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Thrombocytosis is a common finding in hospitalized patients and is of two main types, essential thrombocytosis (ET) and reactive thrombocytosis (RT). It is important to distinguish the two due to increased risk of developing marrow fibrosis, acute leukemia, and thrombosis in the former. Molecular studies are the main tools to differentiate the two but are not available in all hospitals. We aimed to design a highly sensitive scoring system using routine lab data to classify thrombocytosis as essential or reactive. A total of 145 patients were enrolled in this study. Potential predictors included patient demographics and clinical laboratory parameters. Receiver operating characteristic curve analysis was used to decide the optimal cutoff level. Multivariate logistic regression with forward model selection method was performed to decide the predictors. The risk scores by multivariate analysis were as follows: 1 point for WBC > 13,500/μL; 2.5 points for Hb > 10.9 g/dL; 3 points for platelet count > 659,000/μL; and 2 points for MPV > 9.3 fL. The cut off value was set as 4.5 points, and sensitivity of 91.1% and specificity of 75.8% were noted. In this study, we investigated lab data and developed a high-sensitivity convenient-to-use scoring system to differentiate ET from RT. The scoring system was assigned to the resulting model to make it more economical, simple, and convenient for clinical practice.
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http://dx.doi.org/10.3389/fmed.2021.736150 | DOI Listing |
Alzheimers Dement
September 2025
Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea.
Introduction: We developed and validated age-related amyloid beta (Aβ) positron emission tomography (PET) trajectories using a statistical model in cognitively unimpaired (CU) individuals.
Methods: We analyzed 849 CU Korean and 521 CU non-Hispanic White (NHW) participants after propensity score matching. Aβ PET trajectories were modeled using the generalized additive model for location, scale, and shape (GAMLSS) based on baseline data and validated with longitudinal data.
Front Rehabil Sci
August 2025
Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Introduction: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.
Methods: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes.
Alzheimers Dement (Amst)
September 2025
Introduction: Simple screening tools are critical for assessing Alzheimer's disease (AD)-related pre-dementia changes. This study investigated longitudinal scores from the Quick Dementia Rating System (QDRS), a brief study partner-reported measure, in relation to baseline levels of the AD biomarker plasma pTau217 in individuals unimpaired at baseline.
Methods: Data from the Wisconsin Registry for Alzheimer's Prevention (N = 639) were used to examine whether baseline plasma pTau217 (ALZpath assay on Quanterix platform) modified QDRS or Preclinical Alzheimer's Cognitive Composite (PACC3) trajectories (mixed-effects models; time = age).
Front Immunol
September 2025
Department of Medicine, Division of Hematology, Bioclinicum and Center for Molecular Medicine, Karolinska Institute and Karolinska University Hospital Solna, Stockholm, Sweden.
Background: Metabolic reprogramming is an important hallmark of cervical cancer (CC), and extensive studies have provided important information for translational and clinical oncology. Here we sought to determine metabolic association with molecular aberrations, telomere maintenance and outcomes in CC.
Methods: RNA sequencing data from TCGA cohort of CC was analyzed for their metabolic gene expression profile and consensus clustering was then performed to classify tumors into different groups/subtypes.
Nat Sci Sleep
September 2025
Department of Geriatrics, Tianjin Medical University General Hospital; Tianjin Key Laboratory of Elderly Health; Tianjin Geriatrics Institute, Tianjin, People's Republic of China.
Background: Sleep and frailty are established influencing factors for cardiometabolic diseases (CMDs). However, their joint effects on cardiometabolic multimorbidity (CMM) in older adults remain poorly understood. This study aimed to assess the joint effect of sleep health and frailty on CMD prevalence and severity, with an emphasis on subgroup-specific health risk profiles.
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