SARS-CoV-2 Infection, A Risk Factor for Pituitary Apoplexy? A Case Series and Literature Review
Bibliographic record
Abstract
Introduction: Pituitary apoplexy (PA) is a rare phenomenon, characterized by a hemorrhagic or ischemic event of the pituitary gland, most often in association with a pituitary lesion. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the strain of virus responsible for the internationally recognized global pandemic COVID-19. Multiple clinical manifestations associated with this virus have been described, ranging from asymptomatic, mild flu symptoms to acute respiratory distress syndrome, end-organ failure leading to death. Cases of patients with concomitant COVID-19 infections and PA are being further recognized in the literature, but the causal association between the 2 entities remains speculative. Objectives: The objectives of this case series are 3-fold: to describe additional cases of patients with concomitant COVID-19 infection and PA (1), to review the current evidence regarding this potential complication associated with a COVID-19 infection (2), and to discuss physiopathological hypotheses, treatments, and prognoses of this newly recognized association (3). Method: We conducted an electronic chart review of patients treated for PA with concomitant COVID-19 infection from March 2020 to December 2021. A literature review was performed using MEDLINE, Web of Science, and Embase databases to identify other cases of COVID-19-associated PA. Results: From March 2020 to December 2021, 3 patients presented to our center with PA following a symptomatic COVID-19 infection. Two of these patients developed PA symptoms days following the viral infection, whereas the third patient developed PA after a 2-month period. The 2 first patients were managed surgically because of persistent visual symptoms. Results from our literature review yielded 12 other cases of COVID-19-associated PAs. Conclusions: The association between COVID-19 infection and PA has been increasingly reported in the literature. With the addition of the 3 cases described in our article, a total of 15 cases have been published. Many contributing mechanisms may lead to PA following COVID-19 infection. Coagulopathy is probable major contributing cause responsible for hemorrhage or infarction of the pituitary gland. Our case series provides further arguments that PA may be a direct manifestation of a COVID-19 infection.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".