Association of Kidney-Related Safety Events with Incident Chronic Kidney Disease in Veterans

    

    

    Figure 4: Calibration plot. Predicted probability of incident stage 3 CKD using
our model was compared to the observed probability of incident stage 3 CKD.
Calibration was evaluated with the cohort divided into 100 groups.
    

Discussion

The presence of multiple comorbidities along with exposures to safety events can impact the development and progression of CKD. In our case-control study conducted in a large VA population, we found multiple comorbidities, intravenous contrast exposures; NSAID use and AKI events were associated with the development of incident stage 3 CKD. Our study uniquely included a large sample size and regional distribution of participants and evaluated multiple safety exposures simultaneously.

Several generalized prediction models have been developed to understand risks for developing incident CKD, many of which also identify older age, lower baseline eGFR, hypertension, diabetes, CHF, and CAD as risk factors for stage 3 CKD development [4-15]. Hanratty et al. studied 10,420 patients with hypertension in Denver, Colorado. Patients with lower baseline eGFR, older age, diabetes, and vascular disease (composite of CAD, peripheral vascular disease and cerebral vascular disease) had increased risks of incident CKD. CHF was not found to be associated, however only 37 patients had a history of CHF [5]. A study of general community patients from the Atherosclerosis Risk in Communities Study and Cardiovascular Health Study did find CHF associated with CKD at a risk level similar to our findings for our middle-aged groups with an OR of 1.7 in their best-fitted model [11]. They also found age, female gender, diabetes, hypertension, PVD, anemia, and low high-density lipoprotein levels associated with incident CKD. In the mainly white population of the Framingham study, increased age, lower baseline eGFR, diabetes and smoking were associated with incident CKD [9]. This same population was used to build a prediction model of incident CKD at 10 years that included eGFR, age, diabetes, hypertension and albuminuria [31]. There have also been multiple prediction models in Asian populations that have identified additional risk factors of waist circumference, Body Mass Index (BMI), systolic and diastolic blood pressures, education, C-reactive protein, triglycerides, glucose, and uric acid in various models [7,10,12].

Effect modification was not evaluated in the North American studies. Our study showed an interaction between hypertension, diabetes, CHF and age, with stronger associations between CKD and each comorbidity at a younger age. This likely reflects a survivor bias for younger patients with comorbidities, but also identifies a higher risk population for CKD that may need more intensive monitoring of kidney function.

In addition to more traditional risk factors, Hao et al.’s study evaluating the use of machine learning methods to predict incident CKD at 1-year in a Maine population identified risk factors such as number of outpatient visits and radiology tests and different medications, which suggests the possible importance of patient care events in understanding kidney function decline [32].

Inpatient AKI events are recognized contributors to CKD development, as shown in other VA studies [20-22,33,34]. A VA cohort comprised of veterans with diabetes who developed AKI during hospitalization was at increased risk for stage 4 CKD development, with each AKI episode approximately doubling the risk [33]. A general VA inpatient study of AKI severity and recovery time conducted by Heung et al. found that mild cases of AKI demonstrated a Hazard Ratio (HR) of 1.43 for the development of CKD within 1 year of admission [20]. Our study is unique in that we assessed both inpatient and outpatient AKI episodes, with outpatient AKI demonstrating a stronger association with developing stage 3 CKD. We did not, however, determine the severity of AKI events, and our control group would be limited to less severe episodes of AKI since the group is defined by all eGFR values remaining >60mL/min/1.73m². This may account for the large associations found in our study.

The role of NSAIDs in kidney function decline is still debated. Several studies in healthy populations from the Nurses’ Health Study and Physicians’ Health Study have not found an association [35-38]. These studies determined NSAID use via questionnaires, which are subject to recall bias [39]. Studies also vary significantly in how they quantify NSAID exposure, with some quantifying by dosage and others quantifying by varying metrics of duration [35-38]. A study based in the United Kingdom that incorporated >2 NSAID prescriptions in the preceding 6 months into a model for risk of moderate-severe CKD development noted an increased risk due to NSAID use, with an HR of 1.3 [40]. In a young active military cohort, patients who were prescribed ≥7 doses per month had a 20% increased risk of CKD, but <7 NSAID doses was not associated with an increased risk [41]. Most similar to our findings is the dose response of NSAID exposure in a large hypertensive Taiwanese cohort that found an HR 1.18 for 1 to 89 days of NSAID prescriptions and an HR of 1.32 for ≥90 days of NSAIDs [42]. Other studies have demonstrated that certain NSAIDs, such as ketorolac, oxicams, rofecoxib, ibuprofen, and indomethacin, have increased risk for kidney damage [25,43]. Since we did not separate NSAID prescriptions by type, we were unable to assess the effect of specific NSAIDs.

