Serial evaluation of the serum lactate level with the SOFA score to predict mortality in patients with sepsis.
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SUBMITTER: Park H
PROVIDER: S-EPMC10113181 | biostudies-literature | 2023 Apr
REPOSITORIES: biostudies-literature
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Serial evaluation of the serum lactate level with the SOFA score to predict mortality in patients with sepsis.
Park Heemoon H Lee Jinwoo J Oh Dong Kyu DK Park Mi Hyeon MH Lim Chae-Man CM Lee Sang-Min SM Lee Hong Yeul HY
Scientific reports 20230418 1
In patients with sepsis, outcome prediction plays an important role in influencing therapeutic decision making. In this nationwide, prospective, observational cohort study of sepsis patients conducted between September 2019 and December 2020, we evaluated a novel scoring system using serial Sequential Organ Failure Assessment (SOFA) scores and serum lactate to accurately predict mortality in sepsis. Based on the serum lactate score (Lac-score), patients were assigned to 5 categories: lactate < 2 ...[more]
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Project description:BackgroundSepsis is a common critical condition caused by the body's overwhelming response to certain infective agents. Many biomarkers, including the serum lactate level, have been used for sepsis diagnosis and guiding treatment. Recently, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) recommended the Sequential Organ Failure Assessment (SOFA) and the quick SOFA (qSOFA) rather than lactate for screening sepsis and assess prognosis. Here, we aim to explore and compare the prognostic accuracy of the lactate level, the SOFA score and the qSOFA score for mortality in septic patients using the public Medical Information Mart for Intensive Care III database (MIMIC III).MethodsThe baseline characteristics, laboratory test results and outcomes for sepsis patients were retrieved from MIMIC III. Survival was analysed by the Kaplan-Meier method. Univariate and multivariate analysis was performed to identify predictors of prognosis. Receiver operating characteristic curve (ROC) analysis was conducted to compare lactate with SOFA and qSOFA scores.ResultsA total of 3713 cases were initially identified. The analysis cohort included 1865 patients. The 24-h average lactate levels and the worst scores during the first 24 h of ICU admission were collected. Patients in the higher lactate group had higher mortality than those in the lower lactate group. Lactate was an independent predictor of sepsis prognosis. The AUROC of lactate (AUROC, 0.664 [95% CI, 0.639-0.689]) was significantly higher than that of qSOFA (AUROC, 0.547 [95% CI, 0.521-0.574]), and it was similar to the AUROC of SOFA (AUROC, 0.686 [95% CI, 0.661-0.710]). But the timing of lactate relative to SOFA and qSOFA scores was inconsistent.ConclusionLactate is an independent prognostic predictor of mortality for patients with sepsis. It has superior discriminative power to qSOFA, and shows discriminative ability similar to that of SOFA.
| S-EPMC6492372 | biostudies-literature
Project description:PurposeThe final decision for discharge from the intensive care unit (ICU) is uncertain because it is made according to various patient parameters; however, it should be made on an objective evaluation. Previous reports have been inconsistent and unreliable in predicting post-ICU mortality. To identify predictive factors associated with post-ICU mortality, we analyzed physiological and laboratory data at ICU discharge.MethodsPatients admitted to our ICU between September 2012 and August 2013 and staying for critical care>2 days were included. Sequential Organ Failure Assessment (SOFA) score; systemic inflammatory response syndrome score; white blood cell count; and serum C reactive protein, procalcitonin (PCT), interleukin-6 (IL-6), lactate, albumin, and hemoglobin levels were recorded. The primary end point was 90-day mortality after ICU discharge. Two hundred eighteen patients were enrolled (195 survivors, 23 non-survivors).ResultsNon-survivors presented a higher SOFA score and serum PCT, and IL-6 levels, as well as lower serum albumin and hemoglobin levels. Serum PCT, albumin, and SOFA score were associated with 90-day mortality in multiple logistic regression analysis. Hosmer-Lemeshow test showed chi-square value of 6.96, and P value of 0.54. The area under the curve (95% confidence interval) was 0.830 (0.771-0.890) for PCT, 0.688 (0.566-0.810) for albumin, 0.861 (0.796-0.927) for SOFA score, and increased to 0.913 (0.858-0.969) when these were combined. Serum PCT level at 0.57 ng/mL, serum albumin at 2.5 g/dL and SOFA score at 5.5 predict 90-day mortality, and high PCT, low albumin and high SOFA groups had significantly higher mortality. Serum PCT and SOFA score were significantly associated with survival days after ICU discharge in Cox regression analysis.ConclusionsSerum PCT level and SOFA score at ICU discharge predict post-ICU mortality and survival days after ICU discharge. The combination of these two and albumin level might enable accurate prediction.
