Tag: nevin manimala

JAMA Netw Open. 2025 Mar 3;8(3):e251271. doi: 10.1001/jamanetworkopen.2025.1271.

ABSTRACT

IMPORTANCE: Evidence from diverse global populations suggests that household food insecurity (HFI) is associated with adult disability, but the association between household water insecurity (HWI) and disability remains understudied. Examinations of the joint association of dual HFI and HWI with disability are lacking.

OBJECTIVE: To explore independent and joint associations of HFI and HWI with functional disability in Ecuadorian adults.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the 2018 Ecuadorian National Health and Nutrition Survey, a nationally representative, population-based survey conducted in Ecuador. The study included adults (aged 18-99 years) with information on sociodemographic characteristics, household food and water security, and functional disability status. Data were collected in 2 waves of the survey, from November 2018 to January 2019 and June to July 2019. Statistical analysis was performed from May to December 2024.

EXPOSURES: HFI, WFI, or both.

MAIN OUTCOMES AND MEASURES: The primary outcome was self-reported functional disability, assessed using the Washington Group Short Set on Functioning, a tool that uses a set of 6 questions to measure activity limitations.

RESULTS: Among 42 071 participants (mean [SE] age, 48.0 [0.1] years; 31 683 male [75.3%]; 1840 African descendant [4.4%], 5184 Indigenous [12.3%], and 35 047 Mestizo ethnic majority group [83.3%]), most lived in urban areas (26 164 participants [62.2%]). Exposure to HFI only was associated with an increased risk for any functional disability (adjusted relative risk [aRR], 1.44; 95% CI, 1.37-1.52), as well as sensory (aRR, 1.43; 95% CI, 1.35-1.52), physical (aRR, 1.56, 95% CI, 1.42-1.72), and cognitive (aRR, 1.78; 95% CI, 1.61-1.98) disabilities. HWI exposure only was associated with increased risk for any functional disability (aRR, 1.12; 95% CI, 1.06-1.20), as well as sensory (aRR, 1.17; 95% CI, 1.09-1.25), physical (aRR, 1.15; 95% CI, 1.05-1.26), and cognitive (aRR, 1.17; 95% CI, 1.03-1.34) disabilities. Exposure to dual HFI and HWI was associated with a greater increase in risk than HFI or HWI alone of any functional disability (aRR, 1.61; 95% CI, 1.50-1.72), as well as sensory (aRR, 1.65; 95% CI, 1.52-1.79), physical (aRR, 1.72; 95% CI, 1.59-1.87), and cognitive (aRR, 2.01; 95% CI, 1.76-2.29) disabilities.

CONCLUSION AND RELEVANCE: In this study, dual exposure to HFI and HWI was associated with a greater increase in risk of any and specific functional disabilities compared with independent contributions of HFI and HWI alone. These findings highlight the importance of addressing HFI and HWI jointly rather than independently when conducting research on disability and other health outcomes and in designing policies and programs to protect at-risk adults and their households.

PMID:40111365 | DOI:10.1001/jamanetworkopen.2025.1271

JAMA Netw Open. 2025 Mar 3;8(3):e251281. doi: 10.1001/jamanetworkopen.2025.1281.

ABSTRACT

IMPORTANCE: Emergency medical services (EMS) clinicians commonly care for patients with behavioral health emergencies (BHEs), including acute agitation. There are known racial and ethnic disparities in the use of physical restraint and chemical sedation for BHEs in emergency department settings, but less is known about disparities in prehospital use of restraint or sedation.

OBJECTIVE: To investigate the association of patient race and ethnicity with the use of prehospital physical restraint and chemical sedation during EMS encounters for BHEs.

DESIGN, SETTING, AND PARTICIPANTS: This nationwide retrospective cohort study used data from EMS agencies across the US that participated in the 2021 ESO Data Collaborative research dataset. Emergency medical services encounters among patients aged 16 to 90 years with a primary or secondary impression, sign or symptom, or protocol use associated with a BHE from January 1 to December 31, 2021, were included. Statistical analysis was conducted from July 2023 to March 2024.

EXPOSURES: Patient race and ethnicity, which was categorized as Hispanic, non-Hispanic Black, non-Hispanic White, non-Hispanic other (American Indian or Alaska Native, Asian, Hawaiian Native or Other Pacific Islander, other, or multiracial), and unknown.

MAIN OUTCOMES AND MEASURES: The primary outcome was administration of any physical restraint and/or chemical sedation (defined as any antipsychotic medication, benzodiazepine, or ketamine).

