Hospitalization among adults with chronic kidney disease: results from the KoreaN cohort study for Outcomes in patients With Chronic Kidney Disease (KNOW-CKD) study

Article information

Korean J Nephrol. 2024;.j.krcp.23.263
Publication date (electronic) : 2024 July 25
doi : https://doi.org/10.23876/j.krcp.23.263
1Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
2Seoul National University College of Medicine, Seoul, Republic of Korea
3Department of Biostatistics, Korea University College of Medicine, Seoul, Republic of Korea
4Department of Transplantation Center, Seoul National University Hospital, Seoul, Republic of Korea
5Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
6Department of Internal Medicine, Seoul St Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
7Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
8Department of Internal Medicine and Institute of Kidney Disease, Yonsei University College of Medicine, Seoul, Republic of Korea
9Kidney Research Institute, Seoul National University Medical Research Center, Seoul, Republic of Korea
Correspondence: Kook-Hwan Oh Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea. E-mail: khoh@snu.ac.kr
*Yeong-Won Park and Jaeseung Hwang contributed equally to this study as co-first authors.
Received 2023 October 20; Revised 2024 January 18; Accepted 2024 February 6.

Abstract

Background

Chronic kidney disease (CKD) patients are hospitalized for various conditions. Hospitalization increases the readmission rate and mortality rate, seriously deteriorating patients’ quality of life. Consequently, it is crucial to analyze the reasons for hospitalization in CKD patients from a broader perspective according to CKD grade.

Methods

This is a prospective cohort study of CKD patients entitled the KoreaN cohort study for Outcomes in patients With Chronic Kidney Disease (KNOW-CKD). A total of 2,238 patients were examined, and the reasons for hospitalization were classified into 16 disease categories. The incidence rate ratio (IRR) according to CKD stage was compared using negative bimodal regression analysis.

Results

The all-cause hospitalization incidence was 184.96 per 1,000 person-years. The most common reason for hospitalization was circulatory system disease, followed by infection and digestive system disease. Among hospitalizations for acute kidney injury, endocrine-nutrition-metabolic–related illness, blood-related disease, and diseases of the nervous system and sensory organs, IRR increased as CKD grade advanced. The incidence of ophthalmologic surgery during hospitalization increased according to the CKD stage. The IRR of KNOW-CKD patients was 6.19 (95% confidence interval, 5.92–6.48; p < 0.001) compared with the general population.

Conclusion

This in-depth analysis of hospitalizations among CKD patients confirmed that CKD patients were hospitalized for various reasons, such as metabolic, ophthalmic, and hematologic diseases. Early detection and intervention regarding causative diseases of CKD are important to reduce the hospitalization burden and improve patients’ quality of life.

Introduction

Chronic kidney disease (CKD) is highly prevalent worldwide and is drawing considerable attention from clinical and public health perspectives [1]. Numerous studies have provided evidence that declining kidney function is associated with increased hospitalization, and that CKD is an essential predictor of hospitalization, causing a tremendous health burden to patients [14]. Hospitalizations that occur in CKD patients are also more likely to lead to further complications, including greater re-hospitalization rates [5], higher mortality [3,6], worsening kidney function [3], and severely diminishing quality of life [7,8] compared with patients without CKD.

Many of the hospitalizations experienced by CKD patients are due to cardiovascular disease [3,9] or renal-related events [10]. However, little is known about the other reasons for hospitalization or why people with kidney disease have a higher risk of hospitalization. Therefore, it is important to understand cause-specific hospitalizations in CKD patients, not only for significant causes like cardiovascular disease and renal events but also to gain a broader perspective of risks associated with CKD. Analysis of the incidence of cause-specific surgeries according to CKD stage is also crucial because hospitalization due to surgery type is not systematically known, even though many hospitalization events are for planned surgical treatments.

The purpose of this study is to characterize the hospitalization burden in CKD patients with a multicenter observational study: KoreaN cohort study for Outcomes in patients With Chronic Kidney Disease (KNOW-CKD). We examined the incidence rate of cause-specific hospitalization in CKD patients, along with the incidence rate of cause-specific surgeries practiced in CKD patients. We also explored the association between CKD stage and hospitalization risk. This study is expected to clarify and improve treatment for CKD disease by ascertaining various hospitalization-related events that may occur in CKD patients.

