Evidence map›Paper›PMID 32207172›Full record

SynthesisPaediatric and perinatal epidemiology2020

Composite neonatal morbidity indicators using hospital discharge data: A systematic review.

Elodie Lebreton, Catherine Crenn-Hébert, Claudie Menguy, Elizabeth A Howell, Jeffrey B Gould, Agnès Dechartres, Jennifer Zeitlin

Abstract readSystematic Review
In one paragraph

Synthesis in Paediatric and perinatal epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Association of maternal primary language with neurodevelopmental outcomes in high-risk infants.Journal of perinatology : official journal of the California Perinatal Association · 2025
    Article
  5. Article
  6. The validity of hospital diagnostic and procedure codes reflecting morbidity in preterm neonates born <32 weeks gestation.Journal of perinatology : official journal of the California Perinatal Association · 2023
    Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Elodie LebretonData Science and Analytics Department, SESAN, Paris, France.ORCID 0000-0003-2281-2942
Catherine Crenn-HébertPerinat-ARS-IDF, Regional Health Agency of Ile-de-France (ARS-IDF), Paris, France.ORCID 0000-0002-8175-188X
Claudie MenguyPerinat-ARS-IDF, Regional Health Agency of Ile-de-France (ARS-IDF), Paris, France.
Elizabeth A HowellDepartment of Obstetrics, Gynecology, and Reproductive Science, Women's Health Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jeffrey B GouldDepartment of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Agnès DechartresSorbonne Université, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Sorbonne Université, Hôpital Pitié Salpêtrière, Département de Santé Publique, Centre de Pharmacoépidémiologie de l'AP-HP (Cephepi), Paris, France.
Jennifer ZeitlinObstetrical Perinatal and Pediatric Epidemiology Research Team (EPOPé), INSERM, INRA, CRESS, Université de Paris, Paris, France.ORCID 0000-0002-9568-2969

Funding

Pathways to Reduce Infant DeathsR01HD078565 · NICHD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HOWELL, ELIZABETH A · 2015 to 2020
$2.7M
NICHD NIH HHS R01 HD078565NICHD NIH HHS R01HD078565
6 · The paper itself

Abstract

backgroundNeonatal morbidity is associated with lifelong impairments, but the absence of a consensual definition and the need for large data sets limit research.

objectivesTo inform initiatives to define standard outcomes for research, we reviewed composite neonatal morbidity indicators derived from routine hospital discharge data. DATA SOURCES: PubMed (updated on October 12, 2018). The search algorithm was based on three components: "morbidity," "neonatal," and "hospital discharge data." STUDY SELECTION AND DATA EXTRACTION: Studies investigating neonatal morbidity using a composite indicator based on hospital discharge data were included. Indicators defined for specific conditions (eg congenital anomalies, maternal addictions) were excluded. The target population, objectives, component morbidities, diagnosis and procedure codes, validation methods, and prevalence of morbidity were extracted. SYNTHESIS: For each study, we assessed construct validity by describing the methods used to select the indicator components and evaluated whether the authors assessed internal and external validity. We also calculated confidence intervals for the prevalence of the morbidity composite.

resultsSeventeen studies fulfilled inclusion criteria. Indicators targeted all (n = 4), low-/moderate-risk (n = 9), and very preterm (VPT, n = 4) infants. Components were similar for VPT infants, but domains and diagnosis codes within domains varied widely for all and low-/moderate-risk infants. Component selection was described for 8/17 indicators and some form of validation reported for 12/17. Neonatal morbidity prevalence ranged from 4.6% to 9.0% of all infants, 0.4% to 8.0% of low-/moderate-risk infants, and 17.8% to 61.0% of VPT infants.

conclusionsMultiple neonatal morbidity indicators based on hospital discharge data have been used for research, but their heterogeneity limits comparisons between studies. Standard neonatal outcome measures are needed for benchmarking and synthesis of research results.

Indexed as

Congenital AbnormalitiesInfant, Newborn, DiseasesCross-Sectional StudiesHumansInfant, NewbornOutcome Assessment, Health CarePatient Dischargeinfantmorbiditynewbornpatient discharge/statistics & numerical datasystematic review

Identifiers

PMID32207172
PMCPMC7418783

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.