Association between angiotensin converting enzyme inhibitor or angiotensin receptor blocker use prior to major elective surgery and the risk of acute dialysis

Setting and study overview

We conducted a retrospective, population-based cohort study of patients aged 66 years or older admitted to a hospital for a major elective surgery from 1995 to 2010 in Ontario, Canada. Ontario residents have universal access to hospital care and physician services and those aged 65 years or older have universal prescription drug coverage [17]. We performed this study according to a prespecified protocol approved by the research ethics board at Sunnybrook Health Sciences Centre, Toronto, Canada. The board deemed that patient informed consent was not required for this study which used datasets without patient identifiers. The reporting of this study follows guidelines set out for observational studies (detailed in Additional file 1) [18].

Data sources

We used linked large health care databases including hospital discharge, physician billing, and prescription drug claims databases to determine patients’ characteristics, information on comorbidities, outcome data, and drug usage. The Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD) provides detailed diagnostic and procedural information on all hospitalizations. The Ontario Health Insurance Plan (OHIP) database records all health claims for inpatient and outpatient physician services. The Ontario Registered Persons Database (RPDB) records demographic and vital status information. The Ontario Drug Benefits (ODB) database provides highly accurate information on dispensed outpatient medications [17]. These databases have been used extensively to research health outcomes and health services, including drug-induced and perioperative AKI [3, 19–23].

Study population

We included patients aged 66 years or older admitted to a hospital for elective surgery between January 1, 1995 and November 30, 2010. We excluded patients in their first year of universal drug coverage (patients aged 65 years) to avoid incomplete historical medication data. We included five surgical categories: cardiac, vascular, thoracic, abdominal, and retro-peritoneal, which all carry an appreciable risk for AKI-D (sample database codes in Additional file 1) [2, 3, 6, 7, 22]. To avoid selecting emergent or urgent surgery, we excluded all surgeries done during the course of a non-surgical hospital admission. We also excluded hospital admissions associated with missing or invalid identification, or demographic information. To ensure all patients had a recent access to health-care services, we limited our analyses to patients with at least one dispensed outpatient medication prescription in the 120 days prior to surgery.

We excluded patients with end-stage renal disease (ESRD) prior to their surgery (i.e. any evidence of dialysis or kidney transplantation) as the assessment of AKI-D is different and may no longer be relevant. To avoid the need to account for less frequently prescribed anti-hypertensive medications in the analyses, we only considered patients with either no evidence of anti-hypertensive medication use, or evidence of a prescription for the following frequently prescribed anti-hypertensive medications in the 120 days prior to surgery: ACEi, ARB, β-blocker, calcium channel blocker, non-potassium sparing diuretic (loop diuretic or thiazide diuretic). For patients with multiple eligible surgeries during the study period, we randomly selected one surgical procedure to avoid within patient clustering in the analyses.

Preoperative ACEi/ARB use

We grouped selected surgical cohort into ACEi/ARB users and non-users according to whether the patient filled at least one prescription for an ACEi or ARB (or not) in the 120 days prior to surgery. We selected a time frame of 120 days because the provincial drug plan requires each prescription to be renewed at least once every 100 days and 20 extra days were considered to accommodate any missed doses resulting in a longer period between renewal [24].

Baseline characteristics

We assessed demographic characteristics and comorbidities using validated database codes whenever possible (detailed in Additional file 1) [25–32]. We also determined concomitant medication use in the 120 days prior to surgery.

Primary and secondary outcomes

Our primary outcome was AKI-D within 14 days of surgery. AKI-D was determined using a set of high performance service fee codes (detailed in Additional file 1). Our secondary outcome was all-cause mortality within 90 days of surgery (in our data sources the code has a sensitivity of 97.8% and specificity of 100% for the finding of death) [33].

