Effects of NSAIDs on Early CKD Development: A 10-Year Population-Based Study Using the Korean Senior Cohort

Abstract

Background

Nonsteroidal anti-inflammatory drugs (NSAIDs) are widely used for pain management but are associated with nephrotoxicity, particularly in senior populations. While the acute nephrotoxicity of NSAIDs is well established, evidence on their long-term effects on renal function—particularly in community-dwelling older adults—has been mixed across studies.

Objectives

This study investigated the association between NSAID use and chronic kidney disease (CKD) risk in the general senior population.

Methods

Data from the National Health Insurance Service-Senior Cohort (NHIS-SC) in South Korea were analyzed, including 1812 participants (604 NSAID users and 1208 controls) matched 1:2 by propensity score. Kidney dysfunction was defined as glomerular filtration rate (eGFR) < 60 mL/min/1.73m² with a ≥ 10% decline from baseline. Hazard ratios (HRs) for CKD were estimated using Cox regression.

Results

NSAID use was associated with an increased CKD risk (HR 1.46; 95% confidence interval (CI) 1.11–1.93) and faster eGFR decline. Subgroup analysis showed elevated risks for Cox-1 (HR 1.53) and Cox-2 inhibitors (HR 1.61). End-stage renal disease (ESRD) incidence was rare and not significant.

Conclusions

NSAIDs increase CKD risk and accelerate kidney function decline in senior individuals. Cautious prescription and regular kidney monitoring are recommended, and further randomized trials are needed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40266-025-01239-9.

Key Points

Regular use of NSAIDs in older adults was associated with a higher risk of chronic kidney disease (CKD), even after adjusting for comorbidities.

Both COX-1 and COX-2 inhibitors were linked to accelerated kidney function decline.

These findings support the need for careful NSAID prescribing and routine kidney function monitoring in the aging population.

Introduction

Nonsteroidal anti-inflammatory drugs (NSAIDs) are a large group of medications commonly indicated for osteoarthritis, rheumatoid arthritis, chronic pain, and postoperative rehabilitation; they also act as effective analgesics and antipyretics [1]. However, these drugs have significant side effects, including gastrointestinal, cardiovascular, and renal toxicities, as well as hepatotoxicity [2].

The renal effects of NSAIDs are particularly concerning owing to their mechanism of action, which involves the inhibition of prostaglandin synthesis. Prostaglandins play a critical role in maintaining renal blood flow, and their inhibition can lead to reduced perfusion, acute renal failure, and other adverse outcomes [3, 4]. These risks are elevated in typical older adult patients and those with comorbid pathologies such as heart failure, liver cirrhosis, or chronic kidney disease (CKD), particularly if NSAIDs are combined with renin–angiotensin blockers or diuretics [5].

Chronic kidney disease (CKD) is among the top five causes of premature human mortality on a global scale, with progression leading to end-stage renal disease (ESRD) and the need for renal replacement therapy [6]. Preventing the progression of CKD is essential, especially in high-risk populations. Although the acute renal side effects of NSAIDs, including sodium retention and edema, have been well recognized, data about the long-term effect of NSAIDs on renal function are limited and conflicting. Initial studies [7–9], indicated an increased risk of CKD associated with long-term use of NSAIDs, but more recent studies have produced conflicting results that require further exploration [10–13].

Previous reports have focused on specific populations, for example, patients with rheumatoid arthritis [14] or military members [15], ultimately restricting generalizing abilities. Many employed designs that have inherent, limiting features, such as nested case–control methods [16] or outcomes associated with ESRD progression or mortality [17].

To fill these gaps, this study used a large, population-based cohort with 10 years of follow-up data to evaluate the association between NSAID use and CKD risk in older adults. By using propensity score matching, this study reduced confounders, thereby offering strong evidence on the nephrotoxic risks of NSAIDs. In addition, by examining both Cox-1 and Cox-2 inhibitors, this study offers novel insights into their differential effects, paving the way for safer prescription practices and improved CKD prevention strategies in high-risk populations.

