ABSTRACT
We evaluated the renal outcomes and safety of spironolactone added to renin–angiotensin system inhibitors (RASis) among patients with type 2 diabetes (T2D), given its uncertain role alongside RASis, the cornerstone of T2D with renal disease management. In this retrospective study at National Cheng Kung University Hospital (2014–2021), we identified adult T2D patients receiving RASis alone or combined with spironolactone. Propensity score matching between treatment groups was implemented to achieve between‐group comparability. The primary outcome was a composite renal outcome (including end‐stage renal disease [ESRD], renal transplant, or a ≥ 30% estimated glomerular filtration rate [eGFR] decline). Secondary outcomes included proteinuria, major adverse cardiovascular events, and hyperkalemia. Cox proportional hazard model analyses were adopted to assess the treatment outcomes. 404 PS‐matched pairs of RASis‐alone and RASis+spironolactone users were included. Adding spironolactone to RASis was associated with increased composite renal event (hazard ratio [95% CI]: 1.27 [1.06–1.51]), persistent eGFR decline ≥ 30% (1.31 [1.09–1.58]), and hyperkalemia (1.57 [1.21–2.04]) risks while associated with a higher likelihood of achieving ≥ 30% proteinuria reduction (HR 1.34 [1.12–1.60]). Having heart failure (HF) was a significant effect modifier, that is, using RASis+spironolactone versus RASis alone was associated with a lower ESRD/renal transplant risk among patients with HF (0.62 [0.38–1.02]) but an increased risk for those without HF (1.32 [0.98–1.78]) (p for interaction = 0.011). Adding spironolactone to RASis might increase renal adverse events and hyperkalemia but reduce proteinuria in T2D patients. Notably, heart failure status significantly modified these associations, underscoring the importance of personalized medicine.
Keywords: chronic kidney disease, hyperkalemia, renin–angiotensin system (RAS) inhibitors, spironolactone, type 2 diabetes
Study Highlights
- What is the current knowledge on the topic?
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○Overactivation of mineralocorticoid receptors promotes renal inflammation and fibrosis in type 2 diabetes (T2D). Steroidal mineralocorticoid receptor antagonists (MRAs) such as spironolactone reduce albuminuria, but their long‐term effects on renal disease progression among real‐world T2D populations on renin–angiotensin system inhibitors (RASis) warrant further confirmation in diverse clinical settings, particularly given the risk of hyperkalemia.
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- What question did this study address?
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○We investigated whether spironolactone added to RASis therapy improves renal outcomes or increases adverse events in routine T2D care, and whether effects differ across patient subgroups.
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- What does this study add to our knowledge?
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○In a real‐world cohort of patients with T2D, add‐on spironolactone reduced proteinuria but increased the risks of composite renal outcomes, sustained ≥ 30% eGFR decline, and hyperkalemia. Heart failure modified these effects: patients with heart failure showed possible renal benefit, whereas those without faced increased risk.
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- How might this change clinical pharmacology or translational science?
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○These findings emphasize the need for individualized therapy and careful electrolyte monitoring when prescribing steroidal MRAs in T2D. They may inform clinical decision‐making regarding the choice between spironolactone and newer nonsteroidal MRAs such as finerenone, while guiding future translational studies and real‐world benefit–risk assessments in diabetic kidney disease.
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1. Introduction
The pathophysiology of CKD in patients with T2D is multifactorial, involving metabolic, hemodynamic, inflammatory, and fibrotic processes [1, 2, 3]. Renin–angiotensin system inhibitors (RASis), including angiotensin‐converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), are currently the cornerstone of therapy for diabetic kidney disease. While RASis delay CKD progression, the residual risk of renal deterioration remains high. A key contributing factor is the phenomenon known as “aldosterone breakthrough,” where plasma aldosterone levels return to or exceed baseline values despite chronic suppression with ACEIs or ARBs [4]. This incomplete blockade leads to the overactivation of the mineralocorticoid receptor (MR), which drives renal inflammation, fibrosis, and endothelial dysfunction. Aldosterone also induces mitochondrial stress, reactive oxygen species generation, and extracellular matrix deposition, accelerating renal injury [5]. These mechanisms provide a strong rationale for MR antagonists (MRAs) as therapeutic agents.
