Dataset Information

Reconsidering lactate as a sepsis risk biomarker.

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.

SUBMITTER: Moran JL

PROVIDER: S-EPMC5626033 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Reconsidering lactate as a sepsis risk biomarker.

Moran John L JL Santamaria John J

PloS one 20171003 10

<h4>Objectives</h4>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.<h4>Design, setting and participants</h4>A sepsis cohort was identified from the ICU database of an Australian tertiary referral hospital using APACHE III diagnostic codes. Demographic information, APACHE III sco ...[more]

PMID: 28972976

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Project description:IntroductionThe intrinsic heterogeneity of clinical septic shock is a major challenge. For clinical trials, individual patient management, and quality improvement efforts, it is unclear which patients are least likely to survive and thus benefit from alternative treatment approaches. A robust risk stratification tool would greatly aid decision-making. The objective of our study was to derive and test a multi-biomarker-based risk model to predict outcome in pediatric septic shock.MethodsTwelve candidate serum protein stratification biomarkers were identified from previous genome-wide expression profiling. To derive the risk stratification tool, biomarkers were measured in serum samples from 220 unselected children with septic shock, obtained during the first 24 hours of admission to the intensive care unit. Classification and Regression Tree (CART) analysis was used to generate a decision tree to predict 28-day all-cause mortality based on both biomarkers and clinical variables. The derived tree was subsequently tested in an independent cohort of 135 children with septic shock.ResultsThe derived decision tree included five biomarkers. In the derivation cohort, sensitivity for mortality was 91% (95% CI 70 - 98), specificity was 86% (80 - 90), positive predictive value was 43% (29 - 58), and negative predictive value was 99% (95 - 100). When applied to the test cohort, sensitivity was 89% (64 - 98) and specificity was 64% (55 - 73). In an updated model including all 355 subjects in the combined derivation and test cohorts, sensitivity for mortality was 93% (79 - 98), specificity was 74% (69 - 79), positive predictive value was 32% (24 - 41), and negative predictive value was 99% (96 - 100). False positive subjects in the updated model had greater illness severity compared to the true negative subjects, as measured by persistence of organ failure, length of stay, and intensive care unit free days.ConclusionsThe pediatric sepsis biomarker risk model (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl) reliably identifies children at risk of death and greater illness severity from pediatric septic shock. PERSEVERE has the potential to substantially enhance clinical decision making, to adjust for risk in clinical trials, and to serve as a septic shock-specific quality metric.

Project description:Objectives Our purpose was to investigate the influencing factors for mortality in sepsis patients without lactate levels increasing in the early stage. Methods We conducted a retrospective observational study involving 830 adult sepsis patients admitted to ICU. We calculated time-weighted lactate (LacTW), a dynamic value that incorporates both the magnitude of change and the time interval of such change, to represent lactate levels in the first 24 hours. ROC curve was used to find the cutoff of LacTW for predicting mortality, and the influencing factors for lactate levels and mortality in the low lactate group were further studied. The primary outcome was hospital mortality. Results Among 830 patients, LacTW > 1.975 mmo/L was found to be the cutoff threshold for predicting mortality (AUC = 0.646, P < 0.001). The following indexes related to organ dysfunction influenced LacTW: acute physiology and chronic health evaluation II (APACHE II) score (P < 0.001), activated partial thromboplastin time (APTT) (P = 0.002), total bilirubin (P = 0.012), creatinine (P = 0.037), with hypotension (P < 0.001), chronic kidney disease (P = 0.013), and required continuous renal replacement therapy (CRRT) (P < 0.001). Of the 394 patients in the low lactate group, age (P = 0.002), malignancy (P < 0.001), lactate dehydrogenase (P = 0.006), required treatment such as mechanical ventilation (P < 0.001), CRRT (P < 0.001), vasoactive drugs (P < 0.001), and glucocorticoid (P < 0.001), and failure to reach the target fluid resuscitation of 30 ml/kg within 6 hours (P = 0.003) were independently associated with hospital mortality. Conclusions Due to the lower incidence of early organ dysfunction, lactate levels are not increased or delayed in some septic shock patients in the early stage, thus affecting the alertness of clinicians and the timeliness and adequacy of fluid resuscitation, and finally affects the prognosis.

Project description:ObjectivesTimely empiric antimicrobial therapy is associated with improved outcomes in pediatric sepsis, but minimal data exist to guide empiric therapy. We sought to describe the prevalence of four pathogens that are not part of routine empiric coverage (e.g., Staphylococcus aureus, Pseudomonas aeruginosa, Clostridium difficile, and fungal infections) in pediatric sepsis patients in a contemporary nationally representative sample.DesignThis was a retrospective cohort study using administrative data.SettingWe used the Nationwide Readmissions Database from 2014, which is a nationally representative dataset that contains data from nearly half of all discharges from nonfederal hospitals in the United States.PatientsDischarges of patients who were less than 19 years old at discharge and were not neonatal with a discharge diagnosis of sepsis.InterventionsNone.Measurements and main resultsOf the 19,113 pediatric admissions with sepsis (6,300 [33%] previously healthy and 12,813 [67%] with a chronic disease), 31% received mechanical ventilation, 19% had shock, and 588 (3.1%) died during their hospitalization. Among all admissions, 8,204 (42.9%) had a bacterial or fungal pathogen identified. S. aureus was the most common pathogen identified in previously healthy patients (n = 593, 9.4%) and those with any chronic disease (n = 1,430, 11.1%). Methicillin-resistant S. aureus, P. aeruginosa, C. difficile, and fungal infections all had high prevalence in specific chronic diseases associated with frequent contact with the healthcare system, early surgery, indwelling devices, or immunosuppression.ConclusionsIn this nationally representative administrative database, the most common identified pathogen was S. aureus in previously healthy and chronically ill children. In addition, a high proportion of children with sepsis and select chronic diseases had infections with methicillin-resistant S. aureus, fungal infections, Pseudomonas infections, and C. difficile. Clinicians caring for pediatric patients should consider coverage of these organisms when administering empiric antimicrobials for sepsis.

Dataset Information

Reconsidering lactate as a sepsis risk biomarker.

Objectives

Design, setting and participants

Measurements and main results

Conclusions

Publications

Reconsidering lactate as a sepsis risk biomarker.

Similar Datasets

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