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Objective: Many researchers and physicians attempt to determine the prognosis and short- and long-term mortality risks of dementia for formulating suitable care plans for patients and their families. However, the published prediction models have been insufficient for this purpose and have worked only in certain specific populations. For medical autonomy and end-of-life decisions, an informative tool to predict 6-month, 1-year, 2-year, 3-year, and 5-year mortality rates for dementia patients merits further investigation.
Methods: Patients aged ≥ 65 years who received ICD-9-CM diagnoses of dementia between 2002 and 2009 were identified from Taiwan's National Health Insurance Research Database and followed until the end of 2013. Patient characteristics and comorbidities that were considered potential risk factors for mortality were assessed. Mortality-predicting risk scores were developed using a regression coefficient-based scoring approach. In total, 6,556 patients were identified and then randomly divided into a derivation cohort (n = 4,371) and validation cohort (n = 2,185).
Results: By the end of the study, 1,693 of the 4,371 dementia patients (38.7%) in the derivation cohort were deceased. Mean duration of follow-up was 6.26 years. Eleven acute and chronic factors were identified for building the predictive score model, which produced scores from 0 to 24 points (higher scores indicated higher mortality). The score model exhibited good predictive power for various life expectancies (area under receiver operating characteristic curve: 6-month = 0.852, 1-year = 0.779, 2-year = 0.725, 3-year = 0.721, 5-year = 0.703) and good calibration in the validation cohort (Hosmer-Lemeshow test, χ² = 4.709, P = .788).
Conclusions: The developed predictive score model may be the first tool that uses the same clinical factors to determine both short- and long-term mortality risks in patients with dementia.
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http://dx.doi.org/10.4088/JCP.18m12629 | DOI Listing |
Wounds
August 2025
Department of Day Surgery, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorder, Chongqing, China; China International Science and Technology Coopera
Background: Current management of pediatric cutaneous abscesses involves either spontaneous healing by secondary intention or suturing through tertiary intention, which are often lengthy processes that cause discomfort and distress among children. As it is noninvasive and simple, a novel zipper device is widely used for the primary wound closure of surgical incisions.
Objective: To describe the effectiveness of novel zipper device use for pediatric cutaneous abscess wound closure in an outpatient context.
Knee Surg Relat Res
September 2025
Florida Orthopaedic Institute, Gainesville, FL, 32607, USA.
Background: A clear understanding of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) is essential for effectively implementing patient-reported outcome measurements (PROMs) as a performance measure for total knee arthroplasty (TKA). Since not achieving MCID and SCB may reflect suboptimal surgical benefit, the primary aim of this study was to use machine learning to predict patients who may not achieve the threshold-based outcomes (i.e.
View Article and Find Full Text PDFGeroscience
September 2025
Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden.
To evaluate a simplified version of the Clinical Frailty Scale (SCFS) among older adults presenting to the emergency department (ED) with acute dyspnea. In this retrospective single-center cohort study, we included patients from the Acute Dyspnea Study (ADYS) cohort. Severity of illness was assessed using the Medical Emergency Triage and Treatment System (METTS).
View Article and Find Full Text PDFOral Radiol
September 2025
Department of Oral and Maxillofacial Radiology, Eskisehir Osmangazi University, Meşelik Campus, Büyükdere Neighborhood, Prof. Dr. Nabi Avcı Boulevard No:4, Odunpazarı, Eskişehir, 26040, Turkey.
Objectives: The primary objective of this study is to evaluate the effectiveness of artificial intelligence-assisted segmentation methods in detecting carotid artery calcification (CAC) in panoramic radiographs and to compare the performance of different YOLO models: YOLOv5x-seg, YOLOv8x-seg, and YOLOv11x-seg. Additionally, the study aims to investigate the association between patient gender and the presence of CAC, as part of a broader epidemiological analysis.
Methods: In this study, 30,883 panoramic radiographs were scanned.
Immunol Res
September 2025
Department of Immunology and Allergy, Faculty of Medicine, Necmettin Erbakan University, Konya, Türkiye.
Background: Variants of uncertain significance (VUS) represent a major diagnostic challenge in the interpretation of genetic testing results, particularly in the context of inborn errors of immunity such as severe combined immunodeficiency (SCID). The inconsistency among computational prediction tools often necessitates expensive and time-consuming wet-lab analyses.
Objective: This study aimed to develop disease-specific, multi-class machine learning models using in silico scores to classify SCID-associated genetic variants and improve the interpretation of VUS.