Spironolactone (SL), a well‐established steroidal MRA, is widely used to manage heart failure with reduced ejection fraction (HFrEF) [6] and resistant hypertension [7]. It reduces proteinuria [8, 9] but does not appear to provide long‐term benefits in slowing renal disease progression, including renal function decline and ESRD prevention in patients with CKD [10, 11]. Evidence of its use in real‐world T2D patients with diverse clinical characteristics is scarce, considering existing evidence mainly from homogenous trial populations, small sample sizes, lack of hard renal outcome (e.g., only albuminuria reduction) in limited study periods (e.g., 1 year) [12, 13] or patients with comorbid with other conditions (e.g., hypertension and macroalbuminuria at baseline) [14]. Although finerenone, a nonsteroidal MRA with proven reno‐protective efficacy in patients with T2D and CKD [15, 16, 17], SL's affordability and accessibility make it a potentially valuable option, particularly in resource‐limited settings.
Against this background, this study evaluated the impact of SL on renal composite outcomes, including proteinuria reduction, persistent estimated glomerular filtration rate (eGFR) decline and hard renal outcomes (i.e., ESRD and renal replacement therapy), in a real‐world patient population with T2D. We seek to provide critical insights into the clinical benefits and risks of SL use in this vulnerable population by addressing the current evidence gap.
2. Materials and Methods
2.1. Data Source and Study Cohort
We conducted a retrospective cohort study based on the electronic hospital records (EMRs) of the National Cheng Kung University Hospital (NCKUH) from 2011 to 2021. As a premier medical center in southern Taiwan, the NCKUH serves an average of 6310 outpatient visits, 261 emergency admissions, and 141 inpatient visits per day [18]. The EMRs incorporated comprehensive data from outpatient visits, inpatient admissions, emergency room encounters, and pharmacy services across 28 clinical specialties. This study was approved by the Institutional Review Board of NCKUH (B‐ER‐108‐140).
Through the EMRs, we identified individuals (1) aged ≥ 18 years, (2) diagnosed with T2D (defined as having two outpatient visits with T2D diagnosis [ICD‐9‐CM codes: 250.x0, 250.x2, where x = 0–9; ICD‐10‐CM code: E11] within a year, or one outpatient visit with T2D diagnosis and any prescriptions for glucose‐lowering agents (GLAs) within the same year), and (3) prescribed renin–angiotensin system inhibitors (RASis) (including angiotensin‐converting enzyme inhibitors [ACEIs] and angiotensin receptor blockers [ARBs]) or SL based on stable RASis use. The patients were further classified into two groups: (1) RASis alone or (2) RASis combined with SL (RASis+SL). The RASis group consisted of new users who had used RASis between January 1, 2015 and June 30, 2021 but had no exposure to SL during the study period. Conversely, the RASis+SL group comprised patients who initiated SL while maintaining stable RASis use. Specifically, stable use was defined as at least three consecutive prescriptions of RASis or SL, with no more than 30 days between the refills. The index date was determined as the date of the first stable prescription for either RASis (for the RASis group) or SL (for the RASis+SL group). We further excluded patients with ESRD or malignancy and those without any available laboratory data or missing eGFR, albumin‐creatinine ratio (ACR), or total protein‐creatinine ratio (PCR) data.
To enhance the between‐treatment group comparability in clinical characteristics at baseline (i.e., index date), a 1:1 propensity score (PS) matching was performed with the individual PS estimated (i.e., a greedy nearest‐neighbor method with a caliper width of 0.25) [19] using the variables selected based on clinical relevance and their association with treatment selection and study outcomes. These variables were measured a year before or at the index date, including demographics (i.e., age, gender), comorbidities, laboratory tests, the adapted diabetes complications severity index (aDCSI) score [20], glucose‐lowering agents, and CVD‐related medications (Tables S1 and S2). The between‐group comparability at baseline after the matching was assessed using standardized mean differences (SMDs), with an absolute SMD > 0.1 indicating a potential imbalance (Figures S1 and S2).
2.2. Study Outcomes
The primary outcome was a composite renal event, comprising the occurrence of ESRD, renal transplantation, or a ≥ 30% decline in eGFR as sustained across ≥ 2 measures ≥ 90 days apart [21]. The eGFR was calculated based on creatinine level via the MDRD formula [22]. The secondary outcomes included a ≥ 30% reduction in the urine ACR from baseline on ≥ 2 measures, 3‐point major adverse cardiovascular events (MACE) (i.e., nonfatal stroke, nonfatal myocardial infarction, and cardiovascular death), hyperkalemia, and hyponatremia. The renal events of interest were identified using the ICD‐9‐CM and ICD‐10‐CM codes supplemented by laboratory test results (detailed in Table S2).
