conducted during daytime hours of weekdays from October 2022 through September 2023, covering the first year of PAB’s 24/7 operations. The on-call psychiatrist documented requisitions from which statistical data have been compiled. The sample is comprised of 830 requisitions.

RESULTS: There was a recognizable demand for PAB in the Capital Region during weekday daytime hours. Most requisitions were made by family physicians and staff at sheltered homes. The majority of requisitions were considered relevant for PAB. Telephone consultations and mobile outreach services were utilized equally. Data from 2022 and 2023 exhibited similar activity patterns.

CONCLUSIONS: This brief report concludes that there is a clinically relevant need for PAB in the Capital Region of Denmark. PAB is a competent psychiatric emergency service that provides a qualified mobile crisis assessment with subsequent relevant action, and the strategic collaboration between psychiatrists and law enforcement enhances its efficiency. The clinical benefits derived from extended operational hours justify the associated costs.

PMID:40440091 | DOI:10.1080/08039488.2025.2511072

JAMA Netw Open. 2025 May 1;8(5):e2512689. doi: 10.1001/jamanetworkopen.2025.12689.

ABSTRACT

IMPORTANCE: Hip fractures present a substantial public health challenge, with projections of more than 500 000 per year by 2040. As such, frailty indices such as the Revised Risk Analysis Index (RAI) and the Modified Five-Item Frailty Index (mFI-5) have been recently investigated as metrics for preoperative risk stratification for these patients.

OBJECTIVE: To understand the accuracy of frailty, as measured by the RAI and the mFI-5, for estimating 30-day mortality following surgically managed hip fractures.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cross-sectional analysis used the American College of Surgeons’ National Surgical Quality Improvement database. Patients aged 65 years old with surgically managed traumatic hip fracture from 2015 to 2019 were included. Frailty was evaluated using the RAI, a 5-domain scale with 14 weighted variables graded from 0 to 81, and the mFI-5, a 2-domain scale with 5 unweighted variables graded from 0 to 5; for both, a higher score denotes worse frailty. Data collection occurred from May to June 2024.

EXPOSURE: Diagnosis of hip fracture and undergoing surgical fixation, hemiarthroplasty, or total hip arthroplasty.

MAIN OUTCOMES AND MEASURES: The primary outcome was 30-day mortality. Multivariable regression was conducted to assess the estimating value of frailty scales. Discriminatory accuracy was assessed using a receiver operating characteristic curve and quantified using a C-statistic.

RESULTS: The cohort consisted of 114 359 patients (70 038 female [69.9%]; median [IQR] age, 84 [77-89] years) with 51 071 prefrail patients (44.7%) according to the mFI-5 and 31 883 very frail patients (27.9%) according to the RAI comprising the largest frailty groups. Increasing frailty status was associated with greater odds ratio (OR) for 30-day mortality for both the mFI-5 (prefrail OR, 1.35 [95% CI, 1.24-1.47]; frail OR, 2.11 [95% CI, 1.94-2.30]; severely frail OR, 3.53 [95% CI, 3.20-3.90]; P < .001 for all) and RAI (normal OR, 1.55 [95% CI, 1.35-1.79]; frail OR, 2.97 [95% CI, 2.59-3.42]; very frail OR, 6.17 [95% CI, 5.38-7.08]; P < .001 for all). The RAI demonstrated superior discriminatory accuracy for 30-day mortality compared with the mFI-5 (area under the receiver operating characteristic curve, 0.73 [95% CI, 0.72-0.73] vs 0.61 [95% CI, 0.60-0.62]; P < .001).

CONCLUSIONS AND RELEVANCE: In this cross-sectional study of 114 359 patients, the RAI demonstrated superior odds and discriminatory accuracy for estimating 30-day mortality following surgical management of hip fractures. The RAI may be considered as a risk stratification tool for orthopedic surgeons to adjunct surgical planning, thereby reducing postoperative mortality.

