Tag: nevin manimala

BMC Health Serv Res. 2026 Feb 21. doi: 10.1186/s12913-026-14195-w. Online ahead of print.

ABSTRACT

BACKGROUND: Health system responsiveness encompasses the non-clinical aspects of healthcare, such as dignity, confidentiality, and communication that meet patients’ expectations. It is a core component of the World Health Organization’s framework for people-cantered care. Although responsiveness has been widely studied in general healthcare settings, evidence from mental health services remains limited, particularly in low- and middle-income countries such as Ethiopia.

OBJECTIVE: To assess health system responsiveness and its associated factors among patients with mental illness receiving outpatient care in public hospitals in Addis Ababa, Ethiopia, 2025.

METHODS: A facility-based cross-sectional study was conducted from March 1 to April 30, 2025, among 509 patients attending outpatient mental health services in selected public hospitals. Participants were selected using a multistage approach, with hospitals randomly chosen and participants within each hospital selected by systematic random sampling. Data were collected using a pretested questionnaire based on the WHO’s seven-domain responsiveness framework. Bivariate and multivariable logistic regression analyses were performed, and adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. Statistical significance was set at p < 0.05.

RESULT: Among the 509 participants, 276 (54.22%) reported good health system responsiveness. The dignity domain had the highest mean score, whereas the choice domain had the lowest. Higher odds of good responsiveness were observed among patients with health insurance (AOR = 1.89; 95% CI: 1.27-2.82), those who experienced shorter waiting times (< 30 mins: AOR = 3.36, 95% CI: 1.81-6.24; 30-60 mins: AOR = 2.00, 95% CI: 1.03-3.92), those who reported consistent availability of prescribed medications (AOR = 1.77; 95% CI: 1.12-2.83), and those attended by providers who introduced themselves (AOR = 1.71; 95% CI: 1.13-2.59). Conversely, rare (AOR = 0.40; 95% CI: 0.24-0.68) and absent (AOR = 0.18; 95% CI: 0.04-0.87) availability of medications were associated with significantly lower responsiveness.

CONCLUSION AND RECOMMENDATION: Responsiveness of outpatient mental health services was suboptimal. Health insurance coverage, shorter waiting times, consistent availability of prescribed medications, and provider self-introduction during consultations were statistically significant factors associated with good responsiveness. To improve responsiveness, efforts should focus on expanding health insurance coverage, minimizing patient waiting times, ensuring reliable medication availability, and encouraging respectful provider introductions.

PMID:41723465 | DOI:10.1186/s12913-026-14195-w

BMC Med. 2026 Feb 21. doi: 10.1186/s12916-026-04709-y. Online ahead of print.

ABSTRACT

BACKGROUND: While medications are essential for preventing and treating disease, they can also cause harm. Evidence synthesis has been widely adopted for evaluating harms, but traditional methods are resource-intensive and may constrain timely decision-making. This study aims to validate a Trial Bank approach towards rapid evidence synthesis.

METHODS: A Trial Bank consisting of 13,650 RCTs of pharmaceutical or biopharmaceutical agents for children was established using artificial intelligence (AI) and humans, based on five databases (e.g., PubMed) up to February 14, 2023. The Trial Bank approach for evidence synthesis was validated in two ways: First, the percentage of trials within 1,996 Cochrane meta-analyses of drug safety in children that were also available in the Trial Bank was reported as the Trial Bank coverage (TBC). Second, the agreement of pooled effects from trials limited to those in the Trial Bank was compared to the full Cochrane meta-analyses in terms of their direction and statistical significance.

RESULTS: Of 1,020 trials included in the Cochrane meta-analyses, there was an overall 80.2% TBC, with an average TBC of 85.7% per meta-analysis (n = 1,996). With regards to agreement of meta-analytical results, use of only the Trial Bank trials achieved an agreement of 93.0% (95% confidence interval [CI]: 90.8% to 94.8%) in the direction, 95.8% (95%CI: 94.0% to 97.2%) in significance, and 89.1% (95%CI: 94.0% to 97.2%) in both direction and significance to Cochrane meta-analytical results for meta-analyses that had 2 or more trials (n = 668). Sensitivity analysis by removing unpublished trials from Cochrane meta-analyses showed slightly higher agreement (e.g., 90.7% in both direction and significance).

CONCLUSIONS: The Trial Bank approach demonstrated considerable coverage and agreement with Cochrane meta-analyses, suggesting it is a potentially feasible and efficient strategy for supporting living evidence synthesis of medication safety in children.

PMID:41723462 | DOI:10.1186/s12916-026-04709-y

BMC Oral Health. 2026 Feb 21. doi: 10.1186/s12903-026-07937-z. Online ahead of print.