2.3. Statistical Analyses
The patient clinical characteristics at baseline before and after the matching are analyzed using descriptive statistics, including frequencies (percentages) and means (SDs) for categorical and continuous variables. The crude event rates of renal events of interest were calculated as the number of first events during follow‐up divided by the total person‐years at risk. Person‐years at risk were computed from the index date until the first occurrence of an event, death, or December 31, 2021, whichever came first. The risk of a renal event of interest between treatment groups (i.e., RASis vs. RASis+SL) was evaluated using the Cox proportional‐hazards regression model analyses and expressed as hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Moreover, to examine the potential modification effect of patient baseline characteristics on the treatment effect, the treatment exposure with baseline patients' characteristics (i.e., baseline eGFR, hemoglobin A1c [HbA1c] levels, and heart failure history) was treated as the interaction term and included in the analysis. All data analyses were carried out using SAS software version 9.4.
3. Results
3.1. Baseline Characteristics of Study Patients After the PS Matching
404 PS matching pairs of RASis alone, and RASis+SL patients were included to analyze the primary outcome (i.e., a composite renal event) (Figure 1). Prior to the PS matching, patients in the RASis+SL group exhibited higher rates of CVD (e.g., heart failure: 31.6% vs. 6.1%, myocardial infarction [MI]: 5.6% vs. 2.0%), used more CVD‐related medications (e.g., beta‐blockers: 53.6% vs. 34.4%, antiarrhythmics: 16.4% vs. 6.0%) and sodium‐glucose cotransporter 2 inhibitors (SGLT2is) (i.e., 7.2% vs. 2.9%), had lower baseline eGFR level (i.e., 61.3 ± 22.0 vs. 73.3 ± 20.9 mL/min/1.73 m2), comprised fewer individuals with ACR < 30 mg/g (25.1% vs. 42.6%) than the RASis alone group. After the matching, no significant between‐group differences in these characteristics remained, as supported by the SMD values < 0.1 (Table 1).
FIGURE 1.
Flowchart of study subjects.
TABLE 1.
Baseline patient characteristics before and after propensity score matching in overall study patients.
| Baseline characteristics | Before matching | After matching | ||||
|---|---|---|---|---|---|---|
| RASis+SL (N = 414) | RASis (N = 3,873) | SMD | RASis+SL (N = 404) | RASis (N = 404) | SMD | |
| Age at index date b , mean (SD), year | 64.5 (12.6) | 63.7 (12.2) | 0.07 | 64.5 (12.5) | 65.6 (12.7) | 0.09 |
| Male (%) | 240 (58.0) | 2,076 (53.6) | 0.09 | 234 (57.9) | 241 (59.7) | 0.04 |
| Comorbidities history in the year before/at index date | ||||||
| Stroke (%) | 41 (9.9) | 391 (10.1) | 0.01 | 41 (10.1) | 49 (12.1) | 0.06 |
| Ischemic heart disease (%) | 124 (30.0) | 882 (22.8) | 0.16 a | 122 (30.2) | 121 (30.0) | 0.01 |
| Heart failure (%) | 131 (31.6) | 237 (6.1) | 0.69 a | 122 (30.2) | 109 (27.0) | 0.07 |
| MI (%) | 23 (5.6) | 77 (2.0) | 0.19 a | 22 (5.4) | 23 (5.7) | 0.01 |
| Liver cirrhosis (%) | 17 (4.1) | 34 (0.9) | 0.21 a | 15 (3.7) | 14 (3.5) | 0.01 |
