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2. Delineating endogenous Cushing’s syndrome by GC-MS urinary steroid metabotyping

3. Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort

4. Steroidomics-Based Screening for Primary Aldosteronism: Impact of antihypertensive Drugs.

5. The saline infusion test with mass spectrometric measurements of aldosterone in patients tested for primary aldosteronism

7. #357 Sex differences in the aldosterone-renin system must be taken into account during screening for primary aldosteronism

8. Identification of Succinate Dehydrogenase Gene Variant Carriers by Blood Biomarkers.

9. Screening for Primary Aldosteronism by Mass Spectrometry Versus Immunoassay Measurements of Aldosterone: A Prospective Within-Patient Study.

10. Asymmetric Adrenals: Sexual Dimorphism of Adrenal Tumors

11. Asymmetric Adrenals: Sexual Dimorphism of Adrenal Tumors.

12. Lack of sensitivity of diagnostic Cushing-scores in Germany: a multicenter validation

13. The Saline Infusion Test for Primary Aldosteronism: Implications of Immunoassay Inaccuracy

15. Screening for primary aldosteronism using steroidomics with machine learning and comparison to aldosterone:renin ratios

18. Determinants of disease-specific survival in patients with and without metastatic pheochromocytoma and paraganglioma

19. Plasma Steroid Profiling in Patients With Adrenal Incidentaloma

20. Determinants of disease-specific survival in patients with and without metastatic pheochromocytoma and paraganglioma

21. Case report: Incidentally discovered case of pheochromocytoma as a cause of long COVID-19 syndrome

22. Silent pheochromocytoma and paraganglioma: Systematic review and proposed definitions for standardized terminology

23. Head/neck paragangliomas: focus on tumor location, mutational status and plasma methoxytyramine

24. Determinants of disease-specific survival in patients with and without metastatic pheochromocytoma and paraganglioma

25. Head/neck paragangliomas: focus on tumor location, mutational status and plasma methoxytyramine

26. Plasma metanephrines and prospective prediction of tumor location, size and mutation type in patients with pheochromocytoma and paraganglioma

27. The Saline Infusion Test for Primary Aldosteronism: Implications of Immunoassay Inaccuracy

28. Plasma Steroid Profiling in Patients With Adrenal Incidentaloma

30. Plasma metanephrines and prospective prediction of tumor location, size and mutation type in patients with pheochromocytoma and paraganglioma

31. Plasma metanephrines and prospective prediction of tumor location, size and mutation type in patients with pheochromocytoma and paraganglioma

32. Mass spectrometry reveals misdiagnosis of primary aldosteronism with scheduling for adrenalectomy due to immunoassay interference

33. Overnight/first-morning urine free metanephrines and methoxytyramine for diagnosis of pheochromocytoma and paraganglioma: is this an option?

34. Glucocorticoid excess in patients with pheochromocytoma compared to paraganglioma and other forms of hypertension

35. Plasma metanephrines and prospective prediction of tumor location, size and mutation type in patients with pheochromocytoma and paraganglioma

36. Pheochromocytoma Concealed By Chronic Methamphetamine Abuse

37. Mass spectrometry reveals misdiagnosis of primary aldosteronism with scheduling for adrenalectomy due to immunoassay interference

38. Glucocorticoid Excess in Patients with Pheochromocytoma Compared with Paraganglioma and Other Forms of Hypertension

39. Overnight/first-morning urine free metanephrines and methoxytyramine for diagnosis of pheochromocytoma and paraganglioma: is this an option?

41. Optimizing Genetic Workup in Pheochromocytoma and Paraganglioma by Integrating Diagnostic and Research Approaches

44. How can cortisol-normalized adrenal venous sampling miss some Conn's adenoma

45. Legg Calve Perthes disease and growth hormone treatment

47. Aggressive macroprolactinoma - exception to the rule

50. Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort

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