Background: Postoperative delirium (POD) is an acute brain dysfunction that is frequently observed in patients undergoing cardiac surgery. Increasing evidence indicates POD is related to higher mortality among cardiac surgical patients, but the results remain controversial. Moreover, a quantitative evaluation of the influence of POD on hospital days, intensive care unit (ICU) time, and mechanical ventilation (MV) time has not been performed.Objective: This study aimed to evaluate the correlation between POD and outcomes in patients undergoing cardiac surgery by a systematic review and meta-analysis.Materials and methods: A total of 7 electronic databases (Cochrane Library, PubMed, EMBASE, CINAHL Complete, MEDLINE, Wan-fang database, and China National Knowledge Infrastructure) were searched from January 1980 to July 20, 2021, with language restrictions to English and Chinese, to estimate the impact of the POD on outcome in patients who underwent cardiac surgery. The meta-analysis was registered with PROSPERO (Registration: CRD42021228767).Results: Forty-two eligible studies with 19785 patients were identified. 3368 (17.0%) patients were in the delirium group and 16417 (83%) were in the non-delirium group. The meta-analysis showed that compared to patients without POD, patients with POD had 2.77-fold higher mortality (OR = 2.77, 95% CI 1.86–4.11, P < 0.001), 5.70-fold higher MV (>24h) rate (OR = 5.70, 95% CI 2.93–11.09, P < 0.001); and longer MV time (SMD = 0.83, 95% CI 0.57–1.09, P < 0.001), ICU time (SMD = 0.91, 95% CI 0.60–1.22, P < 0.001), hospital days (SMD = 0.62, 95% CI 0.48–0.76, P < 0.001).Conclusion: The synthesized evidence suggests that POD is causally related to the increased risk of mortality, prolonged length of ICU and hospital stay, and a longer duration of MV time. Future research should focus on the interventions for POD, to reduce the incidence.Systematic review registration: [www.crd.york.ac.uk/PROSPERO], identifier [CRD42021228767].

Hypertension is a major public health issue worldwide. The imbalance of gut microbiota is thought to play an important role in the pathogenesis of hypertension. The authors conducted the systematic review and meta‐analysis to clarify the relationship between gut microbiota and hypertension through conducting an electronic search in six databases. Our meta‐analysis included 19 studies and the results showed that compared with healthy controls, Shannon significantly decreased in hypertension [SMD = −0.13, 95%CI (−0.22, −0.04), p = .007]; however, Simpson [SMD = −0.01, 95%CI (−0.14, 0.12), p = .87], ACE [SMD = 0.18, 95%CI (−0.06, 0.43), p = .14], and Chao1 [SMD = 0.11, 95%CI (−0.01, 0.23), p = .08] did not differ significantly between hypertension and healthy controls. The F/B ratio significantly increased in hypertension [SMD = 0.84, 95%CI (0.10, 1.58), p = .03]. In addition, Shannon index was negatively correlated with hypertension [r = −0.12, 95%CI (−0.19, −0.05)], but had no significant correlation with SBP [r = 0.10, 95%CI (−0.19, 0.37)] and DBP [r = −0.39, 95%CI (−0.73, 0.12)]. At the phylum level, the relative abundance of Firmicutes [SMD = −0.01, 95%CI (−0.37, 0.34), p = .94], Bacteroidetes [SMD = −0.15, 95%CI (−0.44, 0.14), p = .30], Proteobacteria [SMD = 0.25, 95%CI (−0.01, 0.51), p = .06], and Actinobacteria [SMD = 0.21, 95%CI (−0.11, 0.53), p = .21] did not differ significantly between hypertension and healthy controls. At the genus level, compared with healthy controls, the relative abundance of Faecalibacterium decreased significantly [SMD = −0.16, 95%CI (−0.28, −0.04), p = .01], while the Streptococcus [SMD = 0.20, 95%CI (0.08, 0.32), p = .001] and Enterococcus [SMD = 0.20, 95%CI (0.08, 0.33), p = .002] significantly increased in hypertension. Available evidence suggests that hypertensive patients may have an imbalance of gut microbiota. However, it still needs further validation by large sample size studies of high quality.

