Nevin Manimala

J Emerg Nurs. 2025 Dec 12:S0099-1767(25)00471-4. doi: 10.1016/j.jen.2025.11.016. Online ahead of print.

ABSTRACT

Pediatric emergency nurses play a central role in mass casualty incident response, yet persistent gaps in readiness remain. This quality improvement project evaluated baseline mass casualty incident readiness among registered nurses in a large pediatric emergency department and assessed the impact of an educational intervention combining didactic review and simulation-based functional exercises. Using a pre-/postintervention design, nurses completed a readiness survey and participated in timed functional tasks to assess knowledge, confidence, and efficiency. The intervention comprised a didactic review of institutional protocols, a practical review of supply locations, and 30-minute functional simulation drills focused on zone leader responsibilities. A total of 63 nurses completed preassessments, and 64 completed postassessments. After the intervention, 92% accurately identified supply locations, 98% described zone leader roles, and 100% reported feeling at least neutral in preparedness. Knowledge gains in this project were statistically significant (P < .001). The results indicate that structured education combined with simulation improved pediatric emergency nurses’ readiness for mass casualty incidents within this setting. The intervention’s effectiveness was further demonstrated when it was applied successfully during an actual mass casualty incident. Incorporating pediatric-focused mass casualty incident training into ongoing ED education may continue to enhance nurse competence, support team performance, and strengthen institutional disaster preparedness.

PMID:41389075 | DOI:10.1016/j.jen.2025.11.016

Clin Neuropsychol. 2025 Dec 13:1-12. doi: 10.1080/13854046.2025.2601744. Online ahead of print.

ABSTRACT

Objective: Teleneuropsychology (TeleNP) shows promise as an alternative visit type for patients in which face-to-face (FTF) neuropsychological evaluation is not a viable option. Undergoing FTF presurgical deep brain stimulation (DBS) neuropsychological evaluations may represent a hardship for some patients with movement disorders, yet comparison of performance for TeleNP and FTF for the commonly used Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has not been studied in this population. The current study aimed to examine RBANS performance of FTF and TeleNP administration in a cohort of movement disorders patients in a clinical setting, hypothesizing similar performance regardless of modality. Method: Four hundred six patients with Parkinson’s disease or essential tremor completed the RBANS between two medical centers between 2020 and 2024 as part of standard clinical care within their presurgical assessment for candidacy for DBS or High-Intensity Focused Ultrasound thalamotomy. Results: The TeleNP sample was significantly older than the FTF sample (p = .02). There were no statistical differences in gender (p = .18) or education (p = .66) between the samples. After controlling for age and motor diagnosis differences between the two groups, 9 of the 11 RBANS subtests were comparable, with the TeleNP group performing significantly better on the Picture Naming subtest and the FTF group performing significantly better on the Figure Recall subtest. The effect size of these differences were small, indicating relatively low clinical meaningfulness. Conclusions: The findings of the current study suggest the two methods of administration were associated with broadly comparable performances in this movement disorder population, suggesting TeleNP may be a viable option for presurgical evaluation.

PMID:41389068 | DOI:10.1080/13854046.2025.2601744

Med Phys. 2025 Dec;52(12):e70191. doi: 10.1002/mp.70191.

ABSTRACT

BACKGROUND: Four-dimensional computed tomography (4DCT) imaging is a crucial component to lung cancer radiotherapy planning and enables CT-ventilation-based functional avoidance planning to mitigate radiation toxicity. However, 4DCT scans are frequently impaired by acquisition artifacts that corrupt downstream analyses that depend on lung segmentation and deformable image registration, such as CT-ventilation and dose accumulation.

PURPOSE: This study develops 3D deep learning models to identify phase-binning artifacts at the voxel level and a heuristic, rule-based method to identify interpolation slices within 4DCT images.

METHODS: We introduce a generator that systematically inserts synthetic phase-binning and interpolation artifacts into any artifact-free breathing phase obtained from nine different clinical 4DCT datasets to produce ground-truth data for (1) training modified nnUNet and SwinUNETR models to detect phase-binning artifacts, and (2) to determine thresholds in the rule-based detection method for interpolation artifacts. The use of multiple datasets incorporates robustness across artifact severities, lung geometries, and cancer progressions.

