Association between serum alkaline phosphatase and clinical prognosis in patients with acute liver failure following cardiac arrest: a retrospective cohort study.

BACKGROUND: Acute liver failure (ALF) following cardiac arrest (CA) poses a significant healthcare challenge, characterized by high morbidity and mortality rates. This study aims to assess the correlation between serum alkaline phosphatase (ALP) levels and poor outcomes in patients with ALF following CA. METHODS: A retrospective analysis was conducted utilizing data from the Dryad digital repository. The primary outcomes examined were intensive care unit (ICU) mortality, hospital mortality, and unfavorable neurological outcome. Multivariable logistic regression analysis was employed to assess the relationship between serum ALP levels and clinical prognosis. The predictive value was evaluated using receiver operator characteristic (ROC) curve analysis. Two prediction models were developed, and model comparison was performed using the likelihood ratio test (LRT) and the Akaike Information Criterion (AIC). RESULTS: A total of 194 patients were included in the analysis (72.2% male). Multivariate logistic regression analysis revealed that a one-standard deviation increase of ln-transformed ALP were independently associated with poorer prognosis: ICU mortality (odds ratios (OR) = 2.49, 95% confidence interval (CI) 1.31-4.74, P = 0.005), hospital mortality (OR = 2.21, 95% CI 1.18-4.16, P = 0.014), and unfavorable neurological outcome (OR = 2.40, 95% CI 1.25-4.60, P = 0.009). The area under the ROC curve for clinical prognosis was 0.644, 0.642, and 0.639, respectively. Additionally, LRT analyses indicated that the ALP-combined model exhibited better predictive efficacy than the model without ALP. CONCLUSIONS: Elevated serum ALP levels upon admission were significantly associated with poorer prognosis of ALF following CA, suggesting its potential as a valuable marker for predicting prognosis in this patient population.

[Exploring the optimal range of pulse oxygen saturation in patients with sepsis: a retrospective study based on MIMIC- IV data].

OBJECTIVE: To explore the optimal pulse oxygen saturation (SpO2) range during hospitalization for patients with sepsis. METHODS: A case-control study design was employed. Demographic information, vital signs, comorbidities, laboratory parameters, critical illness scores, clinical treatment information, and clinical outcomes of sepsis patients were extracted from the Medical Information Mart for Intensive Care- IV (MIMIC- IV). A generalized additive model (GAM) combined with a Loess smoothing function was employed to analyze and visualize the nonlinear relationship between SpO2 levels during hospitalization and in-hospital all-cause mortality. The optimal range of SpO2 was determined, and Logistic regression model along with Kaplan-Meier curve were utilized to validate the association between the determined range of SpO2 and in-hospital all-cause mortality. RESULTS: A total of 5 937 patients met the inclusion criteria, among whom 1 191 (20.1%) died during hospitalization. GAM analysis revealed a nonlinear and U-shaped relationship between SpO2 levels and in-hospital all-cause mortality among sepsis patients during hospitalization. Multivariable Logistic regression analysis further confirmed that patients with SpO2 levels between 0.96 and 0.98 during hospitalization had a decreased mortality compared to those with SpO2 < 0.96 [hypoxia group; odds ratio (OR) = 2.659, 95% confidence interval (95%CI) was 2.190-3.229, P < 0.001] and SpO2 > 0.98 (hyperoxia group; OR = 1.594, 95%CI was 1.337-1.900, P < 0.001). Kaplan-Meier survival curve showed that patients with SpO2 between 0.96 and 0.98 during hospitalization had a higher probability of survival than those patient with SpO2 < 0.96 and SpO2 > 0.98 (Log-Rank test: χ 2 = 113.400, P < 0.001). Sensitivity analyses demonstrated that, with the exception of subgroups with smaller sample sizes, across the strata of age, gender, body mass index (BMI), admission type, race, heart rate, systolic blood pressure, diastolic blood pressure, mean arterial pressure, respiratory rate, body temperature, myocardial infarction, congestive heart failure, cerebrovascular disease, chronic liver disease, diabetes mellitus, sequential organ failure assessment (SOFA), simplified acute physiology score II (SAPS II), systemic inflammatory response syndrome score (SIRS), and Glasgow coma score (GCS), the mortality of patients with SpO2 between 0.96 and 0.98 was significantly lower than those of patients with SpO2 < 0.96 and SpO2 > 0.98. CONCLUSIONS: During hospitalization, the level of SpO2 among sepsis patients exhibits a U-shaped relationship with in-hospital all-cause mortality, indicating that heightened and diminished oxygen levels are both associated with increased mortality risk. The optimal SpO2 range is determined to be between 0.96 and 0.98.