Methods

Study design

This is a longitudinal study from a prospective cohort of nondialyzed CKD patients in South Korea, entitled KNOW-CKD, which enrolled adult (20–75 years old) patients with CKD stages G1 to G5 from nine centers between 2011 and 2016 [11]. Exclusion criteria included history of chronic dialysis, severe heart failure, liver cirrhosis, history of malignancy, current pregnancy, organ transplantation, or single kidney due to trauma or nephrectomy. Enrolled patients were prospectively followed up for hospitalization events until March 31, 2020. Of the 2,238 subjects enrolled, subjects during the follow-up period were censored on the date of their death, dialysis, or at the end of follow-up, whichever came first (Fig. 1). Informed consent was obtained from all patients voluntarily at the time of enrollment. The study was approved by the Institutional Review Board of each participating hospital: Seoul National University Hospital (No. H-1704-025-842), Seoul National University Bundang Hospital (No. B-1106/129-008), Severance Hospital (No. 4-2011-0163), Kangbuk Samsung Medical Center (No. 2011-01-076), The Catholic University of Korea, Seoul St. Mary’s Hospital (No. KC11OIMI0441), Gachon University Gil Medical Center (No. GIRBA2553), Eulji Medical Center (No. 201105-01), Chonnam National University Hospital (No. CNUH-2011-092), and Pusan Paik Hospital (No. 11-091). This study follows the guidelines of the Declaration of Helsinki.

Figure 1.

Flow chart of participant recruitment and follow-up.

KNOW-CKD, KoreaN cohort study for Outcomes in patients With Chronic Kidney Disease.

Data collection and measurements

Demographic and laboratory data were collected, including CKD and comorbidities. Among demographic data, the Charlson comorbidity index (CCI) was used to quantify different patients’ severity and health status in clinical studies. CCI is calculated by assigning a constant weight of 1 to 6 points to 17 diseases defined through medical record surveys, and then adjusting the sum of those weights [12]. The following laboratory variables were measured using a blood sample with at least 8 hours of fasting at each participating center’s laboratory: estimated glomerular filtration rate (eGFR), hemoglobin, albumin, and high-sensitivity C-reactive protein. The CKD epidemiology collaboration equation based on serum creatinine was used to calculate eGFR [13]. For urine biochemistry, urine protein and creatinine were measured using immunoturbidimetry.

Event adjudication

Hospitalization in the KNOW-CKD patients was defined as admission to the hospital through any route. The date, main reason for hospitalization, surgery history, and department of surgery during the hospitalization were collected. The main reason for hospitalization was determined based on diagnosis and treatment performed, categorized by primary reason for admission first confirmed by investigators in each center, and then cross-adjudicated by two different nephrologists at a central adjudication committee afterward. Surgical treatment related to dialysis access (such as arteriovenous fistula and peritoneal dialysis catheter insertion) was excluded.

Reasons for hospitalization were categorized into 16 groups, as previously described elsewhere [14]: 1) acute kidney injury (AKI), 2) all-cause infectious disease, 3) neoplasm (including chemotherapy), 4) endocrine-nutrition-metabolic–related causes, 5) diseases of the blood and blood-forming organs, 6) mental illness, 7) diseases of the nervous system and sensory organs, 8) circulatory system diseases, 9) respiratory tract diseases, 10) digestive system diseases, 11) diseases of the genitourinary system, 12) pregnancy complications, 13) diseases of the musculoskeletal system and connective tissue, 14) injuries and poisonings, 15) diseases of the skin and subcutaneous tissues, 16) other symptoms, signs, and ill-defined conditions and factors influencing health status. Detailed information on the above classifications is attached as Supplementary Table 1 (available online).

Control population

All-cause hospitalization in the KNOW-CKD patients was compared with hospitalization data from the general population. Control population data were procured from the National Sample Cohort Database of the National Health Insurance Service, which is generally considered the most nationally representative data for Korea because, as the single Korean insurer, it includes nearly the entire Korean population [15,16]. Major exclusion criteria were: 1) subjects who had been previously admitted with a disease code for pregnancy, cancer, liver cirrhosis, or organ transplantation; or 2) subjects who had already experienced dialysis. The control group did not exclude the nondialysis CKD population. Therefore, it is estimated that about 5% of our control population has CKD [17]. Eventually, 224,756 subjects were sorted from a one million cohort sample from 2002 to 2013 whose hospitalization data were compared with our study patients.

Statistical methods

Baseline characteristics were compared with outcomes using the chi-square test and the analysis of variance test. For non-normally distributed continuous variables, the Kruskal-Wallis test was used. Hospitalization incidence by each category with respect to the CKD stage was compared with the Jonckheere-Terpstra test. Incidence rates are represented as per 1,000 person-years. All-cause hospitalization rates for each stage were then compared in a negative binomial regression model to account for overdispersion. Using variables that showed significant differences between CKD stages and after removing potential mediator variables, models were adjusted for age, sex, diabetes mellitus (DM), and body mass index (BMI). Length of follow-up was also included to account for varying durations of follow-up periods between stages. The incidence rate ratio (IRR) was calculated with a 95% confidence interval. All statistical analyses were performed using IBM SPSS version 26.0 (IBM Corp.) and R version 4.1.1 (R Foundation for Statistical Computing). The p-value significance limit was set at 0.05.

