Tag: nevin manimala

Inquiry. 2025 Jan-Dec;62:469580251382395. doi: 10.1177/00469580251382395. Epub 2025 Nov 1.

ABSTRACT

Non-suicidal self-injury (NSSI) and suicidal ideation (SI) represent significant mental health challenges among university students. In low- and middle-income contexts like Bangladesh, there is limited understanding of how these behaviors differentially affect students with and without mental illness. This study addresses these gaps by investigating the prevalence and risk factors of NSSI and SI, with stratified analyses by mental illness status, to predict these behaviors. This cross-sectional study recruited 1401 university students between December 2024 and January 2025. Data was collected via a self-administered questionnaire assessing socio-demographics, and psychological factors. Traditional statistical analyses, including chi-square tests and logistic regression, were conducted in SPSS 27. The prevalence of NSSI and SI was 21.4% and 17.2%, respectively. Both NSSI and SI were more common among students with symptoms of depression or anxiety (mental illness) than those without. Multivariable analyses identified smoking, cyberbullying, and probable eating disorder as significant predictors of both NSSI and SI, with these associations persisting after stratification by mental illness status. Subgroup analyses showed that among students without mental illness, female gender, older age, smoking, cyberbullying, and eating disorder symptoms significantly predicted NSSI, while smoking, cyberbullying, eating disorder, and older age predicted SI. In students with mental illness, smoking and cyberbullying remained robust predictors of both NSSI and SI, while eating disorder was significantly associated with NSSI but not SI. The regression models explained 12.9% of the variance in NSSI and 16.6% in SI. The findings highlight the necessity to adopt interventions that address modifiable risk factors, with a strong emphasis on behavioral and mental health variables, to effectively reduce self-harming and suicidal behaviors in young adults.

PMID:41174978 | DOI:10.1177/00469580251382395

Int J Gynaecol Obstet. 2025 Nov 1. doi: 10.1002/ijgo.70634. Online ahead of print.

NO ABSTRACT

PMID:41174961 | DOI:10.1002/ijgo.70634

Pediatr Allergy Immunol. 2025 Nov;36(11):e70234. doi: 10.1111/pai.70234.

ABSTRACT

BACKGROUND: Patients with chronic granulomatous disease (CGD) can develop hemophagocytic lymphohistiocytosis (HLH), exacerbating mortality risk. Despite its clinical significance, data on HLH in CGD from international cohorts remain limited. This study aims to describe the occurrence of HLH in a cohort of patients with CGD, providing clinical insight into this association and emphasizing the need for early recognition and effective management.

METHODS: The records of 60 patients with CGD were reviewed. Those meeting the diagnostic criteria for HLH based on the HScore were included in the analysis. Both descriptive and inferential statistics were employed to evaluate the data.

RESULTS: Eleven patients (18.3%) fulfilled the HLH diagnostic criteria. The median interval between CGD genetic diagnosis and HLH onset was 36 months, with a median age at HLH diagnosis of 67 months. Infectious triggers were identified in eight cases, with Salmonella and Aspergillus species being the most common. One case involved an inflammatory trigger-multisystem inflammatory syndrome in children (MIS-C) following SARS-CoV-2 infection. Mortality was high: 72.7% of the patients with HLH died. No significant difference (p = .338) was observed between those who died after receiving only immunosuppressive therapy (n = 2) and those who received both intravenous immunoglobulin and immunosuppressive therapy (n = 6).

CONCLUSION: HLH in CGD is associated with a high mortality rate. Notably, MIS-C can present as an inflammatory trigger for HLH in this population. Careful evaluation of HLH parameters is recommended for all patients with CGD admitted with infection or inflammation to facilitate early diagnosis and guide management.

PMID:41174960 | DOI:10.1111/pai.70234

Int J Biostat. 2025 Nov 3. doi: 10.1515/ijb-2025-0011. Online ahead of print.