Serum lactate/creatinine ratio and acute kidney injury in cardiac arrest patients.

OBJECTIVES: Serum lactate and creatinine levels upon admission in cardiac arrest (CA) patients significantly correlate with acute kidney injury (AKI) post-restoration of autonomic circulation. However, the association between serum lactate/creatinine ratio (LCR) and AKI in this population remains unclear. This study aimed to explore the relationship between LCR at admission and cardiac arrest-associated acute kidney injury (CA-AKI). DESIGN AND METHODS: We conducted a secondary analysis of previously published data on CA patient resuscitation, categorizing them into tertiles based on LCR levels. Univariate and multivariate logistic regression models and subgroup analyses were employed to investigate the association between LCR and CA-AKI. Non-linear correlations were explored using restricted cubic splines, and a two-piece wise logistic proportional hazards model for both sides of the inflection point was constructed. RESULTS: A total of 374 patients (72.19 % male) were included, with intensive care unit mortality, in-hospital mortality, and neurologic dysfunction rates of 51.87 %, 56.95 %, and 39.57 %, respectively. The overall CA-AKI incidence was 59.09 %. Multivariate logistic proportional hazards analysis revealed a negative association between LCR and CA-AKI incidence (adjusted odds ratio [OR] 0.85, 95 % confidence intervals [CI] = 0.78-0.93, P=0.001). Triple spline restriction analysis depicted an L-shaped correlation between baseline LCR and CA-AKI incidence. Particularly, a baseline LCR<0.051 was negatively associated with CA-AKI incidence (OR 0.494, 95 % CI=0.319-0.764, P=0.002). Beyond the LCR turning point, estimated dose-response curves remained consistent with a horizontal line. CONCLUSIONS: Baseline LCR in CA patients exhibits an L-shaped correlation with AKI incidence following restoration of autonomic circulation. The threshold for CA-AKI is 0.051. This finding suggests that LCR may aid in identifying CA patients at high risk of AKI.

Construction and validation of a risk prediction model for acute kidney injury in patients after cardiac arrest.

OBJECTIVE: Identifying patients at high risk for cardiac arrest-associated acute kidney injury (CA-AKI) helps in early preventive interventions. This study aimed to establish and validate a high-risk nomogram for CA-AKI. METHODS: In this retrospective dataset, 339 patients after cardiac arrest (CA) were enrolled and randomized into a training or testing dataset. The Student's t-test, non-parametric Mann-Whitney U test, or χ2 test was used to compare differences between the two groups. Optimal predictors of CA-AKI were determined using the Least Absolute Shrinkage and Selection Operator (LASSO). A nomogram was developed to predict the early onset of CA-AKI. The performance of the nomogram was assessed using metrics such as area under the curve (AUC), calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: In total, 150 patients (44.2%) were diagnosed with CA-AKI. Four independent risk predictors were identified and integrated into the nomogram: chronic kidney disease, albumin level, shock, and heart rate. Receiver operating characteristic (ROC) analyses showed that the nomogram had a good discrimination performance for CA-AKI in the training dataset 0.774 (95%CI, 0.715-0.833) and testing dataset 0.763 (95%CI, 0.670-0.856). The AUC values for the two groups were calculated and compared using the Hanley-McNeil test. No statistically significant differences were observed between the groups. The calibration curve demonstrated good agreement between the predicted outcome and actual observations. Good clinical usefulness was identified using DCA and CIC. CONCLUSION: An easy-to-use nomogram for predicting CA-AKI was established and validated, and the prediction efficiency of the clinical model has reasonable clinical practicability.