The effect of iodine-based contrast exposure on kidney function is another heavily debated topic and has focused mainly on AKI events following exposures. Decreased eGFR is the only reproducible risk factor for the development of intravenous contrast-induced AKI, which are events directly related to contrast effects on the kidney [44]. Patients with an eGFR greater than 60mL/min/1.73m² have a risk approaching 0% for these events, yet may still experience a risk of 5% for contrast-associated AKI events, which are changes in kidney function of any cause around the timing of contrast exposure [26,28,44]. This reflects a growing concern that AKI events may be due to other patient-related factors at the time of contrast exposure, putting into question the direct nephrotoxicity of contrast in patients with better kidney function. A large meta-analysis did not find an increased risk for either AKI or ESKD after exposure to CT contrast compared to CT without contrast [45]. Hinson et al. performed a propensity score matched analysis of emergency room patients who did and did not receive CT contrast and did not find an association between contrast exposure and CKD diagnosis 6 months after exposure [46]. This study only evaluated one contrast exposure, and 6 months may not have been enough time to develop CKD after exposure. We evaluated multiple intravenous contrast exposures over a longer time and found a 30% increased odds of incident CKD with contrast exposure. The lack of dose response between 1-2 intravenous contrast exposures and ≥3 contrast exposures warrants more evaluation since the lack of a dose response is less supportive of a true correlation. We also did not directly determine if CT studies were associated with the AKI events, however, as AKI events are rare at higher eGFR values, the effect of contrast in this context would likely be reflective of more subtle changes to kidney function.

Arterial contrast exposures have mainly been studied in patients undergoing LHC and incur higher risks of AKI compared to intravenous contrast. Secondary analysis of a randomized control trial of patients comparing LHC to CT angiography for the evaluation of atypical angina revealed 13.2% of patients undergoing LHC experienced AKI versus 5.6% of patients undergoing CT angiography [47]. Patients that experienced AKI after LHC were found to be at higher risk of CKD and kidney decline [27,47]. It is still uncertain how much of these effects are due to the contrast itself versus other clinical factors surrounding the need for LHC. This concern may reflect our finding that non-cardiac angiograms were not found to be associated with incident CKD in our multivariate analysis, and more research is needed to understand the possible role of contrast from non-cardiac angiograms in kidney function decline.

Our study has several limitations. Since this was a retrospective analysis, causal association between kidney-related safety events and incident stage 3 CKD cannot be determined. There may also be additional confounding from variables that were not evaluated in this analysis such as BMI, smoking and proteinuria. Due to missing race data, there may be misclassification of CKD cases and race could not be evaluated in the final model. Analysis with available race data did not significantly alter model estimates; however, black race carried increased odds of incident CKD in the analysis of participants with race data (Supplementary Table 2). Our conclusions are also limited mainly to men due to the small number of female veterans in this VA cohort. We were also unable to assess the influence of events either occurring prior to the study period or occurring outside the VA that may affect CKD risk. Additionally, the use of ICD-9 codes to identify exposures and comorbidities likely resulted in an underestimation of events and cannot assess the severity of comorbidities. In previous analyses, billing codes for AKI have demonstrated low sensitivity and high specificity, with a tendency to under-report AKI events and typically identify higher severity AKI events [48]. Along similar lines, use of NSAID prescription data does not necessarily indicate total NSAIDs taken by the patient since we could not determine adherence to prescriptions or use of over the counter and external prescriptions. Lastly, we did not validate our findings externally and our findings may not be applicable to patients outside of the VA system.

