Bibliographic record
Abstract
Endogenous Cushing's syndrome results in significant multisystemic morbidity and elevated mortality if left untreated i . The manifestations of this condition impact multiple organs and systems, and clinical presentation of the disease vary widely among individuals. A high index of clinical suspicion is essential for accurate diagnosis, which necessitates multiple sequential tests, each requiring careful interpretation ii . The complexity of diagnosing and managing this condition demands individualized approaches and present ongoing challenges for endocrinologists iii .This Research Topic emcompasses original papers addressing critical clinical questions aimed at improving the diagnosis and treatment of patients with Cushing's syndrome. The objective is to gather novel insights into the disease to assist clinicians in the patient management and to inform research initiatives.The study by Pekul et al. emphasizes the relevance of USP and TP53 mutations in pituitary tumors for prognostic guidance, comparing corticotroph tumors causing Cushing's disease (CD) with their silent counterparts. Feelders and al share the results of the extension of a multicenter Phase II study examining patients initially treated with pasireotide, who were subsequently combined with cabergoline if cortisol remained elevated. The study demonstrates that this combination of pituitary-targeted therapies can yield sustained long-term e icacy in selected patients.Zhang and Ioachimescu discuss the post-surgical recovery phase in a mini-review, highlighting the need for clinicians to anticipate the glucocorticoid withdrawal syndrome and adequately prepare their patients for this challenging phase, during which symptoms may initially worsen before improving. This review presents novel data to enhance understanding of the condition and suggests management strategies.This Research Topic emphazises several key areas of ongoing research aimed at advancing our understanding of Cushing's syndrome. It underscores the importance of collaborative e to improve the health and quality of life for patients a ected by this condition.The author declare that no funding was received to write this manuscript which was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.024 | 0.015 |
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".