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Cited by 30Pituitary Gland Disorders and TreatmentsTraumatic Brain Injury and Neurovascular DisturbancesTraumatic Brain Injury Research

The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index; none of the 21 sources its claims cite is checked for support yet.

Acute and chronic hypopituitarism following traumatic brain injury: a systematic review and meta-analysis

Open access
Aljboor, Ghaith S., Tulemat, Aoun, Al-Saedi, Ali Ridha, Radoi, Mugurel Petrinel, Toader, Corneliu, Papacocea, Toma Marius·2024·Neurosurgical Review

Abstract

Traumatic brain injury (TBI) is associated with various endocrine abnormalities, including pituitary axis dysfunction. Understanding the prevalence and temporal patterns of these dysfunctions is crucial for effective clinical management. This study aimed to systematically review the literature and conduct a meta-analysis to determine the prevalence of pituitary axis dysfunction following TBI, assess temporal patterns across different post-injury durations, and identify potential contributing factors. A comprehensive search was conducted across multiple electronic databases between 1st of January 2000 until 31st March 2024. Studies reporting the prevalence of pituitary axis dysfunction post-TBI were included. Pooled estimates with 95% confidence intervals (CIs) were calculated using random-effects models in the R statistical software. Subgroup analyses were performed based on duration post-TBI (< 3 months, 3–6 months, 6–12 months, > 12 months) to explore temporal variations. Heterogeneity was assessed using the I^2 statistic. A total of 52 studies were included in the meta-analysis, encompassing 7367 participants. The pooled estimate for the prevalence of any pituitary axis dysfunction post-TBI was 33% (95% CI [28%; 37%]). Subgroup analysis by duration revealed varying prevalence rates: < 3 months (40%, 95% CI [27%; 53%]), 3–6 months (31%, 95% CI [15%; 47%]), 6–12 months (26%, 95% CI [19%; 33%]), and > 12 months (32%, 95% CI [26%; 38%]). Prevalence of multiple axes affection was 7% (95% CI [6%; 9%]), with varying rates across durations. Specific axes affection varied: Growth Hormone (GH) deficiency was 18% (95% CI [14%; 21%]), adrenocorticotropic hormone (ACTH) deficiency was 10% (95% CI [8%; 13%]), pituitary–gonadal axis hormones deficiency was 16% (95% CI [12%; 19%]), and thyroid-stimulating hormone (TSH) deficiency was 6% (95% CI [5%; 7%]). This meta-analysis highlights a significant prevalence of pituitary axis dysfunction following TBI, with temporal variations observed across different post-injury durations. The findings underscore the importance of tailored clinical management strategies based on the duration and type of dysfunction. Further research addressing potential contributing factors is warranted to enhance understanding and management of these conditions.

Overview

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TL;DR

This systematic review and meta-analysis of 52 studies and 7367 participants found that the pooled prevalence of any pituitary axis dysfunction after traumatic brain injury was 33% (95% CI [28%; 37%]). Prevalence varied by time since injury and by specific pituitary axis, with growth hormone deficiency being the most common.

Key findings

  • Pooled prevalence of any pituitary axis dysfunction post-TBI was 33% (95% CI [28%; 37%]); by duration, it was 40% (95% CI [27%; 53%]) at <3 months, 31% (95% CI [15%; 47%]) at 3–6 months, 26% (95% CI [19%; 33%]) at 6–12 months, and 32% (95% CI [26%; 38%]) at >12 months.
  • Multiple axes affection had an overall pooled prevalence of 7% (95% CI [6%; 9%]), with 13% (95% CI [6%; 20%]) at <3 months and 7% at later intervals.
  • Specific axis deficiencies: GH deficiency 18% (95% CI [14%; 21%]), pituitary–gonadal axis hormones deficiency 16% (95% CI [12%; 19%]), ACTH deficiency 10% (95% CI [8%; 13%]), and TSH deficiency 6% (95% CI [5%; 7%]).
  • Pituitary–gonadal axis deficiency was highest within the first 3 months at 34% (95% CI [21%; 47%]), while GH deficiency was highest beyond 12 months at 19% (95% CI [14%; 24%]).

