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Variability in Glycated Hemoglobin and Risk of Poor Outcomes Among Diabetes Care 1 Julia A. Critchley, Iain M. Carey, Tess Harris, Variability in Glycated Stephen DeWilde, and Derek G. Cook Hemoglobin and Risk of Poor Outcomes Among People With Type 2 Diabetes in a Large Primary Care Cohort Study https://doi.org/10.2337/dc19-0848 EPIDEMIOLOGY/HEALTH SERVICES RESEARCH OBJECTIVE Diabetes mellitus (DM) guidelines focus on target glycated hemoglobin (HbA1c) levels. Long-term variability in HbA1c may be predictive of hospitalization or mortality, but its importance at different average levels or trajectories is unclear. RESEARCH DESIGN AND METHODS Using English primary care data, 58,832 patients with type 2 DM had HbA1c average (mean of annual means), variability (coefficient of variation), and trajectory (annual regression slope) estimated during 2006–2009. Hazard ratios (HRs) for mortality and emergency hospitalization during 2010–2015, with adjustment for age, sex, smoking, BMI, duration of DM, and deprivation, were estimated using Cox regression. The simultaneous impact of HbA1c average, variability, and trajectory was estimated using percentiles. RESULTS In mutually adjusted models, HbA1c variability showed a consistent dose-response relationship with all-cause mortality, while average level was only important among individuals in the highest or lowest 10% of the distribution, and trajectory had no independent effect. Individuals with the most unstable HbA (top 10%) were almost Population Health Research Institute, St. 1c George’s, University of London, London, U.K. twice as likely to die (HR 1.93 [95% CI 1.72–2.16]) than were those with the most d Corresponding author: Julia A. Critchley, jcritchl@ stable (bottom 10%) an association attenuated but not explained by hypogly- sgul.ac.uk cemia. For emergency hospitalizations, similar trends were seen except for coronary Received29 April 2019andaccepted1 September artery diseases (CADs) and ischemic stroke (IS), where increasing average rather 2019 than variability was predictive. This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/suppl/ CONCLUSIONS doi:10.2337/dc19-0848/-/DC1. HbA1c variability was strongly associated with overall mortality and emergency © 2019 by the American Diabetes Association. Readers may use this article as long as the work hospitalization and not explained by average HbA1c or hypoglycemic episodes. Only for CAD and IS hospitalizations was no association found, with average HbA is properly cited, the use is educational and not 1c for profit, and the work is not altered. More infor- strongly predictive. Targets should focus on both stability and absolute level of mation is available at http://www.diabetesjournals HbA1c. .org/content/license. Diabetes Care Publish Ahead of Print, published online October 3, 2019 2 Variability in HbA1c in People With DM Diabetes Care There is substantial evidence that in- (12,14); a recent overview concluded disability, crime, barriers to housing creases in chronic levels of average hy- that variability in HbA1c was “not yet and services, and living environment), perglycemia (as generally measured by established” as an independent risk ranking local areas from the most glycated hemoglobin [HbA1c]) are asso- factor for DM complications (13). deprived (1) to the least deprived ciated with higher risk of various diabetes While randomized data might be ideal, (32,884) (25). mellitus (DM) complications including individual RCTs lack statistical power for microvascular and macrovascular events teasing out the relative impact of vari- Study Design (1,2), particularly when levels are sub- ability, after accounting for interrelated We carried out a further analysis of indi- stantially elevated (for example, .8% HbA1c parameters such as trajectory viduals with DM from a previously pub- HbA1c [64 mmol/mol]) (3). Randomized (direction and gradient of any trend in lished retrospective matched cohort study controlled trials (RCTs) showed that HbA1c over time; whether up or down) and (7,22). DM type was classified using a lower HbA1c is associated with significant average HbA1c. Larger registry or data- combination of DM Read Codes and pre- reductions in risk of microvascular com- base analyses are therefore critical, but scribing of anti-DM medication (22). Read plications (3,4), though less convincingly relatively few have been published Codes are a primary care clinical terminol- or consistently in risk of all-cause mor- (15,16), and all had limitations. In par- ogy used extensively in the U.K. (26). They tality or cardiovascular disease (CVD) ticular few previously published registry have a hierarchical structure similar to (5–8). Average HbA1c does not explain or observational studies adjusted for ICD codes, and cross-mapping is possible