Category: Statistics

BMC Infect Dis. 2025 Jul 23;25(1):937. doi: 10.1186/s12879-025-11315-5.

ABSTRACT

OBJECTIVE: This study, aimed at determining the effect of ivermectin on scabies, which has recently reached epidemic proportions, was conducted by the Department of Dermatology and Venereology at Dicle University. The study aims to evaluate the success of ivermectin in the treatment of scabies, identify variables affecting this success, and contribute positively to the development of future national treatment protocols. Additionally, the study seeks to test the hypothesis that ivermectin, which is significantly easier to use in cases of failure with topical treatments, is a good first-line treatment option.

MATERIALS AND METHODS: In this retrospective study, 412 patients diagnosed with scabies via clinical examination by a specialist physician and recommended a 200 µg/kg dose of ivermectin at one-week intervals, who presented to Dicle University Dermatology and Venereology Clinic between January 1, 2023, and June 30, 2024, were examined. Fifty-two patients whose records lacked the parameters evaluated in the study were excluded. A total of 360 patients were included in the study. Data on children under five years of age, those weighing less than 15 kg, and pregnant or lactating women were not obtained due to insufficient information regarding oral ivermectin use in these groups. Data were evaluated with SPSS-21.0 statistical program and the value, mean, median value, standard deviation, incidence rate and frequency of each parameter in total patients were recorded. Associations were analysed using Kolmogorov-Smirnov test, dependent t test, Wilcoxon test, Pearson Chi-square (χ2) test, Yates Chi-square (χ2) test, Fisher Chi-square (χ2) test analysis, Mc-Nemar test, Pearson/spearman correlation analysis, logistic regression analysis. A p-value of < 0.05 was considered statistically significant.

RESULTS: The ivermectin treatments for all 360 patients were prescribed by a specialist physician, and 78.6% (283) of the patients benefited from the treatment. Of these 360 patients, 295 (81.94%) had tried at least one other treatment option before ivermectin and did not benefit from it, while 66.1% (43 out of 65) of those who had not previously undergone treatment benefited from ivermectin. Furthermore, 81.36% (240 out of 295) of patients who did not respond to previous treatments benefited from ivermectin.

CONCLUSION: This study concluded that ivermectin could be a significant treatment option for patients diagnosed with scabies. The superiority of appropriately dosed ivermectin treatment over other treatments was observed, particularly in patients resistant to other scabies treatments.

PMID:40702460 | DOI:10.1186/s12879-025-11315-5

Gait Posture. 2025 Jul 17;122:190-198. doi: 10.1016/j.gaitpost.2025.07.320. Online ahead of print.

ABSTRACT

BACKGROUND: The Conventional Gait Model II (CGM2) aims to address the limitations of the Conventional Gait Model (CGM) in a standardised way. Evidence supporting the use of CGM2 has come from independent studies within adult populations, which has hindered the uptake of the model by paediatric centres.

RESEARCH QUESTION: What is the effect of CGM2 model variants on gait kinematics and kinetics in a cohort of typically developing children?

METHODS: Secondary analysis of three-dimensional gait analysis data of thirty-two typically developing children. Gait kinematics and kinetics were reprocessed for each of the CGM2 model variants. These variants include the introduction of new hip joint centre equations, inverse kinematics, and marker clusters. Differences between kinematics and kinetics were compared using statistical parametric mapping 1D, and root mean squared difference (RMSD).

RESULTS: Differences were seen in kinematics and kinetics across all models, with the largest changes seen in the transverse plane for the hip, knee and ankle, with an average RMSD relative to CGM1.0 of 6.1°, 22.7°, and 9.9° respectively. All other gait variables had an average RMSD of less than 5° for kinematics, 0.1 Nm for moments, and 0.19 W for powers. Changes to the Gait Profile Score were less than 0.14° on average.

SIGNIFICANCE: The CGM2 model has addressed several known limitations by improving the hip joint centre locations, reducing the number of required anthropometric measures, and introducing inverse kinematics and cluster-based segment tracking. Our results highlight the importance of consistency in model variants and processing methods when comparing data.

PMID:40700788 | DOI:10.1016/j.gaitpost.2025.07.320

Burns. 2025 Jul 14;51(8):107614. doi: 10.1016/j.burns.2025.107614. Online ahead of print.

ABSTRACT

BACKGROUND: Burn mortality prediction remains a critical aspect in burn medicine. Established scores, such as the ABSI or Baux score, experience continuous revision and improvement due to advances in critical care and surgical procedures. However, these scores often rely on predefined variables and limited statistical models. This study aimed to create a new prediction score that is based solely on machine learning techniques and to assess its performance against established traditional scoring systems.