| S-EPMC4252062 | biostudies-literature
Project description:PurposeThe Quick Sequential Organ Failure Assessment (qSOFA) score proposed by Sepsis-3 as a sepsis screening tool has shown suboptimal accuracy. Heparin-binding protein (HBP) has been shown to identify early sepsis with high accuracy. Herein, we aim to investigate whether or not HBP improves the model performance of qSOFA.MethodsWe conducted a multicenter prospective observational study of 794 adult patients who presented to the emergency department (ED) with presumed sepsis between 2018 and 2019. For each participant, serum HBP levels were measured and the hospital course was followed. The qSOFA score was used as the comparator. The data was split into a training dataset (n = 556) and a validation dataset (n = 238). The primary endpoint was 30-day all-cause mortality.ResultsCompared with survivors, non-survivors had significantly higher serum HBP levels (median: 71.5 ng/mL vs 209.5 ng/mL, p < 0.001). Serum level of HBP weakly correlated with qSOFA class (r 2 = 0.240, p < 0.001). Compared with the qSOFA model alone, the addition of admission HBP level to the qSOFA model significantly improved 30-day mortality discrimination (AUC, 0.70 vs. 0.80; P < 0.001), net reclassification improvement [26% (CI, 17-35%); P < 0.001], and integrated discrimination improvement [12% (CI, 9-14%); P < 0.001]. Addition of C-reactive protein (CRP) level or neutrophil-to-lymphocyte ratio (NLR) to qSOFA did not improve its performance. A web-based mortality risk prediction calculator was created to facilitate clinical implementation.ConclusionThis study confirms the value of combining qSOFA and HBP in predicting sepsis mortality. The web calculator provides a user-friendly tool for clinical implementation. Further validation in different patient populations is needed before widespread application of this prediction model.
| S-EPMC9402998 | biostudies-literature
Project description:ObjectiveIn intensive care settings, blood lactate level measurement proved to be an excellent predictor of outcomes. In patients requiring less urgent treatment, the arterial blood lactate is less sensitive and its usefulness remains to be proven. Capillary blood lactate dosing, an emergent point-of-care technique readily available should be more sensitive to changes in these settings.Methodprospective, observational, monocentric study conducted in a polyvalent internal medicine ward in a French University Hospital. The inclusion criteria were the existence of new symptoms of abrupt onset in an otherwise stable patient. All the patients had a point of care measurement of baseline capillary and venous lactate levels (EDGE, ApexBio) and standardized control before any therapeutic means were initiated. A follow-up test was performed once again within 12 to 36 hours. All the patients received standard medical care adapted to their condition. The primary outcomes were considered dying within 30 days or requiring intensive care or invasive therapeutic procedures.Results13 patients were analyzed. Seven patients reached the composite outcome with 3 deaths. The superimposed complication proved to be infectious in every case. The median lactate levels were at baseline (mmol/ l): capillary Mc0=5.2(2.16), venous Mv0=2.3(2.0) and arterial Ma0=1.8(1.7) and at follow-up (mmol/ l) capillary: Mc1=3.3(1.1), venous Mv1=1.8(1.8) and arterial Ma1=1.3(0.7). In nonparametric analysis, the absence of normalization of capillary lactate at follow-up was correlated well with poor outcomes (p=.05). This was not the case of arterial or venous lactate measurements. The positive lactate clearance was present in the majority of patients (83.3%) but it did not predict the outcomes (p=.435) and there was no correlation between the baseline lactate and the clinical outcome (p>.05).ConclusionIn non intensive care settings, capillary lactate level could be a more sensitive method than the classical lactate measurement for predicting the outcomes of acute conditions, especially infectious. A persistently high lactate level rather than its initial value or clearance seems to correlate better with poorer outcomes.AbbreviationsSSC = Surviving sepsis campaign, ED = Emergency department, ICU = intensive care unit, , POC = Point of care, ICC = inter class coefficient.