Conclusion

CKD is a common condition with many factors that influence its development and progression. Our study demonstrates associations of multiple safety events with incident CKD concurrently, including AKI events, NSAIDs use and contrast exposures. More research is needed to understand the role of preventable safety events in developing CKD and how to best manage exposures to these events to prevent kidney function decline. Preventative efforts may be most beneficial in younger patients with CHF, diabetes, and hypertension.

Acknowledgements

Funding was provided by Pharmaceutical Research Computing, University of Maryland School of Pharmacy, USA.

References

1. Saran R, Robinson B, Abbott KC, Agodoa LYC, Bragg-Gresham J, Balkrishnan R, et al. US Renal Data System 2018 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am J Kidney Dis Off J Natl Kidney Found. 2019; 73: A7-A8.
2. Webster AC, Nagler EV, Morton RL, Masson P. Chronic Kidney Disease. The Lancet. 2017; 389: 1238-1252.
3. Murphy D, McCulloch CE, Lin F, Banerjee T, Bragg-Gresham JL, Eberhardt MS, et al. Trends in prevalence of chronic kidney disease in the United States. Ann Intern Med. 2016; 165: 473-481.
4. Fox CS, Larson MG, Leip EP, Meigs JB, Wilson PWF, Levy D. Glycemic Status and Development of Kidney Disease: The Framingham Heart Study. Diabetes Care. 2005; 28: 2436-2440.
5. Hanratty R, Chonchol M, Miriam Dickinson L, Beaty BL, Estacio RO, MacKenzie TD, et al. Incident chronic kidney disease and the rate of kidney function decline in individuals with hypertension. Nephrol Dial Transplant. 2010; 25: 801-807.
6. Gosmanov AR, Lu JL, Sumida K, Potukuchi PK, Rhee CM, Kalantar-Zadeh K, et al. Synergistic Association of Combined Glycemic and Blood Pressure Level with Risk of Complications in US Veterans with Diabetes. J Hypertens. 2016; 34: 907-913.
7. Chia YC, Ching SM. Hypertension and the development of New onset chronic kidney disease over a 10year period: a retrospective cohort study in a primary care setting in Malaysia. BMC Nephrol. 2012; 13: 173.
8. Burrows NR, Vassalotti JA, Saydah SH, Stewart R, Gannon M, Chen S-C, et al. Identifying High-Risk Individuals for Chronic Kidney Disease: Results of the CHERISH Community Demonstration Project. Am J Nephrol. 2018; 48: 447-455.
9. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PWF, Levy D. Predictors of New-Onset Kidney Disease in a Community-Based Population. JAMA. 2004; 291: 844-850.
10. Chien K-L, Lin H-J, Lee B-C, Hsu H-C, Lee Y-T, Chen M-F. A Prediction Model for the Risk of Incident Chronic Kidney Disease. Am J Med. 2010; 123: 836-846.e2.
11. Kshirsagar AV, Bang H, Bomback AS, Vupputuri S, Shoham DA, Kern LM, et al. A Simple Algorithm to Predict Incident Kidney Disease. Arch Intern Med. 2008; 168: 2466-2473.
12. Wen J, Hao J, Zhang Y, Cao K, Zhang X, Li J, et al. Risk scores for predicting incident chronic kidney disease among rural Chinese people: a village-based cohort study. BMC Nephrol. 2020; 21.
13. Whaley-Connell AT, Sowers JR, Stevens LA, McFarlane SI, Shlipak MG, Norris KC, et al. CKD in the United States: Kidney Early Evaluation Program (KEEP) and National Health and Nutrition Examination Survey (NHANES) 1999-2004. Am J Kidney Dis. 2008; 51: S13-S20.
14. McCullough PA, Li S, Jurkovitz CT, Stevens LA, Wang C, Collins AJ, et al. CKD and Cardiovascular Disease in Screened High-Risk Volunteer and General Populations: The Kidney Early Evaluation Program (KEEP) and National Health and Nutrition Examination Survey (NHANES) 1999-2004. Am J Kidney Dis. 2008; 51: S38-S45.
