Urinary clonidine suppression testing for the diagnosis of pheochromocytoma
Bibliographic record
Abstract
OBJECTIVE: The diagnosis of pheochromocytoma/paraganglioma (PPGL) involves detection of elevated levels of plasma and/or 24-h urine catecholamines and/or their metabolites, including metanephrines. Although these tests are reasonably sensitive, false-positive results are often encountered. Follow-up tests can provide additional information to correctly diagnose PPGL. In this regard, the utility of the urinary clonidine suppression test (UCST) remains unknown. METHODS: To assess the diagnostic accuracy of the UCST in confirming or excluding PPGL, we conducted a retrospective analysis of all patients who underwent a UCST between 2000 and 2013 (n = 59; 15 PPGLs) at a single centre. Twelve-hour urine catecholamines and metanephrines were assessed before and after clonidine administration, and examined in relation to final diagnosis, PPGL or non-PPGL. Receiver operating characteristic analyses were used to identify optimal positivity cut-offs. Sensitivity, specificity, positive and negative predictive values were calculated. RESULTS: Clonidine significantly decreased urine creatinine-corrected norepinephrine and normetanephrine in patients without PPGL (P < 0.001 pairwise) but not in patients with PPGL. Epinephrine and metanephrine levels were not significantly reduced in either group. Receiver operating characteristic (ROC) area under the curve was 0.955 [95% confidence interval (95% CI) 0.906-1.000, P < 0.001] and 0.823 (95% CI 0.706-0.940, P < 0.001) for norepinephrine and normetanephrine, respectively. Optimal cut-offs were established at 50 and 15% reductions in norepinephrine and normetanephrine, respectively, which provided high sensitivities (93.3% for both) and negative predictive values (97.4 and 96.3%). When both were concordant, higher diagnostic accuracy was achieved (100% sensitivity, 92.0% specificity). Results were similar in subgroups of individuals with borderline initial testing (n = 40) or on interfering drugs (n = 25). CONCLUSION: The UCST appears to be a highly accurate test for PPGL. Further prospective studies are needed to validate these results before routine use is encouraged.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".