PMID:40440016 | DOI:10.1001/jamanetworkopen.2025.12689

JAMA Netw Open. 2025 May 1;8(5):e2512941. doi: 10.1001/jamanetworkopen.2025.12941.

ABSTRACT

IMPORTANCE: Migrant and refugee populations are increasing globally, and children and adolescents in these populations are particularly susceptible to mental disorders. North Korean refugee (NKR) youths now living in South Korea share a culture, language, and history with South Korean (SK) youths, making these 2 groups suitable for studying the environmental factors in psychiatric health.

OBJECTIVE: To compare the risk of developing mental illness and individual psychiatric disorders among NKR youths and SK youths.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study obtained data from Korea’s National Health Insurance Service claims database from 2005 to 2021. Participants were aged 1 to 18 years between 2007 and 2010 who had no prior psychiatric claims, whether as outpatients or inpatients. Children and adolescents of the SK general population matched 1:10 on sex and age were compared with the NKR youth population. Statistical analyses were performed from August 2024 to March 2025.

MAIN OUTCOMES AND MEASURES: Risk, presented as hazard ratio (HR), of developing psychiatric disorders in NKR youths compared with SK youths. This risk was assessed using a Cox proportional hazards regression model and Kaplan-Meier time-to-event probabilities.

RESULTS: In total, 1618 NKR youths (810 males [50.1%]; mean [SD] age, 9.48 [4.62] years) and 308 927 SK youths (194 331 females [62.9%]; mean [SD] age, 11.80 [4.72] years) were included in this study. NKR youths showed a significantly higher risk of developing psychiatric disorders (HR, 1.29; 95% CI, 1.17-1.43) compared with SK youths. Individual psychiatric disorder risks were higher for NKR youths, including posttraumatic stress disorder (HR, 2.33; 95% CI, 1.34-4.06; P = .003), attention-deficit/hyperactivity disorder (HR, 1.67; 95% CI, 1.32-2.11; P < .001), bipolar affective disorders (HR, 1.61; 95% CI, 1.20-2.15; P < .001), major depressive disorder (HR, 1.53; 95% CI, 1.33-1.75; P < .001), and anxiety (HR, 1.25; 95% CI, 1.11-1.42; P < .001).

CONCLUSIONS AND RELEVANCE: In this cohort study, compared with SK youths, NKR youths showed a significantly higher risk of developing psychiatric disorders overall and individual psychiatric disorders, such as posttraumatic stress disorder, attention-deficit/hyperactivity disorder, bipolar disorder, major depressive disorder, and anxiety. This finding is important for establishing medical and educational service plans and policies for the increasing number of refugee youths in South Korea.

PMID:40440014 | DOI:10.1001/jamanetworkopen.2025.12941

JAMA Netw Open. 2025 May 1;8(5):e2512947. doi: 10.1001/jamanetworkopen.2025.12947.

ABSTRACT

IMPORTANCE: Fair clinical prediction models are crucial for achieving equitable health outcomes. Intersectionality has been applied to develop algorithms that address discrimination among intersections of protected attributes (eg, Black women rather than Black persons or women separately), yet most fair algorithms default to marginal debiasing, optimizing performance across simplified patient subgroups.

OBJECTIVE: To assess the extent to which simplifying patient subgroups during training is associated with intersectional subgroup performance in emergency department (ED) admission models.

DESIGN, SETTING, AND PARTICIPANTS: This prognostic study of admission prediction models used retrospective data from ED visits to Beth Israel Deaconess Medical Center Medical Information Mart for Intensive Care IV (MIMIC-IV; n = 160 016) from January 1, 2011, to December 31, 2019, and Boston Children’s Hospital (BCH; n = 22 222) from June 1 through August 13, 2019. Statistical analysis was conducted from January 2022 to August 2024.