RESULTS: After training on generated synthetic data and several configurations (region-based learning masks, left-right lung separation), the nnUNet and SwinUNETR models demonstrated state-of-the-art artifact detection accuracy, averaging 0.957 $\pm$ 0.024 (95% CI: [0.956, 0.958]), with an nnUNet configuration achieving the highest averaged accuracy of 0.965, sensitivity of 0.805, and specificity of 0.998 when inferring artifact-affected axial slices from voxel-level predictions. By interpolating and comparing groups of slices, the accuracy, sensitivity, and specificity of the proposed interpolation detection method is 0.97, 0.97, and 0.97 on manually labeled true artifact cases. We propose a localized artifact correction method that simply replaces the predicted artifact-affected voxels with the average surrounding lung intensity value, resulting in 65% of lung segmentation masks with Dice scores greater than 0.95 (opposed to 11% of cases before correction) when applying an automatic segmentation tool and within a tight artifact-bound region. When applied to 1989 cases with true artifacts, SwinUNETR configurations tend to be more generalizable despite marginally lower performance on synthetic artifacts. We quantify this performance without ground-truth artifact masks by statistically comparing artifact properties of detected synthetic and true cases.

CONCLUSIONS: We demonstrate state-of-the-art artifact detection accuracy using 3D deep learning models trained on synthetic data and a rule-based approach configured on true data, providing interpretability by highlighting which voxel locations indicate a slice is artifact-affected. The SwinUNETR model accuracy and fast run-time have the potential to enable more targeted artifact correction methods or signal an imaging technologist when to re-scan a patient in real-time.

PMID:41389065 | DOI:10.1002/mp.70191

Neuromodulation. 2025 Dec 13:S1094-7159(25)01150-X. doi: 10.1016/j.neurom.2025.11.006. Online ahead of print.

ABSTRACT

OBJECTIVES: Deep brain stimulation (DBS) is increasingly being used to treat a variety of neuropsychiatric conditions, many of which exhibit idiosyncratic symptom presentations and neural correlates across individuals. Thus, we have used inpatient stereoelectroencephalography (sEEG) to identify personalized therapeutic stimulation sites for long-term implantation of DBS. Informed by our experience, we have developed a statistics-driven framework for stimulation testing to identify therapeutic targets.

MATERIALS AND METHODS: Fourteen participants (major depressive disorder = 6, chronic pain = 6, obsessive-compulsive disorder = 2) underwent inpatient testing using sEEG and symptom monitoring to identify personalized stimulation targets for subsequent DBS implantation. We present a structured approach to this sEEG testing, integrating a Stimulation Testing Decision Tree with power analysis and effect size considerations to inform adequately powered results to detect therapeutic stimulation sites with statistical rigor.

RESULTS: Effect sizes (Hedges’ g) of stimulation-induced symptom score changes ranged from -1.5 to +2.39. The SD of sham trial responses was a strong predictor of stimulation response variability, as confirmed by a leave-one-out cross-validated linear regression (R² = 0.67, permutation p < 0.001). Thus, early sham trial data could be used to estimate the variability of stimulation responses for power analysis calculations. We show that approximately ten sham trials were needed to robustly estimate sham variability. Power analysis (using a paired t-test) showed that for effect sizes ≥1.1, approximately ten trials should be used per stimulation site for sufficiently powered results.

CONCLUSIONS: The presented workflow is adaptable to multiple indications and is specifically designed to overcome key challenges experienced during stimulation site testing. Through incorporating sham trials, effect size calculations, and tolerability testing, the described approach can be used to identify personalized and clinically efficacious stimulation sites.

PMID:41389045 | DOI:10.1016/j.neurom.2025.11.006

J Hosp Med. 2025 Dec 13. doi: 10.1002/jhm.70245. Online ahead of print.

ABSTRACT

BACKGROUND: Left atrial enlargement (LAE) is predictive of cardiovascular morbidity and mortality. Prior studies of point-of-care ultrasound (POCUS) interpretation methods for identifying LAE utilized older echocardiographic reference ranges.

OBJECTIVES: Compare the test characteristics of hospitalist-performed POCUS techniques for identifying LAE as compared to contemporary echocardiographic reference ranges.

METHODS: Fully paired, comparative diagnostic accuracy study of two index tests applied to archived echocardiogram images: visual assessment of the left atrium to aorta diameter (LAE sign) and left atrial (LA) anteroposterior diameter >4 cm in the parasternal long axis view. The reference test was moderate to severe LAE by echocardiography-derived left atrial volumetric index.

RESULTS: After exclusion criteria, 239 of 321 (74.5%) exams were included. The LAE sign had a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 67.5%, 71.4%, 32.1%, and 91.6%. LA diameter of >4 cm had a sensitivity, specificity, PPV, and NPV of 87.5%, 75.9%, 42.2%, and 96.8%. The difference in sensitivity (p = .005) and specificity (p = .049) between the index tests was statistically significant. The diameter measurement had better positive and negative likelihood ratios (LR + 3.63, LR-0.16) than the LAE sign (LR + 2.36, LR- 0.46).

CONCLUSIONS: Both POCUS techniques for diagnosing LAE performed reasonably well compared to current echocardiographic reference ranges, with LA diameter >4 cm having better sensitivity and specificity than visual estimation of the LAE sign. These tests can help identify patients at risk for cardiovascular disease who may benefit from echocardiogram referral.

