Background
The risk of death in sepsis patients with acute respiratory distress syndrome (ARDS) was as high as 20–50%. Few studies focused on the risk identification of ARDS among sepsis patients. This study aimed to develop and validate a nomogram to predict the ARDS risk in sepsis patients based on the Medical Information Mart for Intensive Care IV database.
Methods
A total of 16,523 sepsis patients were included and randomly divided into the training and testing sets with a ratio of 7:3 in this retrospective cohort study. The outcomes were defined as the occurrence of ARDS for ICU patients with sepsis. Univariate and multivariate logistic regression analyses were used in the training set to identify the factors that were associated with ARDS risk, which were adopted to establish the nomogram. The receiver operating characteristic and calibration curves were used to assess the predictive performance of nomogram.
Results
Totally 2422 (20.66%) sepsis patients occurred ARDS, with the median follow-up time of 8.47 (5.20, 16.20) days. The results found that body mass index, respiratory rate, urine output, partial pressure of carbon dioxide, blood urea nitrogen, vasopressin, continuous renal replacement therapy, ventilation status, chronic pulmonary disease, malignant cancer, liver disease, septic shock and pancreatitis might be predictors. The area under the curve of developed model were 0.811 (95% CI 0.802–0.820) in the training set and 0.812 (95% CI 0.798–0.826) in the testing set. The calibration curve showed a good concordance between the predicted and observed ARDS among sepsis patients.
Conclusion
We developed a model incorporating thirteen clinical features to predict the ARDS risk in patients with sepsis. The model showed a good predictive ability by internal validation.
Heart failure (HF) is a rising global cardiovascular epidemic driven by aging and chronic inflammation. As elderly populations continue to increase, precision treatments for age-related cardiac decline are urgently needed. Here we report that cardiac and blood expression of IGFBP7 is robustly increased in patients with chronic HF and in an HF mouse model. In a pressure overload mouse HF model, Igfbp7 deficiency attenuated cardiac dysfunction by reducing cardiac inflammatory injury, tissue fibrosis and cellular senescence. IGFBP7 promoted cardiac senescence by stimulating IGF-1R/IRS/AKT-dependent suppression of FOXO3a, preventing DNA repair and reactive oxygen species (ROS) detoxification, thereby accelerating the progression of HF. In vivo, AAV9-shRNA-mediated cardiac myocyte Igfbp7 knockdown indicated that myocardial IGFBP7 directly regulates pathological cardiac remodeling. Moreover, antibody-mediated IGFBP7 neutralization in vivo reversed IGFBP7-induced suppression of FOXO3a, restored DNA repair and ROS detoxification signals and attenuated pressure-overload-induced HF in mice. Consequently, selectively targeting IGFBP7-regulated senescence pathways may have broad therapeutic potential for HF.
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