ABSTRACT: OBJECTIVES:There has been renewed interest in lactate as a risk biomarker in sepsis and septic shock. However, the ability of the odds ratio (OR) and change in the area under the receiver operator characteristic curve (AUC-ROC) to assess biomarker added-value has been questioned. DESIGN, SETTING AND PARTICIPANTS:A sepsis cohort was identified from the ICU database of an Australian tertiary referral hospital using APACHE III diagnostic codes. Demographic information, APACHE III scores, 24-hour post-admission patient lactate levels, and hospital mortality were accessed. MEASUREMENTS AND MAIN RESULTS:Hospital mortality was modelled using a base predictive logistic regression model and sequential addition of admission lactate, lactate clearance ([lactateadmission-lactatefinal]/lactateadmission), and area under the lactate-time curve (LTC). Added-value was assessed using lactate index OR; AUC-ROC difference (base-model versus lactate index addition); net (mortality) reclassification index (NRI; range -2 to +2); and net benefit (NB), the number of true positives per patient adjusted for the number of false positives. The data set comprised 717 patients with mean(SD) age and APACHE III score 61.1(16.5) years and 68.3(28.2) respectively; 59.2% were male. Admission lactate was 2.3(2.5) mmol/l; with lactate of ? 4 mmol/L (37% hospital mortality) in 17% and patients with lactate < 4 mmol/L having 18% hospital mortality. The admission base-model had an AUC-ROC = 0.81 with admission lactate OR = 1.127 (95%CI: 1.038, 1.224), AUC-ROC difference of 0.0032 (-0.0037, 0.01615; P = 0.61), and NRI 0.240(0.030, 0.464). The over-time model had an AUC-ROC = 0.86 with (i) clearance OR = 0.771, 95%CI: 0.578, 1.030; P = 0.08; AUC-ROC difference 0.001 (-0.003, 0.014; P = 0.78), and NRI 0.109(-0.193, 0.425) and (ii) LTC OR = 0.997, 95%CI: 0.989, 1.005, P = 0.49; AUC-ROC difference 0.004 (-0.002, 0.004; P = 0.34), and NRI 0.111(-0.222, 0.403). NB was not incremented by any lactate index. CONCLUSIONS:Lactate added-value assessment is dependent upon the performance of the underlying predictive model and should incorporate risk reclassification and net benefit measures.
Project description:BACKGROUND:We performed an exclusive study to investigate the associations between a total of 23 lactate-related indices during the first 24h in an intensive care unit (ICU) and in-hospital mortality. METHODS:Nine static and 14 dynamic lactate indices, including changes in lactate concentrations (? Lac) and slope (linear regression coefficient), were calculated from individual critically ill patient data extracted from the Multiparameter Intelligent Monitoring for Intensive Care (MIMIC) III database. RESULTS:Data from a total of 781 ICU patients were extracted, consisted of 523 survivors and 258 non-survivors. The in-hospital mortality rate for this cohort was 33.0%. A multivariate logistic regression model identified maximal lactate concentration at 24h after ICU admission (max lactate at T24) as a significant predictor of in-hospital mortality (odds ratio = 1.431, 95% confidence interval [CI] = 1.278-1.604, p<0.001) after adjusting for predefined confounders (age, gender, sepsis, Elixhauser comorbidity score, mechanical ventilation, renal replacement therapy, vasopressors, ICU severity scores). Area under curve (AUC) for max lactate at T24 was larger (AUC = 0.776, 95% CI = 0.740-0.812) than other indices (p<0.001), comparable to an APACHE III score of 0.771. When combining max lactate at T24 with APACHE III, the AUC was increased to 0.815 (95% CI:0.783-0.847). The sensitivity, specificity, and positive and negative predictive values for the cut-off value of 3.05 mmol/L were 64.3%, 77.4%, 58.5%, and 81.5%, respectively. Kaplan-Myer survival curves of the max lactate at T24 for 90-day survival after admission to ICU demonstrated a significant difference according to the cut-off value (p<0.001). CONCLUSIONS:These data indicate that the maximal arterial lactate concentration at T24 is a robust predictor of in-hospital mortality as well as 90-day survival in unselected ICU patients with predictive ability as comparable with APACHE III score.
