Evidence map›Paper›PMID 36482998›Full record

ReviewFrontiers in endocrinology2022

The promising role of risk scoring system for Cushing syndrome: Time to reconsider current screening recommendations.

C E Lam-Chung, D Cuevas-Ramos

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in endocrinology, 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
0.6field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
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

2 authors at 1 institution in 1 country.

C E Lam-ChungDepartment of Endocrinology and Metabolism, Complejo Hospitalario Dr. Manuel Amador Guerrero, Colón, Panama.
D Cuevas-RamosNeuroendocrinology Clinic, Department of Endocrinology and Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the current screening approach for Cushing syndrome (CS), delayed diagnosis is common due to broad spectrum of presentation, poor discriminant symptoms featured in diabetes and obesity, and low clinical index of suspicion. Even if initial tests are recommended to screen CS, divergent results are not infrequent. As global prevalence of type 2 diabetes and obesity increases, CS may not be frequent enough to back routine screening to avoid false-positive results. This represents a greater challenge in countries with limited health resources. The development of indexes incorporates clinical features and biochemical data that are largely used to provide a tool to predict the presence of disease. In clinical endocrinology, indexes have been used in Graves' ophthalmology, hirsutism, and hypothyroidism. The use of clinical risk scoring system may assist clinicians in discriminating CS in the context of at-risk populations and, thus, may provide a potential intervention to decrease time to diagnosis. Development and validation of clinical model to estimate pre-test probability of CS in different geographic source population may help to establish regional prediction model for CS. Here, we review on the latest progress in clinical risk scoring system for CS and attempt to raise awareness for the use, validation, and/or development of clinical risk scores in CS.

Indexed as

Cushing SyndromeDiabetes Mellitus, Type 2EndocrinologyHumansObesityRisk FactorsACTHcorticotropincortisolobesitypituitary adenoma

Identifiers

PMID36482998
PMCPMC9725023
OpenAlexW4309688948

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.