15. Taal MW, Brenner BM. Predicting initiation and progression of chronic kidney disease: Developing renal risk scores. Kidney Int. 2006; 70: 1694-1705.
16. Chapin E, Zhan M, Hsu VD, Seliger SL, Walker LD, Fink JC. Adverse Safety Events in Chronic Kidney Disease: The Frequency of “Multiple Hits”. Clin J Am Soc Nephrol CJASN. 2010; 5: 95-101.
17. Weir MR, Fink JC. Safety of medical therapy in patients with chronic kidney disease and end-stage renal disease. Curr Opin Nephrol Hypertens. 2014; 23: 306-313.
18. Seliger SL, Zhan M, Hsu VD, Walker LD, Fink JC. Chronic Kidney Disease Adversely Influences Patient Safety. J Am Soc Nephrol JASN. 2008; 19: 2414-2419.
19. Chawla LS, Eggers PW, Star RA, Kimmel PL. Acute Kidney Injury and Chronic Kidney Disease as Interconnected Syndromes. N Engl J Med. 2014; 371: 58-66.
20. Heung M, Steffick DE, Zivin K, Gillespie BW, Banerjee T, Hsu C, et al. Acute Kidney Injury Recovery Pattern and Subsequent Risk of CKD: An Analysis of Veterans Health Administration Data. Am J Kidney Dis. 2016; 67: 742-752.
21. Jones J, Holmen J, De Graauw J, Jovanovich A, Thornton S, Chonchol M. Association of Complete Recovery From Acute Kidney Injury With Incident CKD Stage 3 and All-Cause Mortality. Am J Kidney Dis. 2012; 60: 402-408.
22. Coca SG, Singanamala S, Parikh CR. Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis. Kidney Int. 2012; 81: 442-448.
23. Cabassi A, Tedeschi S, Perlini S, Verzicco I, Volpi R, Gonzi G, et al. Nonsteroidal anti-inflammatory drug effects on renal and cardiovascular function: from physiology to clinical practice. Eur J Prev Cardiol. 2020; 27: 850-867.
24. Huerta C, Castellsague J, Varas-Lorenzo C, García Rodríguez LA. Nonsteroidal anti-inflammatory drugs and risk of ARF in the general population. Am J Kidney Dis. 2005; 45: 531-539.
25. Winkelmayer WC, Waikar SS, Mogun H, Solomon DH. Nonselective and Cyclooxygenase-2-Selective NSAIDs and Acute Kidney Injury. Am J Med. 2008; 121: 1092-1098.
26. Mehran R, Dangas GD, Weisbord SD. Contrast-Associated Acute Kidney Injury. N Engl J Med. 2019; 380: 2146-2155.
27. James MT, Ghali WA, Tonelli M, Faris P, Knudtson ML, Pannu N, et al. Acute kidney injury following coronary angiography is associated with a long-term decline in kidney function. Kidney Int. 2010; 78: 803-809.
28. McCullough PA, Adam A, Becker CR, Davidson C, Lameire N, Stacul F, et al. Risk Prediction of Contrast-Induced Nephropathy. Am J Cardiol. 2006; 98: 27-36.
29. Ellis JH, Khalatbari S, Yosef M, Cohan RH, Davenport MS. Influence of Clinical Factors on Risk of Contrast-Induced Nephrotoxicity From IV Iodinated Low-Osmolality Contrast Material in Patients With a Low Estimated Glomerular Filtration Rate. Am J Roentgenol. 2019; 213: W188-W193.
30. Lim E, Jang J-H, Yoon D, Min Y-G, Kim H-H. Does Exposure to Computed Tomography Contrast Media Increase Risk of End-Stage Renal Disease? Med Sci Monit Int Med J Exp Clin Res. 2020; 26: e921303-1-e921303-7.
31. O’Seaghdha CM, Lyass A, Massaro JM, Meigs JB, Coresh J, D’Agostino RB, et al. A Risk Score for Chronic Kidney Disease in the General Population. Am J Med. 2012; 125: 270-277.
32. Hao S, Fu T, Wu Q, Jin B, Zhu C, Hu Z, et al. Estimating One-Year Risk of Incident Chronic Kidney Disease: Retrospective Development and Validation Study Using Electronic Medical Record Data From the State of Maine. JMIR Med Inform. 2017; 5.