MAIN OUTCOMES AND MEASURES: The primary outcome was admission to an in-patient service. The accuracy of admission predictions among intersectional subgroups was measured under variations on model training with respect to optimizing for group level performance. Under different fairness definitions (calibration, error rate balance) and modeling methods (linear, nonlinear), overall performance and subgroup performance of marginal debiasing approaches were compared with intersectional debiasing approaches. Subgroups were defined by self-reported race and ethnicity and gender. Measures include area under the receiver operator characteristic curve (AUROC), area under the precision recall curve, subgroup calibration error, and false-negative rates.

RESULTS: The MIMIC-IV cohort included 160 016 visits (mean [SD] age, 53.0 [19.3] years; 57.4% female patients; 0.3% American Indian or Alaska Native patients, 3.7% Asian patients, 26.2% Black patients, 10.0% Hispanic or Latino patients, and 59.7% White patients; 29.5% admitted) and the BCH cohort included 22 222 visits (mean [SD] age, 8.2 [6.8] years; 52.1% male patients; 0.1% American Indian or Alaska Native patients, 4.0% Asian patients, 19.7% Black patients, 30.6% Hispanic or Latino patients, 0.2% Native Hawaiian or Pacific Islander patients, 37.7% White patients; 16.3% admitted). Among MIMIC-IV groups, intersectional debiasing was associated with a reduced subgroup calibration error from 0.083 to 0.065 (22.3%), while marginal fairness debiasing was associated with a reduced subgroup calibration error from 0.083 to 0.074 (11.3%; difference, 11.1%); among BCH groups, intersectional debiasing was associated with a reduced subgroup calibration error from 0.111 to 0.080 (28.3%), while marginal fairness debiasing was associated with a reduced subgroup calibration error from 0.111 to 0.086 (22.6%; difference, 5.7%). Among MIMIC-IV groups, intersectional debiasing was associated with lowered subgroup false-negative rates from 0.142 to 0.125 (11.9%), while marginal debiasing was associated with lowered subgroup false-negative rates from 0.142 to 0.132 (6.8%; difference, 5.1%). Fairness improvements did not decrease overall accuracy compared with baseline models (eg, MIMIC-IV: mean [SD] AUROC, 0.85 [0.00], both models). Intersectional debiasing was associated with lowered error rates in several intersectional subpopulations compared with other strategies.

CONCLUSIONS AND RELEVANCE: This study suggests that intersectional debiasing better mitigates performance disparities across intersecting groups than marginal debiasing for admission prediction. Intersectionally debiased models were associated with reduced group-specific errors without compromising overall accuracy. Clinical risk prediction models should consider incorporating intersectional debiasing into their development.

PMID:40440013 | DOI:10.1001/jamanetworkopen.2025.12947

JAMA Netw Open. 2025 May 1;8(5):e2512994. doi: 10.1001/jamanetworkopen.2025.12994.

ABSTRACT

IMPORTANCE: Large language models (LLMs) have not yet been compared with traditional diagnostic decision support systems (DDSSs) on unpublished clinical cases.

OBJECTIVE: To compare the performance of 2 widely used LLMs (ChatGPT, version 4 [hereafter, LLM1] and Gemini, version 1.5 [hereafter, LLM2]) with a DDSS (DXplain [hereafter, DDSS]) on 36 unpublished general medicine cases.

DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study, conducted from October 6, 2023, to November 22, 2024, looked for the presence of the known case diagnosis in the differential diagnoses of the LLMs and DDSS after data from previously unpublished clinical cases from 3 academic medical centers were entered. The systems’ performance was assessed both with and without laboratory test data. Each case was reviewed by 3 physicians blinded to the case diagnosis. Physicians identified all clinical findings as well as the subset deemed relevant to making the diagnosis for mapping to the DDSS’s controlled vocabulary. Two other physicians, also blinded to the diagnoses, entered the data from these cases into the DDSS, LLM1, and LLM2.

