Group-based trajectory modeling of intracranial pressure in patients with acute brain injury: Results from multi-center ICUs, 2008-2019

Effects of 24-hour urine-output trajectories on the risk of acute kidney injury in critically ill patients with cirrhosis: a retrospective cohort analysis

BACKGROUND

Acute kidney injury (AKI) is one of the most common complications for critically ill patients with cirrhosis, but it has remained unclear whether urine output fluctuations are associated with the risk of AKI in such patients. Thus, we explored the influence of 24-h urine-output trajectory on AKI in patients with cirrhosis through latent category trajectory modeling.

MATERIALS AND METHODS

This retrospective cohort study examined patients with cirrhosis using the MIMIC-IV database. Changes in the trajectories of urine output within 24 h after admission to the intensive care unit (ICU) were categorized using latent category trajectory modeling. The outcome examined was the occurrence of AKI during ICU hospitalization. The risk of AKI in patients with different trajectory classes was explored using the cumulative incidence function (CIF) and the Fine-Gray model with the sub-distribution hazard ratio (SHR) and the 95% confidence interval (CI) as size effects.

RESULTS

The study included 3,562 critically ill patients with cirrhosis, of which 2,467 (69.26%) developed AKI during ICU hospitalization. The 24-h urine-output trajectories were split into five classes (Classes 1-5). The CIF curves demonstrated that patients with continuously low urine output (Class 2), a rapid decline in urine output after initially high levels (Class 3), and urine output that decreased slowly and then stabilized at a lower level (Class 4) were at higher risk for AKI than those with consistently moderate urine output (Class 1). After fully adjusting for various confounders, Classes 2, 3, and 4 were associated with a higher risk of AKI compared with Class 1, and the respective SHRs (95% CIs) were 2.56 (1.87-3.51), 1.86 (1.34-2.59), and 1.83 1.29-2.59).

CONCLUSIONS

The 24-h urine-output trajectory is significantly associated with the risk of AKI in critically ill patients with cirrhosis. More attention should be paid to the dynamic nature of urine-output changes over time, which may help guide early intervention and improve patients' prognoses.

Combined blood pressure and heart rate trajectories are associated with prognosis in critically ill patients with acute aortic dissection: A group-based multi-trajectory analysis

Background

Managing systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) is pivotal in acute aortic dissection (AAD) care. However, no prior studies have jointly analyzed the trajectories of these parameters. This research aimed to characterize their joint longitudinal trajectories and investigate the influence on AAD prognosis.

Methods

We included AAD patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Using group-based multi-trajectory modeling (GBMTM), we identified combined trajectories of SBP, DBP, and HR within the initial 24 h of intensive care unit (ICU) admission. Cox proportional hazard regression, log-binomial regression, and logistic regression were employed to assess the association between trajectory groups and mortality outcomes.

Results

Data from 337 patients were analyzed. GBMTM identified five combined trajectory groups. Group 1 featured rapidly declining SBP and DBP with high pulse pressure and low HR; Group 2 showed high to moderate SBP with slight rebound and persistently low HR; Group 3 displayed persistently moderate BP and HR; Group 4 was characterized by moderate blood pressure with persistently high HR; and Group 5 had high to moderate SBP with slight rebound, high but gradually declining DBP, and slightly high HR. Group 3 demonstrated a lower risk of mortality, with an adjusted hazard ratio of 0.32 (95 % CI, 0.14-0.74), and the adjusted relative risks for in-hospital, 30-day, and 1-year mortalities were 0.37 (95 % CI, 0.15-0.87), 0.25 (95 % CI, 0.10-0.62), and 0.41 (95 % CI, 0.22-0.79), respectively. The time-independent C-index curve demonstrated that the multi-trajectory groups had higher C-index values than any univariate trajectory groups or admission values of SBP, DBP, and HR.

Conclusions

Utilization of GBMTM can yield data-driven insights to identify distinct subphenotypes in AAD patients. The combined trajectories of SBP, DBP, and HR within 24 h of ICU admission significantly influenced the mortality rate.

Longitudinal hemoglobin trajectories and acute kidney injury in patients undergoing cardiac surgery: a retrospective cohort study

Object

The purpose of this study was to describe the longitudinal dynamic hemoglobin trajectories in patients undergoing cardiac surgery and to explore whether they provide a broader perspective in predicting AKI compared to traditional threshold values. Additionally, the interaction of red blood cell transfusion was also investigated.

Methods

The MIMIC-IV database was searched to identify patients undergoing cardiac surgery with cardiopulmonary bypass. Group-based trajectory modeling (GBTM) was used to determine the hemoglobin trajectories in the first 72 h after ICU admission. The correlation between hemoglobin trajectories and AKI was evaluated using multivariable logistic regression and inverse probability of treatment weighting. Receiver operating characteristic (ROC) curves were created in the dataset to further validate previously reported thresholds.

Results

A total of 4,478 eligible patients were included in this study. Three hemoglobin trajectories were identified by GBTM, which were significantly different in the initial hemoglobin level and evolution pattern. Compared to the "the lowest, rising, and then declining" trajectory, patients in the "the highest, declining" and "medium, declining" trajectory groups had significantly lower AKI risk (OR 0.56; 95% CI 0.48, 0.67) and (OR 0.70; 95% CI 0.55, 0.90), respectively. ROC analysis yielded a disappointing result, with an AUC of 0.552, sensitivity of 0.25, and specificity of 0.86 when the hemoglobin threshold was set at 8 g/dl in the entire cohort. In the subgroup analysis of red blood cell transfusion, hemoglobin levels above 10 g/dl predicted higher AKI risk, and there was no correlation between hemoglobin trajectories and AKI in the non-red blood cell transfusion subgroup.

Conclusion

This study identified a hemoglobin trajectory that is associated with an increased risk of AKI after cardiac surgery. It is noteworthy that fixed hemoglobin thresholds should not be applied to all patient types. In patients receiving red blood cell transfusion, maintaining hemoglobin levels above 10 g/dl through transfusion was associated with an increased risk of AKI.

The intracranial compartmental syndrome: a proposed model for acute brain injury monitoring and management

For decades, one of the main targets in the management of severe acute brain injury (ABI) has been intracranial hypertension (IH) control. However, the determination of IH has suffered variations in its thresholds over time without clear evidence for it. Meanwhile, progress in the understanding of intracranial content (brain, blood and cerebrospinal fluid) dynamics and recent development in monitoring techniques suggest that targeting intracranial compliance (ICC) could be a more reliable approach rather than guiding actions by predetermined intracranial pressure values. It is known that ICC impairment forecasts IH, as intracranial volume may rapidly increase inside the skull, a closed bony box with derisory expansibility. Therefore, an intracranial compartmental syndrome (ICCS) can occur with deleterious brain effects, precipitating a reduction in brain perfusion, thereby inducing brain ischemia. The present perspective review aims to discuss the ICCS concept and suggest an integrative model for the combination of modern invasive and noninvasive techniques for IH and ICC assessment. The theory and logic suggest that the combination of multiple ancillary methods may enhance ICC impairment prediction, pointing proactive actions and improving patient outcomes.