Evidence mapPaperPMID 38601176Full record

ArticleThe Lancet regional health. Southeast Asia2024

Centre-level variation in the survival of patients receiving haemodialysis in India: findings from a nationwide private haemodialysis network.

Carinna Hockham, Arpita Ghosh, Ankit Agarwal, Kamal Shah, Mark Woodward, Vivekanand Jha

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Article in The Lancet regional health. Southeast Asia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Carinna HockhamThe George Institute for Global Health, School of Public Health, Imperial College London, London, UK.
Arpita GhoshThe George Institute for Global Health, UNSW International, New Delhi, India.
Ankit AgarwalNephroPlus Dialysis Network, Hyderabad, India.
Kamal ShahNephroPlus Dialysis Network, Hyderabad, India.
Mark WoodwardThe George Institute for Global Health, School of Public Health, Imperial College London, London, UK.
Vivekanand JhaThe George Institute for Global Health, School of Public Health, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There are no large studies examining survival in patients receiving haemodialysis in India or considering centre-level effects on survival. We measured survival variation between dialysis centres across India and evaluated the extent to which differences are explained by measured centre characteristics. Methods: This is a multilevel analysis of patient survival in centres of the NephroPlus dialysis network consisting of 193 centres across India. Patients receiving haemodialysis at a centre for ≥90 days between April 2014 and June 2019 were included, with analyses restricted to centres with ≥10 such patients. The primary outcome was all-cause mortality, measured from 90 days after joining a centre. Proportional hazards models with shared frailty were used to model centre- and patient-level effects on survival. Findings: Amongst 23,601 patients (median age 53 years; 29% female), the unadjusted centre-specific 180-day Kaplan-Meier survival estimates ranged between 55% (95% confidence interval [CI] 38-80%) and 100%, with a median of 88% (interquartile interval 83%-92%). After accounting for multilevel factors, estimated 180-day survival ranged between 83% (73-89%) and 97% (95-98%), with 90% 180-day survival in the average centre. The mortality rate in patients attending rural centres was 32% (Hazard Ratio 1.32; 95% CI 1.06-1.65) higher than those at urban centres in adjusted analyses. Multiple patient characteristics were associated with mortality. Interpretation: This is the first national benchmark for survival amongst dialysis patients in India. Centre- and patient-level characteristics are associated with survival but there remains unexplained variation between centres. As India continues to widen dialysis access, ongoing quality improvement programs will be an important part of ensuring that patients experience the best possible outcomes at the point of care. Funding: This project received no external funding.

Indexed as

Dialysis centresFrailty modelsHaemodialysisMortalitySurvival analysis

Identifiers

PMID38601176
PMCPMC11004392

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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 Socratic graph.