Predictive Value For 28-day Mortality Research Articles

Hypernatremia is associated with mortality in severe elderly sepsis patients.

To explore the relationship between hypernatremia and 28-day mortality in elderly sepsis patients. A total of 179 elderly patients (age ≥65 years) with elevated serum sodium admitted to the Department of Critical Care Medicine of Nanjing Hospital affiliated with Nanjing Medical University from September 2021 to September 2022 were included in this retrospective observational study. The clinical data of all patients were collected, and the patients were divided into septic group and nonseptic groups according to the Sepsis 3.0 definition. The clinical features, acute physiological and chronic health II score (APACHE II score), mechanical ventilation time, serum sodium value and duration of serum sodium elevation were compared between the two groups. ROC curves were drawn to evaluate the predictive value of each index on the prognosis of sepsis patients, and Kaplan‒Meier survival analysis was carried out on patients with different serum sodium peaks. (1) The changes in serum sodium within 48 hours after admission in the sepsis group were small and statistically significant compared with those in the nonsepsis group (P = 0.039); however, the serum sodium elevation duration was longer (P = 0.018). (2) Compared with nonseptic patients, the 7-day mortality of septic patients was higher (15.8 vs. 7.7, P<0.001). The 28-day mortality of septic patients was higher than that of nonseptic patients, but there was no significant difference between the two groups (P = 0.086). (3) The serum sodium level in the sepsis group was higher than that in the nonsepsis group on the 1st, 3rd, 5th and 7th days (P<0.001). There was no significant difference in mechanical ventilation time or duration of stay in the ICU between the two groups. (4) The ROC curve analysis showed that the peak value of serum sodium had predictive value for the prognosis severity of elderly patients with sepsis. The area under the curve (AUC) was 0.753, the 95% confidence interval (95% CI) was 0.639~0.867, and the best cut-off value was 154.9 mmol/L. (5) According to the best cut-off value of the serum sodium peak, the septic patients were divided into two groups: the peak value of serum sodium was ≥154.9 mmol/L (group A), and the peak value of serum sodium was <154.9 mmol/L (group B). Among them, the case fatality rate was higher at 7 days and 28 days when the peak value of serum sodium was ≥154.9 mmol/L (group A) (22.0% vs. 8.6%); the χ2 value was 35.379, P<0.05; 75.6% vs. 37.1%, χ2 = 14.21, P = 0.003). There was no significant difference in mechanical ventilation time or duration of stay in the ICU between the two groups. (6) Kaplan‒Meier survival analysis showed that the median survival time of patients with a serum sodium peak ≥154.9 mmol/L (group A) was significantly shorter than that of patients with a serum sodium peak < 154.9 mmol/L (group B) (16.7±1.4 d vs. 24.8±1.2 d, P <0.05). The serum sodium increase in elderly sepsis patients lasts for a long time, and the serum sodium fluctuation is relatively small. The serum sodium peak value has predictive value for 28-day mortality.

A prognostic prediction model for acute pulmonary embolism.

Acute pulmonary embolism (APE) is a very common and important medical emergency in intensive care units with an unfavorable prognosis. This study aims to explore the prognostic factors of APE and to construct a prognostic prediction model. A retrospective analysis was conducted on 252 APE patients in the emergency department of our hospital from January 2020 to March 2024. The initial observation endpoint was set as the mortality status of patients within 30 days of admission. Cox multivariate regression analysis was used to identify independent risk factors for prognosis. Based on these factors, a nomogram predictive model was constructed and evaluated using R software. Within 30 days of admission, 42 patients died with an overall mortality rate of 16.6% (42/252). Binary Cox multivariate regression analysis indicated that age ≥ 62.5 (HR: 2.64, 95% CI: 1.23-5.63, p = 0.012), right ventricular dysfunction (RVD) (HR: 4.58, 95% CI: 1.76-11.96, p = 0.002), white blood cell count (WBC) ≥ 13.1 (HR: 2.35, 95% CI: 1.20-4.60, p = 0.013), albumin/fibrinogen ratio (AFR) < 9.15 (HR: 3.36, 95% CI: 1.76-6.42, p < 0.001), Prognostic Nutritional Index (PNI) < 50.3 (HR: 4.35, 95% CI: 1.62-11.71, p = 0.004), and Systemic Inflammation Response Index (SIRI) ≥ 1.05 (HR: 7.21, 95% CI: 3.38-15.37,p < 0.001) were independent risk factors for mortality. The nomogram model based on these factors demonstrated a good predictive value for 30-day mortality, with an AUC of 0.908. The nomogram model based on age, RVD, WBC, AFR, PNI, and SIRI has a well prognostic value for APE patients.

