Sex-Related Differences in Self-Reported Symptoms at Diagnosis in Pheochromocytomas and Paragangliomas
Bibliographic record
Abstract
Abstract Context Biological sex can play a role in the severity of certain diseases. Objective Our objective was to evaluate whether sex-related differences affect the signs and symptoms of pheochromocytomas and paragangliomas (PPGLs) at presentation. Methods We reviewed the records of patients with PPGLs at our center from 1995 to 2022. Results Our study included 385 patients with PPGLs: 118 (30.6%) head and neck paragangliomas (HNPGLs), 58 (15.1%) thoracoabdominal paragangliomas (TAPGLs) and 209 (54.3%) pheochromocytomas (PHEOs). The cohort consisted of 234 (60.8%) women and 151 (39.2%) men. At diagnosis, more women than men presented with headaches (47.5% vs 32.4%; P = .007); however, more men presented with diabetes (21.1% vs 12.5%; P = .039). When subdivided by tumor location, headaches occurred more often in women with HNPGLs and TAPGLs (31.0% vs 11.4%; P = .0499 and 60.0% vs 21.7%; P = .0167). More men presented with diabetes among patients with PHEOs (28.2% vs 11.2%; P = .0038). In regard to nonsecretory PPGLs, women presented with a higher prevalence of headaches (46.9% vs 3.6%; P = .0002), diaphoresis (16.3% vs 0.0%; P = .0454), and palpitations (22.4% vs 0.0%; P = .0057). In patients with secretory tumors, women presented with more headaches (58.9% vs 42.7%; P = .0282) and men with more diabetes (29.3% vs 12.5%; P = .0035). Conclusion In our cohort, more women presented with headaches across all tumor types and secretory statuses. More men presented with diabetes among patients with PHEOs and secretory tumors. In nonsecretory PPGLs, women had more adrenergic symptoms. These findings can be explained by differences in adrenergic receptor sensitivity, self-reported symptoms, and possibly other vasoactive peptides and sex-hormone status.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".