Emily B. Schroeder

Hypertension, Blood Pressure, and Heart Rate Variability. The Atherosclerosis Risk in Communities (ARIC) Study

Abstract—Dysregulation of the autonomic nervous system has been implicated in the development of hypertension. Heart rate variability is a noninvasive tool to quantitatively estimate cardiac autonomic activity and has been used to document decreased cardiac autonomic activity in hypertension. The ability of decreased heart rate variability to predict incident hypertension has not been well studied, and there are no studies of whether hypertension leads to changes in heart rate variability. We investigated the temporal sequence linking hypertension, blood pressure, and heart rate variability in a population-based cohort of 11 061 individuals aged 45 to 54 years at baseline. Individuals with hypertension had decreased heart rate variability at baseline, and this association was present across the full blood pressure range. Among 7099 individuals without hypertension at baseline, low heart rate variability predicted greater risk of incident hypertension over 9 years of follow-up. The hazard ratio (95% confidence interval [CI]) for the lowest compared with the highest quartile of the standard deviation of normal-to-normal R-R intervals was 1.24 (95% CI, 1.10–1.40), for the root mean square of successive differences in normal-to-normal R-R intervals was 1.36 (95% CI, 1.21–1.54), and for R-R interval was 1.44 (95% CI, 1.27–1.63). Over 9 years, there was no measurable difference in the rate of change in heart rate variability among those with and without hypertension, although the differences in heart rate variability at follow-up were smaller than those at baseline. These findings thus support the thesis that the autonomic nervous system is involved in the development of hypertension, yet suggest that differences in the autonomic profile of hypertensives and normotensives do not increase with time.

Determinants of Use of Emergency Medical Services in a Population With Stroke Symptoms: The Second Delay in Accessing Stroke Healthcare (DASH II) Study

Background and Purpose With the advent of time-dependent thrombolytic therapy for ischemic stroke, it has become increasingly important for stroke patients to arrive at the hospital quickly. This study investigates the association between the use of emergency medical services (EMS) and delay time among individuals with stroke symptoms and examines the predictors of EMS use. Methods The Second Delay in Accessing Stroke Healthcare Study (DASH II) was a prospective study of 617 individuals arriving at emergency departments in Denver, Colo, Chapel Hill, NC, and Greenville, SC, with stroke symptoms. Results EMS use was associated with decreased prehospital and in-hospital delay. Those who used EMS had a median prehospital delay time of 2.85 hours compared with 4.03 hours for those who did not use EMS (P =0.002). Older individuals were more likely to use EMS (odds ratio [OR] 1.21 for each 5-year increase, 95% CI 1.14 to 1.29), as were individuals who expressed a high sense of urgency about their symptoms (OR 1.69, 95% CI 1.09 to 2.62). Knowledge of stroke symptoms was not associated with increased EMS use (OR 0.63, 95% CI 0.40 to 0.98). Patients were more likely to use EMS if someone other than the patient first identified that there was a problem (OR 2.35, 95% CI 1.61 to 3.44). Conclusions Interventions aimed at increasing EMS use among stroke patients need to stress the urgency of stroke symptoms and the importance of calling 911 and need to be broad-based, encompassing not only those at high risk for stroke but also their friends and family.

Construction of a Multisite DataLink Using Electronic Health Records for the Identification, Surveillance, Prevention, and Management of Diabetes Mellitus: The SUPREME-DM Project

Introduction Electronic health record (EHR) data enhance opportunities for conducting surveillance of diabetes. The objective of this study was to identify the number of people with diabetes from a diabetes DataLink developed as part of the SUPREME-DM (SUrveillance, PREvention, and ManagEment of Diabetes Mellitus) project, a consortium of 11 integrated health systems that use comprehensive EHR data for research. Methods We identified all members of 11 health care systems who had any enrollment from January 2005 through December 2009. For these members, we searched inpatient and outpatient diagnosis codes, laboratory test results, and pharmaceutical dispensings from January 2000 through December 2009 to create indicator variables that could potentially identify a person with diabetes. Using this information, we estimated the number of people with diabetes and among them, the number of incident cases, defined as indication of diabetes after at least 2 years of continuous health system enrollment. Results The 11 health systems contributed 15,765,529 unique members, of whom 1,085,947 (6.9%) met 1 or more study criteria for diabetes. The nonstandardized proportion meeting study criteria for diabetes ranged from 4.2% to 12.4% across sites. Most members with diabetes (88%) met multiple criteria. Of the members with diabetes, 428,349 (39.4%) were incident cases. Conclusion The SUPREME-DM DataLink is a unique resource that provides an opportunity to conduct comparative effectiveness research, epidemiologic surveillance including longitudinal analyses, and population-based care management studies of people with diabetes. It also provides a useful data source for pragmatic clinical trials of prevention or treatment interventions.

