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Comparison of pediatric scoring systems for mortality in septic patients and the impact of missing information on their predictive power: a retrospective analysis.

ABSTRACT: Background:Scores can assess the severity and course of disease and predict outcome in an objective manner. This information is needed for proper risk assessment and stratification. Furthermore, scoring systems support optimal patient care, resource management and are gaining in importance in terms of artificial intelligence. Objective:This study evaluated and compared the prognostic ability of various common pediatric scoring systems (PRISM, PRISM III, PRISM IV, PIM, PIM2, PIM3, PELOD, PELOD 2) in order to determine which is the most applicable score for pediatric sepsis patients in terms of timing of disease survey and insensitivity to missing data. Methods:We retrospectively examined data from 398 patients under 18 years of age, who were diagnosed with sepsis. Scores were assessed at ICU admission and re-evaluated on the day of peak C-reactive protein. The scores were compared for their ability to predict mortality in this specific patient population and for their impairment due to missing data. Results:PIM (AUC 0.76 (0.68-0.76)), PIM2 (AUC 0.78 (0.72-0.78)) and PIM3 (AUC 0.76 (0.68-0.76)) scores together with PRSIM III (AUC 0.75 (0.68-0.75)) and PELOD 2 (AUC 0.75 (0.66-0.75)) are the most suitable scores for determining patient prognosis at ICU admission. Once sepsis is pronounced, PELOD 2 (AUC 0.84 (0.77-0.91)) and PRISM IV (AUC 0.8 (0.72-0.88)) become significantly better in their performance and count among the best prognostic scores for use at this time together with PRISM III (AUC 0.81 (0.73-0.89)). PELOD 2 is good for monitoring and, like the PIM scores, is also largely insensitive to missing values. Conclusion:Overall, PIM scores show comparatively good performance, are stable as far as timing of the disease survey is concerned, and they are also relatively stable in terms of missing parameters. PELOD 2 is best suitable for monitoring clinical course.

SUBMITTER: Niederwanger C

PROVIDER: S-EPMC7543722 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comparison of pediatric scoring systems for mortality in septic patients and the impact of missing information on their predictive power: a retrospective analysis.

Niederwanger Christian C Varga Thomas T Hell Tobias T Stuerzel Daniel D Prem Jennifer J Gassner Magdalena M Rickmann Franziska F Schoner Christina C Hainz Daniela D Cortina Gerard G Hetzer Benjamin B Treml Benedikt B Bachler Mirjam M

PeerJ 20201005

<h4>Background</h4>Scores can assess the severity and course of disease and predict outcome in an objective manner. This information is needed for proper risk assessment and stratification. Furthermore, scoring systems support optimal patient care, resource management and are gaining in importance in terms of artificial intelligence.<h4>Objective</h4>This study evaluated and compared the prognostic ability of various common pediatric scoring systems (PRISM, PRISM III, PRISM IV, PIM, PIM2, PIM3, ...[more]

PMID: 33083117

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Project description:BACKGROUND:An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted ISS (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. METHODS:Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank. The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients younger than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. RESULTS:The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 versus 0.86 in ISS of 1 to 74 and 0.77 versus 0.64 in ISS of 25 to 74 (p < 0.0001). The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 vs. 19.7 for ISS = 1-74 and 10.9 vs. 12.6 for ISS = 25-74). The wISS showed even better discrimination with the Nationwide Emergency Department Sample. CONCLUSION:By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children. LEVEL OF EVIDENCE AND STUDY TYPE:Prognostic/epidemiological, level IV.

Project description:BackgroundPediatric postcardiotomy veno-arterial extracorporeal membrane oxygenation (VA-ECMO) patients have high mortality and morbidity. There are currently three scoring systems available to predict mortality: the Pediatric Extracorporeal Membrane Oxygenation Prediction (PEP) model, Precannulation Pediatric Survival After VA-ECMO (Pedi-SAVE) score, and Postcannulation Pedi-SAVE score. These methods provide risk stratification scores for pediatric patients requiring ECMO for cardiac support. However, comparative validation of these scoring systems remains scarce. We aim to assess the ability of these models to predict outcomes in a cohort of pediatric patients undergoing VA-ECMO after cardiac surgery, and identify predictors of in-hospital mortality.MethodsA retrospective analysis of 101 children admitted to Fuwai Hospital who received VA-ECMO from January 1, 2010 to December 31, 2020 was performed. Patients were divided into two groups, survivors (n = 49) and non-survivors (n = 52) according to in-hospital mortality. PEP model and Pedi-SAVE scores were calculated. The primary outcomes were the risk factors of in-hospital mortality, and the ability of the PEP model, Precannulation Pedi-SAVE and Postcannulation Pedi-SAVE scores to predict in-hospital mortality.ResultsPostcannulation Pedi-SAVE score accessing the entire ECMO process had the greatest area under receiver operator curve (AUROC), 0.816 [95% confidence interval (CI): 0.733-0.899]. Pre-ECMO PEP model could predict in-hospital mortality [AUROC = 0.691 (95% CI: 0.565-0.817)], and Precannulation Pedi-SAVE score had the poorest prediction [AUROC = 0.582(95% CI: 0.471-0.694)]. Lactate value at ECMO implantation [OR = 1.199 (1.064-1.351), P = 0.003] and infectious complications [OR = 5.169 (1.652-16.172), P = 0.005] were independent risk factors for in-hospital mortality.ConclusionPediatric cardiac ECMO scoring systems, including multiple risk factors before and during ECMO, were found to be useful in this cohort. Both the pre-ECMO PEP model and the Postcannulation Pedi-SAVE score were found to have high predictive value for in-hospital mortality in pediatric postcardiotomy VA-ECMO.