| aDCSI measured in the year before/at index date, mean (SD) | 2.5 (1.5) | 1.6 (1.4) | 0.57 a | 2.4 (1.5) | 2.5 (1.6) | 0.07 |
| Laboratory results | ||||||
| HbA1c, mean (SD), % | 7.8 (1.5) | 7.7 (1.5) | 0.09 | 7.8 (1.5) | 7.9 (1.5) | 0.01 |
| eGFR, mean (SD), mL/min/1.73m2 | 61.3 (22.0) | 73.3 (20.9) | 0.56 a | 61.4 (22.1) | 59.5 (24.1) | 0.08 |
| ACR, n (%), | 0.50 a | 0.03 | ||||
| < 30 mg/g | 104 (25.1) | 1,648 (42.6) | 103 (25.5) | 97 (24.0) | ||
| 30–300 mg/g | 132 (31.9) | 1,342 (34.7) | 127 (31.4) | 125 (30.9) | ||
| > 300 mg/g | 178 (43.0) | 883 (22.8) | 174 (43.1) | 182 (45.0) | ||
| Na, mean (SD), mmol/L c | 138.6 (3.7) | 139.5 (3.6) | 0.22 a | 138.6 (3.7) | 139.4 (3.7) | — |
| K, mean (SD), mEq/L c | 4.2 (0.5) | 4.3 (0.4) | 0.06 a | 4.2 (0.5) | 4.2 (0.5) | — |
| Glucose‐lowering agents in the year before/at index date | ||||||
| Metformin (%) | 276 (66.7) | 3,071 (79.3) | 0.29 a | 270 (66.8) | 273 (67.6) | 0.02 |
| DPP4is (%) | 244 (58.9) | 1,771 (45.7) | 0.27 a | 236 (58.4) | 251 (62.1) | 0.08 |
| TZD (%) | 45 (10.9) | 291 (7.5) | 0.12 a | 44 (10.9) | 47 (11.6) | 0.02 |
| GLP‐1RA (%) | 12 (2.9) | 75 (1.9) | 0.06 | 10 (2.5) | 11 (2.7) | 0.02 |
| SGLT2is (%) | 30 (7.2) | 111 (2.9) | 0.20 a | 28 (6.9) | 21 (5.2) | 0.07 |
| CVD medications in the year before/at index date | ||||||
| Lipid‐modifying agents (%) | 314 (75.8) | 2,835 (73.2) | 0.06 | 307 (76.0) | 298 (73.8) | 0.05 |
| Diuretics (without SL) (%) | 271 (65.5) | 1,253 (32.4) | 0.70 a | 261 (64.6) | 277 (68.6) | 0.08 |
| α‐blocker (%) | 28 (6.8) | 194 (5.0) | 0.07 | 28 (6.9) | 31 (7.7) | 0.03 |
| β‐blocker (%) | 222 (53.6) | 1,332 (34.4) | 0.39 a | 213 (52.7) | 210 (52.0) | 0.01 |
| CCB (%) | 282 (68.1) | 2,447 (63.2) | 0.10 a | 277 (68.6) | 288 (71.3) | 0.06 |
| Antiarrhythmics (%) | 68 (16.4) | 234 (6.0) | 0.33 a | 63 (15.6) | 64 (15.8) | 0.01 |
| Cardiac glycosides (%) | 35 (8.5) | 36 (0.9) | 0.36 a | 29 (7.2) | 22 (5.4) | 0.07 |
| Vasodilators used in cardiac diseases (%) | 142 (34.3) | 738 (19.1) | 0.35 a | 134 (33.2) | 120 (29.7) | 0.07 |
| Anti‐platelet (%) | 203 (49.0) | 1,542 (39.8) | 0.19 a | 197 (48.8) | 208 (51.5) | 0.05 |
| Anti‐coagulant (%) | 32 (7.7) | 98 (2.5) | 0.24 a | 28 (6.9) | 28 (6.9) | 0.00 |
Abbreviations: ACR, urine albumin to creatinine ratio; aDCSI, adapted diabetes complications severity index; CCB, calcium channel blocker; CVD, cardiovascular disease; DPP4is, dipeptidyl peptidase 4 inhibitors; eGFR, estimated glomerular filtration rate; GLP‐1RA, glucagon ‐like peptide‐1; HbA1c, glycated haemoglobin; K, Potassium; MI, myocardial infarction; Na, Sodium; RASis, renin‐angiotensin system inhibitors; RASis+SL, renin angiotensin system inhibitors plus spironolactone; SD, standard deviation; SGLT2is, sodium‐glucose co‐transporter 2 inhibitors; TZD, Thiazolidinedione.
An absolute standardized mean difference (SMD) > 0.1 indicates a significant between‐group difference in the baseline characteristics.
Index date refers to the date of initiation of RASis or SL treatment in the study period of 2015‐2021.
Serum potassium and sodium data were not included in propensity score matching; shown descriptively.
