SGLT2 Inhibition in Patients With Type 2 Diabetes Mellitus Post-Nephrectomy: A Single-Center Case Series
Bibliographic record
Abstract
Background: Nephrectomy is the mainstay of treatment for many kidney cancers, but has been correlated with increased incidence of acute kidney injury (AKI) and chronic kidney disease (CKD). Recently, sodium-glucose cotransporter-2 (SGLT2) inhibition has been shown to decrease the incidence of end-stage kidney disease and death in people with type 2 diabetes mellitus (T2D). However, at present, there has been no description of the use of SGLT2 inhibition in patients with T2D and solitary kidney despite the high risk of CKD progression. Objective: To characterize the use of SGLT2 inhibition and kidney function in a series of patients with T2D with prior nephrectomy for renal cell carcinoma (RCC). Design: Retrospective case series. Setting: University hospital outpatient onco-nephrology clinic. Patients: Patients post-nephrectomy for RCC with T2D who were prescribed an SGLT2 inhibitor. Measurements: Serum creatinine, albumin to creatinine ratio (ACR), HgA1c, and blood pressure measurements. Methods: Patients post-nephrectomy with incident use of SGLT2 inhibitor were identified from an existing registry of patients followed in the Onco-Nephrology Clinic at our institution from May 2019 to March 2021. Demographics, medication use, time since nephrectomy, cancer diagnosis, serum creatinine, ACR measurements, and blood pressure measurements were extracted from electronic medical records. Results: Five patients were identified who had initiated SGLT2 inhibition post-nephrectomy. All patients were male, had T2D, and a prior history of hypertension. Renal cell carcinoma was the clinical indication for nephrectomy in all patients. None of patients were prescribed diuretics, and all were receiving renin-angiotensin system (RAS) inhibition therapies. The time from nephrectomy to SGLT2 inhibitor initiation ranged from 5 to 74 months. Baseline mean estimated glomerular filtration rate (eGFR) values were 49 mL/min/1.73 m 2 (95% confidence interval [CI]: 31.5-66.5), and mean ACRs were 8.7 mg/mmol (95% CI: 0.6-16.9). After 6 months of SGLT2 inhibition, the mean eGFR and ACR values were 58 mL/min/1.73 m 2 (95% CI: 29.7-86.2) and 23.8 mg/mmol (95% CI: 0-60), respectively. After 16 to 18 months of follow-up (4 patients), the mean eGFR was 56 mL/min/1.73 m 2 (95% CI: 37.3-74.7), and mean ACR was 10.5 (95% CI: 0-30.5), similar to baseline values before SGTL2i therapy initiation. At baseline, mean systolic blood pressure was 128 mm Hg (95% CI: 118.3-140.9) and remained similar after 12 months of treatment (mean 131 mm Hg [95% CI: 112.3-149.7]). There were no adverse events related to AKI, electrolyte disturbances, ketoacidosis, or genitourinary infections during the 18-month follow-up period. Limitations: Small sample size, lack of a comparison group, and the variable timing of clinical data collection, including eGFR levels following initiation of SGLT2 inhibition. Conclusions: SGLT2 inhibition is becoming a standard component of nephrology care to reduce kidney function decline, cardiovascular risk, and mortality. To our knowledge, our report is the first to provide longitudinal data on SGLT2 inhibitor usage in patients with T2D and solitary kidneys post-nephrectomy. Larger prospective studies are needed to determine the efficacy and safety of SGLT2 inhibition strategies for kidney protection in patients post-nephrectomy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".