Results

Basic characteristics

Baseline characteristics are reported elsewhere and summarized in Table 1. The median age was 55 years, and 61.1% were male. Among 2,238 study subjects, 360 (16.1%) were in CKD G1, 425 (19.0%) in G2, 835 (37.3%) in G3a–3b, and 618 (27.6%) in G4–5. The most common CKD etiology in the KNOW-CKD population was glomerular disease followed by DM and hypertension.

Comparison of baseline clinical characteristics according to CKD stage

When subjects were stratified into four groups according to CKD stage, we found differences between groups in mean age, sex proportion, BMI, blood pressure, CKD etiology, comorbidities, and laboratory findings. Higher stages were associated with a higher prevalence of comorbid diseases such as congestive heart failure, peripheral vascular disease, cerebrovascular disease, connective tissue disease, and DM. CCI scores were also higher in the advanced CKD stage.

Hospitalization incidence rate according to chronic kidney disease stage

The incidence rate of all-cause hospitalization and cause-specific hospitalization is shown in Table 2. A total of 184.96 hospitalizations per 1,000 person-years were observed in the cohort, and the hospitalizations were categorized into 16 groups. The most common cause of hospitalization was circulatory system disease, followed by infection, and neoplasm, indicating incidence rates of 29.23, 23.46, and 21.57 per 1,000 person-years, respectively. AKI occurred at an incidence of 10.88 per 1,000 person-years.

Incidence rate of hospitalization categorized by etiology

All-cause hospitalization incidences increased significantly as the CKD stage increased. As the stage increased, incidence rates of AKI, endocrine-nutrition-metabolic–related disease, blood- or blood-forming organ-related disease, and diseases of the nervous system and sensory organs significantly increased. In contrast, no significant difference was found in hospitalization rates related to infection, neoplasm, digestive system disease, diseases of the musculoskeletal system or connective tissue, injury or poisonings, respiratory tract diseases, and mental illness. Hospitalization incidence rate due to genitourinary system diseases and pregnancy-related complications showed a decreasing pattern.

Note that the main cause of hospitalization varies depending on the cause of CKD (Supplementary Table 2, available online). The most common cause of hospitalization in diabetic kidney disease and hypertensive nephropathy was circulatory system disease, whereas infection was the most common cause of hospitalization in patients with polycystic kidney disease.

Surgical incidence rate according to chronic kidney disease stage

This study also analyzed surgery during admission (Table 3). Among surgical departments, the highest incidence was found among ophthalmologic surgery followed by musculoskeletal surgery, and intraabdominal surgery. The ophthalmologic surgery incidence rate increased while intraabdominal surgery was associated with a decreasing trend with increasing the CKD stage. Operation incidence based on the etiology of CKD is presented as Supplementary Table 3 (available online).

Incidence rate of operation during hospitalization categorized by department

Hospitalization incidence rate ratio according to chronic kidney disease stage

The IRR for all-cause hospitalization is shown in Table 4, with G1 as the reference. The IRR of G3 and G4–5 was statistically higher than G1 in a crude model. The increasing trend of all-cause hospitalization was also statistically significant after adjustments for age, sex, and follow-up duration. We further analyzed IRR based on age and presence of DM (Table 5). The hospitalization rate was significantly elevated at advanced CKD stages regardless of age and DM. The elderly subgroup (aged >65 years, n = 418, 18.7% of the total cohort population) showed a marginally significant increase of IRR for advanced CKD stages (IRR of 1.85, 2.21, and 3.38 for G2, G3a–3b and G4, respectively) possibly due to insufficient statistical power.

IRRs of all-cause hospitalization in a negative binomial regression model

Adjusted IRRs of all-cause hospitalization in patients depends on age and presence of DM

Hospitalization incidence rate ratio compared with the general population

Table 6 shows the IRR for all-cause hospitalization between the control group and the study population. A total of 11,780,421 person-years were observed, and there were 38.95 hospitalization events/1,000 person-years. The KNOW-CKD subjects had a 6.19-fold higher all-cause hospitalization event rate after adjusting for multiple variables. Hospitalization rates were also consistently elevated with higher CKD stages after adjusting for covariates, except between G3 and G4–5.

IRRs of all-cause hospitalizations compared with the control population

Discussion

Hospitalization is a major health burden for patients with CKD. Previous studies observing hospitalization in CKD patients confirmed that the hospitalization rate in CKD patients was higher than among the general population, but few studies have evaluated the causative diseases that lead to hospitalization [3,4,18]. We analyzed the medical and surgical reasons for hospitalization in the KNOW-CKD patient cohort. According to this study, circulatory system disease, infection, and neoplastic disease were the three most common reasons for hospitalization in CKD patients. As the CKD stage increased, patients became more vulnerable to comorbid diseases such as AKI, endocrine-nutrition-metabolic–related disease, blood and blood-forming organ-related disease, and diseases of the nervous system and sensory organs. The most common reason for surgery among CKD patients was ophthalmologic treatment, followed by musculoskeletal and intraabdominal surgery.

