Assessment of Nutritional Risk Scores (the Nutritional Risk Screening 2002 and Modified Nutrition Risk in Critically Ill Scores) as Predictors of Mortality in Critically Ill Patients on Extracorporeal Membrane Oxygenation.

Nutritional risk is associated with intensive care unit (ICU) stay and mortality, the Nutritional Risk Screening 2002 (NRS 2002) and the modified Nutritional Risk in the Critically Ill (mNUTRIC) score are assessment instruments and useful in predicting the risk regarding mortality in ICU patients. Our aim was to assess the effects of mNUTRIC and NRS 2002 on mortality in patients on extracorporeal membrane oxygenation (ECMO). A retrospective cohort study was performed and 78 patients were included for final analysis. In the current study, the NRS 2002 and the mNUTRIC score within 24 hours before starting ECMO were applied to assess patients' nutritional status on ECMO and explore the relationship between nutritional status and patient outcomes. This study suggests that both mNUTRIC and NRS 2002 scores were found to be significant independent risk and prognostic factors for in-hospital and 90 day morality among ECMO patients based on multivariable logistic regression analysis ( p < 0.05), with those in the high-risk group having higher in-hospital and 90 day mortality rates than those identified as being at low risk ( p < 0.001). In comparison to the NRS 2002 score, the mNUTRIC score demonstrated a superior prognostic ability in ECMO patients.

Development of a nomogram for predicting 90-day mortality in patients with sepsis-associated liver injury.

The high mortality rate in sepsis patients is related to sepsis-associated liver injury (SALI). We sought to develop an accurate forecasting nomogram to estimate individual 90-day mortality in SALI patients. Data from 34,329 patients were extracted from the public Medical Information Mart for Intensive Care (MIMIC-IV) database. SALI was defined by total bilirubin (TBIL) > 2 mg/dL and the occurrence of an international normalized ratio (INR) > 1.5 in the presence of sepsis. Logistic regression analysis was performed to establish a prediction model called the nomogram based on the training set (n = 727), which was subsequently subjected to internal validation. Multivariate logistic regression analysis showed that SALI was an independent risk factor for mortality in patients with sepsis. The Kaplan‒Meier curves for 90-day survival were different between the SALI and non-SALI groups after propensity score matching (PSM) (log rank: P < 0.001 versus P = 0.038), regardless of PSM balance. The nomogram demonstrated better discrimination than the sequential organ failure assessment (SOFA) score, logistic organ dysfunction system (LODS) score, simplified acute physiology II (SAPS II) score, and Albumin-Bilirubin (ALBI) score in the training and validation sets, with areas under the receiver operating characteristic curve (AUROC) of 0.778 (95% CI 0.730-0.799, P < 0.001) and 0.804 (95% CI 0.713-0.820, P < 0.001), respectively. The calibration plot showed that the nomogram was sufficiently successful to predict the probability of 90-day mortality in both groups. The DCA of the nomogram demonstrated a higher net benefit regarding clinical usefulness than SOFA, LODS, SAPSII, and ALBI scores in the two groups. The nomogram performs exceptionally well in predicting the 90-day mortality rate in SALI patients, which can be used to assess the prognosis of patients with SALI and may assist in guiding clinical practice to enhance patient outcomes.

Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients.

Objective: To investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model. Methods: A total of 105 patients with extracorporeal membrane oxygenation (ECMO) were admitted to the Department of Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, from January 2018 to March 2021. Cox regression analysis screened out the risk factors. Based on the results of multivariate analysis, the nomogram model was established by using R software, and the discrimination of the model was verified by bootstrap and calibration. Results: The results showed that sex, acute physiology and chronic health evaluation (APACHE) II score, disseminated intravascular coagulation (DIC) score before ECMO initiation and average daily dose of norepinephrine were independent risk factors for prognosis. Verify that the nomogram model is verified by bootstrap internally, and the corrected C-index is C-index: 0.886, showing a good degree of discrimination. The calibration curve (calibration) showed that the nomogram model had good agreement. The decision curve analysis(DCA) curve shows good clinical validity above the two extreme curves. Kaplan-Meier curves were drawn for patients in the tertile and compared with the first and second groups. The third group predicted the worst 30-day prognosis for ECMO patients. Conclusion: The nomogram prediction model constructed based on the sex, APACHE II and DIC score, average daily dose of norepinephrine can effectively screen out the factors affecting the prognosis and provide a reference for individualized treatment of ECMO patients.