METHODS: Using different advanced machine learning methods, data from the German burn registry, encompassing over 10,000 cases, were analyzed regarding the most relevant factors concerning mortality and a new prediction score was created. A new prediction model was constructed, employing algorithms such as random forests and gradient boosting. Internal validation was conducted using cross-validation to ensure robustness and reproducibility.

RESULTS: The Bochum Burn Survival (BoBS) score demonstrates strong predictive performance with an accuracy of 93.1 % and ROC AUC of 92.4 %, therefore surpassing traditional scores in predictive performance. Factors such as TBSA and age showed the strongest correlation with mortality, while comorbidities and treatment-specific variables contributed to model refinement. However, further adjustments and external validation beyond the German Burn Registry are crucial in the future.

DISCUSSION: The BoBS score represents a paradigm shift in burn mortality prediction, leveraging the potential of machine learning to analyze complex, high-dimensional datasets. Compared to traditional models, the BoBS score offers improved accuracy while providing insights into underexplored variables that might impact patient outcomes. But challenges remain in integrating such models into clinical workflows and validating them across diverse populations.

CONCLUSION: This score represents a significant advancement in burn mortality prediction by providing an interpretable, machine learning-based scoring system developed using multicenter data from the German Burn Registry. Its application has the potential to enhance decision-making in burn care, marking a significant step forward in personalized medicine for critically injured burn patients.

PMID:40700784 | DOI:10.1016/j.burns.2025.107614

Clin Biomech (Bristol). 2025 Jul 15;128:106621. doi: 10.1016/j.clinbiomech.2025.106621. Online ahead of print.

ABSTRACT

BACKGROUND: Posterosuperior massive rotator cuff tears remain challenging to manage. While lower trapezius transfer restores posterior cuff function, it lacks the superior cuff’s biomechanical role. Middle trapezius tendon transfer has shown efficacy in addressing superior cuff deficiencies with dynamic joint-centering and spacer effects. This study aimed to compare the biomechanical effects of lower trapezius transfer alone versus combined lower and middle trapezius transfer for posterosuperior massive rotator cuff tears.

METHODS: Eight cadaveric shoulders were tested under four conditions: intact, posterosuperior cuff tear, lower trapezius transfer, and combined lower and middle trapezius transfer. Superior translation, subacromial contact pressure, and rotational range of motion were measured at multiple abduction and external rotation positions. Statistical analysis was performed using a linear mixed-effects model.

FINDINGS: Both lower trapezius and combined lower and middle trapezius transfers significantly reduced superior humeral head translation versus the tear condition (p < .041). The combined transfer restored translation to intact levels and was more effective than lower trapezius transfer alone at 0° and 20° abduction (p < .031). Subacromial contact pressure decreased significantly with both transfers at 20° and 40° abduction (p < .030), and with combined transfer also at 0° abduction and 30° ER (p < .042). Total rotational range of motion was preserved in all conditions.

INTERPRETATION: Combined lower and middle trapezius transfer offers superior biomechanical restoration of glenohumeral joint stability compared to lower trapezius transfer alone without compromising range of motion. These findings support the potential of dual tendon transfer in addressing both posterior and superior cuff deficiencies, warranting further clinical evaluation.

PMID:40700779 | DOI:10.1016/j.clinbiomech.2025.106621

Orthop Nurs. 2025 Jul-Aug 01;44(4):231-235. doi: 10.1097/NOR.0000000000001137. Epub 2025 Jul 18.

ABSTRACT

In this study, the authors examine the establishment and significance of spine surgery registries, particularly the American Spine Registry (ASR). The historical development of spine registries in the United States is outlined along with the role of registries in evaluating clinical outcomes and improving healthcare quality. The ASR aims to collect comprehensive data on spine surgeries, including patient-reported outcomes and performance metrics, to enhance quality standards and clinical practice guidelines. Studies from European registries demonstrate the utility of registry data in identifying trends, assessing cost-effectiveness, and improving patient care. This paper also discusses the economic implications of participation in spine registries and emphasizes the potential cost savings and benefits for healthcare organizations. Ethical and legal considerations, data security, and patient confidentiality are addressed, along with the challenges associated with registry participation such as resource allocation. Increased transparency, collaboration, and clarity are needed to promote broader engagement in spine surgery registries.

PMID:40700763 | DOI:10.1097/NOR.0000000000001137

J Am Med Inform Assoc. 2025 Jul 23:ocaf121. doi: 10.1093/jamia/ocaf121. Online ahead of print.