External validation of the BE-ALIVE score for predicting 30-day mortality in patients presenting with acute coronary syndromes

IntroductionThe BE-ALIVE score is an additive scoring system for estimating 30-day mortality in patients presenting with an acute coronary syndrome (ACS) [1]. However, it had only previously been tested on an internal validation cohort. The aim was to assess the scoring system on an external validation cohort. MethodsThe scoring system comprises six domains: (1) Base Excess (1 point for < −2 mmols/L), (2) Age (<65 years: 0 points, 65–74: 1 point, 75–84: 2 points, ≥ 85: 3 points), (3) Lactate (<2 mmols/L: 0 points, 2–4.9: 1 point, 5–9.9: 3 points, ≥ 10: 6 points), (4) Intubated & Ventilated (2 points), (5) Left Ventricular function (normal or mildly impaired: -1 point, moderately impaired: 1 point, severely impaired: 3 points) and (6) External / out of hospital cardiac arrest (1 point).We applied the BE-ALIVE score was applied to 205 consecutive patients at a different institution. ResultsCalibration was strong, with an observed to expected ratio of 1.01, a calibration slope of 1.26 and calibration in the large of −0.03. The Spiegelhalter's Z-statistic was −0.95 (p = 0.34). The AUC was 0.95 (0.92–0.98) in the external validation cohort versus 0.90 (0.85–0.95) during internal validation.Overall performance was excellent with a Brier score of 0.07 versus 0.06 during internal validation. The negative predictive value for 30-day mortality of a BE-ALIVE score < 4 was 98 %, with a positive predicted value of a score ≥ 10 of 95 %. ConclusionsThe BE-ALIVE score remains a robust predictor of 30-day mortality in an external validation cohort.

STREM-1 as a Predictive Biomarker for Disease Severity and Prognosis in COVID-19 Patients.

Research on biomarkers associated with the severity and adverse prognosis of COVID-19 can be beneficial for improving patient outcomes. However, there is limited research on the role of soluble TREM-1 (sTREM-1) in predicting the severity and prognosis of COVID-19 patients. A total of 115 COVID-19 patients admitted to the emergency department of Beijing Youan Hospital from February to May 2023 were included in the study. Demographic information, laboratory measurements, and blood samples for sTREM-1 levels were collected upon admission. Our study found that sTREM-1 levels in the plasma of COVID-19 patients increased with the severity of the disease (moderate vs mild, p=0.0013; severe vs moderate, p=0.0195). sTREM-1 had good predictive value for disease severity and 28-day mortality (area under the ROC curve was 0.762 and 0.805, respectively). sTREM-1 also exhibited significant correlations with age, body temperature, respiratory rate, PaO2/FiO2, PCT, CRP, and CAR. Ultimately, through multivariate logistic regression analysis, we determined that sTREM-1 (OR 1.008, 95% CI: 1.002-1.013, p=0.005), HGB (OR 0.966, 95% CI: 0.935-0.998, p=0.036), D-dimer (OR 1.001, 95% CI: 1.000-1.001, p=0.009), and CAR (OR 1.761, 95% CI: 1.154-2.688, p=0.009) were independent predictors of 28-day mortality in COVID-19 patients. The combination of these four markers yielded a strong predictive value for 28-day mortality in COVID-19 cases with an AUC of 0.919 (95% CI: 0.857 -0.981). sTREM-1 demonstrated good predictive value for disease severity and 28-day mortality, serving as an independent prognostic factor for adverse patient outcomes. In the future, we anticipate conducting large-scale multicenter studies to validate our research findings.

Machine learning algorithm for predicting 30-day mortality in patients receiving rapid response system activation: A retrospective nationwide cohort study

This study investigated the accuracy of a machine learning algorithm for predicting mortality in patients receiving rapid response system (RRS) activation. This retrospective cohort study used data from the In-Hospital Emergency Registry in Japan, which collects nationwide data on patients receiving RRS activation. The missing values in the dataset were replaced using multiple imputations (mode imputation, BayseRidge sklearn. linear model, and K-nearest neighbor model), and the enrolled patients were randomly assigned to the training and test cohorts. We established prediction models for 30-day mortality using the following four types of machine learning classifiers: Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting, random forest, and neural network. Fifty-two variables (patient characteristics, details of RRS activation, reasons for RRS initiation, and hospital capacity) were used to construct the prediction algorithm. The primary outcome was the accuracy of the prediction model for 30-day mortality. Overall, the data from 4,997 patients across 34 hospitals were analyzed. The machine learning algorithms using LightGBM demonstrated the highest predictive value for 30-day mortality (area under the receiver operating characteristic curve, 0.860 [95 % confidence interval, 0.825–0.895]). The SHapley Additive exPlanations summary plot indicated that hospital capacity, site of incidence, code status, and abnormal vital signs within 24 h were important variables in the prediction model for 30-day mortality.

Presepsin as a prognostic biomarker in COVID-19 patients: combining clinical scoring systems and laboratory inflammatory markers for outcome prediction

BackgroundThere is still limited research on the prognostic value of Presepsin as a biomarker for predicting the outcome of COVID-19 patients. Additionally, research on the combined predictive value of Presepsin with clinical scoring systems and inflammation markers for disease prognosis is lacking.MethodsA total of 226 COVID-19 patients admitted to Beijing Youan Hospital’s emergency department from May to November 2022 were screened. Demographic information, laboratory measurements, and blood samples for Presepsin levels were collected upon admission. The predictive value of Presepsin, clinical scoring systems, and inflammation markers for 28-day mortality was analyzed.ResultsA total of 190 patients were analyzed, 83 (43.7%) were mild, 61 (32.1%) were moderate, and 46 (24.2%) were severe/critically ill. 23 (12.1%) patients died within 28 days. The Presepsin levels in severe/critical patients were significantly higher compared to moderate and mild patients (p < 0.001). Presepsin showed significant predictive value for 28-day mortality in COVID-19 patients, with an area under the ROC curve of 0.828 (95% CI: 0.737–0.920). Clinical scoring systems and inflammation markers also played a significant role in predicting 28-day outcomes. After Cox regression adjustment, Presepsin, qSOFA, NEWS2, PSI, CURB-65, CRP, NLR, CAR, and LCR were identified as independent predictors of 28-day mortality in COVID-19 patients (all p-values < 0.05). Combining Presepsin with clinical scoring systems and inflammation markers further enhanced the predictive value for patient prognosis.ConclusionPresepsin is a favorable indicator for the prognosis of COVID-19 patients, and its combination with clinical scoring systems and inflammation markers improved prognostic assessment.