Project description:<b>Objective: </b>To evaluate the usefulness of a new marker, pentraxin, as a prognostic marker in septic shock patients.<br><br><b>Materials and methods: </b>Single-centre prospective observational study that included all consecutive patients 18 years or older who were admitted to the intensive care unit (ICU) with septic shock. Serum levels of procalcitonin (PCT), C-reactive protein (CRP) and pentraxin (PTX3) were measured on ICU admission.<br><br><b>Results: </b>Seventy-five septic shock patients were included in the study. The best predictors of in-hospital mortality were the severity scores: SAPS II (AUC = 0.81), SOFA (AUC = 0.79) and APACHE II (AUC = 0.73). The ROC curve for PTX3 (ng/mL) yielded an AUC of 0.70, higher than the AUC for PCT (0.43) and CRP (0.48), but lower than lactate (0.79). Adding PTX3 to the logistic model increased the predictive capacity in relation to SAPS II, SOFA and APACHE II for in-hospital mortality (AUC 0.814, 0.795, and 0.741, respectively). In crude regression models, significant associations were found between in-hospital mortality and PTX3. This positive association increased after adjusting for age, sex and immunosuppression: adjusted OR T3 for PTX3 = 7.83, 95% CI 1.35-45.49, linear P trend = 0.024.<br><br><b>Conclusion: </b>Our results support the prognostic value of a single determination of plasma PTX3 as a predictor of hospital mortality in septic shock patients.
Project description:We conducted a prospective, observational study to assess the prognostic value of hemostasis-related parameters in unselected ICU patients. We collected baseline characteristics from 497 consecutive unselected medical and trauma patients during their ICU stay. Each hemostasis-related parameter was analyzed alone or combined with APACHE II scores for any association with ICU mortality by calculating the under the curve (AUC) of the ROC curve, the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. Of all hemostasis-related indicators examined, the AUC for fibrin degradation products (FDPs) was less than that for APACHE II scores, but larger than that for disseminated intravascular coagulation (DIC) scores. The prediction power of FDPs is relatively low. Multiple regression analysis revealed that FDPs and APACHE II scores significantly predicted primary outcome. The combined use of FDPs level and APACHE II scores generated an NRI of 9.94% and an IDI of 3.54%. In conclusion, FDP is the best independent indicator of ICU mortality among all hemostasis-related indicators examined. The use of FDP level and APACHE II scores in parallel significantly improves the ability to predict ICU mortality, suggesting the application of these parameters could be used to improve patient care and management in the ICU.
Project description:Background:Lactate has been widely used as a risk indicator of outcomes in critically ill patients due to its ready measurement and good predictive ability. However, the interconnections between lactate metabolism and glucose metabolism have not been sufficiently explored, yet. In this study, we aimed to investigate whether glucose levels could influence the predictive ability of lactate and design a more comprehensive strategy to assess the in-hospital mortality of critically ill patients. Methods:We analyzed the clinical data of 293 critically ill patients. The primary outcome was in-hospital mortality. The logistic regression analysis and the area under the receiver operating characteristic curve (AUROC) were applied to evaluate the predictive ability of lactate in association with glucose. Results:The lactate level showed significant association with in-hospital mortality, and its predictive ability was also comparable to other prognostic scores such as the SOFA score and APACHE II score. We further divided 293 patients into three groups based on glucose levels: low-glucose group (<7?mmol/L), medium-glucose group (7-9?mmol/L), and high-glucose group (>9?mmol/L). The lactate level was associated with in-hospital mortality in the low- and high- glucose groups, but not in the medium-glucose group, whereas the SOFA score and APACHE II score were associated with in-hospital mortality in all three glucose groups. The AUROC of lactate in the medium-glucose group was also the lowest among the three glucose groups, indicating a decrease in its predictive ability. Conclusions:Our findings demonstrated that the predictive ability of lactate to assess in-hospital mortality could be influenced by glucose levels. In the medium glucose level (i.e., 7-9?mmol/L), lactate was inadequate to predict in-hospital mortality and the SOFA score; the APACHE II score should be utilized as a complementation in order to obtain a more accurate prediction.