RESULTS: A total of 661 307 encounters (median age, 41 years [IQR, 30-56 years]; 56.9% male) were included. Race and ethnicity were documented as 9.9% Hispanic, 20.2% non-Hispanic Black, 59.5% non-Hispanic White, 1.9% non-Hispanic other, and 8.6% unknown race and ethnicity. Restraint and/or sedation was used in 46 042 (7.0%) of encounters, and use differed across racial and ethnic groups (Hispanic, 10.6%; non-Hispanic Black, 7.9%; non-Hispanic White, 6.1%; non-Hispanic other, 10.9%; unknown race and ethnicity, 5.9%; P < .001). In mixed-effects logistic regression models accounting for clustering by EMS agency and adjusted for age, gender, urbanicity, and community diversity, patients who were non-Hispanic Black had significantly greater odds of being restrained or sedated across all categories compared with non-Hispanic White patients (eg, any restraint and/or sedation: adjusted odds ratio [AOR], 1.17 [95% CI, 1.14-1.21]; physical restraint: AOR, 1.22 [95% CI, 1.18-1.26]). There was no significant difference in adjusted odds of any restraint and/or sedation use for the remaining racial and ethnic groups compared to non-Hispanic White patients. Clustering was associated with agency-level variation in restraint or sedation use (intraclass correlation coefficient, 0.16 [95% CI, 0.14-0.17]).

CONCLUSIONS AND RELEVANCE: This nationwide retrospective cohort study of EMS encounters for patients with BHEs found differences in the use of prehospital restraint and/or sedation by patient race and ethnicity and an agency-level association with variation in restraint and/or sedation use. These data may inform improvements to protocols and training aimed at equitable care for BHEs.

PMID:40111364 | DOI:10.1001/jamanetworkopen.2025.1281

JAMA Netw Open. 2025 Mar 3;8(3):e251292. doi: 10.1001/jamanetworkopen.2025.1292.

ABSTRACT

IMPORTANCE: International guidelines use cancer antigen (CA) 125 thresholds to recommend which patients with pelvic masses should undergo evaluation by gynecologic oncologists for ovarian cancer. However, CA-125 thresholds were developed from White populations. If CA-125 levels differ among patient populations, current guidelines may contribute to delayed ovarian cancer diagnoses among women of other races and ethnicities than White.

OBJECTIVE: To examine CA-125 levels at ovarian cancer diagnosis by patient race and ethnicity and associations of elevated CA-125 levels with timely treatment.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included all patients with ovarian cancer diagnosed between January 1, 2004, and December 31, 2020, using the US National Cancer Database. The data analysis was performed between November 1, 2023, and July 10, 2024.

EXPOSURE: Patient race and ethnicity as identified in the National Cancer Database.

MAIN OUTCOME AND MEASURES: Cancer antigen 125 level was defined as elevated or borderline and negative or normal. Multivariable logistic regression models were used to examine the association of patient race and ethnicity with CA-125 level overall and for epithelial and high-grade serous cancers. Generalized linear models were used to examine the association of CA-125 level with days from diagnosis to chemotherapy start for patients with stage II to IV ovarian cancer.

RESULTS: Of the 250 749 patients with ovarian cancer diagnosed between 2004 and 2020 (median [IQR] age, 62.0 [52.0-73.0] years; 0.4% American Indian, 3.7% Asian, 8.6% Black, 85.2% White, and 2.0% other or unknown race and 6.7% Hispanic, 88.8% non-Hispanic, and 4.6% of unknown ethnicity), 212 477 had measured CA-125 levels, and 88.2% had an elevated CA-125 level at diagnosis. Patients with American Indian, Asian, or Black race were less likely to have an elevated CA-125 level at ovarian cancer diagnosis than White patients. In multivariable analyses adjusted for stage, comorbidities, and menopausal status, Black patients had lower odds of elevated CA-125 levels (adjusted odds ratio [AOR], 0.77; 95% CI, 0.74-0.81) compared with White patients, as did American Indian patients (AOR, 0.77; 95% CI, 0.62-0.94). Among patients with high-grade serous ovarian cancer only, Black patients had a lower odds of having an elevated CA-125 level at diagnosis (AOR, 0.81; 95% CI, 0.73-0.91). Patients with stage II to IV ovarian cancer with false-negative CA-125 findings at diagnosis had 9.38 days longer (95% CI, 8.43-10.34 days) to chemotherapy start compared with patients with an elevated CA-125 level.