PMID:41389028 | DOI:10.1002/jhm.70245

J Med Internet Res. 2025 Dec 12. doi: 10.2196/84393. Online ahead of print.

ABSTRACT

BACKGROUND: Cisgender lesbian, bisexual, and queer (LBQ+) women of color (WOC) experience barriers to accessing sexual and reproductive health (SRH) services in the United States (US). Barriers, including limited provider access and poor patient-provider communication, contribute to underutilization of SRH services and poorer outcomes compared to heterosexual counterparts. Digital health modalities, including telemedicine, mobile health, and artificial intelligence (AI)-enabled chatbots, offer potential to expand access to SRH information and services among LBQ+ WOC.

OBJECTIVE: This study investigated current use, influencing factors, acceptability, and concerns regarding digital health modalities (video calls, SMS text messaging, mobile apps) and AI-enabled chatbots to support SRH information and service access among LBQ+ WOC in the US. It also assessed awareness and knowledge of HPV and cervical cancer prevention, and attitudes toward HIV prevention medication.

METHODS: A self-administered online survey was conducted from November 2020 to March 2021 with 285 LBQ+ WOC (aged ≥18 years) residing in the US. The 88-item survey assessed digital health use, SRH knowledge and awareness, and acceptability of and concerns about digital health use for SRH information and services. Data were analyzed using descriptive statistics, Fisher’s exact tests, multivariable logistic regression, and thematic analysis.

RESULTS: Most respondents were comfortable using video calls (81.8%) to communicate with a healthcare provider for SRH support. Respondents with a bachelor’s degree or higher (95% CI 0.00-0.24, P < .001), with health insurance (95% CI 56.1-1025.7, P < .001), and without a usual place of care (95% CI 0.07-0.43, P < .001) were significantly more likely to agree with using video calls. Respondents with a bachelor’s degree or higher (95% CI 0.23-0.74, P < .001), aged <45 years (95% CI 0.07-0.25, P < .001), and with health insurance (95% CI 3.23-12.45, P < .001) were significantly more likely to agree with using a mobile app. Respondents ≥45 years (95% CI 0.14-0.53, P < .001), without health insurance (95% CI 0.01-0.06, P < .001), and with an income < $49,000 (95% CI 1.32-3.93, P < .001) were significantly more likely to agree with the use of SMS text messaging. High acceptance was reported for using chatbots to self-assess risk for sexually transmitted infections (80.3%), but lower acceptance for self-assessing cervical cancer risk (47.8%). Key concerns included data privacy and confidentiality, lack of affective communication, and technology connectivity and digital literacy issues. Respondents also demonstrated low knowledge of HPV and cervical cancer prevention.

CONCLUSIONS: Digital health was highly acceptable for supporting access to SRH information and services among LBQ+ WOC. Culturally tailored, digital tools and interventions could improve awareness, knowledge, and attitudes toward SRH services. Addressing varying levels of digital literacy, concerns about data privacy, technology access, and affective communication when developing digital health solutions may help to advance SRH equity among LBQ+ WOC.

PMID:41388972 | DOI:10.2196/84393

Biostatistics. 2024 Dec 31;26(1):kxaf044. doi: 10.1093/biostatistics/kxaf044.

ABSTRACT

Addressing health disparities across demographic groups remains a critical challenge in public health, with significant gaps in understanding how these disparities evolve over time. This paper extends the traditional Peters-Belson decomposition to a longitudinal setting, focusing on the role of a single explanatory variable, referred to as a modifier, that captures complex interactions with other covariates. The proposed method partitions disparities into 3 components: (i) the portion associated with differences in the conditional distribution of covariates, evaluated under a common distribution of the modifier across groups; (ii) the portion arising from differences in the distribution of the modifier and its interactions with other covariates; and (iii) the unexplained disparity not accounted for by observed covariates. Rather than aggregating the first 2 components into one “explained disparity,” the proposed method allows for a separate characterization of temporal patterns in disparities, distinguishing those that are unassociated with the modifier from those that are associated with it. We illustrate the method using a fetal growth study, examining disparities in fetal development trajectories across racial and ethnic groups during pregnancy.

PMID:41388844 | DOI:10.1093/biostatistics/kxaf044

Alzheimers Dement. 2025 Dec;21(12):e70936. doi: 10.1002/alz.70936.

ABSTRACT

INTRODUCTION: Current biomarkers used to assess cerebrovascular pathology largely reflect end-stage disease, and more sensitive biomarkers are needed. We examined the role of baseline placental growth factor (PlGF) as a susceptibility biomarker for the progression of white matter injury and longitudinal cognitive decline.