ABSTRACT

OBJECTIVE: The World Health Organization (WHO) recommends that cemento-osseous dysplasia (COD) be diagnosed based on imaging findings, avoiding biopsy when possible. This study aimed to evaluate the concordance between imaging and clinical diagnoses in 55 COD patients, and to identify key clinical and radiographic features that may help prevent unnecessary biopsy or inappropriate treatment.

METHODS: Between September 1, 2017, and August 31, 2018, 55 patients diagnosed with COD were randomly selected from the imaging database of West China Hospital of Stomatology. Two radiologists reviewed all cases to assess correlations between COD variants and clinical symptoms, identify common misdiagnoses, and examine subsequent treatment decisions.

RESULTS: The cohort showed a strong female predominance (female: male = 48:7). The concordance rate between imaging and clinical diagnoses was only 1.8% (1/55); the remaining 98.2% were either misdiagnosed or overlooked clinically. Most lesions were incidentally discovered on radiographs (65%), while others were associated with tooth pain (18%), facial swelling (9%), tooth mobility (5%), or abscess (2%). A statistically significant difference was found between symptomatic and asymptomatic groups across COD variants (Fisher’s Exact Test, P < 0.05; Cramer’s V = 0.45, 95% CI: 0.28-0.67). Among 27 clinically overlooked cases, only one was correctly diagnosed. Misdiagnoses included tooth-related diseases (n = 10), tumors or cysts (n = 6), osteomyelitis (n = 3), bone islands (n = 1), and mixed diagnoses (n = 7). No significant differences were observed in COD variants, treatment duration, or the number of clinical visits and departments among the misdiagnosed cases. The only correctly diagnosed patient received surgical curettage. Twenty-two patients received no treatment. Others underwent root canal therapy, extraction, curettage, or combinations thereof. Some patients also received dental implants or orthodontic treatment.

CONCLUSION: Cemento-osseous dysplasia (COD), a type of non-neoplastic fibro-osseous lesion of the jaw, is frequently misdiagnosed in clinical practice. These diagnostic errors often lead to unnecessary interventions and complications. Enhanced clinician training in radiographic interpretation-particularly the use of cone-beam computed tomography (CBCT)-is essential for enhancing diagnostic accuracy and guiding appropriate management.

PMID:41723446 | DOI:10.1186/s12903-026-07937-z

BMC Public Health. 2026 Feb 21. doi: 10.1186/s12889-026-26656-2. Online ahead of print.

NO ABSTRACT

PMID:41723441 | DOI:10.1186/s12889-026-26656-2

BMC Psychiatry. 2026 Feb 21. doi: 10.1186/s12888-026-07895-4. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is linked to extensive gray matter volume (GMV) reductions and frequently co-occurs with metabolic dysfunction. However, the shared genetic basis linking neurostructural abnormalities and metabolic traits remains poorly understood.

METHODS: Using a coordinate-based meta-analytic framework, we synthesized findings from 57 voxel-based morphometry (VBM) studies to characterize GMV alterations in MDD. Spatial transcriptomic correlation analysis was performed using the Allen Human Brain Atlas to identify genes associated with these alterations. In parallel, conjunctional false discovery rate (conjFDR) analysis was applied to genome-wide association study (GWAS) summary statistics from MDD and five metabolic traits-glucose, hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG)-to identify pleiotropic loci. Functional characterization of the intersecting genes was conducted by applying gene ontology enrichment and protein-protein interaction (PPI) analyses.

RESULTS: We identified consistent GMV reductions in the left superior temporal gyrus, inferior frontal gyrus, and insula. A total of 2,585 genes were spatially correlated with GMV alterations. ConjFDR analysis revealed 20-195 pleiotropic loci across metabolic traits and MDD. Gene-level overlap analysis identified 13-73 shared genes per trait, with FADS2 emerging as a common gene across all five traits. Functional annotation highlighted pathways related to lipid metabolism and synaptic signaling.

CONCLUSION: This integrative multi-omics study reveals shared genetic mechanisms linking brain structure in MDD with systemic metabolic traits. FADS2 may serve as a molecular hub underlying this convergence, suggesting that targeting FADS2-mediated lipid metabolism could represent a novel therapeutic strategy for mitigating both neurostructural deficits and metabolic dysregulation in MDD.

CLINICAL TRIAL REGISTRATION: Clinical trial number: Not applicable.

PMID:41723432 | DOI:10.1186/s12888-026-07895-4

BMC Med Res Methodol. 2026 Feb 21. doi: 10.1186/s12874-026-02793-5. Online ahead of print.

NO ABSTRACT

PMID:41723363 | DOI:10.1186/s12874-026-02793-5

BMC Geriatr. 2026 Feb 21. doi: 10.1186/s12877-026-07181-8. Online ahead of print.