Methods

Data Source and Study Design

This study utilized data from the National Health Insurance Service–Senior Cohort (NHIS-SC), a population-based cohort established by the National Health Insurance Service (NHIS) in South Korea. The NHIS-SC includes data from 557,195 individuals, representing 10% of the South Korean population aged 60 years or older as of 2002. The cohort was designed to investigate risk factors and prognoses related to geriatric diseases [18]. For this study, we used 2009–2019 data and SCr (serum creatinine) level, which is required to obtain the estimated glomerular filtration rate (eGFR); SCr data became available after 2009. In this study, we calculated eGFR using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, which is a more accurate and validated indicator of kidney function, especially in older adults.

A retrospective cohort design was employed to evaluate the association between NSAID use and the risk of kidney dysfunction in older adults.

Study Population and Eligibility Criteria

We started with a study population of 244,732 subjects who had an estimated GFR at baseline of 60 mL/min/1.73 m² and whose serum creatinine was in the normal range (0.4–1.5 mg/dL) [16, 19]. Eligible individuals were aged 65 years or older, having at least two health check-ups during the study period. The exclusion criteria were: a history of renal disease (n = 5959), diagnosis of cancer within 1 year following the index date (n = 16,903), and NSAID prescriptions within 1 year prior to the index date (n = 203,495). After applying our exclusion criteria, a total of 41,237 participants were included, of which 32,326 were assigned to the NSAIDs user group and 8911 to the group that never used NSAIDs (control group) (Supplementary Fig. S1).

Exposure Definition (NSAID Use)

NSAID users were additionally defined according to a medication possession ratio (MPR) either ≥ 80% or ≥ 1 month for drug exposure. MPR is a widely used measure of medication adherence and is calculated as the proportion of days within a defined period that a patient has access to their prescribed medication [18]. An MPR of 1.0 indicates perfect adherence, while an MPR below 1.0 reflects suboptimal adherence. Participants with MPR < 80% (n = 24,246) or prescription durations of less than 1 month (n = 9728) were excluded, resulting in a refined NSAID user group of 604 individuals. The control group consisted of 8911 individuals with no record of any NSAID prescriptions during the study period.

Socioeconomic and Diagnostic Classification

Income levels were used as a measure of socioeconomic status and were grouped into four separate groups on the basis of decile category as defined by the National Health Interview Survey (NHIS). Very low income defined the 1st and 2nd deciles, low income the 3rd–5th deciles, high income the 6th–8th deciles, and very high income the 9th and 10th deciles.

For disease registration, the NHIS-SC uses the sixth edition of Korean Classification of Diseases, which is a modification of the tenth revision of the International Classification of Diseases (ICD-10) for the NHIS and medical-care institutions in South Korea.

Ethical Approval

The analysis used data from the NHIS-SC (NHIS-2024-2-060) and was approved by the Seoul National University Institutional Review Board (no. 07-2023-43).

Propensity Score Matching

To limit the potential confounding effects, we conducted propensity score matching at a 1:2 ratio on the basis of baseline covariates, including age, sex, eGFR, income level, chronic comorbidities, and the year of examination. After matching, 7703 records for control participants were excluded, leaving a final cohort of 1812 participants—604 in the NSAID user group and 1208 in the control group.

Outcome Measures

The primary outcome was kidney dysfunction, defined as a follow-up eGFR below 60 mL/min/1.73 m² with a 10% or greater decline from baseline. This definition excluded minor variations in kidney function between check-ups. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was employed to estimate eGFR owing to its higher accuracy for adults [20, 21].

Statistical Analyses

Cox proportional hazards regression models were used to calculate hazard ratios (HRs) for kidney dysfunction. Subgroup analyses assessed the effects of NSAID types, specifically Cox-1 and Cox-2 inhibitors, on kidney function. All statistical analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC, USA), with α < 0.05 considered significant.

Results

Of 244,732 individuals screened, 41,237 met inclusion criteria: 32,326 NSAID users and 8911 controls. After propensity score matching (1:2), 1812 cohorts (604 NSAID users and 1208 controls) were obtained with balanced baseline characteristics. It should also be noted that the proportions of subjects with Charlson Comorbidity Index (CCI) score ≥ 2 in matched cohorts were similar between groups (31.46% versus 32.70%). Hypertension (55.63% in both groups) and diabetes mellitus (24.92% in NSAID users versus 24.67% in controls) were comorbidities with little difference as well (Table 1.)

Table 1.

