Acute and chronic endocrine abnormalities during and after COVID-19 infection in children and adolescents: A mini review
Bibliographic record
Abstract
Background: The COVID-19 pandemic has resulted in widespread disruptions across multiple physiological systems in children and adolescents, including the endocrine system. Emerging global data reveal both acute and chronic endocrine abnormalities linked to SARS-CoV-2 infection and its systemic inflammatory response. Objective: To review and compare the prevalence and mechanisms of endocrine dysfunctions in pediatric populations during and following COVID-19, based on real, validated international studies from 2019 to 2025. Methods: A systematic literature review was conducted across PubMed, Embase, Medline, and Google Scholar between 2019 and 2025. Inclusion criteria included peer-reviewed studies involving pediatric COVID-19 cases and endocrine complications. Data from 41 validated studies were synthesized. A PRISMA diagram was used to track study selection. Descriptive statistics and pooled prevalence were used to compare acute and chronic outcomes, and the methodological quality of studies was assessed using Cochrane and Newcastle–Ottawa criteria. Results: Acute endocrine complications included non-thyroidal illness syndrome (NTIS) (33–88%), HPA axis suppression, adrenal crisis (3.4%), subacute thyroiditis, and transient glycemic disturbances. Chronic complications included a 2–3× rise in central precocious puberty, significant increases in new-onset type 1 diabetes with diabetic ketoacidosis (DKA) in up to 51%, and rising rates of pediatric obesity and metabolic syndrome. These conditions showed variation by age, sex, and geography. Mechanistically, endocrine dysfunctions were driven by direct viral invasion (via ACE2), cytokine storm, autoimmune activation, iatrogenic steroid use, lifestyle disruption, and RAAS imbalance. Conclusion: COVID-19 poses both direct and indirect risks to endocrine health in pediatric populations. Heightened awareness, age- and sex-specific monitoring, and regionally tailored endocrine follow-up protocols are essential to reduce long-term morbidity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".