Disease categories with high incidence rates in this study were observed consistently with previous studies [4,18], but unlike previous reports, admission for AKI was lower in this study. This difference might be due to different classification categories and methods between the previous studies and ours. We analyzed only the primary and main causes of hospitalization. For instance, heart failure with cardiorenal syndrome may be classified as circulatory system disease. Therefore, it is likely that AKI episodes, which are concomitant to, but not the main cause of, hospitalization might be omitted in our analysis. This might underestimate the total AKI episodes in CKD subjects. Nevertheless, our findings are in line with other hospitalization studies, which all found that hospitalizations due to AKI as the primary cause were not uncommon and AKI incidence increased with higher CKD stages.

The hospitalization incidence for endocrine disease, nervous system and sensory organ diseases, and blood-related diseases increased with higher CKD stage. Considering that complications such as anemia and electrolyte imbalance occur as the CKD stage increases, this observation is reasonable. Also, the increasing hospitalization trend for endocrine-nutrition-metabolic–related causes may underscore the importance of nutritional assessment and medical nutrition therapy (MNT), which all seem beneficial but have uncertain effects on mortality reduction among kidney disease patients [19,20]. The effect of MNT on the reduction of hospitalization rates requires further study. Hospitalizations for nervous system and sensory organ diseases might be related to ophthalmic diseases, which will be discussed in future work. The hospitalization rate for genitourinary system diseases seems high at early CKD stages. It is well known that polycystic kidney disease carries multiple renal manifestations such as flank pain, rupture, and stone formation [21]. Early stage of CKD excessively included patients with polycystic kidney disease, which might have contributed to a substantially high incidence rate of hospitalization related to the genitourinary system.

The CRIC (Chronic Renal Insufficiency Cohort) study confirmed a distinct and continuous increase in cardiovascular disease incidence along with the eGFR decrease, as well as an association between low eGFR and risk of all-cause death and hospitalization [3]. Additionally, a study from Japan revealed a high incidence of hospitalizations in CKD patients for the following conditions, in the following order: eye and adnexa, heart disease, and heart failure [4]. Although hospitalization in this CKD cohort tended to increase at advanced CKD stages, the overall hospitalization rates were lower than in other cohort studies [3,4]. As previously described [11], the KNOW-CKD subjects are relatively younger which included only 18.7% of patients with age over 65 years. This might explain the difference from other studies due to insufficient statistical power for the elderly subgroup.

The finding that CKD patients underwent higher rates of orthopedic, general, and ophthalmic surgery is consistent with the fact that CKD patients have a high risk of osteoporosis and eye problems [22,23]. Unlike a previous study in which surgical incidence increased rapidly according to the stage [24], the incidence of overall surgical practice did not increase significantly according to the CKD stage in this study.

Similar to other findings, eye surgery was more common in patients with CKD, especially in diabetic kidney disease patients. The incidence of ophthalmic surgery should be carefully interpreted since the incidence of cataract surgery is unusually high in Korea [25]. Apart from cataracts, CKD patients, especially those with diabetic kidney disease share common risk factors as well as pathophysiology with several ophthalmic diseases such as retinopathy [23,2628]. Early identification and intervention for ophthalmic problems in CKD patients especially with DM may be important for reducing hospitalization. The incidence of general surgery seems to have decreased as the CKD stage increased, but this phenomenon was not seen in the subgroup; rather incidence of intraabdominal surgery increased in polycystic kidney disease. Intraabdominal surgery is commonly known to be increased based on previous studies, and follow-up studies with a population more reflecting real-world might be needed [23,29,30].

The KNOW-CKD population had a 6.19-fold higher hospitalization rate compared with the general population, which is consistent with other studies although the rate ratio of each study was different [4,14]. Simple comparison between countries for hospitalization rates might be impractical because healthcare systems vary between countries. A key finding from our study is that hospitalization rates were higher even at low CKD stages, 3.84- to 5.92-fold more common in G1/G2 stages, compared with the general population after adjustment. It warrants careful interpretation because glomerular disease and polycystic kidney disease are overrepresented in our cohort. These patients were more vulnerable to infection and genitourinary system disease, which were the major causes of hospitalization in G1 CKD patients. This may indicate the importance of individualized monitoring and intervention based on the etiology of CKD, apart from stages.

