Evidence map›Paper›PMID 35633222›Full record

ArticleJNMA; journal of the Nepal Medical Association2022

Neonatal Intensive Care Unit Admissions among Preterm Babies in a Tertiary Care Centre: A Descriptive Cross-sectional Study.

Sahisnuta Basnet, Suraj Adhikari, Jyoti Jha, Mahendra Raj Pandey

Abstract read
In one paragraph

Article in JNMA; journal of the Nepal Medical Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

  1. Article
  2. Observational
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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

4 authors.

Sahisnuta BasnetDepartment of Pediatrics, Manipal College of Medical Sciences, Phulbari, Pokhara, Nepal.
Suraj AdhikariManipal College of Medical Sciences, Phulbari, Pokhara, Nepal.
Jyoti JhaDepartment of Pediatrics, Manipal College of Medical Sciences, Phulbari, Pokhara, Nepal.
Mahendra Raj PandeyDepartment of Obstetrics and Gynecology, Manipal College of Medical Sciences, Phulbari, Pokhara, Nepal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Preterm babies are born before 37 completed weeks of gestation. It is an important cause of neonatal morbidity and mortality. This study aimed to find out the prevalence of neonatal intensive care unit admissions among preterm babies in a tertiary care centre. Methods: A descriptive cross-sectional study on a total of 133 preterm infants was conducted in a tertiary care centre from November, 2020 to April, 2021 with ethical approval from the Institutional Review Committee (Reference number: 380). Preterm babies who met the eligibility criteria were included in the study. Convenience sampling was done. Data were analysed using the Statistical Package for the Social Sciences version 20.0. Point estimate at 95% Confidence Interval was calculated along with frequency and percentage for binary data. Results: Out of 133 preterm babies, 54 (40.60%) (32.25-48.95 at 95% Confidence Interval) had neonatal intensive care unit admissions. Hyaline membrane disease was the most common illness in preterm neonates 34 (62.96%) followed by neonatal sepsis 20 (37.03%). Conclusions: The prevalence of neonatal intensive care unit admissions among preterm babies in our study was similar to other studies done in similar settings. Preterm newborns are significantly vulnerable and maternal risk factors should be taken into account. Anticipated preterm deliveries should have mandatory institutional delivery and adequate postnatal care is needed to improve the outcomes of preterm babies. Keywords: morbidity; mortality; neonatal intensive care unit; preterm infants.

Indexed as

Infant, Newborn, DiseasesIntensive Care Units, NeonatalCross-Sectional StudiesHumansInfantInfant, NewbornInfant, PrematureTertiary Care Centers

Identifiers

PMID35633222
PMCPMC9252253

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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.