Project description:Outcome prediction of critically ill patients is an integral part of care in an Intensive Care Unit (ICU). Acute Physiology and Chronic Health Evaluation (APACHE) scoring systems provide an objective means of mortality prediction in ICU. The aim of this study was to compare the performance of APACHE II and IV scoring system in our ICU.All patients admitted to the ICU between January and June 2014 and who met the inclusion criteria were evaluated. APACHE II and IV score were calculated during the first 24 h of ICU stay based on the worst values. All patients were followed up till discharge from the hospital or death. Statistical analysis was performed using SPSS version 19.0. Discrimination of the model for mortality was assessed using receiver operating characteristic curve and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test.Of a total 1268, 1003 patients were included in this study. The mean (±standard deviation) admission APACHE II score was 19.4 ± 8.9, and APACHE IV score was 59.1 ± 27.2. The APACHE scores were significantly higher among nonsurvivors than survivors (P < 0.001). The overall crude hospital mortality rate was 17.6%. APACHE IV had better discriminative power area under the ROC curve ([AUC] -0.82) than APACHE II (AUC-0.75). Both APACHE II and APACHE IV had poor calibration.APACHE IV showed better discrimination compared to APACHE II in our ICU population. Both APACHE II and APACHE IV had poor calibration. However, APACHE II calibrated better compared to APACHE IV.
Project description:Although significant improvements have been achieved in the renal replacement therapy of acute kidney injury (AKI), the mortality of patients with AKI remains high. The aim of this study is to prospectively investigate the capacity of Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II), Sepsis-related Organ Failure Assessment (SOFA) and Acute Tubular Necrosis Individual Severity Index (ATN-ISI) to predict in-hospital mortality of critically ill patients with AKI. A prospective observational study was conducted in a university teaching hospital. 189 consecutive critically ill patients with AKI were selected according Risk, Injury, Failure, Loss, or End-stage kidney disease criteria. APACHE II, SAPS II, SOFA and ATN-ISI counts were obtained within the first 24?hours following admission. Receiver operating characteristic analyses (ROCs) were applied. Area under the ROC curve (AUC) was calculated. Sensitivity and specificity of in-hospital mortality prediction were calculated. In this study, the in-hospital mortality of critically ill patients with AKI was 37.04% (70/189). AUC of APACHE II, SAPS II, SOFA and ATN-ISI was 0.903 (95% CI 0.856 to 0.950), 0.893 (95% CI 0.847 to 0.940), 0.908 (95% CI 0.866 to 0.950) and 0.889 (95% CI 0.841 to 0.937) and sensitivity was 90.76%, 89.92%, 90.76% and 89.08% and specificity was 77.14%, 70.00%, 71.43% and 71.43%, respectively. In this study, it was found APACHE II, SAPS II, SOFA and ATN-ISI are reliable in-hospital mortality predictors of critically ill patients with AKI. Trial registration number: NCT00953992.
