Sheehan’s Syndrome in a Fifty-Six-Year-Old Woman Presenting With a Retroperitoneal Mass: Perioperative Management During a Major Surgery
Bibliographic record
Abstract
Patients with Sheehan's syndrome (SS) can present with adrenal crisis, myxedema coma, hypoglycemia, and hyponatremia, which could be triggered by an infection or surgery. For the endocrinologist, a patient with SS who is scheduled for surgery presents a significant challenge as more likely to experience delayed emergence from anesthesia, hypotension that does not respond to the standard regimen, a decrease in core body temperature, and a decreased need for anesthetic drugs due to reduced metabolism. Here, to emphasize the significance of perioperative management to reduce the risk of morbidity and mortality from a potential adrenal crisis, we report the successful perioperative management of a 56-year-old woman with SS undergoing major surgery for the resection of a retroperitoneal tumor. The management plan for this patient comprised a perioperative intravenous hydrocortisone supplementation and thyroxine tablets on the morning of the procedure. In the operating room, the patient was started on norepinephrine, and she was given intravenous (IV) crystalloids and albumin. Healthcare providers should be aware of the perioperative risk of SS. No consensus, guidelines, or randomized trials for the safe perioperative management of patients with SS have been identified by a thorough review of the literature. Because of this, the perioperative care of these patients necessitates the utmost caution in addition to successful management based on close coordination between the endocrinologist, surgeon, and anesthetist. J Endocrinol Metab. 2023;13(1):39-42 doi: https://doi.org/10.14740/jem858
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".