Driving pressure association with mortality in post-lung transplant patients: A prospective observational study.

OBJECTIVE: To investigate the association between driving pressure (ΔP) and 90-day mortality in patients following lung transplantation (LTx) in patients who developed primary graft dysfunction (PGD). METHODS: This prospective, observational study involved consecutive patients who, following LTx, were admitted to our intensive care unit (ICU) from January 2022 to January 2023. Patients were separated into two groups according to ΔP at time of admission (i.e., low, ≤15 cmH2O or high, >15 cmH2O). Postoperative outcomes were compared between groups. RESULTS: In total, 104 patients were involved in the study, and of these, 69 were included in the low ΔP group and 35 in the high ΔP group. Kaplan-Meier analysis of 90-day mortality showed a statistically significant difference between groups with survival better in the low ΔP group compared with the high ΔP group. According to Cox proportional regression model, the variables independently associated with 90-day mortality were ΔP and pneumonia. Significantly more patients in the high ΔP group than the low ΔP group had PGD grade 3 (PGD3), pneumonia, required tracheostomy, and had prolonged postoperative extracorporeal membrane oxygenation (ECMO) time, postoperative ventilator time, and ICU stay. CONCLUSIONS: Driving pressure appears to have the ability to predict PGD3 and 90-day mortality of patients following LTx. Further studies are required to confirm our results.

Association between waist triglyceride index, body mass index, dietary inflammatory index, and triglyceride- glucose index with chronic kidney disease: the 1999-2018 cohort study from NHANES.

Purpose: To compare the dietary inflammatory index (DII), triglyceride glucose index (TyG), waist triglyceride index (WTI), and body mass index (BMI) in predicting the survival of chronic kidney disease (CKD). Methodology: Inclusion of 23,099 participants from the NHANES database who met specific criteria. Baseline was established using quartiles of DII index. The relationship between DII index, WTI index, TyG index, and BMI index with mortality rate in CKD patients was evaluated using Kaplan-Meier curves. Univariate and multivariate COX regression risk models were used to study the relationship between DII index, WTI index, and TyG index with mortality risk in CKD patients. Stratification of eGFR by age and gender was conducted to investigate the association between DII index, WTI index, and TyG index with mortality risk in CKD patients. Restricted cubic spline analysis was used to study the correlation between DII index, WTI index, and TyG index with mortality risk in CKD patients. Results: The incidence of CKD increased with the increase of DII index, WTI index and TyG index. After multivariable adjustment, the fourth quartile of DII index, TyG index and WTI index showed the highest risk for CKD [DII: hazard ratio (HR) 1.36, 95% confidential interval (CI) (1.23-1.51); TyG: HR 1.21; 95% CI (1.07-1.37); WTI: HR 1.29; 95% CI (1.13-1.46)]. There was no difference in the risk of developing CKD between the obese group (BMI ≥24 kg/m2) and the normal weight group (P>0.05). Conclusion: This study has identified a significant association between elevated DII index, WTI index, and TyG index with the risk of CKD. Furthermore, the DII index demonstrated superior prognostic capability in predicting CKD compared to other indicators.

A novel nomogram for predicting prolonged mechanical ventilation in lung transplantation patients using extracorporeal membrane oxygenation.

Prolonged mechanical ventilation (PMV) is commonly associated with increased post-operative complications and mortality. Nevertheless, the predictive factors of PMV after lung transplantation (LTx) using extracorporeal membrane oxygenation (ECMO) as a bridge remain unclear. The present study aimed to develop a novel nomogram for PMV prediction in patients using ECMO as a bridge to LTx. A total of 173 patients who used ECMO as a bridge following LTx from January 2022 to June 2023 were divided into the training (122) and validation sets (52). A mechanical ventilation density plot of patients after LTx was then performed. The training set was divided in two groups, namely PMV (95) and non-prolonged ventilation (NPMV) (27). For the survival analysis, the effect of PMV was assessed using the log-rank test. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was established based on the multivariate analysis, and model performance was further assessed in terms of calibration, discrimination, and clinical usefulness. Internal validation was additionally conducted. The difference in survival curves in PMV and NPMV groups was statistically significant (P < 0.001). The multivariate analysis and risk factors in the nomogram revealed four factors to be significantly associated with PMV, namely the body mass index (BMI), operation time, lactic acid at T0 (Lac), and driving pressure (DP) at T0. These four factors were used to develop a nomogram, with an area under the curve (AUC) of 0.852 and good calibration. After internal validation, AUC was 0.789 with good calibration. Furthermore, goodness-of-fit test and decision-curve analysis (DCA) indicated satisfactory performance in the training and internal validation sets. The proposed nomogram can reliably and accurately predict the risk of patients to develop PMV after LTx using ECMO as a bridge. Four modifiable factors including BMI, operation time, Lac, and DP were optimized, which may guide preventative measures and improve prognosis.