| S-EPMC5152613 | biostudies-literature
Project description:Early prognostic prediction of sepsis is essential in adjusting therapeutic protocols to prevent deterioration and reduce mortality. We compared the predictive value of the serum concentration of the soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) for 28-day mortality and for the development of severe sepsis or septic shock on the third day with the levels of interleukin (IL)-6, C-reactive protein (CRP) and procalcitonin (PCT). The study was conducted on 85 patients with sepsis. sTREM-1, CRP, PCT and IL-6 concentrations were measured upon study inclusion (day 0) and on days 1, 2, 3 and 5. APACHE II, SAPS II and SOFA scores were analyzed. The sTREM-1 levels (pg/ml) were higher in non-survivors than in survivors at admission (773 vs. 391, p < 0.001) and on days 1, 2, 3 and 5. In predicting the development of severe sepsis, the highest AUCs were found for PCT (0.744, 95% CI 0.638-0.85) and sTREM-1 (0.664, 95% CI 0.55-0.778); and in septic shock prediction, for PCT (0.766, 95% CI 0.665-0.867) and IL-6 (0.707, 95% CI 0.595-0.819). sTREM-1 positively correlated with APACHE II, SAPS II and SOFA scores. At inclusion, significant AUC for predicting 28-day mortality was 0.772 for the sTREM-1 (95% CI 0.672-0.871), 0.858 for APACHE II (95% CI 0.768-0.948), 0.847 for SAPS II (95% CI 0.733-0.96), 0.806 for SOFA score (95% CI 0.698-0.915). sTREM-1 can early predict the 28-day sepsis mortality, although its effectiveness is lower in comparison with clinical severity scores.
| S-EPMC6061141 | biostudies-literature
Project description:IntroductionSepsis has the characteristics of high incidence, high mortality of ICU patients. Early assessment of disease severity and risk stratification of death in patients with sepsis, and further targeted intervention are very important. The purpose of this study was to develop machine learning models based on sequential organ failure assessment (SOFA) components to early predict in-hospital mortality in ICU patients with sepsis and evaluate model performance.MethodsPatients admitted to ICU with sepsis diagnosis were extracted from MIMIC-IV database for retrospective analysis, and were randomly divided into training set and test set in accordance with 2:1. Six variables were included in this study, all of which were from the scores of 6 organ systems in SOFA score. The machine learning model was trained in the training set and evaluated in the validation set. Six machine learning methods including linear regression analysis, least absolute shrinkage and selection operator (LASSO), Logistic regression analysis (LR), Gaussian Naive Bayes (GNB) and support vector machines (SVM) were used to construct the death risk prediction models, and the accuracy, area under the receiver operating characteristic curve (AUROC), Decision Curve Analysis (DCA) and K-fold cross-validation were used to evaluate the prediction performance of developed models.ResultA total of 23,889 patients with sepsis were enrolled, of whom 3659 died in hospital. Three feature variables including renal system score, central nervous system score and cardio vascular system score were used to establish prediction models. The accuracy of the LR, GNB, SVM were 0.851, 0.844 and 0.862, respectively, which were better than linear regression analysis (0.123) and LASSO (0.130). The AUROCs of LR, GNB and SVM were 0.76, 0.76 and 0.67, respectively. K-fold cross validation showed that the average AUROCs of LR, GNB and SVM were 0.757 ± 0.005, 0.762 ± 0.006, 0.630 ± 0.013, respectively. For the probability threshold of 5-50%, LY and GNB models both showed positive net benefits.ConclusionThe two machine learning-based models (LR and GNB models) based on SOFA components can be used to predict in-hospital mortality of septic patients admitted to ICU.
