Evidence map›Paper›PMID 30167340›Full record

ArticleSouthern African journal of HIV medicine2018

Development of a clinical prediction rule to diagnose

Gary Maartens, Annemie Stewart, Rulan Griesel, Andre P Kengne, Felix Dube, Mark Nicol, Molebogeng X Rangaka, Marc Mendelson

Abstract read
In one paragraph

Article in Southern African journal of HIV medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Chest X-ray Features of HIV-AssociatedOpen forum infectious diseases · 2024
    Article
  4. Clinical microbiology reviews · 2024
    Review
  5. Article
  6. Article
  7. 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

8 authors.

Gary MaartensDivision of Clinical Pharmacology, Department of Medicine, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0003-3080-6606
Annemie StewartDivision of Clinical Pharmacology, Department of Medicine, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0002-0697-491X
Rulan GrieselDivision of Clinical Pharmacology, Department of Medicine, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0003-3633-2878
Andre P KengneNon-Communicable Diseases Research Unit, South African Medical Research Council, South Africa.ORCID https://orcid.org/0000-0002-5183-131X
Felix DubeDivision of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0003-2775-7786
Mark NicolDivision of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0002-1366-4805
Molebogeng X RangakaDepartment of Medicine and School of Public Health, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0001-9594-188X
Marc MendelsonDivision of Infectious Diseases and HIV Medicine, Department of Medicine, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0001-6668-3893

Funding

An evidence based algorithm for diagnosis of tuberculosis in HIV patientsR01AI096735 · NIAID · UNIVERSITY OF CAPE TOWN · PI MAARTENS, GARY, MENDELSON, MARC · 2011 to 2014
$369k
NIAID NIH HHS R01 AI096735
6 · The paper itself

Abstract

backgroundThe World Health Organization (WHO) algorithm for the diagnosis of tuberculosis in seriously ill HIV-infected patients recommends that treatment for

methodsWe developed clinical prediction rules for PJP in a prospective cohort of HIV-infected inpatients with WHO danger signs and cough of any duration. The reference standard for PJP was > 1000 copies/mL of

resultsWe enrolled 500 participants. After imputation for missing values, there were 56 PJP outcome events. Dyspnoea was not independently associated with PJP. Oxygen saturation and respiratory rate were inversely correlated. Two clinical prediction rules were developed: chest X-ray possible/likely PJP, haemoglobin ≥ 9 g/dL and either oxygen saturation < 94% or respiratory rate. The area under the receiver operating characteristic curve of the clinical prediction rule models was 0.761 (95% CI 0.683-0.840) for the respiratory rate model and 0.797 (95% CI 0.725-0.868) for the oxygen saturation model. Both models had zero probability for PJP for scores of zero, and positive likelihood ratios exceeded 10 for high scores.

conclusionWe developed simple clinical prediction rules for PJP, which, if externally validated, could assist decision-making in the WHO seriously ill algorithm.

Identifiers

PMID30167340
PMCPMC6111628

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.