Predictive value of systemic immune inflammation index (SII) and prognostic nutritional index (PNI) on mortality after below-knee amputation.

This retrospective cross-sectional study aimed to evaluate the predictive value of SII (Systemic Immune Inflammation Index) and PNI (Prognostic Nutritional Index) with blood ratios on mortality in diabetic foot patients who underwent below-knee amputation. A total of 231 living (n = 71; 30.7%) and exitus (n = 160; 69.3%) patients were evaluated. The mortality group was divided into 3 groups: 30-day mortality (n = 62; 38.8%), 1-year mortality (n = 62; 38.8%), and over-1-year mortality (n = 36; 22.5%). The hemogram, SII, and PNI parameters of the patients were evaluated. Age, some blood count parameters and SII were significantly higher in the exitus group (P < .05). The lymphocyte, monocyte, eosinophil, albumin, and PNI levels were significantly higher in the living group (P < .05). Mortality was significantly predicted by age (B [regression coefficient] = 0.026, P < .05), NLR (neutrophil lymphocyte ratio) (B = -0.065, P < .05), PNI (B = -0.100, P < .01), and SII (B = 0.00000024, P < .01). The predictive values of CAR (C reactive protein albumin ratio), PNI, and SII were 77.3%, 77.0%, and 76.1%, respectively. For CAR of 30.88 cutoff value, the sensitivity and specificity were 79.4% and 64.8%, respectively. For the PNI 22.0143 cutoff value, the sensitivity and specificity were 66.9% and 5.6%, respectively. For the SII 732249.2481 cutoff value, the sensitivity and specificity were 91.9% and 31.0%, respectively. The predictive value of the PNI was significant for mortality time (B = 0.058; P < .01). The predictive value of PNI for 30-day mortality was significant (AUC (area under curve):0.632; P < .01), whereas its predictive value for 1-year mortality and over-1-year mortality after below-knee amputation was statistically insignificant (P > .05). Both the SII and PNI may be evaluated and used to predict mortality after below-knee amputation. The SII had a significant predictive value for 30-day mortality after below-knee amputation.

Clinical application of serum NLRP3 on the diagnosis and prognosis of sepsis patients complicated with acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is a common complication of sepsis, which significantly increases the mortality rate. This work explored the diagnostic value of serum NOD-like receptor family pyrin domain containing 3 (NLRP3) concentration in patients with sepsis for ARDS, and the predictive value of serum NLRP3 concentration at the time of diagnosis for death 28 days after treatment. A total of 150 sepsis patients were included in this study, including age-matched two groups of patients, 75 patients with ARDS and 75 patients without ARDS. In addition, 60 age-matched healthy patients with physical examination were recruited in this study. Serum NLRP3 concentration was determined by enzyme-linked immunosorbent assay (ELISA). The diagnostic values of serum NLRP3 concentration for ARDS in sepsis patients were evaluated by receiver operating characteristics (ROC) analysis. Correlation of serum NLRP3 with APACHE II score and SOFA were performed by Spearman correlation analysis. Pulmonary infection, APACHE II score and serum NLRP3 concentration were risk factors for patients with sepsis complicated with ARDS. ROC curve results showed that the specificity of serum NLRP3 concentration was 74.67%, the sensitivity was 76.00%, and the area under the curve (AUC) was 0.82 (p<0.001). APACHE II score and SOFA were significantly positively correlated with serum NLRP3 concentration. Baseline serum NLRP3 levels had significant predictive value for 28-day mortality in sepsis patients complicated with ARDS. Serum NLRP3 concentration has clinical value in the diagnosis of sepsis complicated with ARDS.

Predictive value of platelet-related parameters combined with pneumonia severity index score for mortality rate of patients with severe pneumonia.

To analyse the predictive value of platelet-related parameters combined with pneumonia severity index (PSI) score for the mortality rate of patients with severe pneumonia. The clinical data of 428 severe pneumonia patients were retrospectively analysed. They were divided into survivor and death groups according to 28-day prognosis. Platelet-related parameters platelet count (PLT), mean platelet volume (MPV), platelet-large-cell ratio (P-LCR) and platelet distribution width (PDW) were measured within 24 hours after admission. The receiver operating characteristic (ROC) curves were plotted. The areas under the ROC curves (AUC) were used to describe the predictive efficiencies of platelet-related parameters, PSI score and their combination for death within 28 days. On the 28th day, there were 184 deaths and 244 survivors, and the deaths had significantly higher PLT and PSI score but lower PDW, MPV and P-LCR than those of the survivors (P<0.05). The combination of platelet-related parameters and PSI score had the highest sensitivity (96.56%) and specificity (99.34%) and the largest AUC (0.902) for predicting 28-day mortality. PLT, PDW, MPV and P-LCR are significantly abnormal in patients with severe pneumonia, and the combination of platelet-related parameters with PSI score has the highest predictive value for 28-day mortality.