all the variation in risk observed though; hypoglycemic episodes. These are known between systems (27). In this analysis, we including variability in HbA1c improved to increase mortality risk (17,18) and are included only patients who were identi- prediction of microvascular events in not strongly correlated with average fied as having T2DM by 1 January 2008 secondary analyses of the Diabetes Con- HbA1c (19,20). Given the continued un- (n 5 82,492) and continuously registered trol and Complications Trial (9). Recent certainty, we assessed the importance of with their practice to at least 1 January studies using latent growth modeling HbA1c variability in predicting key out- 2010 (Supplementary Fig. 1). From this have also demonstrated that patients comes (all-cause mortality, cause-specific group, we then restricted to 58,832 with type 2 DM (T2DM) with “low and mortality, emergency hospitalization, and (71.3%) patients with at least one HbA1c stable” patterns of HbA1c over time have cause-specific hospitalization) in a large measurement in each calendar year dur- lower risks than those with upward, representative retrospective cohort of ing the 4-year baseline period (2006– downward, or more variable patterns primary care patients in England. Un- 2009). All patients were then followed (10,11). It has thus been hypothesized like previous studies, our large anal- for outcomes from 1 January 2010 until that longer-term variability in serial ysis included both men and women, the earliest date of the following: death, HbA1c measurements may also be im- middle-aged and older age-groups de-registration from practice, practice portant (12,13). (ages 40–89 years), and better charac- leaving CPRD, or 31 December 2015. Existing studies of HbA1c variability terization of variability and average Mean follow-up time for all patients have provided somewhat conflicting ev- HbA1c as well as adjustment for key was ;4.1 years. idence. A systematic review of observa- confounders (12,15,16). tional studies published in 2015 found Outcomes some evidence of higher risk associated RESEARCH DESIGN AND METHODS We measured the following primary out- with HbA1c variability for both type 1 DM Data Source comes during follow-up: all-cause mor- and T2DM (12). Among the 43,000 T2DM The Clinical Practice Research Datalink tality and first emergency hospitalization patients across 13 studies, higher vari- (CPRD) is a large primary care database (defined as an admission that was un- ability resulted in increased risks of CVD representative of the U.K. population predictable and at short notice because and all-cause mortality, as well as certain (21,22). This study is based on 361 general of clinical need). In further analyses, we microvascular outcomes (particularly practices in England only with anony- divided mortality into cardiovascular retinopathy and neuropathy) (12). How- mous linkage to Hospital Episode Statis- (CVD) (any ICD-10 code beginning with ever, most of the included studies had tics and Office for National Statistics “I”) and noncardiovascular using under- limitations such as little adjustment for death registration data (23). Hospital lying cause of death. We subsequently key confounders (12). Almost all included Episode Statistics records clinical and subdivided CVD into those deaths related studies were based solely on secondary administrative information on all Na- to CAD (I20–I25.9) and IS (I63–64) versus care patients, while globally most pa- tional Health Service funded inpatient all other CVD codes. These causes were tients with DM are managed in the episodes and allows for identification of chosen based on a prior study demon- community or primary care. Also, there method of admission (e.g., emergency), strating strong associations with average were high levels of heterogeneity be- in addition to the primary reason for the HbA1c (28). tween studies that could not be ex- admission (24). Linkage is also available We also stratified emergency hospital- plained, possibly related to different to the Index of Multiple Deprivation izations into infection related, CVD, and definitions and measurements of vari- (IMD), the official measure for small CAD 1 IS admissions. We included in- ability, follow-up durations, DM dura- area deprivation in the U.K., a composite fection using previously defined codes tions, or losses to follow-up. Not all ecological measure based on postcodes (8,25) due to strong associations with recent studies have shown substantially (25). IMD combines data from seven hyperglycemia and since infections increased risks associated with variability domains (income, employment, edu- may also promote HbA1c variability (after adjustment for mean HbA1c) cation skills and training, health and (7,22). care.diabetesjournals.org Critchley and
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