Evidence map›Paper›PMID 39045873›Full record

ArticleEndocrine connections2024

Reversible central adrenal insufficiency in survivors of COVID-19: results from a 24-month longitudinal study.

Saroj Kumar Sahoo, Jayakrishnan C Menon, Nidhi Tripathy, Monalisa Nayak, Subhash Yadav

Abstract read
In one paragraph

Article in Endocrine connections, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Saroj Kumar SahooDepartment of Endocrinology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID 0000-0001-6246-3519
Jayakrishnan C MenonDepartment of Endocrinology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID 0000-0002-2658-4505
Nidhi TripathyDepartment of Endocrinology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID 0000-0002-7709-9200
Monalisa NayakDepartment of Liver Intensive Care Unit, King's College Hospital, London, UK.
Subhash YadavDepartment of Endocrinology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID 0000-0003-3275-6673

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We studied the temporal course of hypothalamic-pituitary-adrenal (HPA) dysfunction in patients with coronavirus disease 2019 (COVID-19). Methods: Three hundred and two patients (median age 54 years (interquartile range (IQR) 42-64), 76% males) were recruited. The HPA axis was evaluated by morning cortisol and adrenocorticotrophic hormone (ACTH) at admission (n = 232). Adrenal insufficiency (AI) during acute illness was defined using a morning cortisol <83 nmol/L. AI at 12 months follow-up was defined using a peak cortisol <406 nmol/L in the ACTH stimulation test (APST) (n = 90). Those with AI at 12 months were further assessed by APST every 6 months for recovery of hypoadrenalism. Results: The median morning cortisol and ACTH levels during COVID-19 were 295 (IQR 133-460) nmol/L and 3.9 (0.8-6.9) pmol/L, respectively. AI was present in 33 (14%) patients; ACTH was elevated in three and low or inappropriately normal in the rest 30 patients. At 12 months, AI was seen in 13% (12/90) patients, with all cases being hypothalamic-pituitary in origin; five (42%) of them had not met the diagnostic criteria for AI during COVID-19. AI diagnosed at admission persisted at 12 months in seven patients and recovered in seven; the remaining 19 patients were lost to follow-up. The presence of AI at 12 months was independent of severity and steroid use during COVID-19. A morning cortisol <138 nmol/L during COVID-19 predicted the presence of AI at 12 months. All patients showed recovery of the HPA axis in the ensuing 12 months. Conclusion: Central AI was common during acute COVID-19 and at 12 months of follow-up. AI can be late onset, developing after recovery from COVID-19, and was transient in nature.

Indexed as

adrenal insufficiencyCOVID-19hypothalamic–pituitary–adrenal axisSARS-CoV-2

Identifiers

PMID39045873
PMCPMC11378128

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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.