Demographic characteristics

	Unmatched (N = 9515)					Propensity matched (N = 1812)
	NSAID group (n = 604)		Control group (n = 8911)		Standardized difference	NSAID group (n = 604)		Control group (n = 1208)		Standardized difference
	N	(%)	N	(%)		N	(%)	N	(%)
Age, mean (SD)
Age, years	72.0	5.41	71.2	5.05	− 0.15	72.0	5.41	71.9	5.38	− 0.01
Sex, n (%)
Men	303	50.17	5167	57.98	0.16	303	50.17	583	48.26	− 0.04
Women	301	49.83	3744	42.02	− 0.16	301	49.83	625	51.74	0.04
Income, n (%)
Very low (0–4)	91	15.07	1416	15.89	0.02	91	15.07	143	11.84	− 0.09
Low (5–9)	143	23.68	2092	23.48	0.00	143	23.68	286	23.68	0.00
High (10–14)	182	30.13	2682	30.10	0.00	182	30.13	389	32.20	0.04
Very high (15–20)	188	31.13	2721	30.54	− 0.01	188	31.13	390	32.28	0.02
CCI, n (%)
0	219	36.26	4716	52.92	0.34	219	36.26	450	37.25	0.02
1	195	32.28	2359	26.47	− 0.13	195	32.28	363	30.05	− 0.05
≥ 2	190	31.46	1836	20.60	− 0.25	190	31.46	395	32.70	0.03
CVD history, n (%)
Myocardial infarction	6	0.99	77	0.86	− 0.01	6	0.99	13	1.08	0.01
PCI	1	0.17	22	0.25	0.02	1	0.17	1	0.08	− 0.02
Heart failure	24	3.97	189	2.12	− 0.11	24	3.97	42	3.48	− 0.03
Stroke	64	10.60	631	7.08	− 0.12	64	10.60	129	10.68	0.00
Hemorrhagic	7	1.16	68	0.76	− 0.04	7	1.16	18	1.49	0.03
Ischemic	50	8.28	506	5.68	− 0.10	50	8.28	99	8.20	0.00
Comorbidities, n (%)
Diabetes	156	25.83	1801	20.21	− 0.13	156	25.83	301	24.92	− 0.02
Hypertension	336	55.63	4121	46.25	− 0.19	336	55.63	672	55.63	0.00
Gout	17	2.81	121	1.36	− 0.10	17	2.81	37	3.06	0.01
Obesity	184	30.46	2592	29.09	− 0.03	184	30.46	348	28.81	− 0.04
Hyperlipidemia	116	19.21	1930	21.66	0.06	116	19.21	215	17.80	− 0.04
Medication, n (%)
ACE inhibitor	14	2.32	201	2.26	0.00	14	2.32	29	2.40	0.01
ARB	167	27.65	2051	23.02	− 0.11	167	27.65	321	26.57	− 0.02
Metformin	75	12.42	935	10.49	− 0.06	75	12.42	145	12.00	− 0.01
Statin	153	25.33	1541	17.29	− 0.20	153	25.33	311	25.75	0.01
PPI	39	6.46	204	2.29	− 0.20	39	6.46	69	5.71	− 0.03
Allopurinol	4	0.66	34	0.38	− 0.04	4	0.66	6	0.50	− 0.02
Lifestyle-related, n (%)
Smoking	83	13.74	1341	15.05	0.04	83	13.74	173	14.32	0.02
Drinking	514	85.10	7469	83.82	− 0.04	514	85.10	1059	87.67	0.07
Physical activity	509	84.27	7719	86.62	0.07	509	84.27	1028	85.10	0.02

Values are presented as number (%)

ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; BMI, body mass index; CCI, Charlson Comorbidity Index; NSAID, nonsteroidal anti-inflammatory drug; PCI, percutaneous coronary intervention; PPI, proton pump inhibitor; SD, standard deviation

In univariate and multivariate Cox regression analysis, the use of NSAIDs was statistically significantly associated with an increased risk of developing CKD in matched cohort (hazard ratio (HR) 1.46; 95% confidence interval (CI) 1.11–1.93), but no statistically significant association was found in unmatched cohort (HR 1.15; 95% CI 0.91–1.46) (Table 2.) Users of the NSAIDs demonstrated a more rapid loss of eGFR, especially during the first year, which was also confirmed by Kaplan–Meier survival curve analysis, demonstrating a highly significant higher incidence of CKD (Fig. 1)

Table 2.