Project description:<h4>Objective</h4>Mortality in heart failure (AHF) remains high, especially during the first days of hospitalization. New prognostic biomarkers may help to optimize treatment. The aim of the study was to determine metabolites that have a high prognostic value.<h4>Methods</h4>We conducted a prospective study on a training cohort of AHF patients (n = 126) admitted in the cardiac intensive care unit and assessed survival at 30 days. Venous plasmas collected at admission were used for (1)H NMR--based metabonomics analysis. Differences between plasma metabolite profiles allow determination of discriminating metabolites. A cohort of AHF patients was subsequently constituted (n = 74) to validate the findings.<h4>Results</h4>Lactate and cholesterol were the major discriminating metabolites predicting 30-day mortality. Mortality was increased in patients with high lactate and low total cholesterol concentrations at admission. Accuracies of lactate, cholesterol concentration and lactate to cholesterol (Lact/Chol) ratio to predict 30-day mortality were evaluated using ROC analysis. The Lact/Chol ratio provided the best accuracy with an AUC of 0.82 (P < 0.0001). The acute physiology and chronic health evaluation (APACHE) II scoring system provided an AUC of 0.76 for predicting 30-day mortality. APACHE II score, Cardiogenic shock (CS) state and Lact/Chol ratio ? 0.4 (cutoff value with 82% sensitivity and 64% specificity) were significant independent predictors of 30-day mortality with hazard ratios (HR) of 1.11, 4.77 and 3.59, respectively. In CS patients, the HR of 30-day mortality risk for plasma Lact/Chol ratio ? 0.4 was 3.26 compared to a Lact/Chol ratio of < 0.4 (P = 0.018). The predictive power of the Lact/Chol ratio for 30-day mortality outcome was confirmed with the independent validation cohort.<h4>Conclusion</h4>This study identifies the plasma Lact/Chol ratio as a useful objective and simple parameter to evaluate short term prognostic and could be integrated into quantitative guidance for decision making in heart failure care.
Project description:The development of renal and liver dysfunction may be accompanied by initially subtle derangements in the gluconeogenetic function. Discrepantly low glucose levels combined with high lactate levels might indicate an impaired Cori cycle. Our objective was to examine the relation between early lactate and glucose levels with subsequent renal and liver dysfunction and hospital mortality in critically ill patients.Over a 4-year period (2011 to 2014), all adult patients admitted to our adult 48-bed teaching hospital intensive care unit (ICU) for at least 12 h were retrospectively analyzed. Lactate and glucose were regularly measured with point-of-care analyzers in all ICU patients. Lactate and glucose measurements were collected from 6 h before to 24 h after ICU admission. Patients with fewer than four lactate/glucose measurements were excluded. Patients received insulin according to a computer-guided control algorithm that aimed at a glucose level <8.0 mmol/L. Renal dysfunction was defined as the development of acute kidney injury (AKI) within 7 days, and liver function was based on the maximal bilirubin in the 7-day period following ICU admission. Mean lactate and mean glucose were classified into quintiles and univariate and multivariate analyses were related with renal and liver dysfunction and hospital mortality. Since glucose has a known U-shaped relation with outcome, we also accounted for this.We analyzed 92,000 blood samples from 9074 patients (63% males) with a median age of 64 years and a hospital mortality of 11%. Both lactate quintiles (?1.0; 1.0-1.3; 1.3-1.7; 1.7-2.3; >2.3 mmol/L) and glucose quintiles (?7.0; 7.0-7.6; 7.6-8.2; 8.2-9.0; >9.0 mmol/L) were related with outcome in univariate analysis (p?<?0.001). Acute Physiology and Chronic Health Evaluation (APACHE) IV, lactate, and glucose were associated with renal and liver dysfunction in multivariate analysis (p?<?0.001), with a U-shaped relationship for glucose. The combination of the highest lactate quintile with the lowest glucose quintile was associated with the highest rates of renal dysfunction, liver dysfunction, and mortality (p?<?0.001) with a significant interaction between lactate and glucose (p???0.001).Abnormal combined lactate and glucose measurements may provide an early indication of organ dysfunction. In critically ill patients a 'normal' glucose with an elevated lactate should not be considered desirable, as this combination is related with increased mortality.