Early NSE measurements at the ICU bear prognostic value in patients with and without CPR

Abstract Funding Acknowledgements Type of funding sources: None. Background Neuron-specific enolase (NSE) represents a diagnostic tool for identifying poor neurological outcomes in patients following CPR. As part of multimodal prognostication, NSE values above 60 µg/L after 48h and/or 72h were associated with a worse neurologic outcome (European Resuscitation Council Guidelines 2021). Despite the prognostic value of NSE 48h to 72h after CPR, measurements at admission to the ICU remain the topic of discussion as divergent findings are present in the literature (primarily in small collectives). Purpose Within the proposed study, we aimed to illuminate the prognostic value of NSE measurements on the day of admission to the ICU. Furthermore, we conducted a comparison of patients with and without CPR prior to ICU admission. Due to hemolysis sensitivity, we adjusted NSE values according to a previously published protocol to reveal potential changes in predictive potential through the occurrence of hemolysis. Methods This was a prospective, observational cohort study. 232 consecutive patients admitted to a cardiac ICU were screened over the course of one year. Patients with active malignancies or traumatic brain injuries were excluded. Furthermore, samples with hemolysis index &amp;gt;30 units were excluded to guarantee stable measurements. NSE values were measured on the day of admission to the ICU in a total of 202 patients (154 without previous CPR, 48 with CPR) using specific ELISA kits. According to an earlier publication, hemolysis was considered to account for an artificial increase of 0.29µg/L per unit (range 5-30 units) and was subsequently subtracted. Results Median age was 66.96 (IQR: 55.7-76.9), and 41.1% of the included patients were female. The total 30-day-mortality was calculated to be 27.2%, and 48 patients (23.8%) were admitted following CPR. Interestingly NSE at admission was not higher in patients after CPR (3.23 ± 3.88 µg/L vs 5.43 ± 5.78 µg/L, p = 0.072). However, NSE measurements on the day of admission were significantly elevated in 30-day none-survivors (3.23 ± 3.84 µg/L vs 6.91 ± 6.55 µg/L, p &amp;lt; 0.001). The same findings were made when excluding all patients after CPR (30-day survivors: 3.24 ± 3.99 µg/L vs 30-day none-survivors: 6.15 ± 6.17µg/L, p = 0.001). No statistically significant differences in survival were found when stratifying for the primary cause of admission. Comparing hemolysis-corrected NSE values to raw data showed a slight increase in positive predictive value for 30-day mortality in the total cohort (ROC-AUC: 0.732 vs 0.721) as well as in patients without prior CPR (ROC-AUC: 0.722 vs 0.703). Conclusion We provided evidence for the prognostic value of early NSE measurements at the ICU. In both the total cohort as well as a sub-cohort without patients admitted after CPR, 30-day none-survivors displayed markedly elevated levels of NSE. Moreover, the positive predictive value of these measurements was slightly increased when correcting for hemolysis &amp;gt;5 units.

Predictive value of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio for 28-day death in patients treated with extracorporeal membrane oxygenation

The study aimed to evaluate the predictive value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) for 28-day mortality in patients treated with extracorporeal membrane oxygenation (ECMO). Patients receiving ECMO treatment were selected from the Department of Intensive Care Medicine of Zhejiang Hospital from January 2019 to February 2022. The moment when patients started receiving ECMO treatment was set as the starting point, and death at 28 days was set as the endpoint. The patients were divided into survivors and deaths. Laboratory tests, such as neutrophil, lymphocyte, and platelet counts, using the peripheral blood of all patients were collected within 24 h after ECMO treatment. NLR and PLR were calculated. The risk factors influencing prognosis were analyzed by logistic regression. The correlation between NLR, PLR, acute physiology, and chronic health score Ⅱ (APACHE Ⅱ) was investigated. Receiver operating characteristic (ROC) curve analysis was used to analyze the value of NLR and PLR in predicting the 28-day mortality of patients treated with ECMO. Kaplan-Meier method was used to analyze the cumulative survival of patients at 28 days. The results showed that of 53 patients, 20 survived, and 33 died. The NLR and PLR of the deceased were higher than those of the survivors (NLR: 30.67±14.48 vs. 17.41±7.06;PLR: 303.34±159.23 vs. 191.54±106.03;P<0.001). NLR and PLR were positively correlated with APACHE Ⅱ (r=0.296, r=0.284, P<0.05). ROC curve analysis showed that the area under the curve (AUC) of NLR and PLR to predict the 28 d death of ECMO-treated patients was 0.805 and 0.714, respectively, and the optimal cutoff values of NLR and PLR were 18.93 and 253.0, respectively. The 28-day fatality rate in patients with NLR≥18.93 was higher than that in patients with NLR<18.93 [86.20%(25/29) vs. 33.33%(8/24), χ2=15.625, P<0.01],that in patients with a PLR≥253.0 was higher than that in patients with PLR<253.0 [82.61%(19/23) vs. 46.67%(14/30), χ2=7.158, P<0.01]. Kaplan-Meier survival curve showed that the 28-day cumulative survival rate of NLR≥18.93 was lower than that of NLR<18.93 [9.00 (2.00, 19.50) d vs. 28.00 (10.75, 28.00) d, Z=-3.124, P<0.01], and that of PLR≥253.0 was lower than that of PLR<253.0 [6.00 (2.00, 19.00) d vs. 28.00 (6.25, 28.00) d, Z=-2.673, P<0.01]. Thus, NLR and PLR have good predictive value for 28-day mortality in patients treated with ECMO.