CONCLUSIONS AND RELEVANCE: In this cohort study of patients with ovarian cancer, American Indian and Black patients were 23% less likely to have an elevated CA-125 level at diagnosis. Current CA-125 thresholds may miss racially and ethnically diverse patients with ovarian cancer. Work is needed to develop inclusive CA-125 thresholds and diagnostic guidelines and not compound disparities in ovarian cancer diagnosis and treatment.

PMID:40111363 | DOI:10.1001/jamanetworkopen.2025.1292

Med Phys. 2025 Mar 20. doi: 10.1002/mp.17763. Online ahead of print.

ABSTRACT

BACKGROUND: Accurate segmentation of diffuse large B-cell lymphoma (DLBCL) lesions is challenging due to their complex patterns in medical imaging. Traditional methods often struggle to delineate these lesions accurately.

OBJECTIVE: This study aims to develop a precise segmentation method for DLBCL using 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) and computed tomography (CT) images.

METHODS: We propose a 3D segmentation method based on an encoder-decoder architecture. The encoder incorporates a dual-branch design based on the shifted window transformer to extract features from both PET and CT modalities. To enhance feature integration, we introduce a multi-scale information fusion (MSIF) module that performs multi-scale feature fusion using cross-attention mechanisms with a shifted window framework. A gated neural network within the MSIF module dynamically adjusts feature weights to balance the contributions from each modality. The model is optimized using the dice similarity coefficient (DSC) loss function, minimizing discrepancies between the model prediction and ground truth. Additionally, we computed the total metabolic tumor volume (TMTV) and performed statistical analyses on the results.

RESULTS: The model was trained and validated on a private dataset of 165 DLBCL patients and a publicly available dataset (autoPET) containing 145 PET/CT scans of lymphoma patients. Both datasets were analyzed using five-fold cross-validation. On the private dataset, our model achieved a DSC of 0.7512, sensitivity of 0.7548, precision of 0.7611, an average surface distance (ASD) of 3.61 mm, and a Hausdorff distance at the 95th percentile (HD95) of 15.25 mm. On the autoPET dataset, the model achieved a DSC of 0.7441, sensitivity of 0.7573, precision of 0.7427, ASD of 5.83 mm, and HD95 of 21.27 mm, outperforming state-of-the-art methods (p < 0.05, t-test). For TMTV quantification, Pearson correlation coefficients of 0.91 (private dataset) and 0.86 (autoPET) were observed, with R² values of 0.89 and 0.75, respectively. Extensive ablation studies demonstrated the MSIF module’s contribution to enhanced segmentation accuracy.

CONCLUSION: This study presents an effective automatic segmentation method for DLBCL that leverages the complementary strengths of PET and CT imaging. The method demonstrates robust performance on both private and publicly available datasets, ensuring its reliability and generalizability. Our method provides clinicians with more precise tumor delineation, which can improve the accuracy of diagnostic interpretations and assist in treatment planning for DLBCL patients. The code for the proposed method is available at https://github.com/chenzhao2023/lymphoma_seg.

PMID:40111352 | DOI:10.1002/mp.17763

Med Phys. 2025 Mar 20. doi: 10.1002/mp.17752. Online ahead of print.

ABSTRACT

BACKGROUND: Deep learning (DL)-based systems have not yet been broadly implemented in clinical practice, in part due to unknown robustness across multiple imaging protocols.

PURPOSE: To this end, we aim to evaluate the performance of several previously developed DL-based models, which were trained to distinguish idiopathic pulmonary fibrosis (IPF) from non-IPF among interstitial lung disease (ILD) patients, under standardized reference CT imaging protocols. In this study, we utilized CT scans from non-IPF ILD subjects, acquired using various imaging protocols, to assess the model performance.

METHODS: Three DL-based models, including one 2D and two 3D models, have been previously developed to classify ILD patients into IPF or non-IPF based on chest CT scans. These models were trained on CT image data from 389 IPF and 700 non-IPF ILD patients, retrospectively, obtained from five multicenter studies. For some patients, multiple CT scans were acquired (e.g., one at inhalation and one at exhalation) and/or reconstructed (e.g., thin slice and/or thick slice). Thus, for each patient, one CT image dataset was selected to be used in the construction of the classification model, so the parameters of that data set serve as the reference conditions. In one non-IPF ILD study, due to its specific study protocol, many patients had multiple CT image data sets that were acquired under both prone and supine positions and/or reconstructed under different imaging parameters. Therefore, to assess the robustness of the previously developed models under different (e.g., non-reference) imaging protocols, we identified 343 subjects from this study who had CT data from both the reference condition (used in model construction) and non-reference conditions (e.g., evaluation conditions), which we used in this model evaluation analysis. We reported the specificities from three model under the non-reference conditions. Generalized linear mixed effects model (GLMM) was utilized to identify the significant CT technical and clinical parameters that were associated with getting inconsistent diagnostic results between reference and evaluation conditions. Selected parameters include effective tube current-time product (known as “effective mAs”), reconstruction kernels, slice thickness, patient orientation (prone or supine), CT scanner model, and clinical diagnosis. Limitations include the retrospective nature of this study.