| S-EPMC9903420 | biostudies-literature
Project description:Abstract Background and Aim The efficacy of Sequential Organ Failure Assessment (SOFA) score as predictor of clinical outcomes among ICU‐admitted COVID‐19 patients is still controversial. We aimed to assess whether SOFA‐score in different time intervals could predict 28‐day mortality compared with other well‐acknowledged risk factors of COVID‐19 mortality. Methods This observational prospective cohort was conducted on 1057 patients from March 2020 to March 2022 at Masih Daneshvari Hospital, Iran. The univariate and multivariate Cox proportional analysis were performed to assess the hazards of SOFA‐score models. Receiver operating characteristic (ROC) curves were designed to estimate the predictive values. Results Mean SOFA‐score during first 96 h (HR: 3.82 [CI: 2.75–5.31]), highest SOFA‐score (HR: 2.70 [CI: 1.93–3.78]), and initial SOFA‐score (HR: 1.65 [CI: 1.30–2.11]) had strongest association with 28‐day mortality (p < .0001). In contrast, SOFA scores at 48 and 96 h as well as Δ‐SOFA: 48‐0 h and Δ‐SOFA: 96‐0 h did not show significant correlations. Among them, merely mean SOFA‐score (HR: 2.28 [CI: 2.21–3.51]; p < .001) remained as independent prognosticator on multivariate regression analysis; though having less odds of predicting value compared with age (HR: 3.81 [CI: 1.98–5.21]), hypertension (HR: 3.11 [CI: 1.26–3.81]), coronary artery disease [CAD] (HR: 2.82 [CI: 1.51–4.8]), and diabetes mellitus (HR: 2.45 [CI: 1.36–2.99]). The area under ROC (AUROC) for mean SOFA‐score (0.77) and highest SOFA‐score (0.71) were larger than other SOFA intervals. Calculating the first 96 h of SOFA trends, it was obtained that fatality rate was <12.3% if the score dropped, between 28.8% and 46.29% if the score remained unchanged, and >50.45% if the score increased. Conclusion To predict the 28‐day mortality among ICU‐admitted COVID‐19 patients, mean SOFA upon first 96 h of ICU stay is reliable; while having inadequate accuracy comparing with well‐acknowledged COVID‐19 mortality predictors (age, diabetes mellitus, hypertension, CAD). Notably, increased SOFA levels in the course of first 96 h of ICU‐admission, prognosticate at least 50% fatality regardless of initial SOFA score.
| S-EPMC10154817 | biostudies-literature
Project description:The most common scoring system for critically ill patients is the Sequential Organ Failure Assessment (SOFA) score. Little is known about specific molecular signaling networks underlying the SOFA criteria. We characterized these networks and identified specific key regulatory molecules. We prospectively studied seven patients with sepsis and six controls with high-throughput RNA sequencing (RNAseq). Quantitative reverse transcription PCR (RT-qPCR) confirmation was performed in a second independent cohort. Differentially and significantly expressed miRNAs and their target mRNA transcripts were filtered for admission SOFA criteria and marker RNAs for the respective criteria identified. We bioinformatically constructed molecular signaling networks specifically reflecting these criteria followed by RT-qPCR confirmation of RNAs with important regulatory functions in the networks in the second cohort. RNAseq identified 82 miRNAs (45% upregulated) and 3254 mRNAs (50% upregulated) differentially expressed between sepsis patients and controls. Bioinformatic analysis characterized 6 miRNAs and 76 mRNA target transcripts specific for the SOFA criteria. RT-qPCR validated miRNA and mRNAs included IGFBP2 (respiratory system); MMP9 and PDE4B (nervous system); PPARG (cardiovascular system); AKR1B1, ANXA1, and LNC2/NGAL (acute kidney injury); GFER/ALR (liver); and miR-30c-3p (coagulopathy). There are specific canonical networks underlying the SOFA score. Key regulatory miRNA and mRNA transcripts support its biologic validity.