ABSTRACT

OBJECTIVE: Risk prediction models are used in hospitals to identify pediatric patients at risk of clinical deterioration, enabling timely interventions and rescue. The objective of this study was to develop a new explainer algorithm that uses a patient’s clinical notes to generate text-based explanations for risk prediction alerts.

MATERIALS AND METHODS: We conducted a retrospective study of 39 406 patient admissions to the American Family Children’s Hospital at the University of Wisconsin-Madison (2009-2020). The pediatric Calculated Assessment of Risk and Triage (pCART) validated risk prediction model was used to identify children at risk for deterioration. A transformer model was trained to use clinical notes from the 12-hour period preceding each pCART score to predict whether a patient was flagged as at risk. Then, label-aware attention highlighted text phrases most important to an at-risk alert. The study cohort was randomly split into derivation (60%) and validation (20%) data, and a separate test (20%) was used to evaluate the explainer’s performance.

RESULTS: Our pCART Explainer algorithm performed well in discriminating at-risk pCART alert vs no alert (c-statistic 0.805). Sample explanations from pCART Explainer revealed clinically important phrases such as “rapid breathing,” “fall risk,” “distension,” and “grunting,” thereby demonstrating excellent face validity.

DISCUSSION: The pCART Explainer could quickly orient clinicians to the patient’s condition by drawing attention to key phrases in notes, potentially enhancing situational awareness and guiding decision-making.

CONCLUSION: We developed pCART Explainer, a novel algorithm that highlights text within clinical notes to provide medically relevant context about deterioration alerts, thereby improving the explainability of the pCART model.

PMID:40700686 | DOI:10.1093/jamia/ocaf121

J Eval Clin Pract. 2025 Aug;31(5):e70220. doi: 10.1111/jep.70220.

ABSTRACT

RATIONALE, AIMS AND OBJECTIVES: Colonoscopy, though common, can be uncomfortable, necessitating routine assessment of patient experience per European guidelines. Positive patient experiences are crucial as they influence willingness for repeat procedures. Patient-reported experience measures (PREMs) effectively capture patient perspectives through surveys, empowering patients to influence healthcare quality. These surveys identify areas for improvement and inform research, enhancing healthcare and its quality. The Patient Experience Colonoscopy Scale (PECS) is a colonoscopy-specific PREM that measures adult patient experience after an elective colonoscopy. It consists of items derived from the patient’s perspective and has been found to be content valid. The PECS is multidimensional and divided into five constructs: health motivation, discomfort, information, a caring relationship, and understanding. The current study aims to evaluate the measurement properties of the new PREM, called the PECS regarding reliability and construct validity.

METHOD: The sample comprised 331 adult patients who had undergone an elective colonoscopy at a University Hospital in Sweden. The PECS was evaluated using intraclass correlation coefficients, confirmatory factor analysis, and multi- and unidimensional Rasch analyses.

RESULTS: The test-retest reliability was acceptable, with an average intraclass correlation coefficient of 0.72. Construct validity was tested with three different techniques. The confirmatory factor analysis revealed that the theoretical bifactor model containing the five constructs was supported. The multi- and unidimensional Rasch analyses showed that approximately 60% of the items had acceptable values. Some violation of local independence and some evidence of differential item functioning with respect to age and gender were identified, but they all made subject matter sense. The PECS is well-targeted to patients with less positive experiences. The overall evaluation of the construct validity showed the PECS has acceptable measurement properties.

CONCLUSION: The PECS is a reliable and valid 30-item colonoscopy-specific PREM that can play an important role in gathering data for research and quality improvement initiatives that seek to incorporate patient perspectives on colonoscopy experiences. Some potential areas for improvement were found, but the PECS is ready to be utilised in clinical practice for the purpose of collecting patient experiences.

PMID:40700682 | DOI:10.1111/jep.70220

JCO Clin Cancer Inform. 2025 Jul;9:e2400279. doi: 10.1200/CCI-24-00279. Epub 2025 Jul 23.

ABSTRACT

PURPOSE: Despite its routine use to monitor patients with lung cancer (LC), real-world evaluations of the impact of computed tomography (CT) surveillance on overall survival (OS) have been inconsistent. A major confounder is the absence of imaging indications because patients undergo CT scans for purposes beyond surveillance, like symptom evaluations (eg, cough) linked to poor survival. We propose a novel natural language processing model to predict CT imaging indications (surveillance v others).