Characteristics of Patients with Primary Non-adherence to Medications for Hypertension, Diabetes, and Lipid Disorders

BACKGROUNDInformation comparing characteristics of patients who do and do not pick up their prescriptions is sparse, in part because adherence measured using pharmacy claims databases does not include information on patients who never pick up their first prescription, that is, patients with primary non-adherence. Electronic health record medication order entry enhances the potential to identify patients with primary non-adherence, and in organizations with medication order entry and pharmacy information systems, orders can be linked to dispensings to identify primarily non-adherent patients.OBJECTIVEThis study aims to use database information from an integrated system to compare patient, prescriber, and payment characteristics of patients with primary non-adherence and patients with ongoing dispensings of newly initiated medications for hypertension, diabetes, and/or hyperlipidemia.DESIGNThis is a retrospective observational cohort study.PARTICIPANTS (OR PATIENTS OR SUBJECTS)Participants of this study include patients with a newly initiated order for an antihypertensive, antidiabetic, and/or antihyperlipidemic within an 18-month period.MAIN MEASURESProportion of patients with primary non-adherence overall and by therapeutic class subgroup. Multivariable logistic regression modeling was used to investigate characteristics associated with primary non-adherence relative to ongoing dispensings.KEY RESULTSThe proportion of primarily non-adherent patients varied by therapeutic class, including 7% of patients ordered an antihypertensive, 11% ordered an antidiabetic, 13% ordered an antihyperlipidemic, and 5% ordered medications from more than one of these therapeutic classes within the study period. Characteristics of patients with primary non-adherence varied across therapeutic classes, but these characteristics had poor ability to explain or predict primary non-adherence (models c-statistics = 0.61–0.63).CONCLUSIONSPrimary non-adherence varies by therapeutic class. Healthcare delivery systems should pursue linking medication orders with dispensings to identify primarily non-adherent patients. We encourage conduct of research to determine interventions successful at decreasing primary non-adherence, as characteristics available from databases provide little assistance in predicting primary non-adherence.

Calling emergency medical services for acute stroke: a study of 9-1-1 tapes.

Objective. To obtain a better understanding of how stroke events are communicated to 9-1-1 telecommunicators, andhow telecommunicators andemergency medical services (EMS) personnel respond to such calls. Methods. The authors identified 104 patients with a hospital discharge diagnosis of stroke or transient ischemic attack who were transported to hospital by ambulance in two North Carolina counties during 1999 and2000. Ambulance call reports were abstracted andlinked to 9-1-1 call center audiotapes, which were transcribed andverified. Results. Of the 104 calls, 44 were made by medical personnel, 38 by a family member, eight by a bystander or neighbor, five undetermined, andthree by other nonmedical personnel. In only six instances (6%) was the call placed by the patient. The most common symptoms reported were altered mental status (40%), trouble walking (32%), impaired speech (27%), andabnormal breathing (27%). Although the word “stroke” was often used (45%), 9-1-1 telecommunicators classified the calls as a stroke in only 31% of cases. However, in the majority of cases (79%), paramedics were dispatched at the highest priority. The median time from dispatch of EMS to patient arrival at the hospital was 41 minutes, approximately half of which was spent at the scene. Conclusion. Although typical stroke symptoms are commonly described, calls are often not classified as “strokes” by telecommunicators. Nevertheless, because of the symptoms reported during the calls, the majority of cases are treated as high priority by telecommunicators.

Trends in Diabetes Incidence Among 7 Million Insured Adults, 2006–2011 The SUPREME-DM Project

An observational cohort analysis was conducted within the Surveillance, Prevention, and Management of Diabetes Mellitus (SUPREME-DM) DataLink, a consortium of 11 integrated health-care delivery systems with electronic health records in 10 US states. Among nearly 7 million adults aged 20 years or older, we estimated annual diabetes incidence per 1,000 persons overall and by age, sex, race/ethnicity, and body mass index. We identified 289,050 incident cases of diabetes. Age- and sex-adjusted population incidence was stable between 2006 and 2010, ranging from 10.3 per 1,000 adults (95% confidence interval (CI): 9.8, 10.7) to 11.3 per 1,000 adults (95% CI: 11.0, 11.7). Adjusted incidence was significantly higher in 2011 (11.5, 95% CI: 10.9, 12.0) than in the 2 years with the lowest incidence. A similar pattern was observed in most prespecified subgroups, but only the differences for persons who were not white were significant. In 2006, 56% of incident cases had a glycated hemoglobin (hemoglobin A1c) test as one of the pair of events identifying diabetes. By 2011, that number was 74%. In conclusion, overall diabetes incidence in this population did not significantly increase between 2006 and 2010, but increases in hemoglobin A1c testing may have contributed to rising diabetes incidence among nonwhites in 2011.