Our study had several limitations. First, subjects were followed up for hospitalization events until the development of end-stage renal disease. Therefore, the follow-up duration was shorter for subjects at higher CKD stages median of 2.52 years in G4–5 compared with 4.97 years overall. This might partly explain the decreasing rate ratio for G3 and G4–5 in comparison with the general population. Second, this study had limitations in considering every confounder that may affect the prognosis for CKD patients. Third, admission rates for specific diseases cannot be assessed, and we just estimated etiology based on disease category. Since the study purpose of KNOW-CKD Phase I included the comparison of CKD outcomes among the four main causes of CKD, the study oversampled glomerular disease and polycystic kidney disease patients. Therefore, the cohort population might not exactly mirror the actual Korean CKD patients in the real world. Nevertheless, we had robust findings that highlighted the outcomes of hospitalization for various causes, including differences between causes of CKD. Phase II KNOW-CKD study has recently finished recruitment, which further reflects the real-world Korean population [31], and this follow-up study will provide more concrete perspectives to help specify the patterns of hospitalization in actual CKD patients.

In conclusion, the hospitalization rate in this study was much higher than the general population, even in lower stages. Various causes such as infection, neoplasm, and sensory-nervous system diseases have contributed to the hospitalization event, which showed a difference between the causes of CKD. We hope this study serves as a reference for an individualized approach for active follow-up and care for specific comorbidities of CKD patients regarding causative diseases.

Supplementary Materials

Notes

Conflicts of interest

All authors have no conflicts of interest to declare.

Funding

This study was supported by a research program funded by the Korea Disease Control and Prevention Agency (2011E3300300, 2012E3301100, 2013E3301600, 2013E3301601, 2013E3301602, 2016E3300200, 2016E3300201, 2016E3300202, 2019E320100, 2019E320101, 2019E320102, and 2022-11-007). The KNOW-CKD Study Protocol Summary was registered at ClinicalTrials.gov with accession number NCT01630486. The funders had no role in the study design, data collection or analysis, decision to publish, or preparation of the manuscript.

Data sharing statement

The data presented in this study are available from the corresponding author upon reasonable request.

Authors’ contributions

Conceptualization: HR, YWP, KHO

Formal analysis: YWP, JH, YJ

Funding acquisition: KHO

Investigation: SMK, YJ, Minjung K, EK, HR

Methodology: HR, SKP, KHO

Writing–original draft: YWP, JH

Writing–review & editing: SMK, Minsang K, YK, JCJ, SHH, KHO

All authors read and approved the final manuscript.

Acknowledgements

The authors express our gratitude for the support of the clinical research staff and the nurses who participated in the KNOW-CKD cohort study.

