Evaluation of Severity of Illness Scores in the Pediatric ECMO Population.
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ABSTRACT:
SUBMITTER: Pinto VL
PROVIDER: S-EPMC8506160 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe correlates of COVID-19 illness severity following infection with SARS-Coronavirus 2 (SARS-CoV-2) are incompletely understood.MethodsWe assessed peripheral blood gene expression in 53 adults with confirmed SARS-CoV-2-infection clinically adjudicated as having mild, moderate or severe disease. Supervised principal components analysis was used to build a weighted gene expression risk score (WGERS) to discriminate between severe and non-severe COVID.ResultsGene expression patterns in participants with mild and moderate illness were similar, but significantly different from severe illness. When comparing severe versus non-severe illness, we identified >4000 genes differentially expressed (FDR<0.05). Biological pathways increased in severe COVID-19 were associated with platelet activation and coagulation, and those significantly decreased with T cell signaling and differentiation. A WGERS based on 18 genes distinguished severe illness in our training cohort (cross-validated ROC-AUC=0.98), and need for intensive care in an independent cohort (ROC-AUC=0.85). Dichotomizing the WGERS yielded 100% sensitivity and 85% specificity for classifying severe illness in our training cohort, and 84% sensitivity and 74% specificity for defining the need for intensive care in the validation cohort.ConclusionThese data suggest that gene expression classifiers may provide clinical utility as predictors of COVID-19 illness severity.
| S-EPMC8767880 | biostudies-literature
Project description:The correlates of COVID-19 illness severity following infection with SARS-Coronavirus 2 (SARS-CoV-2) are incompletely understood. We assessed peripheral blood gene expression in 53 adults with confirmed SARS-CoV-2-infection clinically adjudicated as having mild, moderate or severe disease. Supervised principal components analysis was used to build a weighted gene expression risk score (WGERS) to discriminate between severe and non-severe COVID. Gene expression patterns in participants with mild and moderate illness were similar, but significantly different from severe illness. When comparing severe versus non-severe illness, we identified >4000 genes differentially expressed (FDR<0.05). Biological pathways increased in severe COVID-19 were associated with platelet activation and coagulation, and those significantly decreased with T cell signaling and differentiation. A WGERS based on 18 genes distinguished severe illness in our training cohort (cross-validated ROC-AUC=0.98), and need for intensive care in an independent cohort (ROC-AUC=0.85). Dichotomizing the WGERS yielded 100% sensitivity and 85% specificity for classifying severe illness in our training cohort, and 84% sensitivity and 74% specificity for defining the need for intensive care in the validation cohort. These data suggest that gene expression classifiers may provide clinical utility as predictors of COVID-19 illness severity.
| S-EPMC8404885 | biostudies-literature
Project description:BackgroundCurrent prognostic scores for status epilepticus (SE) may not be adequate for patients in ICU who usually have more severe systemic conditions or more refractory episodes of SE. We aimed to compare the prognostic performance of two SE scores, Status Epilepticus Severity Score (STESS) and Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) score, with four systemic severity scores, Acute Physiology and Chronic Health Evaluation 2 (APACHE-2), Simplified Acute Physiology Score 2 (SAPS-2), Sequential Organ Failure Assessment (SOFA) score, and Inflammation, Nutrition, Consciousness, Neurologic function and Systemic condition (INCNS) score in critically ill patients with SE.MethodsThis retrospective observational study of a prospectively identified SE cohort was conducted in the ICU at a tertiary-care center. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and associations with outcomes of STESS, EMSE, INCNS, APACHE-2, SAPS-2, and SOFA score for the prediction of in-hospital mortality and no return to baseline condition were assessed.ResultsBetween January 2015 and December 2020, 166 patients with SE in ICU were included in the study. In predicting in-hospital death, APACHE-2 (0.72), SAPS-2 (0.73), and SOFA score (0.71) had higher AUCs than STESS (0.58) and EMSE (0.69). In predicting no return to baseline condition, the AUC of APACHE-2 (0.75) was the highest, and the AUC of INCNS (0.55) was the lowest. When the specificity approached 90%, the sensitivity values of these scores were not quite acceptable (< 40%). Neither SE scores nor systemic severity scores had desirable prognostic power. In the multivariate logistic regression analyses, the best combinations of scores always included at least one or more systemic severity scores.ConclusionsSTESS and EMSE were insufficient in outcome prediction for SE patients in ICU, and EMSE was marginally better than STESS. Systemic illness matters in ICU patients with SE, and SE scores should be modified to achieve better accuracy in this severely ill population. This study mostly refers to severely ill patients in the ICU.