RESULTS: For all three DL models, the overall specificity of the previously trained IPF diagnosis model decreased (p < 0.05 for two out of three models). GLMM further suggests that for at least one out of three models, mean effective mAs across the scan is the key factor that leads to the decrease in model predictive performance (p < 0.001); the difference of mean effective mAs between the reference and evaluation conditions (p = 0.03) and slice thickness (3 mm; p = 0.03) are flagged as significant factors for one out of three models; other factors are not statistically significant (p > 0.05).

CONCLUSION: Preliminary findings demonstrated the lack of robustness of IPF diagnosis model when the DL-based model is applied to CT series collected under different imaging protocols, which indicated that care should be taken as to the acquisition and reconstruction conditions used when developing and deploying DL models into clinical practice.

PMID:40111345 | DOI:10.1002/mp.17752

Global Spine J. 2025 Mar 20:21925682251328285. doi: 10.1177/21925682251328285. Online ahead of print.

ABSTRACT

Study DesignRetrospective Cohort Study.ObjectivesTo assess long-term alignment descriptors correlating with mechanical complications.MethodsThe study included adult spinal deformity cases older than 18, with a minimum of four instrumented levels and a 5-year follow-up. Exclusions: previous spinal fusion, neuromuscular/rheumatic diseases, active infections, tumors, or incomplete radiographic exams. Collected data: demographic, surgical, pre- and post-operative spinopelvic parameters, and post-operative complications. The GAP score, original Roussouly type restoration, Schwab’s criteria, and Odontoid to hip axis angle were evaluated using machine learning and logistic regression. Complications were evaluated with a Kaplan-Meier curve.ResultsTwo hundred and twelve patients fulfilled the inclusion and exclusion criteria and were enrolled in the study. The observed rate of revision surgery for mechanical complications was 40.6% (86 out of 212 patients). Higher post-operative GAP scores were associated with increased risks of revision for junctional failure (AUC = 0.72 [IC 95%] 0.62-0.80). The inability to restore the original Roussouly spinal shape was statistically associated with higher mechanical failure rates. A machine-learning approach and subsequent logistic regression found that the GAP score and original Roussouly type restoration are the most important predictors for mechanical failure, and GAP score lordosis distribution index and relative pelvic version are the most important factors to predict the risk of mechanical failure.ConclusionsIn our series, a proper post-operative GAP Score and the restoration of the original Roussouly type significantly minimize mechanical complication rates. We observed that junctional failure tends to occur earlier among complications, while implant failure occurs later in the follow-up.

PMID:40111340 | DOI:10.1177/21925682251328285

Rev Med Suisse. 2025 Mar 19;21(910):557-562. doi: 10.53738/REVMED.2025.21.910.557.

ABSTRACT

In elderly patients prone to multiple falls with atrial fibrillation, anticoagulants are often discontinued, primarily due to fear of bleeding. However, even in the presence of repeated falls, the increased risk of stroke associated with discontinuation of anticoagulation significantly outweighs the hemorrhagic risk. The management of fall-prone patients with atrial fibrillation relies on oral anticoagulation along with a systematic assessment of risk factors for bleeding to identify and treat modifiable risk factors. Left atrial appendage closure represents an alternative to anticoagulation that may be considered in cases of irreversible cause of intracerebral hemorrhage and non-modifiable risk factors.

PMID:40111301 | DOI:10.53738/REVMED.2025.21.910.557

Integr Environ Assess Manag. 2025 Mar 20:vjaf036. doi: 10.1093/inteam/vjaf036. Online ahead of print.