Primary analyses

We performed all statistical analyses at the Institute for Clinical Evaluative Sciences using SAS 9.2 (SAS Institute, Cary, NC, USA). We assessed differences in baseline characteristics between ACEi/ARB users and non-users using standardized differences. As recommended by others, we considered a standardized difference of > 10% as a meaningful difference between the two groups [34]. To determine the association between ACEi/ARB use and study outcomes, we conducted multivariable logistic regression analyses and estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs). We interpreted odds ratios as relative risks (RRs) (appropriate given the incidences observed) [35]. In the logistic regression analyses, we adjusted for the following prespecified baseline characteristics associated with ACEi/ARB use and postoperative AKI [2, 3, 6–8, 10, 11, 15, 36, 37]: age, sex, CKD, coronary artery disease, congestive heart failure, cerebrovascular disease, peripheral vascular disease, chronic obstructive pulmonary disease, chronic liver disease, type of surgery (cardiac, vascular, thoracic, abdominal, retro-peritoneal), era of surgery (1995 to 1998, 1999 to 2001, 2002 to 2004, 2005 to 2007, 2008 to 2010), and use of one or more drugs from the following medication groups - anti-diabetic medications, β-blockers, calcium channel blockers, non-potassium sparing diuretics, and statins. The presence of all of these characteristics was assessed with database codes (detailed in Additional file 1).

Additional analyses

Baseline characteristics: ACEi/ARB users and non-users

Primary analyses: AKI-D and all-cause mortality

Additional analyses

Study strengths and limitations

Our study has several strengths. To the best of our knowledge, this is the largest study to describe the association between preoperative ACEi/ARB use and AKI-D (over 230,000 patients from 118 hospitals). We included both cardiac and non-cardiac major surgeries. Unlike other studies, the large number of events of AKI-D (810 events) reduced concerns about statistical overfitting [53]. Given there is <1% yearly emigration from Ontario, the loss to follow up was minimal. Finally, the information available within the large Ontario health care databases reflects routine clinical practice and may be less prone to participation biases that can arise in other types of studies [3, 19–23].

There are several limitations to our study. Due to possible difference in underlying mechanism for the risk of postoperative acute dialysis in emergent surgeries compared to elective surgeries, we excluded emergent surgeries from our analyses. In an emergency situation it is also difficult to manipulate pre-operative medication use. However, exclusion of emergency surgeries may have reduced the generalizability of the study results. We could not determine medication compliance from evidence of a dispensed prescription for ACEi, ARB, or other medications in our data sources. Our study was limited by the absence of key information on perioperative ACEi/ARB use particularly whether it was held prior to surgery and if so when it was held, and when it was restarted after surgery. Important information such as preoperative and intraoperative blood pressure was also not available. These are key elements to guide the optimal and safe use of ACEi/ARB use in the perioperative period, including regimens to be tested in large randomized controlled trials (RCTs). We were also not able to adjust for variables unavailable in our data sources such as body mass index, preoperative proteinuria, non-prescription medication use and in hospital medication use. Another limitation with our data sources is the accuracy of codes for patient related health information. In attempt to limit these concerns, we did use database codes supported by validation studies whenever possible [25–32].

Study implications and future directions

Our study results support the need for RCTs in this setting, to test a regimen of perioperative ACEi/ARB selected for optimal efficacy and safety. Given the low incidence of acute dialysis (about 0.45% in all types of major surgery [1–3]), a very large trial (over 150,000 patients) would be needed to examine a meaningful difference with this as a primary outcome. Such a trial is unlikely to occur. However, if we consider a primary outcome of 90-day all-cause mortality (4.67% of patients in our study), the sample size is tenable at about 15,000 patients. The sample size could be further reduced if there is a rationale to consider a composite of clinically important events including peri-operative cardiac events. Enrolling a large number of patients with CKD may be prudent, as in the current study the signal of benefit for AKI-D was strongest in this group of patients. Given the large number of surgeries complicated by AKI-D worldwide each year, we propose that such RCTs should be undertaken.