METHODS: We used electronic health records of 585 long-term LC survivors (≥5 years) at Stanford, followed for up to 22 years. Their 3,362 post-5-year CT reports (including 1,672 manually annotated) were used for modeling by integrating structured variables (eg, CT intervals) with key-phrase analysis of radiology reports. Naïve analysis compared OS in patients with CT for any indications (including symptoms) versus those without post-5-year CT, as in previous studies. Using model-predicted indications, we conducted exploratory analyses to compare OS between those with post-5-year surveillance CT and those without.

RESULTS: The model showed high discrimination (AUC, 0.86), with key predictors including a longer interval (≥6-month) from the previous CT (odds ratios [OR], 5.50; P < .001) and surveillance-related key phrases (OR, 1.37; P = .03). Propensity-adjusted survival analysis indicated better OS for patients with any post-5-year surveillance CT versus those without (adjusted hazard ratio, 0.60; P = .016). By contrast, no significant survival difference was found (P = .53) between patients with any CT versus those without post-5-year CT.

CONCLUSION: Our model abstracted CT indications from real-world data with high discrimination. Exploratory analyses revealed the obscured imaging-OS association when considering indications, highlighting the model’s potential for future real-world studies.

PMID:40700679 | DOI:10.1200/CCI-24-00279

JCO Clin Cancer Inform. 2025 Jul;9:e2400317. doi: 10.1200/CCI-24-00317. Epub 2025 Jul 23.

ABSTRACT

PURPOSE: Social Determinants of Health (SDoH) have a significant effect on health outcomes and inequalities. SDoH can be extracted from electronic health records (EHR) to aid policy development and research to improve population health. Automated extraction using artificial intelligence (AI) can improve efficiency and cost-effectiveness. The focus of this study was to autonomously extract comprehensive SDoH details from EHR using a natural language processing (NLP)-based AI pipeline.

MATERIALS AND METHODS: A curated set of 1,000 BC Cancer clinical documents with concentrated SDoH information served as the reference standard for training and evaluating NLP models. Two pipelines were used: an open-source pipeline trained on the annotated medical documents and an industrial pretrained solution used as a benchmark. Three experiments optimized the first pipeline’s performance, assessing the effect of including subtype word positions during training. The superior open-source pipeline was then used to extract SDoH information from 13,258 oncology documents.

RESULTS: The open-source pipeline achieved an average F1 score accuracy of 0.88 on the validation data set for extracting 13 SDoH factors, surpassing the benchmark by 5%. It excelled in detailed subtype extraction, while the benchmark performed better in identifying rarely annotated SDoH information in BC Cancer data set. Overall, 60,717 SDoH factors and associated details were extracted from BC Cancer EHR oncology documents. The most frequently extracted SDoH factors included tobacco use, employment status, marital status, alcohol consumption, and living status, occurring between 8k to 12k times.

CONCLUSION: This study demonstrates the potential of an NLP pipeline to extract SDoH factors from clinical notes, with strong performance on limited data, although data set-specific adjustments are needed for broader application across institutions.

PMID:40700678 | DOI:10.1200/CCI-24-00317

Hematology. 2025 Dec;30(1):2535817. doi: 10.1080/16078454.2025.2535817. Epub 2025 Jul 23.

ABSTRACT

BACKGROUND: Growing evidence supports the significant role of inflammatory factors in anemia. This paper intends to ascertain the potential link between MLR and anemia and explore potential mediators.

METHODS: Our analysis employed comprehensive data recourse from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 utilizing weighted logistic regression models to assess the link between MLR and anemia. Restricted cubic spline analyses were implemented to evaluate MLR-anemia nonlinear relationship. Threshold effect analysis identified a critical inflection point. To ensure robustness, we conducted extensive subgroup analyses stratified by demographic and clinical factors. The mediating role of serum albumin on the link between MLR and anemia was investigated through mediation analysis.

RESULTS: 28,616 participants were enrolled, with 2655 (9.28%) with anemia. After adjustment for all covariates, log2-transformed MLR (log2MLR) was linked with an enhanced risk of anemia (OR:1.49, 95%CI:1.33-1.65, P < 0.001). When log2MLR was categorized into quartiles, the trend remained consistent (P < 0.001). A nonlinear positive link was noted between log2MLR and anemia, with an inflection point at -2.812. No statistical interactions were unveiled in any subgroup analyses except for gender and diabetes (interaction P < 0.05). Interestingly, serum albumin partially mediated this association, accounting for 15.39% of the total effect.

CONCLUSION: This study presents groundbreaking findings on the role of MLR in anemia and the mediating effect of serum albumin, offering new perspectives on potential inflammatory pathways underlying hematological disorders.

PMID:40700677 | DOI:10.1080/16078454.2025.2535817