| S-EPMC8468706 | biostudies-literature
Project description:PURPOSE:Sepsis is a common acute life-threatening condition that emergency physicians routinely face. Diagnostic options within the Emergency Department (ED) are limited due to lack of infrastructure, consequently limiting the use of invasive hemodynamic monitoring or imaging tests. The mortality rate due to sepsis can be assessed via multiple scoring systems, for example, mortality in emergency department sepsis (MEDS) score and sepsis patient evaluation in the emergency department (SPEED) score, both of which quantify the variation of mortality rates according to clinical findings, laboratory data, or therapeutic interventions. This study aims to improve the management processes of sepsis patients by comparing SPEED score and MEDS score for predicting the 28-day mortality in cases of emergency sepsis. METHODS:The study is a cross-sectional, prospective study including 61 sepsis patients in ED in Suez Canal University Hospital, Egypt, from August 2017 to June 2018. Patients were selected by two steps: (1) suspected septic patients presenting with at least one of the following abnormal clinical findings: (a) body temperature higher than 38 °C or lower than 36 °C, (b) heart rate higher than 90 beats/min, (c) hyperventilation evidenced by respiratory rate higher than 20 breaths/min or PaCO2 lower than 32 mmHg, and (d) white blood cell count higher than 12,000/μL or lower than 4000/μL; (2) confirmed septic patients with at least a 2-point increase from the baseline total sequential organ failure assessment (SOFA) score following infection. Other inclusion criteria included adult patients with an age ≥18 years regardless of gender and those who had either systemic inflammatory response syndrome or suspected/confirmed infection. Patients were shortly follow-up for the 28-day mortality. Each patient was subject to SPEED score and MEDS score and then the results were compared to detect which of them was more effective in predicting outcome. The receiver operating characteristic curves were also done for MEDS and SPEED scores. RESULTS:Among the 61 patients, 41 died with the mortality rate of 67.2%. The mortality rate increased with a higher SPEED and MEDS scores. Both SPEED and MEDS scores revealed significant difference between the survivors and nonsurvivors (p = 0.004 and p < 0.001, respectively), indicating that both the two systems are effective in predicting the 28-day mortality of sepsis patients. Thereafter, the receiver operating characteristic curves were plotted, which showed that SPEED was better than the MEDS score when applied to the complete study population with an area under the curve being 0.87 (0.788-0.963) as compared with 0.75 (0.634-0.876) for MEDS. Logistic regression analysis revealed that the best fitting predictor of 28-day mortality for sepsis patients was the SPEED scoring system. For every one unit increase in SPEED score, the odds of 28-day mortality increased by 37%. CONCLUSION:SPEED score is more useful and accurate than MEDS score in predicting the 28-day mortality among sepsis patients. Therefore SPEED rather than MEDS should be more widely used in the ED for sepsis patients.
| S-EPMC6921192 | biostudies-literature
Project description:BackgroundSepsis presents a significant healthcare challenge, characterized by high morbidity and mortality rates. There is a scarcity of relevant studies investigating the association between serum lactate dehydrogenase level and the prognosis of sepsis in patients from intensive care unit, with smaller sample sizes compared to other studies.MethodsA retrospective analysis was conducted utilizing data from the Second Affiliated Hospital of Guangzhou Medical University and the Medical Information Mart for Intensive Care IV (MIMIC-IV). The primary outcome was the in-hospital mortality. Multivariate Cox proportional hazards regression was adopted to assess the independent association. Receiver operator characteristic (ROC) curve was used to evaluate the predictive value.ResultsWe included a total of 2148 patients in the Guangzhou Sepsis Cohort (GZSC) database and 5830 patients in the MIMIC-IV database. In multivariate Cox proportional hazards regression, high levels of LDH are significantly associated with higher mortality (HR = 1.21, 95% CI 1.13-1.30, p < 0.001 in the GZSC database and HR = 1.19, 95% CI 1.13-1.25, p < 0.001 in the MIMIC-IV database). The ROC curves showed that the AUC of LDH was 0.663 in the GZSC database and 0.660 in the MIMIC-IV database.ConclusionsA lower lactate dehydrogenase level is associated with reduced in-hospital mortality among patients with sepsis, suggesting its potential as a valuable marker for predicting prognosis in this patient population.
| S-EPMC11531135 | biostudies-literature