33. Thakar CV, Christianson A, Himmelfarb J, Leonard AC. Acute Kidney Injury Episodes and Chronic Kidney Disease Risk in Diabetes Mellitus. Clin J Am Soc Nephrol CJASN. 2011; 6: 2567-2572.
34. Soto K, Campos P, Pinto I, Rodrigues B, Frade F, Papoila AL, et al. The risk of chronic kidney disease and mortality are increased after communityacquired acute kidney injury. Kidney Int. 2016; 90: 1090-1099.
35. Curhan GC, Knight EL, Rosner B, Hankinson SE, Stampfer MJ. Lifetime Nonnarcotic Analgesic Use and Decline in Renal Function in Women. Arch Intern Med. 2004; 164: 1519-1524.
36. Kurth T, Glynn RJ, Walker AM, Rexrode KM, Buring JE, Stampfer MJ, et al. Analgesic use and change in kidney function in apparently healthy men1 1The sponsor of the study had no role in study design, data collection, data analysis, data interpretation, or the writing of the manuscript. Am J Kidney Dis. 2003; 42: 234-244.
37. Rexrode KM, Buring JE, Glynn RJ, Stampfer MJ, Youngman LD, Gaziano JM. Analgesic Use and Renal Function in Men. JAMA. 2001; 286: 315-321.
38. Agodoa LY, Francis ME, Eggers PW. Association of Analgesic Use with Prevalence of Albuminuria and Reduced GFR in US Adults. Am J Kidney Dis. 2008; 51: 573-583.
39. McLaughlin JK, Lipworth L, Chow W-H, Blot WJ. Analgesic use and chronic renal failure: A critical review of the epidemiologic literature. Kidney Int. 1998; 54: 679-686.
40. Hippisley-Cox J, Coupland C. Predicting the risk of Chronic Kidney Disease in Men and Women in England and Wales: prospective derivation and external validation of the QKidney^® Scores. BMC Fam Pract. 2010; 11: 49.
41. Nelson DA, Marks ES, Deuster PA, O’Connor FG, Kurina LM. Association of Nonsteroidal Anti-inflammatory Drug Prescriptions With Kidney Disease Among Active Young and Middle-aged Adults. JAMA Netw Open. 2019; 2: e187896-e187896.
42. Hsu Chih-Cheng, Wang Hongjian, Hsu Yueh-Han, Chuang Shao-Yuan, Huang Ya-Wen, Chang Yu-Kang, et al. Use of Nonsteroidal Anti-Inflammatory Drugs and Risk of Chronic Kidney Disease in Subjects With Hypertension. Hypertension. 2015; 66: 524-533.
43. Ingrasciotta Y, Sultana J, Giorgianni F, Fontana A, Santangelo A, Tari DU, et al. Association of Individual Non-Steroidal Anti-Inflammatory Drugs and Chronic Kidney Disease: A Population-Based Case Control Study. PLoS ONE. 2015; 10.
44. Davenport MS, Perazella MA, Yee J, Dillman JR, Fine D, McDonald RJ, et al. Use of Intravenous Iodinated Contrast Media in Patients with Kidney Disease: Consensus Statements from the American College of Radiology and the National Kidney Foundation. Radiology. 2020; 294: 660-668.
45. Aycock RD, Westafer LM, Boxen JL, Majlesi N, Schoenfeld EM, Bannuru RR. Acute Kidney Injury After Computed Tomography: A Meta-analysis. Ann Emerg Med. 2018; 71: 44-53.e4.
46. Hinson JS, Ehmann MR, Fine DM, Fishman EK, Toerper MF, Rothman RE, et al. Risk of Acute Kidney Injury After Intravenous Contrast Media Administration. Ann Emerg Med. 2017; 69: 577-586.e4.
47. Schönenberger E, Martus P, Bosserdt M, Zimmermann E, Tauber R, Laule M, et al. Kidney Injury after Intravenous versus Intra-arterial Contrast Agent in Patients Suspected of Having Coronary Artery Disease: A Randomized Trial. Radiology. 2019; 292: 664-672.
48. Grams ME, Waikar SS, MacMahon B, Whelton S, Ballew SH, Coresh J. Performance and Limitations of Administrative Data in the Identification of AKI. Clin J Am Soc Nephrol. 2014; 9: 682-689.