Marital status independently predicts the overall survival in young adult patients with lymphoma: A population-based, propensity-matched study.

We predicted that marital status may have predictive effects on young adult patients with cancer. A total of 37,028 young adult patients (20-39 years old) newly diagnosed with lymphoma by positive histology between 1988 and 2015 were collected from the Surveillance, Epidemiology, and End Results database. Patients were separated into married and unmarried groups. Multivariate regression was utilized to explore the association between marital status and overall survival, and propensity score matching and an inverse probability of treatment weighting were applied to corroborate our results. Among 37,028 eligible lymphoma patients, 12,827 married patients, and 12,827 unmarried patients, had equal propensity scores and were eventually recruited in this research. Moreover, married patients reported enhanced 10-year overall survival in the original group and the matched cohort. The multivariable Cox regression analysis revealed a vital advantageous influence of married status on overall mortality, with an adjusted hazard ratio (HR) of 0.54 (95% CI, 0.51-0.57, P < .001) and the association remained robust after propensity score matching (HR, 0.53, 95% CI 0.51-0.55, P < .001) and inverse probability of treatment weighting (HR, 0.53, 95% CI 0.51-0.56, P < .001) after adjusting for confounding factors. Marital status had predictive significance for overall survival in young adult patients with lymphoma.

Preoperative Glucose-to-Lymphocyte Ratio is an Independent Predictor for Acute Kidney Injury After Cardiac Surgery in Patients in Intensive Care Unit.

BACKGROUND: We aimed to investigate the association between preoperative glucose-to-lymphocyte ratio (GLR) and cardiac surgery associated with acute kidney injury (CSA-AKI) in patients in the intensive care unit (ICU). METHODS: The Medical Information Mart for Intensive Care IV (MIMIC-IV version 1.0) database was used to identify adults' patients who performed cardiac surgery during ICU stay. The primary outcome was the development of AKI based on the KDIGO criteria. Multivariable logistic regression was applied to investigate the association between GLR and clinical outcomes, and propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were also used to validate our findings. RESULTS: The optimal cut-off value for GLR was 1.28. Among the 7181 patients who conducted cardiac surgery, 2072 high-GLR group (≥1.28) patients and 2072 low-GLR group (<1.28) patients, had similar propensity scores were included in this study. After matching, the high-GLR group had a significantly higher incidence of AKI (odds ratio, OR, 3.28, 95% confidence index, 95% CI, 2.81-3.84, P <0.001) even after adjustment for confounding factors. Moreover, the performance of GLR was superior to that of SOFA scores and GLR plus clinical model could add more net benefit for CSA-AKI than clinical model alone. CONCLUSION: Preoperative GLR could serve as a good predictor for CSA-AKI in patients in ICU.

Development and External Validation a Novel Inflammation-Based Score for Acute Kidney Injury and Prognosis in Intensive Care Unit Patients.

PURPOSE: We aimed to evaluate the predictive ability of an integrated score based on several inflammatory indices of acute kidney injury (AKI) in patients in the intensive care unit (ICU). PATIENTS AND METHODS: In this observational study, 2555 patients from the Medical Information Mart for Intensive Care III database were randomly assigned to the test set (n=1599) and internal validation set (n=656). Moreover, 412 coronary care unit patients from Zhongnan Hospital, Wuhan University were also included in the external validation set. The AKI-specific inflammatory index (ASII) was created using various inflammatory indices significantly associated with AKI. We further developed and validated two nomograms based on the ASII and other informative clinical features of AKI and prognosis. RESULTS: The ASII was calculated as 2.317×MLR+0.417×GPS+0.007×ALRI. In the training set, patients with a high ASII had a higher risk of incident AKI (odds ratio [OR], 5.33; 95% confidence index [CI], 3.60-7.88; P<0.001) than those with a low ASII with or without pre-existing chronic kidney disease. The nomograms for AKI and prognosis based on the ASII and other significant clinical characteristics had high predictive value in the prediction of AKI and prognosis in patients in the ICU. Moreover, the results in the internal validation set and in the external validation cohort were almost consistent with those in the training set. CONCLUSION: The ASII is an AKI-specific tool based on the combination of available inflammatory indices. A high ASII is a strong predictor of a higher risk of AKI and worse survival outcomes in patients in the ICU.