PLK1 protects intestinal barrier function in sepsis: A translational research.

Sepsis and its related complications are very challenging in the intensive care unit, among which intestinal barrier injury is a general manifestation. Polo-like kinase 1 (PLK1) is widely studied in cancer, while its role in sepsis is poorly understood. In this study, the efficiency of PLK1 as a marker of intestinal barrier function as well as a predictor of mortality in sepsis was evaluated. The level of serum PLK1 was measured in septic patients (n=51) and controls (n=20); subsequently, its correlation with serum diamine oxidase (DAO), d-lactate, and endotoxin levels and its ability topredict mortality were analysed. The survival rate and barrier injury degree were also assessed in septic mice. Serum PLK1 levels were elevated in septic patients, were negatively correlated with serum DAO, d-lactate, and endotoxin levels, and had a high predictive value for 28-day mortality in patients. The serum PLK1 level in non-survivors was lower. The expression of PLK1 in the intestine was decreased in septic mice, and overexpression or inhibition of PLK1 alleviated or aggravated intestinal barrier injury, respectively, as evaluated by Chiu's score, serum levels of DAO and d-lactate, and expression of tight junction proteins. Overexpressing PLK1 also decreased the 72-hour death rate of septic mice. Further study also revealed the negative correlation of PLK1 and IL-6 in patients, and increasing or interfering with PLK1 expression reduced or increased the serum IL-6 level in mice. PLK1 plays a critical role in intestinal barrier function during sepsis, providing a novel perspective for sepsis therapy in the clinic.

Prognostic Value of T peak-T end Interval on Surface ECG in Patients Undergoing Reperfusion Therapy for ST Segment Myocardial Infarction

Background: In post-ST-segment elevation myocardial infarction (STEMI) patients, the indices of repolarization on electrocardiogram (ECG) have shown promise for the prediction of death and malignant arrhythmias. In our study, we analyzed prospectively, in patients with STEMI undergoing reperfusion therapy, the acute effects of the reperfusion on the Tpeak-Tend (TpTe) and its predictive value for 30-day mortality, ventricular arrhythmias, and heart failure. Materials and Methods: We studied 75 STEMI patients aged 18–80 years admitted to Nizam’s Institute of Medical Sciences, Hyderabad, over 6 months. ECGs were taken before and 90 min after reperfusion. TpTe interval was measured before (pre-TpTe) and after reperfusion (post-TpTe). 24-h Holter monitoring was recorded within 72 h of reperfusion to look for any arrhythmias. Patients were followed up for a period of 30 days, and all the major adverse cardiac events (MACE) if any, were noted. Results: In the primary percutaneous transluminal coronary angioplasty (PTCA) group, the mean change in TpTe after intervention was 19.7 ± 16.7 ms, whereas in thrombolysis group, it was 10.7 ± 13.8; and the difference was statistically significant (P < 0.05), suggesting the superiority of primary PTCA compared to thrombolysis. When pre-TpTe interval was compared between who survived (69) and who succumbed (09), higher values were seen in patients who succumbed to death (115 ± 5.48) versus (88 ± 16.5) (P < 0.05). Pre-TpTe value of 105 had 100% sensitivity and 83% specificity in predicting mortality. Conclusion: Primary PTCA was superior to thrombolysis in reducing the TpTe interval and MACE events. The pre-TpTe interval could predict 30-day mortality and ventricular arrhythmias in the immediate and late period after revascularization in STEMI.

Predictive Value of Heart-Type Fatty Acid-Binding Protein for Mortality Risk in Critically Ill Patients.

Our study assessed the predictive value of heart-type fatty acid-binding protein (H-FABP) for critically ill patients. 150 critically ill patients admitted to the emergency department of Beijing Chaoyang Hospital, Capital Medical University, were included in our study from August 2021 to April 2022. Serum H-FABP, procalcitonin (PCT), lactate (LAC), and other markers were determined within 1 h after admission. The Sequential Organ Failure Assessment (SOFA) score and the Acute Physiology and Chronic Health Evaluation II (APACHE II) were calculated. The independent predictors of 28-day mortality in critically ill patients were analyzed by logistic regression, and the receiver operating characteristic curve (ROC) was used to analyze the predictive value for 28-day mortality in critically ill patients. Age, APACHE II, SOFA, GCS, LAC, H-FABP, IL-6, Scr, and D-dimer were significantly different in the nonsurvivor vs. survivor groups (P < 0.05), with H-FABP correlating with cTNI, Scr, PCT, and SOFA scores (P < 0.05). Logistic regression analysis showed that H-FABP, APACHE II, LAC, and age were independent predictors for 28-day mortality in critically ill patients (P < 0.05). The AUC of ROC curve in H-FABP was 0.709 (sensitivity 72.9%, specificity 66.1%, and cut-off 4.35), which was slightly lower than AUC of ROC curve in LAC (AUC 0.750, sensitivity 58.3%, specificity 76.1%, and cut-off 1.95) and APACHE II (AUC 0.731, sensitivity 77.1%, specificity 58.7%, and cut-off 12.5). However, statistically, there was no difference in the diagnostic value of H-FABP compared with the other two indicators (Z 1 = 0.669, P = 0.504; Z 2 = 0.383, P = 0.702). But H-FABP (72.9%) has higher sensitivity than LAC (58.3%). The combined evaluation of H-FABP+APACHE II score (AUC 0.801, sensitivity 71.7%, and specificity 78.2%; Z = 2.612, P = 0.009) had better diagnostic value than H-FABP alone and had high sensitivity (71.7%) and specificity (78.2%). H-FABP, LAC, APACHE II, and age can be used as independent risk factors affecting the prognosis of critically ill patients. Compared with using the above indicators alone, the H-FABP+APACHE II has a high diagnostic value, and the early and rapid evaluation is particularly important for the adjustment of treatment plans and prognosis.

