Heart rate is crucial for patients with septic shock, but there are few studies on the scope of heart rate. Therefore, we studied the relationship between different heart rates and mortality of critically ill patients with septic shock, and explored the optimal heart rate range, in order to provide new insights for clinical treatment of septic shock. This retrospective study utilized time-series heart rate data from the Medical Information Mart for Intensive Care (MIMIC) IV database. Patients with septic shock were identified as the Sepsis 3.0 criteria and received vasopressor therapy in the first 24 h since ICU admission. We calculated the time-weighted average heart rate (TWA-HR) based on the time-series data. The restricted cubic spline (RCS) analysis was employed to investigate the nonlinear relationship between heart rate and 28-day mortality, aiming to explore the optimal heart rate control target for septic patients and using this target as the exposure factor. The primary outcome was 28-day mortality, and the secondary outcome were ICU and in-hospital mortality. For the original cohort, we applied the log-rank test to infer the relationship between heart rate and mortality. To control for bias introduced by confounders, we utilized propensity score matching (PSM) to reduce imbalances between normal TWA-HR and high TWA-HR groups, and we established a series of models [the multivariable Cox model, matching weight (MW)-adjusted Cox model, multivariable logistic regression, MW-adjusted logistic regression, and doubly robust model] as sensitivity analyses and subgroup analyses to demonstrate the robustness of our findings. A total of 13492 patients were included in our study. The RCS analysis based on Cox and logistic regression showed increased risk of mortality (P < 0.001, non-linear P < 0.001) when TWA-HR > 85 beats per minute (bpm). The log-rank test revealed in terms of the 28-day mortality, the hazard ratio (HR) (95% confidence interval [CI]) was 1.92 (1.78—2.06, P < 0.001) for patients with high TWA-HR compared to normal TWA-HR group. Similarly, for the ICU mortality, the HR (95% CI) was 1.64 (1.52—1.78, P < 0.001), and for the in-hospital mortality, the HR (95% CI) was 1.61 (1.48—1.76, P < 0.001). Collectively, the sensitivity analysis consistently demonstrated higher 28-day mortality, ICU mortality, and in-hospital mortality in patients with TWA-HR > 85 bpm. Patients with septic shock whose heart rate was controlled no more than 85 bpm during ICU stay received survival benefit in terms of 28-day, ICU and in-hospital mortality.

The relationship between the dynamic changes in insulin resistance (IR) and the prognosis of septic patients remains unclear. This study aims to investigate the correlation between the clinical subphenotype of IR represented by the triglyceride-glucose (TyG) index trajectory and the mortality rate among patients with sepsis. In this retrospective cohort study, we utilized data from septic patients within the Medical Information Mart for Intensive Care (MIMIC)-IV database version 2.0 to construct trajectories of the TyG index over 72 h. Subsequently, we computed the similarity among various TyG index trajectories with the dynamic time warping (DTW) algorithm and utilized the hierarchical clustering (HC) algorithm to demarcate distinct cluster and identified subphenotypes according to the trajectory trend. Subsequently, we assessed the mortality risk between different subphenotypes using analyses such as survival analysis and validated the robustness of the results through propensity score matching (PSM) and various models. A total of 2350 patients were included in the study. Two trajectory trends: TyG index decreasing (n = 926) and TyG index increasing (n = 1424) were identified, which indicated corresponding to the clinical subphenotype of increased and alleviative IR respectively. The 28-day and in-hospital mortality for the increased IR group was 28.51% and 25.49% respectively. In comparison, patients in the alleviative IR group with a 28-day mortality of 23.54% and an in-hospital mortality of 21.60%. These subphenotypes exhibited distinct prognosis, time dependent Cox model showed the increased IR group with a higher 28-day mortality [hazard ratio (HR): 1.07, 95% confidence interval (CI): 1.02–1.12, P = 0.01] and in-hospital mortality [HR: 1.05, 95% CI: 1.00–1.11, P = 0.045] compared to the alleviative IR group. Sensitivity analyses with various models further validated the robustness of our findings. Dynamic increase in the TyG index trajectory is associated with elevated mortality risk among patients with sepsis, which suggests that dynamic increased IR exacerbates the risk of poor outcomes in patients.

Resistance to targeted drugs is now a challenging clinical problem in the treatment of non-small cell lung cancer (NSCLC). So far, there are no approved targeted therapeutic drugs for patients with disease progression after the third-generation epidermal growth factor receptor-tyrosine kinase inhibitor osimertinib resistance (OR). Super-enhancers (SEs) are large clusters of transcriptional enhancers that drive gene expression. In this study, we aimed to explore the potential pathogenic SEs and their driven genes in OR NSCLC. OR cell line was established by exposure of H1975 cells to incremental dosing of osimertinib. RNA-sequencing and H3K27ac ChIP-sequencing were used to identify the differential expressed genes (DEGs) and SEs in parental and resistant cells. Gene ontology analysis for the OR-specific SEs-associated genes showed that histone citrullination, protein citrullination, and peptidyl-arginine modification are the top three biological processes, and the DEGs involved in these biological processes, including peptidyl arginine deiminase 1 (PADI1), PADI2, and PADI3. Realtime-PCR and western blot detections confirmed these genes were highly expressed in OR cells. SE inhibitor decreases their expression, ensuring that SEs regulate their transcriptional expressions. The PADI inhibitor inhibited OR cells’ proliferation, invasion, and colony formation. This study demonstrates that SE-driven PADI family genes are potential biomarkers and targets for OR NSCLC.