Optimal Targets of the First 24-h Partial Pressure of Carbon Dioxide in Patients with Cerebral Injury: Data from the MIMIC-III and IV Database

Association Between Temperature During Intensive Care Unit and Mortality in Patients With Acute Respiratory Distress Syndrome

The relationship between body temperature changes and prognosis in patients with acute respiratory distress syndrome (ARDS) remains inconclusive. Our study aimed to investigate the clinical value of body temperature in the management of ARDS. Data from the Medical Information Mart for Intensive Care III database were collected. Adult patients with ARDS were enrolled and further grouped based on their temperature values in the intensive care unit. Both the maximum (temperaturemax) and minimum (temperaturemin) temperatures were used. The primary outcome was 28-day mortality rate. Polynomial regression, subgroup analysis, and logistic regression analysis were performed in the final analysis. A total of 3922 patients with ARDS were enrolled. There was a U-shaped relationship between 28-day mortality and body temperature. For patients with infection, the elevated temperaturemax (≥37.0°C) was associated with decreased mortality, with an odds ratio ranging from 0.39 to 0.49, using temperaturemax from 36.5°C to 36.9°C as reference. For patients without infection, a similar tendency was observed, but the protective effect was lost at extremely high temperatures (≥38.0°C, p < 0.05). Elevated temperaturemin (≥37.0°C) and decreased temperaturemin (<35.0°C) were associated with increased mortality, using the temperaturemin from 36.0°C to 36.9°C as a reference. Hypothermia was associated with increased mortality in patients with ARDS, while the effect of hyperthermia (≥37.0°C) on the mortality of patients with ARDS was not fully consistent in the infection and noninfection subgroups. Short-term and transient temperatures above 37.0°C would be beneficial to patients with ARDS, but extreme hyperthermia and persistent temperatures above 37.0°C should be avoided.

Association between the first 24 hours PaCO2 and all-cause mortality of patients suffering from sepsis-associated encephalopathy after ICU admission: A retrospective study

OBJECTIVE

The relationship between the levels of the first 24-h PaCO2 and the prognosis of sepsis-associated encephalopathy (SAE) remains unclear, and the first 24-h optimal target for PaCO2 is currently inconclusive. This study was performed to investigate the correlation between PaCO2 and all-cause mortality for SAE patients, establish a reference range of the initial 24-hour PaCO2 for clinicians in critical care, and explain the possible pathophysiological mechanisms of abnormal PaCO2 levels as a higher mortality risk factor for SAE.

METHODS

The baseline information and clinical data of patients were extracted from the fourth edition Medical Information Mart for Intensive Care database (MIMIC-IV 2.0). Multivariate logistic regressions were performed to assess the relationship between PaCO2 and all-cause mortality of SAE. Additionally, restricted cubic splines, Kaplan-Meier Survival analyses, propensity score matching (PSM) analyses, and subgroup analyses were conducted.

RESULTS

A total of 5471 patients were included in our cohort. In the original and matched cohort, multivariate logistic regression analysis showed that normocapnia and mild hypercapnia may be associated with a more favorable prognosis of SAE patients, and survival analysis supported the findings. In addition, a U-shaped association emerged when examining the initial 24-hour PaCO2 levels in relation to 30-day, 60-day, and 90-day mortality using restricted cubic splines, with an average cut-off value of 36.3mmHg (P for nonlinearity<0.05). Below the cut-off value, higher PaCO2 was associated with lower all-cause mortality, while above the cut-off value, higher PaCO2 was associated with higher all-cause mortality. Subsequent subgroup analyses revealed similar results for the subcohort of GCS≤8 compared to the original cohort. Additionally, when examining the subcohort of GCS>8, a L-shaped relationship between PaCO2 and the three clinical endpoints emerged, in contrast to the previously observed U-shaped pattern. The findings from the subcohort of GCS>8 suggested that patients experiencing hypocapnia had a more unfavorable prognosis, which aligns with the results obtained from corresponding multivariate logistic regression analyses.