Nutritional risk factors for all-cause mortality of critically ill patients: a retrospective cohort study

ObjectivesThis study aimed to explore the predictive value of single and multiple risk factors for the clinical outcomes of critically ill patients receiving enteral nutrition and to establish an effective...

Early quantitative pupillary response parameters have high predictive value for 30-day mortality in patients resuscitated from out-of-hospital cardiac arrest

Abstract Background Despite adequate post-resuscitation treatment following out-of-hospital cardiac arrest (OHCA), early risk of death remains high due to irreversible anoxic brain injury. Objective Neuroprognostication is pivotal, and automated quantitative pupillometry has become an essential part of early multimodal approach. Several quantitative pupillary response parameters are now available, but little evidence exist on their value and timing in neuroprognostication. Purpose To evaluate prognostic value of standard parameters of quantitative pupillometry in OHCA patients. Methods In this observational study we included 138 comatose patients resuscitated from OHCA admitted to a tertiary cardiac intensive care unit. With quantitative pupillometry, change in pupil size (%CH, %), Neurological Pupil index (NPi, scalar value 0–5), constriction velocity (CV, mm/s), maximum CV (MCV, mm/s), dilation velocity (DV, mm/s) and latency of constriction (Lat, s) were measured at admission, at the 24 hours (24h), and 48-hours (48h) time points. Receiver operating characteristics (ROC) curves with calculation of area under the curve (AUC) were applied for assessment of association with 30-day mortality. Results The population were predominantly males, had a mean age of 61±12 years, and 120 (87%) had shockable primary rhythm, 122 (88%) had witnessed cardiac arrest and 51 (37%) died in the first 30 days. Median %CH, CV, MCV, DV and NPi values were significantly lower for diseased patients compared to survivors. ROC analyses (Figure 1) present all parameters, except NPi, at admission with numerically highest values of AUC at 0.82, 0.76, 0.73, and 0.81 for %CH, CV, MCV, and DV respectively, and for NPi at 48h with AUC at 0.81. The admission time point still presented the highest AUC values, &amp;gt;0.84, for CV, MCV, and DV in an adjusted model. Of all the parameters, %CH and NPi maintained the highest prognostic values through all time points, and %CH performed best at admission with AUC at 0.87 and NPi at 24h with AUC at 0.91. At admission the threshold value with 100% specificity for predicting 30-day mortality were 3.75, 0.09, 0.33, and 0.05, with negative predictive value (NPV [95% confidence interval]) at 71% [67–74], 66% [64–69], 67% [65–70], and 69% [66–72] for %CH, CV, MCV, and DV respectively. NPi had best performance at 24h with a cutoff value of 2.90 and NPV at 64% [63–64]. Conclusion %CH and NPi were the strongest prognostic tools for 30-day mortality. Values below 3.75% for %CH at admission and 2.90 for NPi at 24h after archived 100% specificity for 30-day mortality, with NPV at 71% [67–74] and 64% [63–64] respectively. Although performance was persistently high, %CH, CV, MCV, and DV presented numerically highest AUC at admission. Additional parameters of CV, MCV, and DV were also significantly associated with outcome and future research should focus on validation and possible combining these measures into useful indices. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Novo Nordisk Foundation

Development and Internal Validation of a New Prognostic Model Powered to Predict 28-Day All-Cause Mortality in ICU COVID-19 Patients-The COVID-SOFA Score.

