Evidence map›Paper›PMID 32370789›Full record

ArticleTrials2020

Does asymmetry in patient recruitment in large critical care trials follow the Pareto principle?

Mahesh Ramanan, Laurent Billot, Dorrilyn Rajbhandari, John Myburgh, Simon Finfer, Rinaldo Bellomo, Balasubramanian Venkatesh

Abstract read
In one paragraph

Article in Trials, 2020. 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

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

6 citing papers in PubMed.

  1. Trial
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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

7 authors.

Mahesh RamananIntensive Care Unit, Caboolture and The Prince Charles Hospitals, Brisbane, Australia. Mahesh.ramanan@health.qld.gov.au.
Laurent BillotStatistics Division, The George Institute for Global Health, Sydney, Australia.
Dorrilyn RajbhandariCritical Care Division, The George Institute for Global Health, Sydney, Australia.
John MyburghCritical Care Division, The George Institute for Global Health, Sydney, Australia.
Simon FinferUniversity of Sydney, Sydney, Australia.
Rinaldo BellomoIntensive Care Unit, Austin Hospital, Melbourne, Australia.
Balasubramanian VenkateshUniversity of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRandomised controlled trials (RCT) may be hindered by slow recruitment rates, particularly in critically ill patients. While statistical models to predict recruitment rates have been described, no systematic assessment has been conducted of the distribution of recruitment across sites, temporal trends in site participation and impact of competing trials on patient recruitment.

methodsWe used recruitment and screening logs from the SAFE, NICE-SUGAR, RENAL, CHEST and ADRENAL trials, five of the largest critical care RCTs. We quantified the extent of recruitment asymmetry between sites using Lorenz curves and Gini coefficients and assessed whether the recruitment distribution across sites follow the Pareto principle, which states that 80% of effects come from 20% of causes. Peak recruitment rates and growth in participating sites were calculated.

resultsIn total, 25,412 patients were randomised in 99 intensive care units (ICUs) for the five trials. Distribution of recruitment was asymmetric, with a small number of ICUs recruiting a large proportion of the patients. The Gini coefficients ranged from 0.14 to 0.52. The time to peak recruitment rate ranged from 7 to 41 months and was variable (7, 31, 41, 10 and 40 months). Over time, the proportion of recruitment at non-tertiary ICUs increased from 15% to 34%.

conclusionsThere is asymmetry of recruitment with a small proportion of ICUs recruiting a large proportion of patients. The distributions of recruitment were not consistent with the Pareto principle. There has been increasing participation of non-tertiary ICUs in clinical trials.

Indexed as

Intensive Care UnitsPatient SelectionCritical CareCritical IllnessHumansMulticenter Studies as TopicRandomized Controlled Trials as TopicRetrospective StudiesCritical illness, Clinical trials, Intensive care unit, Pareto, Trial recruitment

Identifiers

PMID32370789
PMCPMC7201735

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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.