Evidence map›Paper›PMID 35858649›Full record

Observational studyAmerican journal of perinatology2024

Development and Validation of a Neonatal Physical Maturity Score for Low- and Middle-Income Countries.

Vaisakh Krishnan, Vijay Kumar, Hemadri Vegda, Vidya Ujjanappa, Anju Manari, Ajithkumar V Thamunni, Ashraf T P, Sahana Devadas, Sudindrashayana Fattepur, Paul Basett and 1 more

Open access · greenAbstract readObservational StudyValidation Study
In one paragraph

Observational study in American journal of perinatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% 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.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 4 institutions in 2 countries.

Vaisakh KrishnanDepartment of Brain Sciences, Centre of Perinatal Neuroscience, Imperial College London, London, United Kingdom.
Vijay KumarDepartment of Brain Sciences, Centre of Perinatal Neuroscience, Imperial College London, London, United Kingdom.
Hemadri VegdaDepartment of Brain Sciences, Centre of Perinatal Neuroscience, Imperial College London, London, United Kingdom.
Vidya UjjanappaDepartment of Brain Sciences, Centre of Perinatal Neuroscience, Imperial College London, London, United Kingdom.
Anju ManariInternational Perinatal Epidemiology Unit, Bengaluru, Karnataka, India.
Ajithkumar V ThamunniDepartment of Paediatrics Institute of Maternal and Child Health, Government Medical College, Kozhikode, Kerala, India.
Ashraf T PDepartment of Paediatrics Institute of Maternal and Child Health, Government Medical College, Kozhikode, Kerala, India.
Sahana DevadasDepartment of Paediatrics Bangalore Medical College, Bengaluru, Karnataka, India.
Sudindrashayana FattepurDepartment of Paediatrics Karnataka Institute of Medical Sciences, Hubballi, Karnataka, India.
Paul BasettStasconsultancy, London, United Kingdom.
Sudhin ThayyilDepartment of Brain Sciences, Centre of Perinatal Neuroscience, Imperial College London, London, United Kingdom.
Imperial College London · GBGovernment Medical College · INBangalore Medical College and Research Institute · INKarnataka Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCurrently available gestational age scoring systems are complex and inaccurate for wider use in low- and middle-income countries (LMIC), particularly in infants with neonatal encephalopathy. Here, we aimed to develop a scoring system based on physical characteristics for identifying late preterm infants from term infants. STUDY

designThis was a prospective observational study conducted in 2 phases- the discovery phase and validation phase. In the first phase, we examined the accuracy of 10 objective physical characteristics in a prospective cohort of 1,006 infants recruited from three hospitals in South India. A weighted scoring system and a photo card were then developed based on the six best performing characteristics which were validated in another prospective cohort of 1,004 infants.

resultsThe final score had a sensitivity of 66.0% (95% confidence intervals [CIs], 58.4-73.8%), specificity of 80.0% (95% CI, 77.2-82.7%), and a negative predictive value of 93.0% (95% CI, 90.5-94.5%).

conclusionThis scoring system may have wider applications in LMIC, particularly in community settings and in infants with neonatal encephalopathy. KEY POINTS: · This is an easily administered scoring system using physical characters to identify late preterm infants.. · The scoring is not affected by neurological injury and can be used in encephalopathic infants.. · Overall accuracy is better than previous scores encompassing the physical criteria alone..

Indexed as

Developing CountriesGestational AgeInfant, PrematureFemaleHumansIndiaInfant, NewbornMalePredictive Value of TestsProspective StudiesSensitivity and Specificity

Identifiers

PMID35858649
PMCPMC11105931
OpenAlexW4286009267

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.