A systematic review of neonatal treatment intensity scores and their potential application in low-resource setting hospitals for predicting mortality, morbidity and estimating resource use

Abstract

BackgroundTreatment intensity scores can predict mortality and estimate resource use. They may therefore be of interest for essential neonatal care in low resource settings where neonatal mortality remains high. We sought to systematically review neonatal treatment intensity scores to (1) assess the level of evidence on predictive performance in predicting clinical outcomes and estimating resource utilisation and (2) assess the applicability of the identified models to decision making for neonatal care in low resource settings.MethodsWe conducted a systematic search of PubMed, EMBASE (OVID), CINAHL, Global Health Library (Global index, WHO) and Google Scholar to identify studies published up until 21 December 2016. Included were all articles that used treatments as predictors in neonatal models. Individual studies were appraised using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). In addition, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used as a guiding framework to assess certainty in the evidence for predicting outcomes across studies.ResultsThree thousand two hundred forty-nine articles were screened, of which ten articles were included in the review. All of the studies were conducted in neonatal intensive care units with sample sizes ranging from 22 to 9978, with a median of 163. Two articles reported model development, while eight reported external application of existing models to new populations. Meta-analysis was not possible due heterogeneity in the conduct and reporting of the identified studies. Discrimination as assessed by area under receiver operating characteristic curve was reported for in-hospital mortality, median 0.84 (range 0.75–0.96, three studies), early adverse outcome and late adverse outcome (0.78 and 0.59, respectively, one study).ConclusionExisting neonatal treatment intensity models show promise in predicting mortality and morbidity. There is however low certainty in the evidence on their performance in essential neonatal care in low resource settings as all studies had methodological limitations and were conducted in intensive care. The approach may however be developed further for low resource settings like Kenya because treatment data may be easier to obtain compared to measures of physiological status.Systematic review registrationPROSPERO CRD42016034205Electronic supplementary materialThe online version of this article (10.1186/s13643-017-0649-6) contains supplementary material, which is available to authorized users.

Identificação da gravidade e do uso de intervenções em recém-nascidos com asfixia perinatal

“…However, mean hospital admission was 42.2 days, showing a statistically significant relationship, when associa-ted with the NTISS value (p=0.047), allowing to infer that the NTISS value influences the length of hospitalization. In this way, the importance of its application as a planning, care, and management tool (5) is concluded.…”

“…They score from one to four, where the value one is attributed to less invasive therapy; and the value four is attributed to the most invasive therapy, adding up to 62 as the maximum score. A value of zero is assigned when the item is not used in the patient in that period (5)(6) .…”

“…NTISS was constructed from the Therapeutic Intervention Scoring System, a system of severity measurement of adult patients hospitalized in the Intensive Care Unit, which quantifies the therapeutic interventions of medical and nursing procedures, based on that the more procedures the patient receives, the greater its severity and, consequently, more time spent by the nursing. It was validated in the United States, with 1,643 admitted newborns in neonatal intensive care units, considered a severity score with good accuracy and prognostic value, inclu-ding estimates of risk and hospital mortality rate (5)(6) .…”

Prediction modelling of inpatient neonatal mortality in high-mortality settings

“…In our systematic review on neonatal treatment intensity scores, none of the 10 studies included performed internal validation. 7 Houweling and colleagues conducted cross-validation and again only the after-birth model had an AUC greater than 0.8 (pooled average 0.83, 95% CI 0.79 to 0.86). 21 The most useful aspect of prediction model performance is in an external population to assess generalisability (external 17 After temporal external validation, SENSS had a better calibration slope (0.90, 95% CI 0.78 to 1.01) than NETS (0.76, 95% CI 0.65 to 0.87).…”

“…7 Current models that use treatments as predictors typically focus on those given in intensive care, and there are limitations in the methods used to develop and validate them. 7 These limitations may be addressed by the selection of treatments relevant to the LMIC setting and application of recommended approaches to prognostic model development and validation. 8 Candidate treatment predictors are essential interventions included in clinical practice guidelines for in-hospital neonatal care developed by the WHO and adapted for Kenya.…”