| S-EPMC9841666 | biostudies-literature
Project description:Illness severity scores are regularly employed for quality improvement and benchmarking in the intensive care unit, but poor generalization performance, particularly with respect to probability calibration, has limited their use for decision support. These models tend to perform worse in patients at a high risk for mortality. We hypothesized that a sequential modeling approach wherein an initial regression model assigns risk and all patients deemed high risk then have their risk quantified by a second, high-risk-specific, regression model would result in a model with superior calibration across the risk spectrum. We compared this approach to a logistic regression model and a sophisticated machine learning approach, the gradient boosting machine. The sequential approach did not have an effect on the receiver operating characteristic curve or the precision-recall curve but resulted in improved reliability curves. The gradient boosting machine achieved a small improvement in discrimination performance and was similarly calibrated to the sequential models.
| S-EPMC6695410 | biostudies-literature
Project description:BackgroundThe criteria for the selection of COVID-19 patients that could benefit most from ECMO organ support are yet to be defined. In this study, we evaluated the predictive performance of ECMO mortality predictive models in patients with COVID-19. We also performed a cost-benefit analysis depending on the mortality predicted probability. We conducted a retrospective cohort study in COVID-19 patients who received ECMO at two tertiary care hospitals between March 2020 to July 2021.Materials and methodsWe evaluated the discrimination (C-statistic), calibration (Cox calibration), and accuracy of the prediction of death due to severe ARDS in V-V ECMO score (PRESERVE), the Respiratory Extracorporeal Membrane Oxygenation Survival Score (RESP) score, and the PREdiction of Survival on ECMO Therapy-Score (PRESET) score. In addition, we compared the RESP score with Plateau pressure instead of Peak pressure.ResultsWe included a total of 36 patients, 29 (80%) of them male and with a median (IQR) APACHE of 10 (8-15). The PRESET score had the highest discrimination (AUROCs 0.81 [95%CI 0.67-0.94]) and calibration (calibration-in-the-large 0.5 [95%CI -1.4 to 0.3]; calibration slope 2.2 [95%CI 0.7/3.7]). The RESP score with Plateau pressure had higher discrimination than the conventional RESP score. The cost per QALY in the USA, adjusted to life expectancy, was higher than USD 100 000 in patients older than 45 years with a PRESET > 10.ConclusionThe PRESET score had the highest predictive performance and could help in the selection of patients that benefit most from this resource-demanding and highly invasive organ support.
| S-EPMC9880702 | biostudies-literature
Project description:Sedatives and analgesics are often administered to critically ill children supported by extracorporeal membrane oxygenation (ECMO) to facilitate comfort and to decrease risks of life-threatening complications. Optimization of sedative and analgesic dosing is necessary to achieve desired therapeutic benefits and must consider interactions between the circuit and patient that may affect drug metabolism, clearance, and impact on target organs. This paper reviews existing in vitro and pediatric in vivo literature concerning the effects of the ECMO circuit on sedative and analgesic disposition and offers dosing guidance for the management of critically ill children receiving these drugs.