Project description:BackgroundThere is no gold standard to diagnose septic shock-induced disseminated intravascular coagulation (DIC). The objective of our multicenter prospective study was to assess the performances of the different major scoring systems in terms of mortality prediction and DIC diagnosis. The JAAM-DIC 2016 score, the ISTH overt-DIC 2001 score, the associations of sepsis-induced coagulopathy (SIC) score with JAAM-DIC 2016 or ISTH overt-DIC scores were tested in patients within 12 h of their admission in ICU for septic shock (day 1) and at day 2.Results582 patients were enrolled in the study. 182/567 (32.1%) were diagnosed with DIC according to ISTH overt-DIC score, and 193/561 (34.4%) according to JAAM-DIC score; 486/577 patients (84.2%) were diagnosed with a coagulopathy according to SIC score. A moderate concordance was observed between ISTH overt-DIC and JAAM-DIC [κ = 0.67 (0.60, 0.73), p < 0.001]. The delay of positivity of the scores for early DIC patients was not different between JAAM-DIC and ISTH overt-DIC scores. Although it was positive earlier, SIC score had worse diagnosis specificity, as 84.2% of the patients with septic shock were diagnosed with "coagulopathy". The specificity of SIC score alone to predict mortality was very low [0.18 (0.15; 0.22)], compared to the ones of JAAM-DIC score [0.71 (0.67; 0.75)], and of ISTH overt-DIC score [0.76 (0.72; 0.80)], p < 0.001. The sensitivity of SIC score to predict mortality was 0.95 [0.89; 0.98], and the ones of JAAM-DIC score and ISTH overt-DIC score were 0.61 [0.50; 0.70] and 0.68 [0.58; 0.77], respectively. There was no benefit in sensitivity and specificity in combining SIC score to JAAM-DIC score or to ISTH overt-DIC score, compared to JAAM-DIC score or ISTH overt-DIC score alone.ConclusionsOur data suggest that the added value of SIC score alone or combined with other scores is limited, and that both JAAM-DIC score and ISTH overt-DIC score can be used in septic shock patients. Trial registration clinicaltrial; Trial registration number: NCT02391792; Date of registration: 18/03/2015; URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT02391792?term=meziani&draw=4&rank=1.

Project description:BackgroundThe problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have been developed to address these problems. We are now in the era of high-dimensional data, which is data that can concern billions of variables. These data present new challenges. In particular, it is difficult to discover predictive variables, when each variable has little marginal effect. An example concerns Genome-wide Association Studies (GWAS) datasets, which involve millions of single nucleotide polymorphism (SNPs), where some of the SNPs interact epistatically to affect disease status. Towards determining these interacting SNPs, researchers developed techniques that addressed this specific problem. However, the problem is more general, and so these techniques are applicable to other problems concerning interactions. A difficulty with many of these techniques is that they do not distinguish whether a learned interaction is actually an interaction or whether it involves several variables with strong marginal effects.Methodology/findingsWe address this problem using information gain and Bayesian network scoring. First, we identify candidate interactions by determining whether together variables provide more information than they do separately. Then we use Bayesian network scoring to see if a candidate interaction really is a likely model. Our strategy is called MBS-IGain. Using 100 simulated datasets and a real GWAS Alzheimer's dataset, we investigated the performance of MBS-IGain.Conclusions/significanceWhen analyzing the simulated datasets, MBS-IGain substantially out-performed nine previous methods at locating interacting predictors, and at identifying interactions exactly. When analyzing the real Alzheimer's dataset, we obtained new results and results that substantiated previous findings. We conclude that MBS-IGain is highly effective at finding interactions in high-dimensional datasets. This result is significant because we have increasingly abundant high-dimensional data in many domains, and to learn causes and perform prediction/classification using these data, we often must first identify interactions.