ABSTRACT

Competing risks models are survival models with several events of interest acting in competition and whose occurrence is only observed for the event that occurs first in time. This paper presents a Bayesian approach to these models in which the issue of model selection is treated in a special way by proposing generalizations of some of the Bayesian procedures used in univariate survival analysis. This research is motivated by a study on the survival of patients with heart failure undergoing cardiac resynchronization therapy, a procedure which involves the implant of a device to stabilize the heartbeat. Two different causes of death have been considered: cardiovascular and non-cardiovascular, and a set of baseline covariates are examined in order to better understand their relationship with both causes of death. Model selection, model checking, and model comparison procedures have been implemented and assessed. The posterior distribution of some relevant outputs such as the overall survival function, cumulative incidence functions, and transition probabilities have been computed and discussed.

PMID:41174955 | DOI:10.1515/ijb-2025-0011

Int J Biostat. 2025 Nov 3. doi: 10.1515/ijb-2025-0016. Online ahead of print.

ABSTRACT

The binary classification problem (BCP) aims to correctly allocate subjects in one of two possible groups. The groups are frequently defined as having or not one characteristic of interest. With this goal, we are allowed to use different types of information. There is a huge number of methods dealing with this problem; including standard binary regression models, or complex machine learning techniques such as support vector machine, boosting, or perceptron, among others. When this information is summarized in a continuous score, we have to define classification regions (or subsets) which will determine whether the subjects are classified as positive, with the characteristic under study, or as negative, otherwise. The standard (or regular) receiver-operating characteristic (ROC) curve assumes that higher values of the marker are associated with higher probabilities of being positive and considers as positive those patients with values within the intervals [c, ∞) $\left(c\in R\right)$ , and plots the true- against the false- positive rates (sensitivity against one minus specificity) for all potential c. The so-called generalized ROC curve, gROC, allows that both higher and lower values of the score are associated with higher probabilities of being positive. The efficient ROC curve, eROC, considers the best ROC curve based on a transformation of the score. In this manuscript, we are interested in studying, comparing and approximating the transformations leading to the eROC and to the gROC curves. We will prove that, when the optimal transformation does not have relative maximum, both curves are equivalent. Besides, we investigate the use of the gROC curve on some theoretical models, explore the relationship between the gROC and the eROC curves, and propose two non-parametric procedures for approximating the transformation leading to the gROC curve. The finite-sample behavior of the proposed estimators is explored through Monte Carlo simulations. Two real-data sets illustrate the practical use of the proposed methods.

PMID:41174954 | DOI:10.1515/ijb-2025-0016

Psychiatr Serv. 2025 Nov 1;76(11):944-950. doi: 10.1176/appi.ps.20250086. Epub 2025 Aug 26.

ABSTRACT

OBJECTIVE: This study aimed to evaluate whether three popular chatbots powered by large language models (LLMs)-ChatGPT, Claude, and Gemini-provided direct responses to suicide-related queries and how these responses aligned with clinician-determined risk levels for each question.

METHODS: Thirteen clinical experts categorized 30 hypothetical suicide-related queries into five levels of self-harm risk: very high, high, medium, low, and very low. Each LLM-based chatbot responded to each query 100 times (N=9,000 total responses). Responses were coded as “direct” (answering the query) or “indirect” (e.g., declining to answer or referring to a hotline). Mixed-effects logistic regression was used to assess the relationship between question risk level and the likelihood of a direct response.

RESULTS: ChatGPT and Claude provided direct responses to very-low-risk queries 100% of the time, and all three chatbots did not provide direct responses to any very-high-risk query. LLM-based chatbots did not meaningfully distinguish intermediate risk levels. Compared with very-low-risk queries, the odds of a direct response were not statistically different for low-risk, medium-risk, or high-risk queries. Across models, Claude was more likely (adjusted odds ratio [AOR]=2.01, 95% CI=1.71-2.37, p<0.001) and Gemini less likely (AOR=0.09, 95% CI=0.08-0.11, p<0.001) than ChatGPT to provide direct responses.

