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The study intends to investigate the personal experiences of diabetic kidney disease patients who take part in a separate clinical study including a specific medication intervention. The major focus will be on closely following individuals' rates of trial completion and withdrawal.
The data collected from this study will help improve future outcomes for all diabetic kidney disease as well as those in under-represented demographic groups.
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| Measure | Description | Time Frame |
|---|---|---|
| Number of patients who decide to enroll in a diabetic kidney disease clinical research | 3 months | |
| Rate of patients who remain in a diabetic kidney disease clinical trial to trial completion | 12 months |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with diabetic kidney disease who are actively considering enrolling in a clinical trial for said condition, but have not yet completed enrollment and randomization phases.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Michael B Gill | Contact | (415) 900-4227 | bask@withpower.com |
| Name | Affiliation | Role |
|---|---|---|
| Michael B Gill | Power Life Sciences Inc. | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Power Life Sciences | San Francisco | California | 94107 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33122288 | Background | Schrauben SJ, Shou H, Zhang X, Anderson AH, Bonventre JV, Chen J, Coca S, Furth SL, Greenberg JH, Gutierrez OM, Ix JH, Lash JP, Parikh CR, Rebholz CM, Sabbisetti V, Sarnak MJ, Shlipak MG, Waikar SS, Kimmel PL, Vasan RS, Feldman HI, Schelling JR; CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators. Association of Multiple Plasma Biomarker Concentrations with Progression of Prevalent Diabetic Kidney Disease: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study. J Am Soc Nephrol. 2021 Jan;32(1):115-126. doi: 10.1681/ASN.2020040487. Epub 2020 Oct 29. | |
| 32135136 |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| ICF | No | No | Yes | Informed Consent Form | Oct 20, 2023 | Oct 20, 2023 | ICF_000.pdf |
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| ID | Term |
|---|---|
| D003928 | Diabetic Nephropathies |
| ID | Term |
|---|---|
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
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| Background |
| Tofte N, Lindhardt M, Adamova K, Bakker SJL, Beige J, Beulens JWJ, Birkenfeld AL, Currie G, Delles C, Dimos I, Francova L, Frimodt-Moller M, Girman P, Goke R, Havrdova T, Heerspink HJL, Kooy A, Laverman GD, Mischak H, Navis G, Nijpels G, Noutsou M, Ortiz A, Parvanova A, Persson F, Petrie JR, Ruggenenti PL, Rutters F, Rychlik I, Siwy J, Spasovski G, Speeckaert M, Trillini M, Zurbig P, von der Leyen H, Rossing P; PRIORITY investigators. Early detection of diabetic kidney disease by urinary proteomics and subsequent intervention with spironolactone to delay progression (PRIORITY): a prospective observational study and embedded randomised placebo-controlled trial. Lancet Diabetes Endocrinol. 2020 Apr;8(4):301-312. doi: 10.1016/S2213-8587(20)30026-7. Epub 2020 Mar 2. |
| 33797560 | Background | Chan L, Nadkarni GN, Fleming F, McCullough JR, Connolly P, Mosoyan G, El Salem F, Kattan MW, Vassalotti JA, Murphy B, Donovan MJ, Coca SG, Damrauer SM. Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease. Diabetologia. 2021 Jul;64(7):1504-1515. doi: 10.1007/s00125-021-05444-0. Epub 2021 Apr 2. |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
| D048909 | Diabetes Complications |
| D003920 | Diabetes Mellitus |
| D004700 | Endocrine System Diseases |