Evidence map›Paper›PMID 36223969›Full record

ReviewBMJ open2022

Dose optimisation and scarce resource allocation: two sides of the same coin.

Garth Strohbehn, Govind Persad, William F Parker, Srinivas Murthy

Abstract readReview
In one paragraph

Review in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

4 authors.

Garth StrohbehnCenter for Clinical Management Research, Veterans Affairs Ann Arbor Health Care, Ann Arbor, Michigan, USA gstrohbe@umich.edu.ORCID 0000-0003-2973-3040
Govind PersadSturm College of Law, University of Denver, Denver, Colorado, USA.
William F ParkerMaclean Center for Clinical Medical Ethics, University of Chicago, Chicago, Illinois, USA.
Srinivas MurthyPaediatrics, University of British Columbia, Vancouver, British Columbia, Canada.

Funding

Mending a Broken Heart Allocation System with Machine LearningK08HL150291 · NHLBI · UNIVERSITY OF CHICAGO · PI PARKER, WILLIAM F · 2020 to 2024
$713k
NHLBI NIH HHS K08 HL150291
6 · The paper itself

Abstract

objectiveA deep understanding of the relationship between a scarce drug's dose and clinical response is necessary to appropriately distribute a supply-constrained drug along these lines. SUMMARY OF KEY DATA: The vast majority of drug development and repurposing during the COVID-19 pandemic - an event that has made clear the ever-present scarcity in healthcare systems -has been ignorant of scarcity and dose optimisation's ability to help address it.

conclusionsFuture pandemic clinical trials systems should obtain dose optimisation data, as these appear necessary to enable appropriate scarce resource allocation according to societal values.

Indexed as

COVID-19PandemicsDelivery of Health CareHealth Care RationingHumansCLINICAL PHARMACOLOGYClinical trialsCOVID-19MEDICAL ETHICSPublic healthRationing

Identifiers

PMID36223969
PMCPMC9562718

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.