NO ABSTRACT

PMID:41723350 | DOI:10.1186/s12877-026-07181-8

Ther Innov Regul Sci. 2026 Feb 21. doi: 10.1007/s43441-025-00894-9. Online ahead of print.

ABSTRACT

Medicinal products have benefits and risks that must be carefully balanced to inform decision making. The structured benefit-risk (BR) framework is a powerful approach not only to standardize a holistic BR assessment, but also to incorporate the patient perspective and guide the decisions and discussions of sponsors and regulatory agencies throughout the continuum of drug development. Structured BR assessment has been usually conducted using a qualitative approach during the late development stage. The use of quantitative models that can be applied throughout the drug development process may provide more objective BR information to support scientific recommendations to optimize and inform decisions for critical external and internal development opportunities. A new Multidimensional Benefit-Risk Integrated Evaluation (MBRIE) quantitative model was developed using key attributes of the structured BR assessment. Each attribute was evaluated by assigning a rating score ranging from 1 to 3 (low), 4-6 (medium), 7-10 (high). Also, two dimensions for comparative purposes were considered: standard of care (SOC) and probability of development success (PODS) (likelihood or favorability for development success). Graphical outputs were used to visualize and compare the ranking scores for each of the attributes across the two dimensions. This analysis implements a structured quantitative BR assessment approach earlier in drug development and through the drug lifecycle. The MBRIE model may be an innovative tool to facilitate solutions by fostering a collaborative culture that points to the true objective to improve patient outcomes.

PMID:41723330 | DOI:10.1007/s43441-025-00894-9

J Assist Reprod Genet. 2026 Feb 21. doi: 10.1007/s10815-026-03833-1. Online ahead of print.

ABSTRACT

PURPOSE: This study addressed the practical challenge of missing data in assisted reproductive technology by evaluating the reliability of predicting oocyte yield when anti-Müllerian hormone (AMH) values are unavailable. We examined the ability of AI-based models to recover missing biomarker data and maintain predictive accuracy despite data limitations.

METHOD: We conducted a retrospective analysis using data from 27,435 IVF cycles across multiple centers from 2018 to 2023. Various machine learning models were compared to serve as internal imputation models to fill data gaps and predict oocyte retrieval. We validated the models across a range of missingness rates (0% to 90%) using bootstrapping to ensure statistical robustness and evaluate generalizability across different clinical environments.

RESULTS: The best-performing model using actual AMH achieved an AUC of 0.838. Despite the relatively low explained variance in AMH recovery (R² ≈ 0.2), the imputed values captured enough clinical information to serve as reliable predictive proxies. The model’s performance remained above an illustrative benchmark of 0.80 AUC until the missing rate reached 35.5%. SHAP analysis confirmed that the AI model effectively used age and other clinical variables to compensate for missing AMH data.

CONCLUSIONS: AI-based imputation offers a practical solution for clinical infertility care, where missing data is caused by documentation issues or repeat-cycle workflows. This approach bridges the gap between ideal laboratory records and realistic data limitations, ensuring that data-driven decision support remains accessible even in the presence of incomplete records.

PMID:41723323 | DOI:10.1007/s10815-026-03833-1

Biol Trace Elem Res. 2026 Feb 21. doi: 10.1007/s12011-026-05030-8. Online ahead of print.

ABSTRACT

This study examined the geographical distribution of cadmium (Cd), copper (Cu), mercury (Hg), and lead (Pb) in the Monterrey Metropolitan Area (MMA), Mexico, using feral pigeons (Columba livia) as bioindicators. Trace metals were quantified in tail feathers collected from 74 individuals in nine municipalities using Anodic Stripping Voltammetry (ASV). Copper showed the highest concentrations (maximum mean 21.3 µg/g), followed by Pb (5.2 µg/g), Hg (0.7 µg/g), and Cd, which was detected in a few samples (< 0.6 µg/g). A consistent center-to-periphery gradient was observed for Cu, Hg, and Pb. Cluster analysis identified four spatially distinct groupings based on bioaccumulation, with the highest concentrations occurring in central municipalities characterized by higher human population density, suggesting heterogeneous exposure and increased combined risk from trace metals in more urbanized areas. Leukocyte frequencies varied across municipalities, suggesting site-specific physiological responses associated with differences in trace metal concentrations. Genotoxicity biomarkers showed spatial trends similar to trace metal levels, although differences were not statistically significant, indicating limited genotoxic effects at the observed exposure levels. The concordant spatial patterns between environmental and biological indicators highlight trace metal exposure as a relevant risk in the MMA and support the use of feral pigeons as effective bioindicators of trace metal pollution, with implications for human health in industrial and highly urbanized areas.

PMID:41723310 | DOI:10.1007/s12011-026-05030-8