Purpose: The Aggregate Index of Systemic Inflammation (AISI) has emerged as a novel marker for inflammation and prognosis, but its role in patients with acute myocardial infarction has not been studied. Therefore, this study aimed to investigate the impact of different AISI levels on the clinical outcomes of patients with acute myocardial infarction. Patients and Methods: This study was a retrospective study, including 1044 patients with acute myocardial infarction (AMI) who were treated at the Fujian Medical University Affiliated Union Hospital, China from May 2017 to December 2022. The patients were divided into high and low AISI groups based on the median value (Q1 Group, ≤ 416.15, n=522; Q2 Group, ≥ 416.16, n=522), and the differences in baseline characteristics and clinical outcomes between the two groups were analyzed. The primary outcome included major adverse cardiovascular and cerebrovascular events (MACCEs), while the secondary outcomes included contrast-induced nephropathy (CIN) risk and all-cause rehospitalization rate. Results: The findings of the single-factor analysis suggest that a significant association between high AISI levels and the occurrence of MACCEs in AMI patients. After adjusting for confounding factors, the results indicated that compared to Q1, patients in the Q2 group had a higher risk of all-cause mortality [adjusted odds ratio (aOR) 4.64; 95% CI 1.37– 15.72; p=0.032], new-onset atrial fibrillation (aOR 1.75; 95% CI 1.02– 3.00; p=0.047), and CIN (aOR 1.75; 95% CI 1.02– 3.01; p=0.043), with all differences being statistically significant. Conclusion: In the population of AMI patients, an elevated AISI level is significantly associated with an increased risk of cardiovascular death and can serve as an early marker for adverse prognosis.

Background: Blood glucose variability is associated with poor prognosis after cardiac surgery, but the relationship between glucose variability and postoperative delirium in patients with acute aortic dissection is unclear. The study aims to investigate the association of blood glucose variability with postoperative delirium in acute aortic dissection patients. Methods: We prospectively analyzed 257 patients including 103 patients with delirium. The patients were divided into two groups according to whether delirium was present. The outcome measures were postoperative delirium, the length of the Intensive Care Unit stay, and the duration of hospital stay. Multivariable Cox competing risk survival models was used to assess. Results: A total of 257 subjects were enrolled, including 103 patients with delirium. There were statistically significant differences between the two groups in body mass index, history of cardiac surgery, first admission blood glucose, white blood cell counts, Acute Physiology and Chronic Health Evaluation II score, hypoxemia, mechanical ventilation duration, and the length of Intensive Care Unit stay(P < 0.05). The delirium group exhibited significantly higher values of the mean of blood glucose (MBG) and the standard deviation of blood glucose (SDBG) than in the non-delirium group(P < 0.05). In model 1, the adjusted hazard ratio (AHR) of the standard deviation of blood glucose was 1.436(P < 0.05). In Model 2, the standard deviation of blood glucose (AHR = 1.418, 95%CI = 1.195–1.681, P < 0.05) remained significant after adjusting for confounders. The area under the curve of the SDBG was 0.763(95%CI = 0.704–0.821, P < 0.01). The sensitivity was 81.6%, and the specificity was 57.8%. Conclusions: Glucose variability is associated with the risk of delirium in patients after aortic dissection surgery, and high glycemic variability increases the risk of postoperative delirium.

Markers of prothrombotic state and inflammation are associated with the prognosis of patients with acute type A aortic dissection (AAAD). However, it is unclear that the relationship between these biomarkers and their combined impact on risk stratification. The present study evaluated the prognostic value of platelet counts, lymphocyte to neutrophil ratio (LNR), and lymphocyte to monocyte ratio (LMR), alone and in combination. A retrospective analysis of clinical data of 744 AAAD patients was conducted to identify whether these biomarkers were related to the 30‐day mortality risk. A Kaplan‐Meier analysis and log‐rank test were used to compare survival between groups. A Cox hazard regression multivariable analysis was performed for 30‐day mortality. Individual biomarker (platelet count, LNR, or LMR) was unable to predict 30‐day mortality. However, combinations of all three biomarkers provided additive predictive value over either marker alone, the receiver operating characteristic (ROC) model had a prediction probability of 0.739 when platelet counts, LNR, and LMR were included. Cox hazard regression multivariable analysis showed that combinations of all three biomarkers were the strongest predictor of 30‐day mortality (p < 0.021). Combined with these three easily measurable biomarkers at admission, they could help identify AAAD patients with a high risk of 30‐day mortality.