Clinical nomogram prediction model to assess the risk of prolonged ICU length of stay in patients with diabetic ketoacidosis: a retrospective analysis based on the MIMIC-IV database.

BACKGROUND: The duration of hospitalization, especially in the intensive care unit (ICU), for patients with diabetic ketoacidosis (DKA) is influenced by patient prognosis and treatment costs. Reducing ICU length of stay (LOS) in patients with DKA is crucial for optimising healthcare resources utilization. This study aimed to establish a nomogram prediction model to identify the risk factors influencing prolonged LOS in ICU-managed patients with DKA, which will serve as a basis for clinical treatment, healthcare safety, and quality management research. METHODS: In this single-centre retrospective cohort study, we performed a retrospective analysis using relevant data extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Clinical data from 669 patients with DKA requiring ICU treatment were included. Variables were selected using the Least Absolute Shrinkage and Selection Operator (LASSO) binary logistic regression model. Subsequently, the selected variables were subjected to a multifactorial logistic regression analysis to determine independent risk factors for prolonged ICU LOS in patients with DKA. A nomogram prediction model was constructed based on the identified predictors. The multivariate variables included in this nomogram prediction model were the Oxford acute severity of illness score (OASIS), Glasgow coma scale (GCS), acute kidney injury (AKI) stage, vasoactive agents, and myocardial infarction. RESULTS: The prediction model had a high predictive efficacy, with an area under the curve value of 0.870 (95% confidence interval [CI], 0.831-0.908) in the training cohort and 0.858 (95% CI, 0.799-0.916) in the validation cohort. A highly accurate predictive model was depicted in both cohorts using the Hosmer-Lemeshow (H-L) test and calibration plots. CONCLUSION: The nomogram prediction model proposed in this study has a high clinical application value for predicting prolonged ICU LOS in patients with DKA. This model can help clinicians identify patients with DKA at risk of prolonged ICU LOS, thereby enhancing prompt intervention and improving prognosis.

The paradox of obesity in pressure ulcers of critically ill patients.

The relationship between body mass index and pressure ulcers in critically ill patients is controversial. We aimed to investigate the association between body mass index and pressure ulcers by analysing data from the Medical Information Mart for Intensive Care IV (version 2.0) database. Eligible data (21 835 cases) were extracted from the database (2008-2019). The association between body mass index and pressure ulcers in critically ill patients was investigated by adjusting multivariate trend analysis, restricted cubic spline analysis, and segmented linear models. Subgroup analyses and sensitivity analyses were used to ensure the stability of the results. Trend analysis and restricted cubic spline analysis showed an approximate U-shaped correlation between body mass index and the occurrence of pressure ulcers in critically ill patients, with the risk of pressure ulcers decreasing rapidly with increasing body mass index (8.6% decrease per unit) after adjusting for relevant factors; the trend reached its minimum at a body mass index of 27.5 kg/m2, followed by a slow increase in the risk of pressure ulcers with increasing body mass index (1.4% increase per unit). Among the subgroups, the highest overall risk of pressure ulcers and the risk of severe pressure ulcers were significantly higher in the underweight group than in the other subgroups, and the risk associated with the overweight group was the lowest. There is a U-shaped association between body mass index and pressure ulcers in critically ill patients, and being underweight and obese both increase the risk of pressure ulcers. The risk is highest among underweight patients and lowest among overweight patients (but not patients of normal weight), necessitating targeted prevention strategies for critically ill patients with different body mass indexes.

Utility of Serum Growth Arrest-Specific Protein 6 as a Biomarker of Severity and Prognosis After Severe Traumatic Brain Injury: A Prospective Observational Study.

Objective: Growth arrest-specific protein 6 (Gas6) may harbor protective effects in acute brain injury. This study was designed to determine the relation of serum Gas6 levels to severity and prognosis after traumatic brain injury (TBI). Methods: In this prospective cohort study of 114 controls and 114 patients with severe TBI, multivariate analysis was used to assess relationships between serum Gas6 levels, Glasgow coma scale (GCS) score, Rotterdam computed tomography (CT) score, postinjury 180-day mortality, overall survival and poor prognosis (Extended Glasgow outcome scale score 1-4). Results: Significantly increased serum Gas6 levels of patients (median, 10.3 ng/mL versus 32.5 ng/mL; P < 0.001), as compared with controls, were independently correlated with Rotterdam CT score (t = 3.629, P < 0.001) and GCS score (t=-3.393, P = 0.001), and independently predicted 180-day mortality (odds ratio, 1.078; 95% confidence interval (CI), 1.007-1.154), overall survival (hazard ratio, 1.074; 95% CI, 1.012-1.139) and poor prognosis (odds ratio, 1.129; 95% CI, 1.059-1.205). Areas under receiver operating characteristic curve (AUCs) of serum Gas6 levels for discriminating risks of 180-day mortality and poor prognosis were 0.785 (95% CI, 0.699-0.857) and 0.793 (95% CI, 0.707-0.863), respectively; and serum Gas6 levels above 30.9 ng/mL and 28.3 ng/mL predicted 180-day mortality and poor prognosis with maximum Youden indices of 0.451 and 0.468, respectively. The predictive ability of serum Gas6 levels for mortality was similar to those of GCS score (AUC, 0.833; 95% CI, 0.751-0.896; P = 0.286) and Rotterdam CT score (AUC, 0.823; 95% CI, 0.740-0.888; P = 0.432). The discriminatory capability of serum Gas6 levels for the risk of poor prognosis was in the range of GCS score (AUC, 0.846; 95% CI, 0.766-0.906; P = 0.178) and Rotterdam CT score (AUC, 0.831; 95% CI, 0.750-0.895; P = 0.368). Conclusion: Serum Gas6 may appear as a promising biochemical parameter for aiding in the assessment of trauma severity and prediction of prognosis among patients with severe TBI.

Evaluation of serum pannexin-1 as a prognostic biomarker for traumatic brain injury.

BACKGROUND: Pannexin-1 is a type of hexameric plasma membrane channel-forming proteins, and plays a significant role in brain injury. We investigated the potential prognostic value of pannexin-1 in traumatic brain injury. METHODS: A single peripheral blood sample in 112 patients with severe traumatic brain injury and 112 controls was prospectively collected for subsequent measurement of serum pannexin-1. Clinical follow-up was performed at 6 months. An unfavorable outcome was defined as Glasgow Outcome Scale score of 1-3. RESULTS: The patients showed markedly higher serum pannexin-1 concentrations than the controls. Among the patients, pannexin-1 concentrations were significantly and negatively correlated with Glasgow coma scale scores. On receiver operating characteristic curve analysis, the predictive value in terms of area under the curve was substantially high for serum pannexin-1 as a predictor for both 6-month mortality and unfavorable outcome. Regression analyses confirmed that there was an increased risk of either 6-month mortality, overall survival or unfavorable outcome associated with serum pannexin-1 concentrations after adjusting for possible confounders. CONCLUSIONS: Serum pannexin-1 may represent a potential prognostic biomarker for head trauma.