Prognostic value of oxygen saturation index trajectory phenotypes on ICU mortality in mechanically ventilated patients: a multi-database retrospective cohort study.

BACKGROUND: Heterogeneity among critically ill patients undergoing invasive mechanical ventilation (IMV) treatment could result in high mortality rates. Currently, there are no well-established indicators to help identify patients with a poor prognosis in advance, which limits physicians' ability to provide personalized treatment. This study aimed to investigate the association of oxygen saturation index (OSI) trajectory phenotypes with intensive care unit (ICU) mortality and ventilation-free days (VFDs) from a dynamic and longitudinal perspective. METHODS: A group-based trajectory model was used to identify the OSI-trajectory phenotypes. Associations between the OSI-trajectory phenotypes and ICU mortality were analyzed using doubly robust analyses. Then, a predictive model was constructed to distinguish patients with poor prognosis phenotypes. RESULTS: Four OSI-trajectory phenotypes were identified in 3378 patients: low-level stable, ascending, descending, and high-level stable. Patients with the high-level stable phenotype had the highest mortality and fewest VFDs. The doubly robust estimation, after adjusting for unbalanced covariates in a model using the XGBoost method for generating propensity scores, revealed that both high-level stable and ascending phenotypes were associated with higher mortality rates (odds ratio [OR]: 1.422, 95% confidence interval [CI] 1.246-1.623; OR: 1.097, 95% CI 1.027-1.172, respectively), while the descending phenotype showed similar ICU mortality rates to the low-level stable phenotype (odds ratio [OR] 0.986, 95% confidence interval [CI] 0.940-1.035). The predictive model could help identify patients with ascending or high-level stable phenotypes at an early stage (area under the curve [AUC] in the training dataset: 0.851 [0.827-0.875]; AUC in the validation dataset: 0.743 [0.709-0.777]). CONCLUSIONS: Dynamic OSI-trajectory phenotypes were closely related to the mortality of ICU patients requiring IMV treatment and might be a useful prognostic indicator in critically ill patients.

Polydatin alleviates bleomycin-induced pulmonary fibrosis and alters the gut microbiota in a mouse model.

To investigate the effect and mechanism of polydatin on bleomycin (BLM)-induced pulmonary fibrosis in a mouse model. The lung fibrosis model was induced by BLM. The contents of TNF-α, LPS, IL-6 and IL-1ß in lung tissue, intestine and serum were detected by ELISA. Gut microbiota diversity was detected by 16S rDNA sequencing; R language was used to analyse species composition, α-diversity, ß-diversity, species differences and marker species. Mice were fed drinking water mixed with four antibiotics (ampicillin, neomycin, metronidazole, vancomycin; antibiotics, ABx) to build a mouse model of ABx-induced bacterial depletion; and faecal microbiota from different groups were transplanted into BLM-treated or untreated ABx mice. The histopathological changes and collagen I and α-SMA expression were determined. Polydatin effectively reduced the degree of fibrosis in a BLM-induced pulmonary fibrosis mouse model; BLM and/or polydatin affected the abundance of the dominant gut microbiota in mice. Moreover, faecal microbiota transplantation (FMT) from polydatin-treated BLM mice effectively alleviated lung fibrosis in BLM-treated ABx mice compared with FMT from BLM mice. Polydatin can reduce fibrosis and inflammation in a BLM-induced mouse pulmonary fibrosis model. The alteration of gut microbiota by polydatin may be involved in the therapeutic effect.

Association Between Serum Sodium and Long-Term Mortality in Critically Ill Patients with Comorbid Chronic Obstructive Pulmonary Disease: Analysis from the MIMIC-IV Database.

Purpose: The purpose of our study was to investigate the relationship between serum sodium levels and 1-year and 3-year mortality in critically ill patients with comorbid chronic obstructive pulmonary disease using real-world data. Methods: The data of this study were collected from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. First of all, we used the Kaplan-Meier curves and multivariable Cox regression analyses to measure the relationship between serum sodium levels and 1-year and 3-year mortality for critically ill patients with comorbid COPD. Next, a restricted cubic spline was used to analyze non-parametrically the relationship between mortality and serum sodium as a continuous variable. In addition, we also analyzed the mortality of different subgroups. Results: A total of 5540 eligible subjects were extracted. Compared to normal serum sodium levels, adjusted multivariable Cox regression analysis confirmed that hyponatremia and hypernatremia were still significantly associated with 1-year mortality (HR = 1.551, 95% CI = 1.333~1.805, P<0.001; HR = 1.683, 95% CI = 1.317~2.151, P<0.001, respectively) and 3-year mortality (HR = 1.507, 95% CI = 1.302~1.744, P<0.001; HR = 1.612, 95% CI = 1.269~2.048, P<0.001, respectively). In patients with or without adjustment variables, there was an obvious U-shaped non-linear relationship between serum sodium levels and 1-year and 3-year mortality with a reference level of 139 mmol/L, which indicated that patients in both hyponatremia and hypernatremia had higher mortality than normal serum sodium levels. Conclusion: This study showed that both hyponatremia and hypernatremia were related to increased 1-year and 3-year mortality in critically ill patients with comorbid COPD, which provides a new reference for the control strategy of correcting serum sodium levels.

The relationship of the geriatric nutritional risk index to mortality and length of stay in elderly patients with acute respiratory failure: A retrospective cohort study.

BACKGROUND: Elderly people with acute respiratory failure (ARF) have prolonged length of hospital stay (LOS) and high mortality rates. Malnutrition is negatively correlated with these LOS and mortality. However, no tools have been used to detect the risk of malnutrition and assist in designing nutritional support for these patients. The geriatric nutritional risk index (GNRI) is reported as a novel tool for evaluating the risk of malnutrition. The aim of this study is to explore the relationship of the GNRI score with mortality and LOS in elderly patients with ARF. METHODS: Data of elderly patients diagnosed with ARF were retrieved from the Medical Information Mart for Intensive Care III (MIMIC-III) database. A total of 1250 patients were divided into two groups based on their GNRI score: the malnutrition risk group (GNRI ≤ 98) and no risk group (GNRI > 98). The primary endpoints of this study were hospital mortality and hospital LOS. RESULTS: The higher GNRI score was associated with lower hospital mortality and shorter hospital LOS. Odds ratio (OR) for hospital mortality of patients with nutritional risk (GNRI ≤ 98) was 1.264 (95% CI:1.067-1.497) in the adjusted model. Patients with GNRI ≤98 had longer hospital LOS (adjusted OR: 1.142, 95%CI: 1.044-1.250) compared with those with GNRI > 98. Subgroup analysis showed that higher GNRI was only significantly associated with lower hospital mortality in the patients that did not undergo mechanical ventilator (MV) treatment (adjusted OR: 0.985, 95% CI: 0.977-0.992, P < 0.01). Kaplan-Meier curve analysis showed that the 90-day survival was significantly lower in the group with nutrition risk (GNRI≤98) compared with the no risk group (GNRI > 98, p < 0.05). CONCLUSION: These findings imply that GNRI is a useful prognostic tool in elderly patients with ARF.