Evidence map›Paper›PMID 33644407›Full record

ArticleInternational journal of population data science2020

A composite neonatal adverse outcome indicator using population-based data: an update.

S Todd, J Bowen, I Ibiebele, J Patterson, S Torvaldsen, F Ford, M Nippita, J Morris, D Randall

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in International journal of population data science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05697822 (The Effect of a Patient-involved Mobile Phone and Cloud-based Electronic Contact and Recording System on Institutional Deliveries and Other Maternal and Infant Health Outcomes in Rural Nepal), which is not on this map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 27% of its field
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.

NCT05697822 naunknown statusnot on this mapstarted 2023, after this paper: background citation

The Effect of a Patient-involved Mobile Phone and Cloud-based Electronic Contact and Recording System on Institutional Deliveries and Other Maternal and Infant Health Outcomes in Rural Nepal: A Cluster Randomized Controlled Trial

TypeinterventionalSponsorAmit ArjyalRan2023 to 2024Enrolled360ConditionsMaternal Health, Infant Health, Institutional Delivery, Birth Preparedness and Complication ReadinessArmsMobile Phone and Cloud-based Electronic Contact and Recording System
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
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  4. Bariatric Surgery, Gestational Diabetes and Perinatal Outcomes: A Population-Based Study.BJOG : an international journal of obstetrics and gynaecology · 2026
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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

9 authors at 3 institutions in 1 country.

S ToddThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
J BowenThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
I IbiebeleThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
J PattersonThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
S TorvaldsenThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
F FordThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
M NippitaThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
J MorrisThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
D RandallThe University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia.
University of Sydney · AUNorthern Sydney Local Health District · AUNew South Wales Department of Health · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSevere morbidity rates in neonates can be estimated using diagnosis and procedure coding in linked routinely collected retrospective data as a cost-effective way to monitor quality and safety of perinatal services. Coding changes necessitate an update to the previously published composite neonatal adverse outcome indicator for identifying infants with severe or medically significant morbidity.

objectivesTo update the neonatal adverse outcome indicator for identifying neonates with severe or medically significant morbidity, and to investigate the validity of the updated indicator.

methodsWe audited diagnosis and procedure codes and used expert clinician input to update the components of the indicator. We used linked birth, hospital and death data for neonates born alive at 24 weeks or more in New South Wales, Australia (2002-2014) to describe the incidence of neonatal morbidity and assess the validity of the updated indicator.

resultsThe updated indicator included 28 diagnostic and procedure components. In our population of 1,194,681 live births, 5.44% neonates had some form of morbidity. The rate of morbidity was greater for higher-risk pregnancies and was lowest for those born at 39-40 weeks' gestation. Incidence increased over the study period for overall neonatal morbidity, and for individual components: intravenous infusion, respiratory diagnoses, and non-invasive ventilation. Severe or medically significant neonatal morbidity was associated with double the risk of hospital readmission and 10 times the risk of death within the first year of life.

conclusionThe updated composite indicator has maintained concurrent and predictive validity and is a standardised, economic way to measure neonatal morbidity when using population-based data. Changes within individual components should be considered when examining longitudinal data.

Identifiers

PMID33644407
PMCPMC7893849
OpenAlexW3049426447

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Registered trials

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.