Multivariate Cox regression analysis for predicting the risk of chronic kidney disease development after adjusting all accessible variables

Outcome	Unmatched		Propensity matched
	NSAID group	Control group	NSAID group	Control group
eGFR < 60 mL/min/1.73 m2
Patients, n	604	8911	604	1208
PY, total	3765.45	56,027.89	3765.45	7630.46
PY, mean	6.23	6.29	6.23	6.32
Events, n	76	935	76	124
Rate per 1000 PY	20.18	16.69	20.18	16.25
Rate difference per 1000 PY (95% CI)	3.50 (− 1.17 to 8.16)		3.93 (− 1.43 to 9.30)
HR (95% CI)/model 1a	1.21 (0.96–1.53)	Reference	1.35 (1.06–1.72)	Reference
HR (95% CI)/model 2b	1.15 (0.91–1.46)	Reference	1.46 (1.11–1.93)	Reference
ESRD
Patients, n	604	8911	604	1208
PY, total	4047.09	59,579.01	4047.09	8082.11
PY, mean	6.70	6.69	6.70	6.69
Events, n	4	1	4	1
Rate per 1000 PY	0.99	0.18	0.99	0.12
Rate difference per 1000 PY (95% CI)	0.80 (− 0.17 to 1.78)		0.87 (− 0.13 to 1.86)

PY, patient-years

^aAdjusted for age, sex, and income

^bAdjusted for age, sex, income, Charlson Comorbidity Index (CCI) scores, cardiovascular disease history (including myocardial infarction, percutaneous coronary intervention, heart failure, and stroke), comorbidities (including diabetes mellitus, hypertension, gout, obesity, and hyperlipidemia), medication use (including angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, metformin, statins, and proton pump inhibitors), and lifestyle-related factors (including smoking, alcohol consumption, and physical activity)

Fig. 1.

Kaplan–Meier survival curves; Kaplan–Meier survival curves for time to occurrence of chronic kidney disease among senior people

The subgroup analysis indicated that both Cox-1 and Cox-2 inhibitors raised the risk of CKD with hazard ratios of 1.53 (95% CI 1.16–2.01) and 1.61 (95% CI 1.16–2.23), respectively (Supplementary Tables S2 and S3). End-stage renal disease (ESRD) was uncommon, with four cases in NSAID users and one in controls, leading to a difference in rates that was not statistically significant (0.87 per 1000 person-years; 95% CI − 0.13 to 1.86) (Supplementary Table S1).

This difference was most evident during the first year of follow-up and remained persistent thereafter, indicating a sustained decline in kidney function among NSAID users compared with controls. In the matched cohort, both groups showed a slight increase in eGFR during the first year. From the second year onward, the NSAID user group exhibited a more pronounced decline in eGFR compared with the control group. This divergence in renal function persisted over the follow-up period (Fig. 2B).

Fig. 2.

Observed change from baseline in estimated glomerular filtration rate at each visit

Discussion

The current study showed that NSAIDs increase the risk of chronic kidney disease (CKD) and the rate of eGFR decline in the population aged ≥ 67 years (Fig. 2). Both Cox-1 and Cox-2 inhibitors were associated with increased risk of CKD, with hazard ratios of 1.53 and 1.61, respectively (Supplementary Table S3). However, the incidence of end-stage renal disease (ESRD) was rare and not statistically significant.

Our results are consistent with those of Nelson et al. [15], which showed an increased risk of CKD progression among NSAID users (especially those with higher cumulative exposure) by 20%. However, their study population of young, healthy military personnel limits the generalizability of their results to older, more comorbid populations such as ours. Similarly, Kuo et al. [22] provided evidence for a significant association with ESRD and rofecoxib, a selective COX-2 inhibitor, complementing our observations of a more rapid decline in eGFR among COX-2 inhibitor users. Mitsuboshi et al. [23] showed increased CKD risk when acetaminophen was followed by low-dose aspirin, consistent with cumulative drug effects that enhance nephrotoxicity. Although our study did not include combination therapies, their results highlight the necessity to take into account drug interactions.