References

1. Kim SH, Jo MW, Go DS, Ryu DR, Park J. Economic burden of chronic kidney disease in Korea using national sample cohort. J Nephrol 2017;30:787–793.
2. Wang V, Vilme H, Maciejewski ML, Boulware LE. The economic burden of chronic kidney disease and end-stage renal disease. Semin Nephrol 2016;36:319–330.
3. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296–1305.
4. Iimuro S, Kaneko T, Ohashi Y, et al. Analysis of 2897 hospitalization events for patients with chronic kidney disease: results from CKD-JAC study. Clin Exp Nephrol 2019;23:956–968.
5. Mathew AT, Strippoli GF, Ruospo M, Fishbane S. Reducing hospital readmissions in patients with end-stage kidney disease. Kidney Int 2015;88:1250–1260.
6. Daratha KB, Short RA, Corbett CF, et al. Risks of subsequent hospitalization and death in patients with kidney disease. Clin J Am Soc Nephrol 2012;7:409–416.
7. Mujais SK, Story K, Brouillette J, et al. Health-related quality of life in CKD patients: correlates and evolution over time. Clin J Am Soc Nephrol 2009;4:1293–1301.
8. Kefale B, Alebachew M, Tadesse Y, Engidawork E. Quality of life and its predictors among patients with chronic kidney disease: a hospital-based cross sectional study. PLoS One 2019;14e0212184.
9. Tanaka K, Watanabe T, Takeuchi A, et al. Cardiovascular events and death in Japanese patients with chronic kidney disease. Kidney Int 2017;91:227–234.
10. Hsu CY, Ordoñez JD, Chertow GM, Fan D, McCulloch CE, Go AS. The risk of acute renal failure in patients with chronic kidney disease. Kidney Int 2008;74:101–107.
11. Oh KH, Park SK, Park HC, et al. KNOW-CKD (KoreaN cohort study for Outcome in patients With Chronic Kidney Disease): design and methods. BMC Nephrol 2014;15:80.
12. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–383.
13. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–612.
14. Schrauben SJ, Chen HY, Lin E, et al. Hospitalizations among adults with chronic kidney disease in the United States: a cohort study. PLoS Med 2020;17e1003470.
15. Cheol Seong S, Kim YY, Khang YH, et al. Data resource profile: the National Health Information Database of the National Health Insurance Service in South Korea. Int J Epidemiol 2017;46:799–800.
16. Kyoung DS, Kim HS. Understanding and utilizing claim data from the Korean National Health Insurance Service (NHIS) and Health Insurance Review & Assessment (HIRA) database for research. J Lipid Atheroscler 2022;11:103–110.
17. Kim S, Lim CS, Han DC, et al. The prevalence of chronic kidney disease (CKD) and the associated factors to CKD in urban Korea: a population-based cross-sectional epidemiologic study. J Korean Med Sci 2009;24 Suppl:S11–S21.
18. Iwagami M, Caplin B, Smeeth L, Tomlinson LA, Nitsch D. Chronic kidney disease and cause-specific hospitalisation: a matched cohort study using primary and secondary care patient data. Br J Gen Pract 2018;68:e512–e52.
19. Palmer SC, Maggo JK, Campbell KL, et al. Dietary interventions for adults with chronic kidney disease. Cochrane Database Syst Rev 2017;4:CD011998.
20. Ikizler TA, Burrowes JD, Byham-Gray LD, et al. KDOQI clinical practice guideline for nutrition in CKD: 2020 update. Am J Kidney Dis 2020;76:S1–S107.
21. Chebib FT, Torres VE. Autosomal dominant polycystic kidney disease: core curriculum 2016. Am J Kidney Dis 2016;67:792–810.
22. Cunningham J, Sprague SM, Cannata-Andia J, et al. Osteoporosis in chronic kidney disease. Am J Kidney Dis 2004;43:566–571.
23. Grunwald JE, Alexander J, Ying GS, et al. Retinopathy and chronic kidney disease in the Chronic Renal Insufficiency Cohort (CRIC) study. Arch Ophthalmol 2012;130:1136–1144.
24. Harrison TG, Ruzycki SM, James MT, et al. Estimated GFR and incidence of major surgery: a population-based cohort study. Am J Kidney Dis 2021;77:365–375.
25. Park SJ, Lee JH, Kang SW, Hyon JY, Park KH. Cataract and cataract surgery: nationwide prevalence and clinical determinants. J Korean Med Sci 2016;31:963–971.
26. Tomany SC, Wang JJ, Van Leeuwen R, et al. Risk factors for incident age-related macular degeneration: pooled findings from 3 continents. Ophthalmology 2004;111:1280–1287.
27. Moravski CJ, Kelly DJ, Cooper ME, et al. Retinal neovascularization is prevented by blockade of the renin-angiotensin system. Hypertension 2000;36:1099–1104.
28. Franke S, Dawczynski J, Strobel J, Niwa T, Stahl P, Stein G. Increased levels of advanced glycation end products in human cataractous lenses. J Cataract Refract Surg 2003;29:998–1004.
29. Sharma K, Slawski B. Renal disease and the surgical patient: minimizing the impact. Cleve Clin J Med 2018;85:559–567.
30. Park JT. Postoperative acute kidney injury. Korean J Anesthesiol 2017;70:258–266.
31. Oh KH, Park SK, Kim J, Ahn C, ; Representing the KNOW-CKD Study Investigators. The KoreaN cohort study for Outcomes in patients With Chronic Kidney Disease (KNOW-CKD): a Korean chronic kidney disease cohort. J Prev Med Public Health 2022;55:313–320.

Article information Continued

Figure 1.

Flow chart of participant recruitment and follow-up.

KNOW-CKD, KoreaN cohort study for Outcomes in patients With Chronic Kidney Disease.

Table 1.