EXPOSURES: All cases were entered into each LLM twice, with and without laboratory test results. For the DDSS, each case was entered 4 times: for all findings and for findings relevant to the diagnosis, each with and without laboratory test results. The top 25 diagnoses in each resulting differential diagnosis were reviewed.

MAIN OUTCOMES AND MEASURES: Presence or absence of the case diagnosis in the system’s differential diagnosis and, when present, in which quintile it appeared in the top 25 diagnoses.

RESULTS: Among 36 patient cases of various races and ethnicities, genders, and ages (mean [SD] age, 51.4 [16.4] years), in the version with all findings but no laboratory test results, the DDSS listed the case diagnosis in its differential diagnosis more often (56% [20 of 36]) than LLM1 (42% [15 of 36]) and LLM2 (39% [14 of 36]), although this difference did not reach statistical significance (DDSS vs LLMI, P = .09; DDSS vs LLM2, P = .08). All 3 systems listed the case diagnosis in most cases if laboratory test results were included (all findings DDSS, 72% [26 of 36]; LLM1, 64% [23 of 36]; and LLM2, 58% [21 of 36]).

CONCLUSIONS AND RELEVANCE: In this diagnostic study comparing the performance of a traditional DDSS and current LLMs on unpublished clinical cases, in most cases, every system listed the case diagnosis in their top 25 diagnoses if laboratory test results were included. A hybrid approach that combines the parsing and expository linguistic capabilities of LLMs with the deterministic and explanatory capabilities of traditional DDSSs may produce synergistic benefits.

PMID:40440012 | DOI:10.1001/jamanetworkopen.2025.12994

Adv Ther. 2025 May 29. doi: 10.1007/s12325-025-03207-6. Online ahead of print.

ABSTRACT

INTRODUCTION: Survival outcomes associated with different androgen receptor pathway inhibitors (ARPIs) prescribed for the treatment of metastatic castration (hormone)-sensitive prostate cancer (mCSPC) have not been directly compared. The objective of this study was to compare overall survival (OS) by 24 months among ARPI-naïve patients with mCSPC initiating apalutamide or enzalutamide.

METHODS: A retrospective, causal longitudinal inverse probability of treatment weighted analysis was conducted to compare OS between patients initiating apalutamide or enzalutamide between December 2019 and December 2023 using de-identified linked US clinical and insurance claims data. Patients were excluded if they had prior exposure to ARPIs, had evidence of castration resistance, had < 12 months of database activity prior to ARPI initiation, were diagnosed with other primary cancers, or were treated with other advanced prostate cancer (PC)-related treatment (except docetaxel). Using an intention-to-treat approach, weighted Cox proportional hazards models were used to compare OS by 24 months between patients treated with apalutamide or enzalutamide (primary analyses; exploratory analyses used all available follow-up).

RESULTS: Overall, 1810 and 1909 ARPI-naïve patients who initiated apalutamide or enzalutamide, respectively, were included. Measured baseline characteristics between cohorts were well balanced after weighting (for both: mean age 73.0 years, ~ 60% white, ~ 23% black or African American, ~ 78% Medicare-insured, mean Quan-CCI 8.6, ~ 20% with visceral metastasis, 56.2% with de novo PC). At 24 months post index, there was a statistically significant 23% reduction in the risk of mortality among patients who initiated apalutamide compared with enzalutamide (hazard ratio [HR] 0.77; 95% confidence interval [CI] 0.62, 0.96; p = 0.019). Results remained consistent when using all available follow-up metrics (HR 0.77; 95% CI 0.64, 0.93; nominal p = 0.008).

CONCLUSION: In this head-to-head causal analysis among ARPI-naïve patients with mCSPC, treatment with apalutamide resulted in better survival outcomes at 24 months compared with enzalutamide. Longer follow-up studies are required to fully determine the therapeutic comparator impact of these agents.

PMID:40439959 | DOI:10.1007/s12325-025-03207-6