CONCLUSION

The retrospective study revealed the association between the first 24-h PaCO2 and all-cause mortality risk (30-day, 60-day, and 90-day) for patients with SAE in ICU. The range (35mmHg-50mmHg) of PaCO2 may be the optimal target for patients with SAE in clinical practice.

Development and verification of a nomogram for predicting short-term mortality in elderly ischemic stroke populations

Stroke is a major healthcare problem worldwide, particularly in the elderly population. Despite limited research on the development of prediction models for mortality in elderly individuals with ischemic stroke, our study aimed to address this knowledge gap. By leveraging data from the Medical Information Mart for Intensive Care IV database, we collected comprehensive raw data pertaining to elderly patients diagnosed with ischemic stroke. Through meticulous screening of clinical variables associated with 28-day mortality, we successfully established a robust nomogram. To assess the performance and clinical utility of our nomogram, various statistical analyses were conducted, including the concordance index, integrated discrimination improvement (IDI), net reclassification index (NRI), calibration curves and decision curve analysis (DCA). Our study comprised a total of 1259 individuals, who were further divided into training (n = 894) and validation (n = 365) cohorts. By identifying several common clinical features, we developed a nomogram that exhibited a concordance index of 0.809 in the training dataset. Notably, our findings demonstrated positive improvements in predictive performance through the IDI and NRI analyses in both cohorts. Furthermore, calibration curves indicated favorable agreement between the predicted and actual incidence of mortality (P > 0.05). DCA curves highlighted the substantial net clinical benefit of our nomogram compared to existing scoring systems used in routine clinical practice. In conclusion, our study successfully constructed and validated a prognostic nomogram, which enables accurate short-term mortality prediction in elderly individuals with ischemic stroke.

Prediction of long-term mortality in patients with ischemic stroke based on clinical characteristics on the first day of ICU admission: An easy-to-use nomogram

Background

This study aimed to establish and validate an easy-to-use nomogram for predicting long-term mortality among ischemic stroke patients.

Methods

All raw data were obtained from the Medical Information Mart for Intensive Care IV database. Clinical features associated with long-term mortality (1-year mortality) among ischemic stroke patients were identified using least absolute shrinkage and selection operator regression. Then, binary logistic regression was used to construct a nomogram, the discrimination of which was evaluated by the concordance index (C-index), integrated discrimination improvement (IDI), and net reclassification index (NRI). Finally, a calibration curve and decision curve analysis (DCA) were employed to study calibration and net clinical benefit, compared to the Glasgow Coma Scale (GCS) and the commonly used disease severity scoring system.

Results

Patients who were identified with ischemic stroke were randomly assigned into developing (n = 1,443) and verification (n = 646) cohorts. The following factors were associated with 1-year mortality among ischemic stroke patients, including age on ICU admission, marital status, underlying dementia, underlying malignant cancer, underlying metastatic solid tumor, heart rate, respiratory rate, oxygen saturation, white blood cells, anion gap, mannitol injection, invasive mechanical ventilation, and GCS. The construction of the nomogram was based on the abovementioned features. The C-index of the nomogram in the developing and verification cohorts was 0.820 and 0.816, respectively. Compared with GCS and the commonly used disease severity scoring system, the IDI and NRI of the constructed nomogram had a statistically positive improvement in predicting long-term mortality in both developing and verification cohorts (all with p < 0.001). The actual mortality was consistent with the predicted mortality in the developing (p = 0.862) and verification (p = 0.568) cohorts. Our nomogram exhibited greater net clinical benefit than GCS and the commonly used disease severity scoring system.

Conclusion

This proposed nomogram has good performance in predicting long-term mortality among ischemic stroke patients.