Comparison of baseline clinical characteristics according to CKD stage

Characteristic Total G1 G2 G3a–G3b G4–5 p-value
No. of patients 2,238 360 425 835 618
Age (yr) 55 (45–63) 44 (35–53) 52 (43–60) 58 (48–65) 59 (51–67) <0.001
Male sex 1,368 (61.1) 181 (50.3) 281 (66.1) 236 (28.3) 357 (57.8) <0.001
Body mass index (kg/m2) 24.4 (22.3–26.4) 24.1 (21.8–26.3) 24.5 (22.3–26.4) 24.5 (22.7–26.5) 24.2 (22.1–26.5) 0.49
Systolic BP (mmHg) 127 (118–137) 126 (117–136) 125 (117–134) 126 (116–135) 130 (120–140) <0.001
Diastolic BP (mmHg) 77 (69–84) 79 (70–85) 77 (70–84) 77 (69–83) 76 (68–83) 0.002
Cause of CKD
 Diabetes mellitus 560 (25.0) 27 (7.5) 55 (12.9) 224 (26.8) 254 (41.1) <0.001
 Hypertension 441 (19.7) 32 (8.9) 80 (18.8) 203 (24.3) 127 (20.6) <0.001
 Glomerular disease 714 (31.9) 160 (44.4) 171 (40.2) 241 (28.9) 142 (23.0) <0.001
 Tubulointerstitial disease 13 (0.6) 1 (0.3) 1 (0.2) 9 (1.1) 3 (0.5) <0.001
 Polycystic kidney disease 356 (15.9) 128 (35.6) 94 (22.1) 88 (10.5) 45 (7.3) <0.001
 Others 145 (6.5) 12 (3.3) 23 (5.4) 67 (8.0) 44 (7.1) <0.001
 Missing 7 (0.3) 0 (0) 1 (0.2) 3 (0.4) 3 (0.5) <0.001
Other comorbidities
 Myocardial infarction 38 (1.7) 1 (0.3) 5 (1.2) 16 (1.9) 17 (2.8) 0.03
 Congestive heart failure 34 (1.5) 1 (0.3) 2 (0.5) 9 (1.1) 22 (3.6) <0.001
 Peripheral vascular disease 78 (3.5) 6 (1.7) 9 (2.1) 29 (3.5) 34 (5.5) 0.004
 Cerebrovascular disease 134 (6.0) 9 (2.5) 16 (3.8) 59 (7.1) 51 (8.3) <0.001
 Dementia 0 (0) 0 (0) 0 (0) 0 (0) 1 (0.2) 0.45
 Chronic obstructive pulmonary disease 13 (0.6) 0 (0) 1 (0.2) 9 (1.1) 3 (0.5) 0.08
 Connective tissue disease 137 (6.1) 10 (2.8) 24 (5.6) 53 (6.3) 50 (8.1) 0.01
 Diabetes mellitus 768 (34.3) 58 (16.1) 88 (20.7) 315 (37.7) 306 (49.5) <0.001
Charlson comorbidity index <0.001
 0–3 1,598 (71.4) 358 (99.4) 382 (89.9) 546 (65.4) 313 (50.6)
 4–5 602 (26.9) 2 (0.6) 41 (9.6) 272 (32.6) 288 (46.6)
 6 or higher 36 (1.6) 0 (0) 2 (0.5) 17 (2.0) 17 (2.8)
Laboratory findings
 eGFR (mL/min/1.73 m2) 46.2 (28.3–73.0) 105.2 (98.5–113.5) 72.0 (65.5–80.2) 43.6 (36.2–51.4) 20.7 (15.6–25.9) <0.001
 Hemoglobin (g/dL) 12.7 (11.3–14.3) 14.0 (12.9–15.1) 14.0 (12.5–15.2) 12.8 (11.5–14.3) 11.1 (10.1–12.2) <0.001
 Albumin (g/dL) 4.2 (4.0–4.5) 4.4 (4.1–4.6) 4.3 (4.1–4.5) 4.2 (4.0–4.4) 4.1 (3.8–4.3) <0.001
 hs-CRP (mg/L) 0.5 (0.2–1.5) 0.4 (0.1–1.2) 0.5 (0.2–1.4) 0.6 (0.2–1.5) 0.6 (0.2–1.8) <0.001

Data are expressed as number only, median interquartile range, or number (%).

BP, blood pressure; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; G, grade; hs-CRP, high-sensitivity C-reactive protein.

Table 2.

Incidence rate of hospitalization categorized by etiology

Etiology Total G1 G2 G3a–G3b G4–5 p-value
All-cause hospitalization 184.96 101.99 143.68 193.86 310.11 0.002
1. Acute kidney injury 10.88 1.95 4.23 11.80 27.30 <0.001
2. Infections 23.46 19.52 24.51 19.43 36.03 0.92
3. Neoplasm 21.57 13.66 11.41 28.45 27.31 0.59
4. Endocrine-nutrition-metabolic–related cause 14.85 3.90 7.61 10.41 46.95 <0.001
5. Diseases of blood and blood-forming organs 1.61 . . 2.08 4.37 0.004
6. Mental illness 1.42 0.49 2.96 0.69 2.18 0.87
7. Diseases of the nervous system and sensory organs 20.72 7.32 15.21 26.60 28.94 0.03
8. Diseases of the circulatory system 29.23 12.20 27.05 30.77 47.50 0.06
9. Diseases of the respiratory tract 2.65 2.44 0.85 3.01 4.37 0.51
10. Diseases of the digestive system 14.38 7.32 13.95 15.04 21.29 0.58
11. Diseases of the genitourinary system 10.22 10.74 10.56 10.41 8.74 0.02
12. Complications of pregnancy 1.32 2.44 1.27 0.93 1.09 0.02
13. Diseases of the musculoskeletal system and connective tissue 12.58 9.27 8.87 14.11 17.47 0.97
14. Injuries and poisoning 7.76 4.39 5.07 8.79 12.56 0.19
15. Diseases of the skin and subcutaneous tissue 0.76 - 2.11 - 1.64 0.497
16. Symptoms, signs, and ill-defined conditions and factors influencing health status 11.54 6.34 8.03 11.34 22.37 0.13

Incidence rate is presented as per 1,000 person-years. The incidence of admission by each category was compared by the Jonckheere-Terpstra test for trend analysis.