Project description:OBJECTIVE:To determine the prognostic value of cortisol, Dehydroepiandrosterone (DHEA) and Dehydroepiandrosterone-sulfate (DHEAS), together with their ratios (cortisol/DHEA and cortisol/DHEAS), as independent predictors of mortality in septic patients. METHODS:Prospective cohort study of 139 consecutive patients with a diagnosis of severe sepsis or septic shock. Adrenal hormones were determined within the first 24 hours of the septic process. To determine and compare the predictive ability of each marker for the risk of unfavorable evolution (in-hospital, 28-day and 90-day mortality), ROC (Receiver Operating Characteristic) curves were constructed and the area under the curve (AUC) was determined. As measures of association, adjusted odds ratios (OR) with their 95% confidence intervals (95%CI) were estimated by unconditional logistic regression. Cortisol, DHEA and DHEAS results were compared to lactate, CRP, SOFA and APACHE II Scores. RESULTS:Cortisol showed the best predictive ability, with AUCs of 0.758, 0.759 and 0.705 for in-hospital mortality, and 28-day and 90-day mortality, respectively; whereas AUCs for 28 days mortality for SOFA and APACHE II scores, and other biomarkers studied, such as Lactate or CRP, were 0.644, 0.618, 0.643 and 0.647, respectively. Associations between high cortisol levels (>17.5 ?g/dL) and mortality were strong and statistically significant for in-hospital and 28-day mortality: adjusted ORs 10.13 and 9.45 respectively, and lower for long term mortality (90 days): adjusted OR 4.26 (95% CI 1.34-13.56), p trend 0.014. Regarding adrenal androgens, only positive associations were obtained for DHEAS and most of these positive associations did not yield statistical significance. Regarding Cortisol/DHEA and cortisol/DHEAS ratios, they did not improve the predictive ability of cortisol. The only exception was the cortisol/DHEAS ratio, which was the best predictor of mortality at 90 days (AUC 0.737), adjusted OR for highest cortisol/DHEAS ratio values 6.33 (95%CI 1.77-22.60), p trend 0.002. CONCLUSION:Basal cortisol measured within the first 24 hours of the septic process was the best prognostic factor for in-hospital and 28-day mortality, even superior to the Sequential Organ Failure Assessment (SOFA) or Acute Physiology and Chronic Health Evaluation II (APACHE II) scores. The cortisol/DHEAS ratio was an independent predictor of long-term mortality.
Project description:<h4>Objective</h4>This study assessed the ability of the Acute Physiologic and Chronic Health Evaluation (APACHE) II score, Simplified Acute Physiology Score (SAPS) II, Sequential Organ Failure Assessment (SOFA) score, and out-of-hospital cardiac arrest (OHCA) score to predict the outcome of OHCA patients who underwent therapeutic hypothermia (TH).<h4>Methods</h4>This study included OHCA patients treated with TH between January 2010 and December 2013. The APACHE II score, SAPS II, and SOFA score were calculated at the time of admission and 24 h and 48 h after intensive care unit admission. The OHCA score was calculated at the time of admission. The area under the curve (AUC) of the receiver operating characteristic curve and logistic regression analysis were used to evaluate outcome predictability.<h4>Results</h4>Data from a total of 173 patients were included in the analysis. The APACHE II score at 0 h and 48 h, SAPS II at 48 h, and OHCA score had moderate discrimination for mortality (AUC: 0.715, 0.750, 0.720, 0.740). For neurologic outcomes, the APACHE II score at 0 h and 48 h, SAPS II at 0 h and 48 h, and OHCA score showed moderate discrimination (AUC: 0.752, 0.738, 0.771, 0.771, 0.764). The APACHE II score, SAPS II and SOFA score at various time points, in addition to the OHCA score, were independent predictors of mortality and a poor neurologic outcome.<h4>Conclusions</h4>The APACHE II score, SAPS II, SOFA score, and OHCA score have different capabilities in discriminating and estimating hospital mortality and neurologic outcomes. The OHCA score, APACHE II score and SAPS II at time zero and 48 h offer moderate predictive accuracy. Other scores at 0 h and 48 h, except for the SOFA score, are independently associated with 30-day mortality and poor cerebral performance.