In-hospital mortality and SpO2 incritical care patients with cerebral injury: data from the MIMIC‑IV Database

BACKGROUND

Evidence regarding the relationship between in-hospital mortality and SpO2 was low oxygen saturations are often thought to be harmful, new research in patients with brain damage has found that high oxygen saturation actually enhances mortality. However, there is currently no clear study to point out the appropriate range for oxygen saturation in patients with craniocerebral diseases.  METHODS: By screening all patients in the MIMIC IV database, 3823 patients with craniocerebral diseases (according to ICD-9 codes and ICD-10) were selected, and non-linear regression was used to analyze the relationship between in-hospital mortality and oxygen saturation. Covariates for all patients included age, weight, diagnosis, duration of ICU stay, duration of oxygen therapy, etc. RESULTS: In-hospital mortality in patients with TBI and SAH was kept to a minimum when oxygen saturation was in the 94-96 range. And in all patients, the relationship between oxygen saturation and in-hospital mortality was U-shaped. Subgroup analysis of the relationship between oxygen saturation and mortality in patients with metabolic encephalopathy and other encephalopathy also draws similar conclusions In-hospital mortality and oxygen saturation were all U-shaped in patients with subarachnoid hemorrhage, metabolic and toxic encephalopathy, cerebral infarction, and other encephalopathy, but the nonlinear regression was statistically significant only in patients with cerebral infarction (p for nonlinearity = 0.002).

CONCLUSION

Focusing too much on the lower limit of oxygen saturation and ignoring too high oxygen saturation can also lead to increase in-hospital mortality. For patients with TBI and SAH, maintaining oxygen saturation at 94-96% will minimize the in-hospital mortality of patients.

Plasma anion gap and risk of in-hospital mortality in patients with spontaneous subarachnoid hemorrhage

Background

The association between the serum anion gap (AG) and prognosis of patients with spontaneous subarachnoid hemorrhage (SAH) remains unknown. Thus, this study aimed to explore the association between AG levels and mortality in patients with SAH in the intensive care unit (ICU).

Methods

This was a retrospective analysis of data stored in the Medical Information Mart for Intensive Care–IV and eICU Collaborative Research databases. Critically ill patients diagnosed with spontaneous SAH were included. The primary outcome measure was in-hospital all-cause mortality. A multivariate Cox proportional hazards regression model and a restricted cubic spline were used to evaluate the relationship between AG concentration and outcomes. Kaplan–Meier curves were used to compare cumulative survival among patients with AG levels.

Results

A total of 1,114 patients were enrolled. AG concentration was significantly associated with in-hospital all-cause mortality [hazard ratio ([HR], 1.076 (95% confidence interval (CI), 1.021–1.292; p = 0.006)]. The risk of mortality was higher in the Category 2 group (AG ≥10 mmol/L and <13 mmol/L; HR, 1.961; 95% CI, 1.157–3.324; p = 0.0) and the Category 3 group (AG ≥13 mmol/L; HR, 2.151; 95% CI, 1.198–3.864; p = 0.010) than in the Category 1 group (AG < 10 mmol/L). Cumulative survival rates were significantly lower in patients with higher AG levels (log-rank p < 0.001).

Conclusions

In-hospital and ICU mortalities increase with increasing AG concentration in patients with SAH. An increased serum AG level is an independent, significant, and robust predictor of all-cause mortality. Thus, serum AG levels may be used in the risk stratification of SAH.

Second- and Third-Tier Therapies for Severe Traumatic Brain Injury

Intracranial hypertension is a common finding in patients with severe traumatic brain injury. These patients need treatment in the intensive care unit, where intracranial pressure monitoring and, whenever possible, multimodal neuromonitoring can be applied. A three-tier approach is suggested in current recommendations, in which higher-tier therapies have more significant side effects. In this review, we explain the rationale for this approach, and analyze the benefits and risks of each therapeutic modality. Finally, we discuss, based on the most recent recommendations, how this approach can be adapted in low- and middle-income countries, where available resources are limited.