CONCLUSIONS: LLM-based chatbots’ responses to queries aligned with experts’ judgment about whether to respond to queries at the extremes of suicide risk (very low and very high), but the chatbots showed inconsistency in addressing intermediate-risk queries, underscoring the need to further refine LLMs.

PMID:41174947 | DOI:10.1176/appi.ps.20250086

Psychiatr Serv. 2025 Nov 1;76(11):988-996. doi: 10.1176/appi.ps.20250042.

ABSTRACT

OBJECTIVE: People with serious mental illness (i.e., disabling psychotic, mood, and other disorders) develop chronic medical diseases early in life. This study aimed to examine the effects of integrating primary care into community mental health centers (CMHCs; reverse integrated care) on service use among young adults with serious mental illness who may benefit from early intervention.

METHODS: This retrospective cohort analysis used Medicaid claims of 945 people with serious mental illness (ages 18-40) in CMHC care from 2020 to 2022-315 in reverse integrated care and 630 propensity score matched participants in comparison care (i.e., not reverse integrated care). Logistic regression, adjusted for participant characteristics, enrollment quarter, and past service use, assessed outcomes in the 6 months after enrollment.

RESULTS: Participants’ mean±SD age was 32.56 ± 7.84 years; 29% had a diagnosis of schizophrenia, 40% had a co-occurring substance use disorder, 33% had a medical emergency department (ED) visit in the 6 months before enrollment, and all were enrolled in CMHC care at baseline. During follow-up, participants in reverse integrated care were more likely to have an outpatient medical visit (65% vs. 58%; adjusted odds ratio [AOR]=1.54, p=0.005) and were less likely to have a medical ED visit (26% vs. 33%; AOR=0.70, p=0.035) than those in comparison care.

CONCLUSIONS: Integrating primary care into CMHC services may increase access to outpatient medical care and reduce ED visits for medical reasons among young adults with serious mental illness. Future research should confirm these findings, assess longer-term outcomes, and examine implementation facilitators and barriers.

PMID:41174946 | DOI:10.1176/appi.ps.20250042

Psychiatr Serv. 2025 Nov 1;76(11):1027-1030. doi: 10.1176/appi.ps.20240487.

ABSTRACT

OBJECTIVE: Youths within the child welfare system have high rates of mental health needs and chronic barriers to service access. The cascade-of-care approach was used to explore this population’s use of mental health services.

METHODS: The mental health cascade was used with electronic medical record data to characterize service access among 97 youths served in a child welfare clinic.

RESULTS: Of the total sample, 82% of youths met criteria to identify those needing mental health services, 56% were referred for assessment and services, 33% completed an assessment, 24% had a treatment plan signed, and 17% received services. Time between steps averaged 64.52 days from screening to referral, 65.94 days from referral to assessment, 7.05 days from assessment to signed treatment plan, and 19.84 days from treatment plan to service initiation.

CONCLUSIONS: Significant gaps in the care cascade occurred, especially at earlier stages. Multilayered efforts to reduce service gaps in this population are needed.

PMID:41174942 | DOI:10.1176/appi.ps.20240487

Int J Gynaecol Obstet. 2025 Nov 1. doi: 10.1002/ijgo.70633. Online ahead of print.

ABSTRACT

OBJECTIVE: Our study aimed to evaluate the combined risk of macrosomia and nulliparity. We investigated whether macrosomia is independently associated with an increased rate of intrapartum cesarean delivery (CD) and adverse maternal and neonatal outcomes among nulliparous women delivering at term.