| S-EPMC7671016 | biostudies-literature
Project description:ObjectivesTo develop, evaluate, and explore the use of a pediatric ordinal score as a potential clinical trial outcome metric in children hospitalized with acute hypoxic respiratory failure caused by viral respiratory infections.DesignWe modified the World Health Organization Clinical Progression Scale for pediatric patients (CPS-Ped) and assigned CPS-Ped at admission, days 2-4, 7, and 14. We identified predictors of clinical improvement (day 14 CPS-Ped ≤ 2 or a three-point decrease) using competing risks regression and compared clinical improvement to hospital length of stay (LOS) and ventilator-free days. We estimated sample sizes (80% power) to detect a 15% clinical improvement.SettingNorth American pediatric hospitals.PatientsThree cohorts of pediatric patients with acute hypoxic respiratory failure receiving intensive care: two influenza (pediatric intensive care influenza [PICFLU], n = 263, 31 sites; PICFLU vaccine effectiveness [PICFLU-VE], n = 143, 17 sites) and one COVID-19 ( n = 237, 47 sites).InterventionsNone.Measurements and main resultsInvasive mechanical ventilation rates were 71.4%, 32.9%, and 37.1% for PICFLU, PICFLU-VE, and COVID-19 with less than 5% mortality for all three cohorts. Maximum CPS-Ped (0 = home at respiratory baseline to 8 = death) was positively associated with hospital LOS ( p < 0.001, all cohorts). Across the three cohorts, many patients' CPS-Ped worsened after admission (39%, 18%, and 49%), with some patients progressing to invasive mechanical ventilation or death (19%, 11%, and 17%). Despite this, greater than 76% of patients across cohorts clinically improved by day 14. Estimated sample sizes per group using CPS-Ped to detect a percentage increase in clinical improvement were feasible (influenza 15%, n = 142; 10%, n = 225; COVID-19, 15% n = 208) compared with mortality ( n > 21,000, all), and ventilator-free days (influenza 15%, n = 167).ConclusionsThe CPS-Ped can be used to describe the time course of illness and threshold for clinical improvement in hospitalized children and adolescents with acute respiratory failure from viral infections. This outcome measure could feasibly be used in clinical trials to evaluate in-hospital recovery.
| S-EPMC10688559 | biostudies-literature
Project description:Hypotension or low blood pressure (BP) is a common problem in preterm neonates and has been associated with adverse short and long-term neurological outcomes. Deciding when and whether to treat hypotension relies on an understanding of the relationship between BP and brain functioning. This study aims to investigate the interaction (coupling) between BP and continuous multichannel unedited EEG recordings in preterm infants less than 32 weeks of gestational age. The EEG was represented by spectral power in four frequency sub-bands: 0.3-3 Hz, 3-8 Hz, 8-15 Hz and 15-30 Hz. BP was represented as mean arterial pressure (MAP). The level of coupling between the two physiological systems was estimated using linear and nonlinear methods such as correlation, coherence and mutual information. Causality of interaction was measured using transfer entropy. The illness severity was represented by the clinical risk index for babies (CRIB II score) and contrasted to the computed level of interaction. It is shown here that correlation and coherence, which are linear measures of the coupling between EEG and MAP, do not correlate with CRIB values, whereas adjusted mutual information, a nonlinear measure, is associated with CRIB scores (r = -0.57, p = 0.003). Mutual information is independent of the absolute values of MAP and EEG powers and quantifies the level of coupling between the short-term dynamics in both signals. The analysis indicated that the dominant causality is from changes in EEG producing changes in MAP. Transfer entropy (EEG to MAP) is associated with the CRIB score (0.3-3 Hz: r = 0.428, p = 0.033, 3-8 Hz: r = 0.44, p = 0.028, 8-15 Hz: r = 0.416, p = 0.038) and indicates that a higher level of directed coupling from brain activity to blood pressure is associated with increased illness in preterm infants. This is the first study to present the nonlinear measure of interaction between brain activity and blood pressure and to demonstrate its relation to the initial illness severity in the preterm infant. The obtained results allow us to hypothesise that the normal wellbeing of a preterm neonate can be characterised by a nonlinear coupling between brain activity and MAP, whereas the presence of weak coupling with distinctive directionality of information flow is associated with an increased mortality rate in preterms.
