Objectives: The annual growth in the population of maintenance hemodialysis (MHD) patients is accompanied by a trend towards younger age groups among new cases. Despite the escalating mortality risk observed in MHD patients, there remains a dearth of research focused on young and middle-aged individuals in this cohort, leading to a deficiency in specialized predictive instruments for this demographic. This research seeks to explore the critical determinants impacting mortality risk in young and middle-aged MHD patients and to construct a prediction model accordingly.
Methods: This study involved 127 young and middle-aged patients undergoing MHD in the Blood Purification Center of Chaohu Hospital of Anhui Medical University from January 2019 to January 2022. The follow-up period for each patient ended either at the time of death or on January 31, 2024. Participants were monitored to determine their survival status and categorized into two groups: those who survived (98 patients) and those who deceased (29 patients). Clinical data were gathered for analysis. Logistic regression was utilized to pinpoint independent risk factors for mortality among these patients. Subsequently, a nomogram was established to predict mortality risk. The efficacy of this model was assessed through the area under the receiver operating characteristic curve (AUC-ROC), alongside a calibration curve and the Hosmer-Lemeshow test to examine its fit. Additionally, decision curve analysis (DCA) was conducted to ascertain the clinical relevance of the predictive model.
Results: The study incorporated 127 young and middle-aged patients undergoing MHD, with a mortality rate recorded at 22.83% (29 cases). A logistic regression analysis revealed that age, hemoglobin (HB), serum magnesium (Mg), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-albumin ratio (PAR) were significant independent predictors of mortality among these patients. Utilizing these variables, a nomogram was developed to predict mortality risk, achieving an AUC of 0.899 (95% CI: 0.833-0.966). The model exhibited a specificity of 83.67% and a sensitivity of 82.76%, demonstrating substantial discriminative ability. The model's robustness was confirmed through internal validation with 1,000 bootstrap samples, yielding an AUC of 0.894 (95% CI: 0.806-0.949). The calibration curve closely aligned with the ideal curve, and the Hosmer-Lemeshow goodness-of-fit test yielded a value of 6.312 with a -value of 0.612, verifying the model's high calibration accuracy. Additionally, the DCA indicated that the model provides a net benefit across a wide range of decision thresholds from 0 to 0.99, underscoring its clinical utility.
Conclusion: The nomogram developed from variables including age, HB levels, serum Mg, NLR, and PAR exhibits high levels of discrimination and calibration. This model effectively predicts mortality risk among young and middle-aged patients undergoing MHD, proving its clinical relevance.
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http://dx.doi.org/10.3389/fmed.2024.1508485 | DOI Listing |
BJU Int
January 2025
Faculty of Social Sciences (Health Sciences), Prostate Cancer Research Center, Tampere University, Tampere, Finland.
Objective: To assess the association between prostate-specific antigen (PSA) density (PSAD) and prostate cancer mortality after a benign result on systematic transrectal ultrasonography (TRUS)-guided prostate biopsy.
Patients And Methods: This retrospective study used data from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC) collected between 1996 and 2020. We identified men aged 55-71 years randomised to the screening arm with PSA ≥4.
Thorac Cancer
January 2025
Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background: Tracheal, bronchial, and lung cancers (TBL cancers) pose a significant global health challenge, with rising incidence and mortality rates, particularly in China. Studies from the Global Burden of Disease (GBD), 2021, can guide screening and prevention strategies for TBL cancer. This study aims to provide a comprehensive analysis of the burden of TBL cancers in China compared to global data.
View Article and Find Full Text PDFAngiology
January 2025
Department of Internal Medicine, Texas Tech University Health Science Center, El Paso, TX, USA.
Breast cancer is the most common malignancy among women. While advances in detection and treatment have improved survival, breast cancer survivors face an increased risk of cardiovascular disease. However, limited data exist on cardiac outcomes after ST-elevation myocardial infarction (STEMI) in this population.
View Article and Find Full Text PDFCirc Cardiovasc Interv
January 2025
Department of Cardiology, Radboud University Medical Center, Nijmegen, the Netherlands (R.H.J.A.V., J.-Q.M., N.v.R.).
Background: Despite fractional flow reserve (FFR)-guided deferral of revascularization, recurrent events in patients with diabetes or after myocardial infarction remain common. This study aimed to assess the association between FFR-negative but high-risk nonculprit lesions and clinical outcomes.
Methods: This is a patient-level pooled analysis of the prospective natural-history COMBINE (OCT-FFR) study (Optical Coherence Tomography Morphologic and Fractional Flow Reserve Assessment in Diabetes Mellitus Patients) and PECTUS-obs study (Identification of Risk Factors for Acute Coronary Events by OCT After STEMI and NSTEMI Patients With Residual Non- Flow Limiting Lesions).
Infect Drug Resist
January 2025
Department of Thoracic Surgery, The Second People's Hospital of Liaocheng, Linqing, Shandong, 252600, People's Republic of China.
Objective: This study aimed to investigate the levels of coagulation parameters in elderly patients with severe pneumonia and analyse their correlation with disease severity and prognosis.
Methods: A retrospective study was conducted on 207 elderly patients (aged ≥60 years) with severe pneumonia admitted to our hospital between January 2022 and December 2023. Demographic data, clinical characteristics and coagulation parameters, including prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time and fibrinogen (FIB), were collected.
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