G, grade.

Table 3.

Incidence rate of operation during hospitalization categorized by department

Type of operation Total G1 G2 G3a–G3b G4–5 p-value
Overall surgical procedures 49.01 34.16 41.41 56.68 57.33 0.38
1. Musculoskeletal surgery 11.26 9.27 8.45 12.49 14.20 0.77
2. Intraabdominal surgery 7.10 6.34 8.03 7.63 2.18 0.03
3. Lower urologic/gynecologic surgery 5.30 3.90 4.65 7.63 2.18 0.11
4. Head and neck surgery 4.92 4.88 5.07 5.09 4.37 0.06
5. Vascular surgery 0.28 0.49 - 0.23 0.55 0.97
6. Skin and soft tissue surgery 0.95 0.98 1.69 0.46 1.09 0.24
7. Cardiac surgery - - - - - -
8. Breast surgery 0.85 0.49 0.42 1.16 1.09 0.79
9. Neurosurgical surgery 1.23 1.46 0.85 1.16 1.64 0.59
10. Retroperitoneal surgery 1.23 0.98 0.85 1.62 1.09 0.92
11. Thoracic surgery 0.57 - - 0.93 1.09 0.20
12. Anorectal surgery 1.04 0.49 - 1.16 2.73 0.16
13. Ophthalmic surgery 14.29 4.88 11.41 17.12 21.84 0.03

Incidence rate is presented as per 1,000 person-years. Incidence of admission by each category was compared by the Jonckheere-Terpstra test for trend analysis.

G, grade.

Table 4.

IRRs of all-cause hospitalization in a negative binomial regression model

Grade Crude
Age, sex adjusted
Age, sex, proteinuria, study duration adjusted
IRR (95% CI) p-value IRR (95% CI) p-value IRR (95% CI) p-value
G1 Reference (1) - Reference (1) - Reference (1) -
G2 1.38 (1.06–1.79) 0.02 1.17 (0.90–1.52) 0.25 1.22 (0.91–1.65) 0.18
G3a–G3b 1.73 (1.37–2.18) <0.001 1.29 (1.01–1.64) 0.04 1.44 (1.10–1.90) 0.01
G4–5 1.58 (1.24–2.02) <0.001 1.12 (0.87–1.45) 0.37 2.14 (1.61–2.87) <0.001

CI, confidence interval; G, grade; IRR, incidence rate ratio.

Table 5.

Adjusted IRRs of all-cause hospitalization in patients depends on age and presence of DM

Grade All-cause hospitalization
DM
No DM
Age ≤65 yr
Age >65 yr
IRR (95% CI) p-value IRR (95% CI) p-value IRR (95% CI) p-value IRR (95% CI) p-value
G1 Reference (1) - Reference (1) - Reference (1) - Reference (1) -
G2 1.53 (0.87–2.66) 0.14 1.41 (0.99–1.99) 0.06 1.37 (1.01–1.86) 0.04 1.85 (0.49–6.99) 0.37
G3a–3b 1.78 (1.10–2.90) 0.02 1.80 (1.32–2.46) <0.001 1.73 (1.32–2.27) <0.001 2.21 (0.63–7.84) 0.22
G4–5 2.72 (1.66–4.45) <0.001 2.67 (1.90–3.76) <0.001 2.57 (1.91–3.45) <0.001 3.38 (0.95–12.02) 0.06

Sex, proteinuria, and study duration adjusted.

CI, confidence interval; DM, diabetes mellitus; G, grade; IRR, incidence rate ratio.

Table 6.

IRRs of all-cause hospitalizations compared with the control population

Variable Crude
Age, sex adjusted
Age, sex, study duration adjusted
IRR (95% CI) p-value IRR (95% CI) p-value IRR (95% CI) p-value
General population (Reference)
Total 5.77 (5.52–6.03) <0.001 5.79 (5.53–6.05) <0.001 6.19 (5.92–6.48) <0.001
G1 3.19 (2.79–3.66) <0.001 2.50 (2.18–2.86) <0.001 3.84 (3.35–4.39) <0.001
G2 4.49 (4.04–5.00) <0.001 4.37 (3.93–4.86) <0.001 5.92 (5.32–6.58) <0.001
G3a–G3b 6.04 (5.64–6.46) <0.001 6.71 (6.27–7.19) <0.001 7.23 (6.75–7.74) <0.001
G4–5 9.72 (8.95–10.56) <0.001 11.18 (10.30–12.15) <0.001 6.48 (5.96–7.04) <0.001

CI, confidence interval; G, grade; IRR, incidence rate ratio.