3.2. Primary Outcomes (Composite Renal Events) and Secondary Outcomes (Renal Events, Proteinuria and Hyperkalemia)
Table 2 and Figure 2 provide the event rates and associated HRs for study events. The RASis+SL group had significantly higher composite renal events (Figure 3a, 25.0 vs. 18.1/100 person‐years, HR [95% CI]: 1.27 [1.06–1.51]; p = 0.008) and a 30% eGFR decline (Figure 3c, 19.5 vs. 13.9/100 person‐years, HR [95% CIs]: 1.31 [1.09–1.58]; p = 0.005), but significantly higher likelihood of achieving ≥ 30% ACR reduction (23.7 vs. 16.1/100 person‐years, HR [95% CI]: 1.34 [1.12–1.60]; p = 0.002) and no difference in the events of ESRD/renal transplant (Figure 3b, 7.2 vs. 6.4/100 person‐years, HR [95% CI]: 1.07 [0.83–1.38]; p = 0.595) than the RASis group. Also, the RASis+SL users had an increased hyperkalemia risk by 57% (HR [95% CIs]: 1.57 [1.21–2.04]; p = 0.001) and a trend of lower MACE risk (HR [95% CIs]: 0.82 [0.62–1.07]; p = 0.146) compared to that of RASis‐treated‐alone patients. Two treatment groups had similar hyponatremia events (i.e., 8.6 vs. 6.5/100 person‐years, HR [95% CIs]: 1.31 [0.97–1.77]; p = 0.079).
TABLE 2.
Event rates of study outcomes of interest before and after matching among study subjects.
| Event of interest | Before matching | After matching | ||
|---|---|---|---|---|
| RASis + SL (N = 414) | RASis (N = 3873) | RASis + SL (N = 404) | RASis (N = 404) | |
| Composite renal event a | ||||
| No. cases | 264 | 1621 | 258 | 238 |
| Event rate (per 100 person‐years) | 25.1 | 9.8 | 25.0 | 18.1 |
| Follow‐up time (per person) (years), mean (SD) | 2.5 (2.3) | 4.3 (2.5) | 2.6 (2.3) | 3.3 (2.6) |
| ESRD or renal transplant | ||||
| No. cases | 120 | 711 | 117 | 119 |
| Event rate (per 100 person‐years) | 7.3 | 3.5 | 7.2 | 6.4 |
| Follow‐up time (per person) (years), mean (SD) | 4.0 (2.3) | 5.2 (2.2) | 4.0 (2.3) | 4.6 (2.4) |
| eGFR declined by 30% | ||||
| No. cases | 238 | 1376 | 233 | 209 |
| Event rate (per 100 person‐years) | 19.5 | 7.6 | 19.5 | 13.9 |
| Follow‐up time (per person) (years), mean (SD) | 3.0 (2.4) | 4.7 (2.4) | 3.0 (2.4) | 3.7 (2.6) |
| MACE | ||||
| No. cases | 97 | 813 | 91 | 117 |
| Event rate (per 100 person‐years) | 5.6 | 4.2 | 5.4 | 6.3 |
| Follow‐up time (per person) (years), mean (SD) | 4.2 (2.5) | 5.0 (2.4) | 4.2 (2.5) | 4.6 (2.6) |
| Hyperkalemia | ||||
| No. cases | 145 | 476 | 142 | 96 |
| Event rate (per 100 person‐years) | 12.3 | 4.4 | 12.3 | 7.4 |
| Follow‐up time (per person) (years), mean (SD) | 3.6 (2.4) | 5.3 (2.1) | 3.6 (2.4) | 4.7 (2.4) |
| Hyponatremia | ||||
| No. cases | 106 | 404 | 103 | 73 |
| Event rate (per 100 person‐years) | 8.7 | 4.7 | 8.6 | 6.4 |
| Follow‐up time (per person) (years), mean (SD) | 4.0 (2.4) | 5.3 (2.1) | 4.0 (2.4) | 4.9 (2.2) |
| ACR decreased by 30% | ||||
| No. cases | 260 | 2204 | 254 | 225 |
| Event rate (per 100 person‐years) | 23.7 | 16.2 | 23.7 | 16.1 |
| Follow‐up time (per person) (years), mean (SD) | 2.7 (2.4) | 3.5 (2.7) | 2.7 (2.5) | 3.5 (2.8) |
Abbreviations: ACR, albumin‐to‐creatinine ratio; eGFR, estimated glomerular filtration rate; ESRD, end‐stage renal disease; MACE, major cardiovascular event; RASis, renin–angiotensin system inhibitors; RASis+SL, renin–angiotensin system inhibitors and spironolactone; SD, standard deviation.