In contrast, several studies have reported no association between NSAIDs and CKD. For example, the Nurses’ Health Study [10], a large prospective cohort study, found no association between lifetime NSAID use and decline in renal function, although acetaminophen use was associated with CKD. This difference may relate to differences in population characteristics; their cohort of younger, healthier women contrasts with our cohort of aged, higher-risk individuals. Nissen et al. [12], in a 3-year arthritis trial, also found no increased CKD risk with NSAID use, though the high discontinuation rate (68.8%) and short follow-up period may have influenced their findings. Möller et al. [13] observed no significant renal effects in CKD stages 1–3 but reported accelerated eGFR decline in advanced CKD (stages 4–5), aligning with our findings that baseline kidney function influences NSAID-related risks.

Possible Explanations

The trajectory of renal function decline revealed that the adverse effects of NSAIDs on eGFR became more evident over time. Although both groups exhibited a slight improvement in eGFR during the first year, likely due to regression to the mean or physiological variability, NSAID users experienced a more rapid and sustained decline thereafter (Fig. 2). This pattern suggests a possible cumulative nephrotoxic effect of long-term NSAID exposure. NSAIDs inhibit the COX enzymes, thereby reducing the synthesis of prostaglandins. Prostaglandins play a critical role in maintaining renal blood flow, particularly under conditions of hypovolemia or decreased renal perfusion, where they are essential for preserving adequate glomerular filtration. Inhibition of prostaglandin production by NSAIDs leads to renal vasoconstriction, resulting in reduced renal perfusion and a subsequent decline in GFR. This mechanism is a major contributor to NSAID-induced acute kidney injury (AKI) [24].

AKI causes damage to renal tissue, and if this injury is not fully reversed, it can progress to chronic impairment of renal function. Recurrent episodes of AKI promote renal fibrosis, thereby increasing the risk of developing CKD. Studies have demonstrated that patients with a history of AKI have a significantly higher likelihood of progressing to CKD. Even when renal function appears to recover after an AKI episode, residual kidney injury and alterations in the renal microenvironment—such as persistent inflammation and oxidative stress—can lay the groundwork for subsequent CKD progression [25, 26].

Long-term NSAID use may induce repeated episodes of renal hypoperfusion and subclinical injury, thereby accelerating the transition from AKI to CKD. This interpretation is supported by our observation that both groups initially showed stable or slightly improved eGFR values during the first year, likely due to physiological variability or regression to the mean. However, from the second year onward, the NSAID group experienced a more rapid and sustained decline in eGFR (Fig. 2B), suggesting a possible cumulative nephrotoxic effect over time, especially in older adults with limited renal reserve. This risk is particularly pronounced in individuals with pre-existing risk factors for kidney disease, such as advanced age, diabetes, hypertension, or heart failure. In these populations, NSAID use further elevates the risk of CKD development and progression [11].

Clinical Implications

The findings of this study underscore the critical importance of individualized risk assessment when prescribing NSAIDs, particularly in older patients and those with established risk factors for kidney disease such as diabetes, hypertension, or heart failure. NSAIDs, by inhibiting prostaglandin synthesis, can compromise renal perfusion, especially under conditions of reduced effective circulating volume or pre-existing renal impairment. This can precipitate episodes of AKI, which, as accumulating evidence suggests, are not merely transient events but can serve as a pivotal step in the trajectory toward CKD.

Repeated or subclinical AKI episodes may induce irreversible nephron loss and promote renal fibrosis, thereby accelerating CKD onset and progression. Importantly, even when renal function appears to recover following AKI, persistent subclinical damage and maladaptive repair processes, including ongoing inflammation and oxidative stress—may contribute to a progressive decline in kidney function over time. Therefore, NSAID use should be approached with heightened caution in individuals at increased risk for renal complications.

Routine monitoring of renal function during NSAID therapy is essential to facilitate early detection of nephrotoxicity and to enable timely intervention, such as dose adjustment or discontinuation of the offending agent. This is particularly pertinent for populations with higher baseline susceptibility to kidney injury, such as older adults and those with multiple comorbidities. Implementation of regular kidney function assessment—through measurement of serum creatinine and eGFR—can aid in the identification of early, asymptomatic declines in renal function, thus providing an opportunity for preventive measures before irreversible CKD develops.

Our results highlight the necessity for judicious NSAID prescribing practices, comprehensive patient education regarding potential renal risks, and the establishment of systematic monitoring protocols. Such strategies are likely to mitigate the burden of NSAID-associated kidney injury and contribute to improved long-term renal outcomes, particularly in high-risk patient populations.

