Evidence map›Paper›PMID 35313942›Full record

ArticleCritical care (London, England)2022

Personalization of renal replacement therapy initiation: a secondary analysis of the AKIKI and IDEAL-ICU trials.

François Grolleau, Raphaël Porcher, Saber Barbar, David Hajage, Abderrahmane Bourredjem, Jean-Pierre Quenot, Didier Dreyfuss, Stéphane Gaudry

Abstract read
In one paragraph

Article in Critical care (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. From Indications to Outcomes: Fluid Overload, Sepsis, and Severity Shaping Contemporary Renal Replacement Therapy in Pediatric Acute Kidney Injury.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2026
    Article
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  5. Article
  6. Article
  7. Review
  8. Review
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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

8 authors.

François GrolleauCentre of Research in Epidemiology and Statistics (CRESS), Université de Paris, French Institute of Health and Medical Research (INSERM U1153), French National Research Institute for Agriculture, Food, and Environment (INRAE), Paris, France. francois.grolleau@aphp.fr.
Raphaël PorcherCentre of Research in Epidemiology and Statistics (CRESS), Université de Paris, French Institute of Health and Medical Research (INSERM U1153), French National Research Institute for Agriculture, Food, and Environment (INRAE), Paris, France.
Saber BarbarIntensive Care Department, Nîmes University Hospital, University of Montpellier, Nîmes, France.
David HajageINSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié-Salpêtrière, Département de Santé Publique, Centre de Pharmacoépidémiologie, Sorbonne Université, Paris, France.
Abderrahmane BourredjemClinical Epidemiology Unit, INSERM CIC1432, Dijon, and Clinical Investigation Center, Clinical Epidemiology/Clinical Trials Unit, Dijon Bourgogne University Hospital, Dijon, France.
Jean-Pierre Quenot *Department of Intensive Care, François Mitterrand University Hospital, Lipness Team, INSERM Research Center, LNC-UMR1231 and LabEx LipSTIC, and INSERM CIC 1432, Clinical Epidemiology, University of Burgundy, Dijon, France.
Didier Dreyfuss *Université de Paris, Service de Médecine Intensive-Réanimation, Hôpital Louis Mourier, AP-HP and INSERM, UMR S1155 "Common and Rare Kidney Diseases: From Molecular Events To Precision Medicine", Sorbonne Université, Paris, France.
Stéphane Gaudry *Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, APHP, UFR SMBH, Université Sorbonne Paris Nord, Bobigny, French National Institute of Health and Medical Research (INSERM), Common and Rare kidney Diseases (CORAKID), Hôpital Tenon, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTrials comparing early and delayed strategies of renal replacement therapy in patients with severe acute kidney injury may have missed differences in survival as a result of mixing together patients at heterogeneous levels of risks. Our aim was to evaluate the heterogeneity of treatment effect on 60-day mortality from an early vs a delayed strategy across levels of risk for renal replacement therapy initiation under a delayed strategy.

methodsWe used data from the AKIKI, and IDEAL-ICU randomized controlled trials to develop a multivariable logistic regression model for renal replacement therapy initiation within 48 h after allocation to a delayed strategy. We then used an interaction with spline terms in a Cox model to estimate treatment effects across the predicted risks of RRT initiation.

resultsWe analyzed data from 1107 patients (619 and 488 in the AKIKI and IDEAL-ICU trial respectively). In the pooled sample, we found evidence for heterogeneous treatment effects (P = 0.023). Patients at an intermediate-high risk of renal replacement therapy initiation within 48 h may have benefited from an early strategy (absolute risk difference, - 14%; 95% confidence interval, - 27% to - 1%). For other patients, we found no evidence of benefit from an early strategy of renal replacement therapy initiation but a trend for harm (absolute risk difference, 8%; 95% confidence interval, - 5% to 21% in patients at intermediate-low risk).

conclusionsWe have identified a clinically sound heterogeneity of treatment effect of an early vs a delayed strategy of renal replacement therapy initiation that may reflect varying degrees of kidney demand-capacity mismatch.

Indexed as

Acute Kidney InjuryTime-to-TreatmentHumansIntensive Care UnitsKidneyRenal Replacement TherapyAcute kidney injuryHeterogeneity of treatment effectPersonalized medicineRenal replacement therapy

Identifiers

PMID35313942
PMCPMC8939225

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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.