A composite renal event included the events of ESRD, renal transplant, or eGFR declined by 30%.
FIGURE 2.
Cumulative incidence of composite renal events, MACE, electrolyte imbalance and ≥ 30% ACR reduction in patients with T2D treated with RASis + SL versus RASis alone.
FIGURE 3.
Kaplan–Meier survival curves for renal outcomes in matched patients with T2D treated with RASis + SL versus RASis alone. (a) Composite renal events, (b) ESRD or renal transplantation, and (c) eGFR declined by ≥ 30%. The solid line represents the RASis + SL group, and the dashed line represents the RASis‐alone group. p‐values were calculated using the log‐rank test.
3.3. Subgroup Analyses Using the Interaction Testing on eGFR HbA1c Level and Heart Failure History
Figure 4 reveals the modification effect of patient baseline characteristics (i.e., eGFR and HbA1c levels and heart failure history) on the treatment outcomes of interest. The presence or absence of heart failure history appears to modify the renal outcomes of treatment. That is, the use of RASis+SL versus RASis alone was associated with an insignificantly lower risk of ESRD/renal transplant among patients with prior heart failure (i.e., HR [95% CI]: 0.62 [0.38–1.02]), but an insignificantly increased risk for those without heart failure history (1.32 [0.98–1.78]) (p for interaction = 0.011).
FIGURE 4.
Effect modification by baseline characteristics on the risk of composite renal events, eGFR decline, and ACR reduction.
4. Discussion
This real‐world study provides important evidence on the clinical benefits and risks of adding SL to RASis in patients with T2D across all stages of nondialysis CKD. By applying PS matching, we minimized selection bias and achieved balanced comparisons between treatment groups, thereby strengthening the validity of our results to support clinical treatment decisions. Our findings show that while SL reduced proteinuria, it was associated with higher risks of persistent eGFR decline and hyperkalemia. Importantly, heart failure status appeared to modify these associations: in patients with heart failure, add‐on spironolactone showed a trend toward a lower risk of ESRD/renal transplant, though the confidence interval crossed unity.
4.1. Reduced Proteinuria Risk While Increasing Adverse Renal Outcomes With the Use of SL
Consistent with prior studies, our findings support the clinical effectiveness of SL in reducing proteinuria, a key surrogate marker of renal damage [4, 8, 9, 10, 23, 24]. Our findings align with previous studies conducted in CKD patients, demonstrating a decline in eGFR without prevention for ESRD [10, 11]. Similarly, they are consistent with results from small‐scale, short‐term studies in diabetic nephropathy, which also reported eGFR decline [12, 13, 23, 25]. Aldosterone induces efferent arteriole vasoconstriction and increases vascular resistance [26, 27], leading to elevated intraglomerular pressure. SL's alteration of glomerular hemodynamics may contribute to the observed eGFR decline. However, unlike SGLT2i and RASis, SL does not appear to confer long‐term reno‐protective benefits. One possible explanation is SL's partial MR activity due to its recruitment of MR cofactors, a property not observed with finerenone, a nonsteroidal MRA [28, 29, 30].
4.2. Potential Cardiovascular Benefits While High Hyperkalemia Risk With the Use of SL
Although SL did not significantly impact the MACE of study patients with T2D, its established cardiovascular benefits in heart failure patients should be noted. A previous large‐scale trial, the RALES trial, demonstrated SL's ability to reduce cardiovascular mortality and hospitalizations in patients with HFrEF [6]. Meta‐analyses of steroidal MRAs use in heart failure have also demonstrated reductions in heart failure‐related mortality and hospitalizations across different eGFR levels [14]. These cardiovascular benefits may partly explain why heart failure patients in our study experienced better renal outcomes (Figure 4), as cardiac and hemodynamic stability improvements may indirectly support renal perfusion and function.