Strengths and Limitations

The major strength of this study is the use of a large population-based cohort with longitudinal designs to address the long-term effects of NSAIDs on kidney function in a large population. These matched cases are now free of any confounding, and this enhances the evidence with respect to the findings. Moreover, considering the overall senior population increases the clinical applicability of our findings, bridging the void in studies that have chiefly focused on particular subpopulations such as individuals with rheumatoid arthritis or military persons.

Despite these contributions, our study is not without its limitations. First, its observational design prevents establishment of definitive conclusions about causation, and despite the application of propensity score matching, residual confounding due to unmeasured variables—such as frailty, functional status, or over-the-counter drug use—may remain. Second, while propensity score matching allowed us to control for a wide range of observed baseline characteristics, unmeasured confounding may still exist. As the propensity score (PS) model does not incorporate outcome variables and is limited to recorded covariates, residual bias from unmeasured factors cannot be fully excluded. Third, the inherent heterogeneity of the older population presents challenges in fully capturing variability in susceptibility to NSAID-induced kidney dysfunction. Fourth, using prescription data as a substitute for actual use of medication may not translate to treatment adherence either. Fifth, the low number of observed ESRD cases limited our ability to fully assess long-term risks. Sixth, while baseline comorbidity burden was controlled through propensity score matching using the Charlson Comorbidity Index (CCI), we acknowledge that comorbid conditions may have changed over time during follow-up. For example, severe illnesses such as cancer, chemotherapy, or heart failure could have developed after cohort entry and may have influenced renal outcomes. These dynamic changes were not tracked and represent an inherent limitation of our study. Future studies incorporating time-varying covariates and clinical events would be better suited to address this issue. Furthermore, we were unable to assess the concurrent use of other nephrotoxic agents such as loop diuretics, low-dose aspirin, and certain antibiotics. These medications may influence renal outcomes and are important contributors to cumulative nephrotoxicity. The so-called triple whammy combination (NSAIDs, diuretics, and angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs)) is particularly relevant but could not be fully evaluated owing to data limitations. This remains a limitation of our study. Lastly, over-the-counter (OTC) NSAID use was not captured in our dataset. While this may lead to some underestimation of NSAID exposure, most long-term NSAID use among older adults in Korea occurs via physician prescriptions, thereby limiting the impact of this potential bias.

Future Directions

However, this study does lend some insights into potential nephrotoxicity of NSAIDs in the senior population. The nephrotoxic potential of these agents in at-risk groups is a reminder that judicious use of NSAIDs must include careful consideration of risk and benefit as well as regular renal function monitoring, particularly in this population in whom NSAID use is commonplace.

Future research should prioritize randomized controlled trials to establish causality and investigate the long-term effects of different NSAID types, dosages, and combinations on renal outcomes. In addition, exploring individual susceptibility factors, such as genetic predispositions or baseline kidney function, would enhance our understanding of NSAID-related risks.

Supplementary Information

Below is the link to the electronic supplementary material.

Declarations

Ethics approval

This study was approved by the Institutional Review Board of Seoul National University (IRB no. 07-2023-43). Data were provided by the National Health Insurance Service (NHIS-2024-2-060). All procedures were conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Consent for publication

Not applicable. This study used de-identified, publicly available data from the NHIS-Senior Cohort.

Authors’ contributions

Jung-sun Lim designed the statistical analysis and drafted the manuscript. Bumjo Oh conceptualized the study, supervised the research process, and provided critical revision and oversight. Sunyoung Kim contributed significantly to manuscript revision, interpretation of results, and reviewer responses. Sujeong Han and Jong Seung Kim reviewed interim drafts and provided clinical feedback throughout the study. All authors read and approved the final version of the manuscript.

Conflicts of interest

All authors (Jung-sun Lim, Sujeong Han, Jong Seung Kim, Sunyoung Kim, and Bumjo Oh) declare that they have no competing interests.

Funding

Open Access funding enabled and organized by Seoul National University. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The data that support the findings of this study are available from the National Health Insurance Service (NHIS) of Korea. These data can be accessed by researchers upon request and approval from the NHIS. Access requires submission of a research proposal and payment of associated data usage fees.

Code availability

Not applicable.