Evidence map›Paper›PMID 25092963›Full record

ArticleClinical ophthalmology (Auckland, N.Z.)2014

The impact of different algorithms for ideal body weight on screening for hydroxychloroquine retinopathy in women.

David J Browning, Chong Lee, David Rotberg

Open access · goldAbstract read
In one paragraph

Article in Clinical ophthalmology (Auckland, N.Z.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
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

11 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Hydroxychloroquine retinopathy.Eye (London, England) · 2017
    Review
  9. Article
  10. Article
  11. 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

3 authors at 1 institution in 1 country.

David J BrowningCharlotte Eye, Ear, Nose and Throat Associates, Charlotte, North Carolina, NC, USA.
Chong LeeCharlotte Eye, Ear, Nose and Throat Associates, Charlotte, North Carolina, NC, USA.
David RotbergCharlotte Eye, Ear, Nose and Throat Associates, Charlotte, North Carolina, NC, USA.
Charlotte Eye Ear Nose & Throat Associates · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine how algorithms for ideal body weight (IBW) affect hydroxychloroquine dosing in women.

methodsThis was a retrospective study of 520 patients screened for hydroxychloroquine retinopathy. Charts were reviewed for sex, height, weight, and daily dose. The outcome measures were ranges of IBW across algorithms; rates of potentially toxic dosing; height thresholds below which 400 mg/d dosing is potentially toxic; and rates for which actual body weight (ABW) was less than IBW.

resultsWomen made up 474 (91%) of the patients. The IBWs for a height varied from 30-34 pounds (13.6-15.5 kg) across algorithms. The threshold heights below which toxic dosing occurred varied from 62-70 inches (157.5-177.8 cm). Different algorithms placed 16%-98% of women in the toxic dosing range. The proportion for whom dosing should have been based on ABW rather than IBW ranged from 5%-31% across algorithms.

conclusionAlthough hydroxychloroquine dosing should be based on the lesser of ABW and IBW, there is no consensus about the definition of IBW. The Michaelides algorithm is associated with the most frequent need to adjust dosing; the Metropolitan Life Insurance, large frame, mean value table with the least frequent need. No evidence indicates that one algorithm is superior to others.

Indexed as

actual body weightalgorithmshydroxychloroquineideal body weightretinopathytoxicity

Identifiers

PMID25092963
PMCPMC4116363
OpenAlexW2058743717

What OpenQuestion holds

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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.