Noticeably, a recent U.S. retrospective study, which included patients with more advanced CKD (i.e., T2D patients with urine ACR > 300 mg/g and eGFR < 90 mL/min/1.73 m2) than our cohort and comorbid with hypertension, also found no significant reduction in cardiovascular events, ESRD, or mortality with steroidal MRAs plus RASis [14]. As extending their findings, our study, which included patients of all stages of CKD, suggests that RASis+SL may reduce ESRD risk in T2D patients with heart failure.
However, our study suggests caution while prescribing SL to diabetic patients without heart failure. Although the increased risk of ESRD or renal transplantation did not reach statistical significance (HR = 1.32 [0.98–1.78]), the trend was consistent with our primary findings of worsened renal outcomes, including a sustained ≥ 30% decline in eGFR, with SL use. This aligns with our primary analysis, which indicated worsened renal outcomes in diabetic patients, such as a > 30% persistent decline in eGFR, when SL was added. Supporting this, a randomized trial in stage 3 CKD patients (of whom only 2.4% had baseline heart failure) reported no cardiovascular benefit from SL, and over one‐third (35.4%) discontinued therapy due to eGFR decline [31]. Other trials that excluded heart failure patients demonstrated antialbuminuric effects, but no meaningful protection against eGFR decline [12, 23].
Hyperkalemia remains a significant safety concern with SL use, particularly in CKD patients already on RASis. Our findings align with previous meta‐analyses, which reported a 2‐ to 3‐fold increased risk of hyperkalemia with MRAs [10, 32]. Finerenone, with its balanced tissue distribution and lower propensity for potassium accumulation, has been associated with milder hyperkalemia than SL [28, 33]. However, SL's cost‐effectiveness and accessibility make it an important treatment option in resource‐limited settings, warranting careful monitoring of potassium levels during therapy. Although case reports and observational data have linked SL to hyponatremia [34, 35, 36], major clinical evidence (including the RALES trial and Cochrane meta‐analysis) showed no significant sodium changes [6, 10]. The combination with RASis may be beneficial, which can help maintain sodium balance and reduce excessive thirst [37, 38]. SL was used alongside RASis therapy in our study, and no significant hyponatremia differences were observed.
4.3. Potential Limitations
First, despite PS matching, residual confounding from unmeasured factors, such as medication adherence and lifestyle variables, might not fully be eliminated. Second, limitations regarding medication usage include the lack of evaluation on dosage variations and potential selection bias introduced by excluding patients intolerant to RASis. Third, missing data for ACR, electrolytes, and blood pressure limited our ability to fully incorporate these variables; furthermore, detection bias could have influenced safety outcomes, as patients in the RASis+SL group might have been subject to more frequent electrolyte monitoring, potentially leading to a higher identification rate of hyperkalemia. Finally, the single‐center design, focus on an East Asian population, and the study period concluding in 2021 (predating widespread SGLT2 inhibitor reimbursement) might limit the generalizability of the findings to other populations and contemporary practice settings.
5. Conclusions
Our findings align with previous large‐scale investigations, confirming that adding spironolactone to RASis therapy reduces proteinuria but increases the risks of renal function decline and hyperkalemia. Heart failure status significantly modified these effects, suggesting that risk profiles differ based on comorbidities. These findings underscore the importance of patient stratification and careful monitoring of eGFR and potassium levels when considering SL in routine care.
Author Contributions
Wei‐Ren Lin and Tzu‐Shan Huang wrote the manuscript; Wei‐Ren Lin, Tzu‐Shan Huang, Ho‐Hsiang Chang, Jo‐Yen Chao, Huang‐Tz Ou, and Wei‐Hung Lin designed the research; Wei‐Ren Lin, Tzu‐Shan Huang, Yi‐Hsin Chang, and Chen‐Yi Yang performed the research; Yi‐Hsin Chang and Chen‐Yi Yang analyzed the data.
Funding
This study was supported by the Ministry of Science and Technology in Taiwan (grant MOST 112–2628‐B‐006‐008‐MY3, recipient: Dr. Ou) and National Cheng Kung University grants (grant NCKUH‐11503026, recipient: Dr. Huang).
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Data S1: cts70509‐sup‐0001‐Supinfo.docx.
Acknowledgments
During the preparation of this work, the authors used large language models for language editing and proofreading to improve readability. The authors reviewed and edited the content as needed and took full responsibility for the content of the publication.
Contributor Information
Huang‐Tz Ou, Email: huangtz@mail.ncku.edu.tw.
Wei‐Hung Lin, Email: dindonwhlin@hotmail.com.
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