| S-EPMC6014641 | biostudies-literature
Project description:Plasma cell-free DNA (cfDNA) levels have been associated with disease and survival status in septic humans and dogs. To date, studies investigating cfDNA levels in association with critical illness in foals are lacking. We hypothesized that cfDNA would be detectable in the plasma of foals, that septic and sick-nonseptic foals would have significantly higher cfDNA levels compared to healthy foals, and that increased cfDNA levels would be associated with non-survival. Animals used include 80 foals of 10 days of age or less admitted to a tertiary referral center between January and July, 2020 were stratified into three categories: healthy (n = 34), sick non-septic (n = 11) and septic (n = 35) based on specific criteria. This was a prospective clinical study. Blood was collected from critically ill foals at admission or born in hospital for cfDNA quantification and blood culture. Previously published sepsis score (SS) and neonatal SIRS score (NSIRS) were also calculated. SS, NSIRS, blood culture status and cfDNA concentrations were evaluated to predict survival. Continuous variables between groups were compared using Kruskal-Wallis ANOVA with Dunn's post hoc test. Comparisons between two groups were assessed using the Mann-Whitney U-test or Spearman rank for correlations. The performance of cfDNA, sepsis score and NSIRS score to predict survival was assessed by receiver operator characteristic (ROC) curve analysis including area under the curve, sensitivity and specificity using cutoffs. Plasma cfDNA was detectable in all foals. No significant differences in cfDNA concentration were detected between healthy foals and septic foals (P = 0.65) or healthy foals and sick non-septic foals (P = 0.88). There was no significant association between cfDNA and culture status, SS, NSIRS or foal survival. SS (AUC 0.85) and NSIRS (AUC 0.83) were superior to cfDNA (AUC 0.64) in predicting survival. Although cfDNA was detectable in foal plasma, it offers negligible utility to diagnose sepsis or predict survival in critical illness in neonates.
| S-EPMC8075268 | biostudies-literature
Project description:ObjectiveA neonatal illness severity score, The Score for Neonatal Acute Physiology-II (SNAP-II), predicts neurodevelopmental impairments at two years of age among children born extremely preterm. We sought to evaluate to what extent SNAP-II is predictive of cognitive and other neurodevelopmental impairments at 10 years of age.Study designIn a cohort of 874 children born before 28 weeks of gestation, we prospectively collected clinical, physiologic and laboratory data to calculate SNAP-II for each infant. When the children were 10 years old, examiners who were unaware of the child's medical history assessed neurodevelopmental outcomes, including neurocognitive, gross motor, social and communication functions, diagnosis and treatment of seizures or attention deficit hyperactivity disorder (ADHD), academic achievement, and quality of life. We used logistic regression to adjust for potential confounders.ResultsAn undesirably high SNAP-II (⩾30), present in 23% of participants, was associated with an increased risk of cognitive impairment (IQ, executive function, language ability), adverse neurological outcomes (epilepsy, impaired gross motor function), behavioral abnormalities (attention deficit disorder and hyperactivity), social dysfunction (autistic spectrum disorder) and education-related adversities (school achievement and need for educational supports. In analyses that adjusted for potential confounders, Z-scores ⩽-1 on 11 of 18 cognitive outcomes were associated with SNAP-II in the highest category, and 6 of 18 were associated with SNAP-II in the intermediate category. Odds ratios and 95% confidence intervals ranged from 1.4 (1.01, 2.1) to 2.1 (1.4, 3.1). Similarly, 2 of the 8 social dysfunctions were associated with SNAP-II in the highest category, and 3 of 8 were associated with SNAP-II in the intermediate category. Odds ratios and 95% confidence intervals were slightly higher for these assessments, ranging from 1.6 (1.1, 2.4) to 2.3 (1.2, 4.6).ConclusionAmong very preterm newborns, physiologic derangements present in the first 12 postnatal hours are associated with dysfunctions in several neurodevelopmental domains at 10 years of age. We are unable to make inferences about causality.
| S-EPMC5407946 | biostudies-literature