METHODS: A total of 272 functionally intact older adults completed baseline blood draws, with plasma analyzed for PlGF (Meso Scale Discovery), and longitudinal neuroimaging and neuropsychological testing. A subset of 110 participants (n = 110) had banked plasma assayed on a different biomarker platform (NULISAseq) to evaluate replicability.

RESULTS: Higher baseline PlGF was associated with steeper declines in memory and processing speed. Elevated baseline PlGF also associated with greater baseline white matter hyperintensities and lower global fractional anisotropy (FA), but not white matter or FA trajectories.

DISCUSSION: Elevated baseline plasma PlGF associated with faster declines in cognition even among functionally intact older adults across two biomarker platforms. Our findings highlight PlGF as a potential susceptibility/risk biomarker of vascular-related cognitive decline.

HIGHLIGHTS: Higher plasma placental growth factor (PlGF) concentrations relate to greater baseline white matter injury. Elevated baseline plasma PlGF associates with steeper cognitive decline over time. PlGF may represent an upstream biomarker of endothelial-related cognitive decline.

PMID:41388837 | DOI:10.1002/alz.70936

J Inj Violence Res. 2025 Dec 13;17(2). Online ahead of print.

ABSTRACT

BACKGROUND: Unintentional injuries are a major contributor to morbidity and healthcare burden in early childhood. While falls and fractures are globally recognized as the most common pediatric injuries, region-specific data from primary care emergency settings in Southeast Europe remain scarce. The objective was to investigate the mechanisms, anatomical distribution, and contextual factors of injuries in children aged 0 to 6 years treated in a primary care pediatric service in Bosnia and Herzegovina.

METHODS: This retrospective study included ninety-nine children aged 0 to 6 years who presented with injuries to a primary care service between September 2019 and December 2024. Data were collected from medical records and included age, sex, mechanism of injury, type of injury, anatomical site, supervision, home safety, and treatment outcome. Descriptive statistics and chi-square tests were used to analyze associations between demographic variables and injury characteristics. Logistic regression was also applied to examine predictors of fracture occurrence, adjusting for age group and sex.

RESULTS: Falls were the leading cause of injury, accounting for 69.7% of all cases, with the highest number recorded in the 13- to 36-month age group. Fractures were the most frequent injury type, of which 74.4% affected the upper limbs, particularly the radius and humerus. Head injuries were more prevalent among infants, while boys experienced a higher overall injury rate. No statistically significant associations were found between injury occurrence and supervision or home safety, largely due to missing data and limited sample size.

CONCLUSIONS: Falls were the predominant cause of injury in early childhood, with upper limb fractures being common, especially among toddlers. While these findings provide important insights for prevention and pediatric emergency care planning in Bosnia and Herzegovina, larger prospective studies are needed to validate and extend these results.

PMID:41388830

J Inj Violence Res. 2025 Dec 7;17(2). Online ahead of print.

ABSTRACT

BACKGROUND: Suicide remains a critical global health crisis that disproportionately targets young adults, and medical students consistently display higher prevalence rates than their non-medical peers. The main aim of this study was investigation of the mediating roles of three intrapersonal factors-perfectionism, difficulties in emotion regulation, and self-disgust-in the relationship between psychological distress and suicidal ideation within in medical students.

METHODS: The present study utilized correlational research design with path analysis. A convenience sample of 404 medical students from Kermanshah University of Medical Sciences (KUMS), Iran was selected in the latter half of the 2024-2025 academic year. Data were collected using structured questionnaires, including the Psychological Distress Scale (PDS), Beck Scale for Suicidal Ideation (BSSI), Difficulties in Emotion Regulation Scale (DERS), Frost Multidimensional Perfectionism Scale (FROST-MPS), and Multidimensional Self-Disgust Scale (MSDS). SPSS software version 26 handled descriptive statistics and assumption checks, whereas Amos software performed the structural modeling.

RESULTS: The study found that psychological distress significantly predicted difficulties in emotion regulation (β = 0.370, P less than 0.001), perfectionism (β = 0.426, P less than 0.001), and self-disgust (β = 0.348, P less than 0.001). These variables mediated the relationship between psychological distress and suicidal ideation, with significant indirect effects through perfectionism (indirect effect = 0.094, p less than 0.001), difficulties in emotion regulation (indirect effect = 0.119, P less than 0.001), and self-disgust (indirect effect = 0.096, P less than 0.001). Among the total sample, 148 students (36.6%) were at high risk and 200 (49.5%) at very high risk of suicidal ideation.

CONCLUSIONS: There is a strong correlation between suicidal ideation and psychological distress among medical students. The findings highlight the roles of perfectionism, difficulties in emotion regulation, and self-disgust in this relationship. Universities should enhance mental health support and offer interventions targeting these factors to reduce suicide risk.

PMID:41388829