[Predictive value of sequential organ failure assessment on 28-day mortality in patients with post-cardiac arrest syndrome].

OBJECTIVE: To evaluate the predictive value of sequential organ failure assessment (SOFA) for 28-day mortality in patients with post-cardiac arrest syndrome (PCAS). METHODS: Retrospective analysis of 125 patients with PCAS who were treated in Emergency Intensive Care Unit (EICU) of Wenzhou People's Hospital from July 2016 to July 2021. Clinical data were collected, including age, gender, underlying diseases, acute physiology and chronic health evaluation II (APACHE II), SOFA score on admission to EICU and 28-day mortality. Univariate and multivariate Logistic regression model was constructed to analyze the influencing factors of PCAS patients, which was used to examine the independent correlation between SOFA score and 28-day mortality. Receiver operator characteristic curve (ROC curve) was used to determine the best predictive value of SOFA score and 28-day mortality in PCAS patients. RESULTS: Among the 125 PCAS patients, there were 91 males and 34 females with an average age of (58.7±15.1) years old, and 97 died and 28 survived within 28 days. The overall SOFA score ranged from 7 to 15 points, with an average of 10.9 (10.0, 12.0) points. The SOFA score of non-survival group was significantly higher than that of the survival group [points: 11.0 (10.0, 12.0) vs. 9.5 (9.0, 10.0), P < 0.05]. This difference between SOFA score mainly caused by the neurological and cardiovascular systems. After excluding neurological factors, the SOFA score of the non-survival group was still significantly higher than that of the survival group [points: 8.0 (6.0, 8.0) vs. 6.5 (6.0, 7.0), P < 0.05]. SOFA score was found to be an independent risk factor for 28-day mortality in PCAS patients by multifactorial Logistic regression analysis [odds ratio (OR) = 1.97, 95% confidence interval (95%CI) was 1.24-3.04]. The correlation between neurological score and mortality was the highest in subgroups (OR = 3.47, 95%CI was 1.04-11.52). The area under the ROC curve (AUC) predicted by SOFA score was 0.81 (95%CI was 0.73-0.89). When SOFA score cut-off value was 10.5 points (10 or 11 points), the sensitivity and specificity of SOFA score for predicting 28-day mortality in patients with PCAS were 67.0% and 82.1%, respectively. CONCLUSIONS: The SOFA score is quite accurate in predicting 28-day mortality in patients with PCAS.

Relationship between serum lactate dehydrogenase and mortality after cardiac arrest: A retrospective cohort study.

Serum lactate dehydrogenase (LDH) has been identified as an independent risk factor for predicting all-cause mortality in patients with multiple diseases. However, the prognostic value of LDH levels in post-cardiac arrest patients remains uncertain. This study aimed to assess the association between LDH and mortality in intensive care unit (ICU) patients after cardiac arrest. This retrospective observational study is based on data from the Dryad Digital Repository, which included 374 consecutive adult patients after cardiac arrest. Patients were divided into 2 groups based on median LDH values. A multivariate Cox proportional hazards model was established to assess the independent relationship between LDH and ICU mortality. Cumulative mortality was compared using Kaplan-Meier curves. The cohort included 374 patients, of which 51.9% (194/374) died in the ICU. The overall death rate from cardiac arrest was significantly higher for patients with LDH ≥ 335 IU/L (59.6%) than for those with LDH < 335 IU/L (44.1%). In multiple Cox regression models, hazard ratios (HR) and corresponding 95% confidence intervals (CI) for logLDH and the 2 LDH groups were 1.72 (1.07, 2.78) and 1.42 (1.04, 1.93), respectively. Participants with LDH ≥ 335IU/L had a higher incidence of ICU mortality than LDH < 335 IU/L, as shown by the Kaplan-Meier curves (P = .0085). Subgroup analysis revealed that the association between LDH and ICU mortality was vitally stable, with all P interactions from different subgroups >.05. Serum LDH levels are positively associated with ICU mortality in patients after cardiac arrest, especially for patients with LDH ≥ 335 IU/L.