Methods

  • Systematic review and meta-analysis following PRISMA; searched PubMed, Web of Science, Scopus, Medline, Cochrane Library, and Google Scholar for English-language studies published from 1 January 2000 to 31 March 2024.
  • Included observational, cohort, case–control, and cross-sectional studies of adults with TBI, requiring clear diagnostic criteria, prevalence data, sample size ≥10, and Newcastle–Ottawa Scale score ≥7; 52 studies with 7367 participants were included.
  • Pooled prevalence estimates used random-effects models in R with the DerSimonian–Laird method; subgroup analyses were by duration post-TBI (<3, 3–6, 6–12, >12 months), with heterogeneity assessed by I² and publication bias by funnel plots.

Limitations

  • The paper states that potential risk factors remain unclear, publication bias is possible, English-language restriction may limit generalizability, incomplete reporting challenged data extraction/quality assessment, and some relevant recent studies may have been overlooked.
  • The text makes evident substantial heterogeneity: overall I² was 95% for any axis affection, 89–97% across duration subgroups, and up to 96% for specific axes, so pooled estimates should be interpreted cautiously.
  • The text also makes evident variability across included study designs (28 prospective, 9 retrospective, 15 cross-sectional) and diagnostic/time definitions, which likely contributes to inconsistent prevalence estimates.

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Integrity signals

Registry

Crossref · 10.1007/s10143-024-03088-3

Cites

69 of 69 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 PRISMA flow diagram for summary of search and screening processes
Fig. 1 PRISMA flow diagram for summary of search and screening processesCC BY · PubMed Central
Fig. 2 Forest plot of the pooled prevalence of any axis affection (n = 52)
Fig. 2 Forest plot of the pooled prevalence of any axis affection (n = 52)CC BY · PubMed Central
Fig. 3 Forest plot of the pooled prevalence of multiple axes affection (n = 36)
Fig. 3 Forest plot of the pooled prevalence of multiple axes affection (n = 36)CC BY · PubMed Central
Fig. 4 Forest plot of the pooled prevalence of growth hormone deficiency (n = 46)
Fig. 4 Forest plot of the pooled prevalence of growth hormone deficiency (n = 46)CC BY · PubMed Central
Fig. 5 Forest plot of the pooled prevalence of adrenocorticotrophic hormone deficiency (n = 47)
Fig. 5 Forest plot of the pooled prevalence of adrenocorticotrophic hormone deficiency (n = 47)CC BY · PubMed Central
Fig. 6 Forest plot of the pooled prevalence of pituitary–gonadal axis hormones deficiency (n = 45)
Fig. 6 Forest plot of the pooled prevalence of pituitary–gonadal axis hormones deficiency (n = 45)CC BY · PubMed Central
Fig. 7 Forest plot of the pooled prevalence of TSH deficiency (n = 45)
Fig. 7 Forest plot of the pooled prevalence of TSH deficiency (n = 45)CC BY · PubMed Central

Verification

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Citations

Cites

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Research works printed but not linked: 2

  1. Verma PK, Rege SV, Jatav G, Kumar A (2021) Assessment of patterns of pituitary dysfunction after severe traumatic brain injury. Int J Surg 5(4):251–4
  2. Zacharia SS (2022) Endocrine dysfunction in patients with moderate to severe traumatic brain injury 6 months to 2 years after injury. Doctoral Dissertation, Christian Medical College, Vellore

Cited by

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Metadata

Authors
Aljboor, G. S., Tulemat, A., Al-Saedi, A. R., Radoi, M. P., Toader, C., & Papacocea, T. M.
Affiliations
Carol Davila University of Medicine and Pharmacy (RO)
Corresponding author
Aljboor, Ghaith S.
Venue
Neurosurgical Review
Published
2024-11-11
Volume
47
Issue
1
Pages
841-841
ISSN
  • 0344-5607 (ISSN-L)
  • 1437-2320
OpenAlex
W4404221588
Cited by
30
References
69
Citations by year
2026: 16 · 2025: 14
FWCI
1.40
Type
journal article
Language
en
Open access
Licence
Locations
  • Neurosurgical Review (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pituitary Gland Disorders and Treatments
  • Health Sciences › Medicine › Clinical Neurology › Traumatic Brain Injury and Neurovascular Disturbances
  • Health Sciences › Medicine › Clinical Neurology › Traumatic Brain Injury Research
Keywords
traumatic brain injury, hypopituitarism, growth hormone deficiency, ACTH deficiency, gonadotropin deficiency, thyroid-stimulating hormone deficiency, prevalence, temporal patterns, endocrine dysfunction, risk factors, pituitary imaging, pituitary surgery, hormone replacement therapy, quality of life
MeSH terms
Brain Injuries, Traumatic, Chronic Disease, Humans, Hypopituitarism, Prevalence

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.