Project description:BackgroundSepsis remains a major problem in intensive care medicine. It is often accompanied by coagulopathies, leading to thrombotic occlusion of small vessels with subsequent organ damage and even fatal multi-organ failure. Prediction of the clinical course and outcome-especially in the heterogeneous group of pediatric patients-is difficult. Antithrombin, as an endogenous anticoagulant enzyme with anti-inflammatory properties, plays a central role in controling coagulation and infections. We investigated the relationship between antithrombin levels and organ failure as well as mortality in pediatric patients with sepsis.MethodsData from 164 patients under the age of 18, diagnosed with sepsis, were retrospectively reviewed. Antithrombin levels were recorded three days before to three days after peak C-reactive protein to correlate antithrombin levels with inflammatory activity. Using the concept of developmental haemostasis, patients were divided into groups <1 yr and ?1 yr of age.ResultsIn both age groups, survivors had significantly higher levels of antithrombin than did deceased patients. An optimal threshold level for antithrombin was calculated by ROC analysis for survival: 41.5% (<1 yr) and 67.5% (?1 yr). The mortality rate above this level was 3.3% (<1 yr) and 9.5% (?1 yr), and below this level 41.7% (<1 yr) and 32.2% (?1 yr); OR 18.8 (1.74 to 1005.02), p = 0.0047, and OR 4.46 (1.54 to 14.89), p = 0.003. In children <1 yr with antithrombin levels <41.5% the rate of respiratory failure (66.7%) was significantly higher than in patients with antithrombin levels above this threshold level (23.3%), OR 6.23 (1.23 to 37.81), p = 0.0132. In children ?1 yr, both liver failure (20.3% vs 1.6%, OR 15.55 (2.16 to 685.01), p = 0.0008) and a dysfunctional intestinal tract (16.9% vs 4.8%, OR 4.04 (0.97 to 24.08), p = 0.0395) occurred more frequently above the antithrombin threshold level of 67.5%.ConclusionIn pediatric septic patients, significantly increased mortality and levels of organ failure were found below an age-dependent antithrombin threshold level. Antithrombin could be useful as a prognostic marker for survival and occurrence of organ failure in pediatric sepsis.

Project description:BackgroundPatients with septic shock have the highest risk of death from sepsis, however, racial disparities in mortality outcomes in this cohort have not been rigorously investigated. Our objective was to describe the association between race/ethnicity and mortality in patients with septic shock.MethodsOur study is a retrospective cohort study of adult patients in the OneFlorida Data Trust (Florida, United States of America) admitted with septic shock between January 2012 and July 2018. We identified patients as having septic shock if they received vasopressors during their hospital encounter and had either an explicit International Classification of Disease (ICD) code for sepsis, or had an infection ICD code and received intravenous antibiotics. Our primary outcome was 90-day mortality. Our secondary outcome was in-hospital mortality. Multiple logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) for variable selection was used to assess associations.FindingsThere were 13,932 patients with septic shock in our cohort. The mean age was 61 years (SD 16), 68% of the cohort identified as White (n = 9419), 28% identified as Black (n = 3936), 2% (n = 294) identified as Hispanic ethnicity, and 2% as other races not specified in the previous groups (n = 283). In our logistic regression model for 90-day mortality, patients identified as Black had 1.57 times the odds of mortality (95% CI 1.07-2.29, p = 0.02) compared to White patients. Other significant predictors included mechanical ventilation (OR 3.66, 95% CI 3.35-4.00, p < 0.01), liver disease (OR 1.75, 95% CI 1.59-1.93, p < 0.01), laboratory components of the Sequential Organ Failure Assessment score (OR 1.18, 95% CI 1.16-1.21, p < 0.01), lactate (OR 1.10, 95% CI 1.08-1.12, p < 0.01), congestive heart failure (OR 1.19, 95% CI 1.10-1.30, p < 0.01), human immunodeficiency virus (OR 1.35, 95% CI 1.04-1.75, p = 0.03), age (OR 1.04, 95% CI 1.04-1.04, p < 0.01), and the interaction between age and race (OR 0.99, 95% CI 0.99-1.00, p < 0.01). Among younger patients (<45 years), patients identified as Black accounted for a higher proportion of the deaths. Results were similar in the in-hospital mortality model.InterpretationIn this retrospective study of septic shock patients, we found that patients identified as Black had higher odds of mortality compared to patients identified as non-Hispanic White. Our findings suggest that the greatest disparities in mortality are among younger Black patients with septic shock.FundingNational Institutes of Health National Center for Advancing Translational Sciences (1KL2TR001429); National Institute of Health National Institute of General Medical Sciences (1K23GM144802).

Dataset Information

Comparison of pediatric scoring systems for mortality in septic patients and the impact of missing information on their predictive power: a retrospective analysis.

Publications

Comparison of pediatric scoring systems for mortality in septic patients and the impact of missing information on their predictive power: a retrospective analysis.

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