METHODS: We conducted a retrospective cohort study including nulliparous women with singleton, term (37-42 weeks) deliveries between 2005 and 2024 at two university-affiliated medical centers in Jerusalem, Israel. Women who delivered macrosomic neonates (birth weight ≥4000 g) were compared with those delivering neonates weighing 3000-3500 g. Exclusions included multifetal gestations, preterm deliveries, elective cesareans, fetal anomalies, and antepartum demise. The primary outcome was intrapartum cesarean delivery. Secondary outcomes included a range of maternal and neonatal complications. Multivariable logistic regression was used to adjust for potential confounders including maternal obesity, pre-gestational diabetes, labor induction, and gestational age at delivery.

RESULTS: Among 86 801 eligible nulliparous women, 2762 (3.2%) delivered macrosomic neonates and 40 963 (47.2%) served as the control group. The rate of intrapartum CD was significantly higher among macrosomic deliveries compared to controls (18.6% vs. 7.8%, P < 0.01), though this association was not statistically significant after adjustment (adjusted odds ratio [aOR] 1.81, 95% confidence interval [CI]: 0.91-3.58). Macrosomia was independently associated with increased odds of shoulder dystocia (aOR 33.42, 95% CI: 11.32-98.68), postpartum hemorrhage (aOR 2.13, 95% CI: 1.79-2.54), blood transfusion (aOR 2.45, 95% CI: 1.51-3.98), chorioamnionitis (aOR 2.03, 95% CI: 1.57-2.61), neonatal intensive care unit admission (aOR 1.62, 95% CI: 1.15-2.29), neonatal hypoglycemia (aOR 2.23, 95% CI: 1.32-3.77), and Erb’s palsy or clavicular fracture (aOR 9.43, 95% CI: 4.01-22.21). Stratification by birth weight categories revealed a dose-response relationship, with the highest complication rates among neonates >4500 g.

CONCLUSION: In nulliparous women delivering at term, macrosomia is independently associated with a higher risk of multiple adverse maternal and neonatal outcomes. These findings underscore the compounded risk faced by nulliparous women with macrosomic fetuses and highlight the need for enhanced prenatal surveillance and individualized delivery planning in this population.

PMID:41174933 | DOI:10.1002/ijgo.70633

J Diabetes Sci Technol. 2025 Nov;19(6):1457-1463. doi: 10.1177/19322968251371046. Epub 2025 Oct 14.

ABSTRACT

BACKGROUND: Type 1 diabetes is treated with exogenous insulin using multiple daily injections or insulin pumps. However, both strategies require carbohydrate counting for prandial insulin dosing, which is both burdensome and error prone.

METHODS: We conducted a pilot, randomized, controlled study to eliminate carbohydrate counting in adults (n = 12, 7 females, age 39.5 [15.1], HbA1c 7.4% [0.6]) using an automated insulin and pramlintide fully closed-loop system. The interventions included five arms during which participants underwent 14 hours of outpatient, free-living, supervised experiments of (1) faster aspart with carbohydrate counting (control), faster aspart and pramlintide without carbohydrate counting at (2) 8 µg/U and (3) 10 µg/U ratios, and aspart and pramlintide without carbohydrate counting at (4) 8 µg/U and (5) 10 µg/U ratios.

RESULTS: The median time in target range (3.9-10.0 mmol/L) with the control arm was 78.6 [65.3-92.9], compared with 76.2 [64.6-86.9] and 78.8 [68.8-86.0] with the fully closed-loop faster aspart and pramlintide systems at 8 and 10 µg/U ratios, respectively, and compared with 65.9 [59.9-83.6] and 77.4 [72.1-82.7] with the fully closed-loop aspart and pramlintide systems at 8 and 10 µg/U ratios, respectively. Times spent below 3.9 and 3.0 mmol/L were numerically higher with the fully closed-loop aspart and pramlintide systems than the control arm. None of the differences were statistically significant.

CONCLUSIONS: This study suggests that automated insulin and pramlintide systems have the potential to alleviate carbohydrate counting without degrading time in range. A longer and larger study is underway.

PMID:41174925 | DOI:10.1177/19322968251371046