Evidence map›Paper›PMID 38965471›Full record

ArticleBMC pediatrics2024

Prevalence and associated factors of impaired kidney functions among children and adolescents in India: insights from the Comprehensive National Nutrition Survey (CNNS) 2016-18.

Angad Singh, Madhur Verma, Milan Das, Pragyan Paramita Parija, Saurabh Nayak, Vivekanand Jha

Abstract read
In one paragraph

Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

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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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Angad Singh *International Institute for Population Sciences, Mumbai, India.
Madhur Verma *Community and Family Medicine, All India Institute of Medical Sciences Bathinda, Punjab, India. drmadhurverma@gmail.com.
Milan Das *International Institute for Population Sciences, Mumbai, India.
Pragyan Paramita ParijaCommunity and Family Medicine, All India Institute of Medical Sciences Vijaypur, Jammu, India.
Saurabh NayakNephrology, All India Institute of Medical Sciences Bathinda, Punjab, India.
Vivekanand JhaThe George Institute for Global Health India, UNSW, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) is a significant public health problem. The burden of CKD in children and adolescents in India is not well described. We used data from the recent Comprehensive National Nutrition Survey (CNNS) to estimate the prevalence of impaired kidney function (IKF) and its determinants in children and adolescents between the ages of 5 and 19.

methodsCNNS 2016-18 adopted a multi-stage sampling design using probability proportional to size sampling procedure after geographical stratification of urban and rural areas. Serum creatinine was tested once in 24,690 children and adolescents aged 5-19 years. The estimated glomerular filtration rate (eGFR) was derived using the revised Schwartz equation. The eGFR value below 60 ml/min/1.73 m

resultsThe mean eGFR in the study population was 113.3 + 41.4 mL/min/1.73 m

conclusionsThe prevalence of IKF among children and adolescents in India is high compared to available global estimates. In the absence of repeated eGFR-based estimates, these nationally representative estimates are intriguing and call for further assessment of socio-demographic disparities, genetics, and risk behaviours to have better clinical insights and public health preparedness.

Indexed as

Glomerular Filtration RateNutrition SurveysRenal Insufficiency, ChronicAdolescentChildChild, PreschoolCreatinineCross-Sectional StudiesFemaleHumansIndiaMalePrevalenceRisk FactorsYoung AdultCreatinineChild healthChronic Kidney DiseaseCNNSNoncommunicable diseasesSustainable development goals

Identifiers

PMID38965471
PMCPMC11223285

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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.