Background: The sequential organ failure assessment (SOFA) score has poor discriminative ability for death in severely or critically ill patients with Coronavirus disease 2019 (COVID-19) requiring intensive care unit (ICU) admission. Our aim was to create a new score powered to predict 28-day mortality. Methods: Retrospective, observational, bicentric cohort study including 425 patients with COVID-19 pneumonia, acute respiratory failure and SOFA score ≥ 2 requiring ICU admission for ≥72 h. Factors with independent predictive value for 28-day mortality were identified after stepwise Cox proportional hazards (PH) regression. Based on the regression coefficients, an equation was computed representing the COVID-SOFA score. Discriminative ability was tested using receiver operating characteristic (ROC) analysis, concordance statistics and precision-recall curves. This score was internally validated. Results: Median (Q1–Q3) age for the whole sample was 64 [55–72], with 290 (68.2%) of patients being male. The 28-day mortality was 54.58%. After stepwise Cox PH regression, age, neutrophil-to-lymphocyte ratio (NLR) and SOFA score remained in the final model. The following equation was computed: COVID-SOFA score = 10 × [0.037 × Age + 0.347 × ln(NLR) + 0.16 × SOFA]. Harrell’s C-index for the COVID-SOFA score was higher than the SOFA score alone for 28-day mortality (0.697 [95% CI; 0.662–0.731] versus 0.639 [95% CI: 0.605–0.672]). Subsequently, the prediction error rate was improved up to 16.06%. Area under the ROC (AUROC) was significantly higher for the COVID-SOFA score compared with the SOFA score for 28-day mortality: 0.796 [95% CI: 0.755–0.833] versus 0.699 [95% CI: 0.653–0.742, p < 0.001]. Better predictive value was observed with repeated measurement at 48 h after ICU admission. Conclusions: The COVID-SOFA score is better than the SOFA score alone for 28-day mortality prediction. Improvement in predictive value seen with measurements at 48 h after ICU admission suggests that the COVID-SOFA score can be used in a repetitive manner. External validation is required to support these results.

The relationship between the lipid profiles and inflammation in patients with sepsis

To explore the relationship between the changes in the lipid profiles and the intensity of inflammatory response and disease severity in patients with sepsis, in order to find a biomarker that can quickly evaluate the condition and prognosis of sepsis. A retrospective analysis was performed on 449 patients with sepsis admitted to department of critical care medicine of the First Affiliated Hospital of Zhengzhou University from October 2019 to May 2021, and 355 patients without sepsis hospitalized in the same period served as the control. The general demographic data, blood lipid and other clinical indicators within 24 hours after admission were collected and compared between the two groups. Bivariate correlation study was used to analyze the relationship between blood lipid levels and inflammation indicators and severity of illness in patients with sepsis. The receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of each blood lipid component on the 28-day mortality of patients with sepsis. According to the results of ROC curve analysis, the blood lipids were divided into two groups with different levels, and the Kaplan-Meier survival curve was used to compare the cumulative survival rates of the two groups without end-point event (the 28-day mortality was the end-point event). Compared with non-septic patients, the levels of plasma total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were significantly lower in patients with sepsis [TC (mmol/L): 2.93±1.33 vs. 4.01±1.14, HDL-C (mmol/L): 0.78±0.47 vs. 1.16±0.40, LDL-C (mmol/L): 1.53±1.00 vs. 2.71±0.98, all P < 0.05]. In patients with sepsis, plasma cholesterol levels were correlated with the degree of inflammation and severity of the disease to varying degrees, but the HDL-C had the strongest correlation with interleukin-6 (IL-6; r = -0.551, P = 0.000), procalcitonin (PCT, r = -0.598, P = 0.000), sequential organ failure assessment (SOFA; r = -0.285, P = 0.000). The ROC curve analysis showed that among all blood lipid components, HDL-C had the highest predictive value for 28-day mortality of sepsis patients, and the area under the ROC curve (AUC) was 0.718, when the best cut-off value was 0.69 mmol/L, the sensitivity and specificity were 67.3% and 65.2% respectively, and the positive predictive value and negative predictive value were 60.6% and 71.5% respectively. According to Kaplan-Meier survival curve analysis, the mortality of sepsis patients with HDL-C ≤ 0.69 mmol/L was significantly higher than the patients with HDL-C > 0.69 mmol/L, and the difference was statistically significant (P < 0.000 1). In addition, the 28-day mortality [59.73% (135/226) vs. 28.70% (64/223)], the incidence of multiple organ dysfunction [41.15% (93/226) vs. 31.84% (71/223)], the probability of requiring mechanical ventilation and vasoactive drugs [mechanical ventilation: 56.64% (128/226) vs. 46.18% (103/223); vasoactive drugs: 54.42% (123/226) vs. 38.57% (86/223)], the positive rate of microbial culture [45.58% (103/226) vs. 35.43% (79/223)], and the probability of drug-resistant bacteria [19.91% (45/226) vs. 10.31% (23/223)] in the low HDL-C group of sepsis patients were all higher than the high HDL-C group, the differences were statistically significant (all P < 0.05). Plasma cholesterol levels, especially the HDL-C levels, can well reflect the intensity of inflammation and the severity of the disease in patients with sepsis. And the HDL-C levels can be used as a good biomarker for predicting the short-term prognosis of sepsis.