ABSTRACT

Air pollution from coal-based power plants poses significant health and environmental risks. This study aimed to evaluate the effectiveness of abatement technologies, specifically flue gas desulfurization (FGD) wet scrubbers and selective catalytic reduction (SCR) systems, in reducing air pollution from power plants in Israel. We analyzed air quality data from eight monitoring stations near the Hadera Power Plant, comparing pollutant concentrations before (2015) and after (2019) the installation of abatement systems. Hourly averages of NOx, NO2, and SO2 concentrations were computed and analyzed using Wilcoxon’s paired test and linear regression models. Results showed significant decreases in overall pollutant concentrations following the installation of abatement systems. Total average NOx concentrations decreased from 11.68 to 6.88 ppb in summer and from 9.78 to 7.38 ppb in winter. Similar reductions were observed for NO2 and SO2. Monitoring Stations data -specific analysis revealed statistically significant decreases in 86.7% of all comparisons. Furthermore, in 21 out of 22 linear regression models, the variable indicating the installation of the abatement systems was negatively associated with the pollutants’ concentrations. These findings demonstrate the effectiveness of abatement technologies in reducing air pollution from power plants, supporting their implementation as a viable strategy for improving air quality and protecting public health in areas near coal-fired power plants.

PMID:40111263 | DOI:10.1093/inteam/vjaf036

Pharmacogenomics. 2025 Mar 20:1-13. doi: 10.1080/14622416.2025.2481016. Online ahead of print.

ABSTRACT

AIM: To assess patient perspectives following evaluation in a multidisciplinary pharmacogenomics clinic run by a clinical pharmacist, genetic counselor, and physician.

METHODS: A survey was distributed to 187 adults seen in the Brigham and Women’s Hospital Pharmacogenomics Clinic. Participants who completed the survey were invited to complete a semi-structured interview. Interview subjects were selected based on order of responses, scheduling availability, and range of participant experiences with testing and the clinic process. Surveys were analyzed with descriptive statistics, and interview transcripts were analyzed with thematic analysis.

RESULTS: Forty-two survey responses were received; 13 participants were interviewed. Quantitative data demonstrated high satisfaction with the multidisciplinary clinic model and belief that pharmacogenomic testing has value. Qualitative analysis identified four themes: 1) Self-Advocacy as a Patient Responsibility in the Utilization of Pharmacogenomic Results, 2) High Satisfaction with Multidisciplinary Pharmacogenomics Clinic Model and Team, 3) Utility of Pharmacogenomics, and 4) Desire for Pharmacogenomics Resources.

CONCLUSION: Patients value the care provided by a multidisciplinary pharmacogenomics clinic team, but they need to advocate for the use of their results with other healthcare professionals.

PMID:40111244 | DOI:10.1080/14622416.2025.2481016

Tree Physiol. 2025 Mar 8;45(3):tpaf014. doi: 10.1093/treephys/tpaf014.

ABSTRACT

Seasonal variation of nutrient concentrations in different organs is an essential strategy for temperate trees to maintain growth and function. The seasonal variations and variability (i.e., seasonality) of leaf nutrient concentrations have been well documented, while the trends and magnitudes of such seasonal variations in other tree organs (e.g., twigs) and their associations with leaf nutrients remain poorly understood. We measured the concentrations of 10 nutrients (nitrogen, N; phosphorus, P; potassium, K; calcium, Ca; magnesium, Mg; iron, Fe; manganese, Mn; copper, Cu; zinc, Zn; boron, B) in twigs and leaves of four temperate tree species (i.e., Pinus tabuliformis, Ginkgo biloba, Cotinus coggygria, and Sophora japonica) to explore their seasonal variations and seasonality. Our results showed that macronutrient concentrations (N, P, K, Ca, and Mg) were significantly higher in leaves and micronutrient concentrations (Fe, Mn, Cu, and Zn) were significantly higher in twigs. Concentrations of P and K both showed a negative seasonal covariation between twigs and leaves, while Ca, Fe, Mn, Cu, Zn, and B showed an opposite relationship. Compared with mobile nutrients, nonmobile nutrients exhibited significantly greater seasonality in the leaves but there were no such differences in twigs. The seasonality of nutrient concentrations in twigs was significantly stronger than in leaves and they were positively correlated. Additionally, nutrients with higher physiological requirements in leaves showed weaker seasonality, confirming the hypothesis of seasonal stability of high-demand nutrients, while such relationships were not statistically significant for twigs. This study demonstrates distinct seasonality of nutrients in twigs and leaves of temperate woody plants. These findings highlight that high-demand nutrients show stronger seasonal stability in leaves but not in twigs and uncover the seasonal coordination between twigs and leaves as a nutrient conservation strategy.

PMID:40111226 | DOI:10.1093/treephys/tpaf014