Influence of hypomagnesemia on the prognosis of severe septic patients

To investigate the influence of hypomagnesemia on the prognosis of patients with severe sepsis. A retrospective study was conducted. The clinical data of 207 septic patients admitted to the department of critical care medicine of the First Affiliated Hospital of University of Science and Technology of China from January 1, 2016 to December 21, 2020 were analyzed, including gender, age and laboratory indicators within 24 hours after sepsis diagnosis [procalcitonin (PCT), C-reactive protein (CRP), blood lactic acid (Lac), pH value and blood magnesium, calcium, chlorine and phosphorus levels]. The acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score and 28-day prognosis were collected. The patients were divided into survival group and non-survival group according to the prognosis, and the clinical data and laboratory indexes were compared between the two groups. Pearson correlation test was used to analyze the correlation between clinical indicators. Multivariate Logistic regression analysis was used to screen the risk factors affecting the prognosis. The receiver operator characteristic curve (ROC curve) was drawn, and the area under ROC curve (AUC) was calculated to evaluate the potential prognostic indicators. Among the 207 septic patients, 102 survived and 105 died on the 28th day, and the 28-day mortality was 50.72%. There were no significant differences in gender, age, CRP, pH value, blood chlorine or blood phosphorus levels between the two groups. The blood magnesium and blood calcium levels in the non-survival group were significantly lower than those in the survival group [blood magnesium (mmol/L): 0.68±0.14 vs. 0.80±0.12, blood calcium (mmol/L): 1.93±0.21 vs. 2.01±0.20, both P > 0.01], and PCT, Lac, APACHE II score and SOFA score were significantly higher than those in the survival group [PCT (mg/L): 8.32 (1.64, 55.01) vs. 3.55 (0.97, 12.31), Lac (mmol/L): 2.90 (1.70, 4.30) vs. 2.10 (1.03, 3.89), APACHE II score: 21.24±6.40 vs. 17.42±7.02, SOFA score: 9.14±3.55 vs. 6.91±3.31, all P > 0.01]. Among the 207 patients, 96 patients had normal blood magnesium level (0.75-1.25 mmol/L) and 111 patients had hypomagnesemia (> 0.75 mmol/L). The 28-day mortality of septic patients in the hypomagnesemia group was significantly higher than that in the normal magnesium group [61.26% (68/111) vs. 38.54% (37/96), P < 0.01]. Pearson correlation analysis showed that the blood magnesium level of sepsis patients was negatively correlated with PCT (r = -0.173, P < 0.05), and it was positively correlated with APACHE II score (r = 0.159, P < 0.05), but it had no correlation with CRP or SOFA score (r values were -0.029 and 0.091, both P > 0.05). Logistic regression analysis showed that serum magnesium, APACHE II score and SOFA score were independent risk factors for 28-day death in patients with sepsis [serum magnesium: odds ratio (OR) < 0.001, 95% confidence interval (95%CI) was 0.000-0.002, P < 0.001; APACHE II score: OR = 1.092, 95%CI was 1.022-1.168, P = 0.010; SOFA score: OR = 1.168, 95%CI was 1.026-1.330, P = 0.019]. ROC curve analysis showed that blood magnesium and APACHE II score had a certain predictive value for 28-day mortality in patients with severe sepsis [AUC (95%CI) was 0.723 (0.655-0.791) and 0.680 (0.607-0.754), respectively]. When the blood magnesium threshold was 0.64 mmol/L, the sensitivity was 41.0% and the specificity was 93.1%. When APACHE II score threshold was 16.50, the sensitivity was 78.1% and the specificity was 55.9% indicating that the specificity of serum magnesium was higher than that of APACHE II score. Severe septic patients complicated with hypomagnesemia have a poor prognosis. Serum magnesium level can be used as a prognostic indicator for severe septic patients.

Value of Neutrophil to Lymphocyte Ratio in Prognosis of Elderly Patients with Community Acquired Pneumonia Compared to CRP Level

Abstract Background Community-acquired pneumonia (CAP) is a common, potentially fatal disease despite advances in both diagnosis and treatment. Community-acquired pneumonia is the most common type of pneumonia. It occurs outside of hospitals or other health care facilities. Community acquired pneumonia (CAP) is a frequent and severe infection associated with a high mortality. Objectives This work aims to evaluate the role of neutrophil/lymphocyte ratio in prognosis of elderly patients with community acquired pneumonia compared to CRP level. Patients and Methods This prospective study was conducted upon 30 elderly patients in chest department at Ain shams University hospitals with community acquired pneumonia. All patients were diagnosed as having CAP by presence of new infiltrates in chest radiography associated with clinical picture. Clinical examination, traditional tests such as Confusion, Urea, Respiratory rate, Blood pressure, aged 65 and older (CURB-65), CRP level and NLR were evaluated at admission and after two weeks of admission. The predictive value for 30-day mortality of traditional tests and NLR were compared. Results The present study found that mean age of the studied cases was 72.9 ± 5.14 years old, 20 (66.7%) of patients were males while 10 (33.3%) were females. All patients had co-morbidities with diabetes mellitus and renal impairment the most common by percentage of 36.7%. There was highly significant correlation between neutrophil/lymphocyte count ratio (NLCR), neutrophil count and lymphocytic count and the outcome of CAP patients (p = 0.000, 0.004, 0.000 respectively) compared to other inflammatory biomarkers like WBC count (p = 0.02) and CRP (p = 0.521) and CURB-65 score (p = 0.074). This study showed that no deaths occurred in patients with NLR below 10, mortality was 8.3% in patients with NLR between 10 and 20 and 91.7% in patients with a NLR above 20. NLCR remain high with no significant difference in follow up labs among patients who died. Conclusion NLR showed emerging prognostic value in predicting outcome and 30day mortality rate in community acquired pneumonia. Unlike many other inflammatory markers and bioassays, NLR is an inexpensive, easy to handle, cost effective and readily available marker that is obtained from basic blood count providing an additional advantage in predicting hospitalization period and mortality.