Severe Hypoglycemia Requiring Medical Intervention in a Large Cohort of Adults With Diabetes Receiving Care in U.S. Integrated Health Care Delivery Systems: 2005–2011

OBJECTIVE Appropriate glycemic control is fundamental to diabetes care, but aggressive glucose targets and intensive therapy may unintentionally increase episodes of hypoglycemia. We quantified the burden of severe hypoglycemia requiring medical intervention in a well-defined population of insured individuals with diabetes receiving care in integrated health care delivery systems across the U.S. RESEARCH DESIGN AND METHODS This observational cohort study included 917,440 adults with diabetes receiving care during 2005 to 2011 at participating SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) network sites. Severe hypoglycemia rates were based on any occurrence of hypoglycemia-related ICD-9 codes from emergency department or inpatient medical encounters and reported overall and by age, sex, comorbidity status, antecedent A1C level, and medication use. RESULTS Annual rates of severe hypoglycemia ranged from 1.4 to 1.6 events per 100 person-years. Rates of severe hypoglycemia were higher among those with older age, chronic kidney disease, congestive heart failure, cardiovascular disease, depression, and higher A1C levels, and in users of insulin, insulin secretagogues, or β-blockers (P < 0.001 for all). Changes in severe hypoglycemia occurrence over time were not clinically significant in the cohort as a whole but were observed in subgroups of individuals with chronic kidney disease, congestive heart failure, and cardiovascular disease. CONCLUSIONS Risk of severe hypoglycemia in clinical settings is considerably higher in identifiable patient subgroups than in randomized controlled trials. Strategies that reduce the risk of hypoglycemia in high-risk patients are needed.

Importance of Including Early Nonadherence in Estimations of Medication Adherence

Background Many medication adherence metrics are based on refill rates determined from pharmacy claims databases. However, these methods do not incorporate assessment of nonadherence to new prescriptions when those prescriptions are never dispensed (primary nonadherence), or dispensed only once (early nonpersistence). As a result, published studies may overestimate adherence, but the extent of overestimation posed by not considering patients with primary nonadherence and early nonpersistence has not been assessed. Objective: To estimate the magnitude of misestimation in adherence estimates that results from not including patients with primary nonadherence and early nonpersistence, Methods: We conducted a retrospective cohort study of 15,417 patients enrolled in an integrated health care delivery system who were newly prescribed an antihypertensive, antidiabetic, or antihyperlipidemic medication. We linked prescription orders to medication dispensings. Based on dispensing and refill rates, we stratified patients into primary nonadherent, early nonpersistent, and ongoing dispensings groups. Adherence was estimated using the proportion of days covered (PDC). Standardized observation periods were applied across all groups. Results: A total of 1142 (7.4%) patients were primarily nonadherent, 3356 (21.8%) demonstrated early nonpersistence, and 10,919 (70.8%) patients received ongoing dispensings, with a mean PDC of 84%. Not including primarily nonadherent and early nonpersistent patients in calculations resulted in adherence estimates overestimated by 9-18%. Conclusions: When medication adherence is estimated from pharmacy claims databases, adherence estimates are substantially inflated because primarily nonadherent and early nonpersistent patients are not included in the estimations. An implication of this incorrect estimation is potential distortion of the true relationship between medication adherence and clinical outcomes.

Preventable Major Cardiovascular Events Associated With Uncontrolled Glucose, Blood Pressure, and Lipids and Active Smoking in Adults With Diabetes With and Without Cardiovascular Disease: A Contemporary Analysis

OBJECTIVE The objective of this study was to assess the incidence of major cardiovascular (CV) hospitalization events and all-cause deaths among adults with diabetes with or without CV disease (CVD) associated with inadequately controlled glycated hemoglobin (A1C), high LDL cholesterol (LDL-C), high blood pressure (BP), and current smoking. RESEARCH DESIGN AND METHODS Study subjects included 859,617 adults with diabetes enrolled for more than 6 months during 2005–2011 in a network of 11 U.S. integrated health care organizations. Inadequate risk factor control was classified as LDL-C ≥100 mg/dL, A1C ≥7% (53 mmol/mol), BP ≥140/90 mm Hg, or smoking. Major CV events were based on primary hospital discharge diagnoses for myocardial infarction (MI) and acute coronary syndrome (ACS), stroke, or heart failure (HF). Five-year incidence rates, rate ratios, and average attributable fractions were estimated using multivariable Poisson regression models. RESULTS Mean (SD) age at baseline was 59 (14) years; 48% of subjects were female, 45% were white, and 31% had CVD. Mean follow-up was 59 months. Event rates per 100 person-years for adults with diabetes and CVD versus those without CVD were 6.0 vs. 1.7 for MI/ACS, 5.3 vs. 1.5 for stroke, 8.4 vs. 1.2 for HF, 18.1 vs. 40 for all CV events, and 23.5 vs. 5.0 for all-cause mortality. The percentages of CV events and deaths associated with inadequate risk factor control were 11% and 3%, respectively, for those with CVD and 34% and 7%, respectively, for those without CVD. CONCLUSIONS Additional attention to traditional CV risk factors could yield further substantive reductions in CV events and mortality in adults with diabetes.

A comparison of emergency medical services times for stroke and myocardial infarction

Objective. Since stroke symptoms are often vague, and acute therapies for stroke are more recently available, it has been hypothesized that stroke patients may not be treated with the same urgency as myocardial infarction (MI) patients by emergency medical services (EMS). To examine this hypothesis, EMS transport times were examined for both stroke and MI patients who used a paramedic-level, county-based EMS system for transportation to a single hospital during 1999. Methods. Patients were first identified by their hospital discharge diagnosis as stroke (ICD-9 430–436, n = 50) or MI (ICD-9 410, n = 55). Trip sheets with corresponding transport times were retrospectively obtained from the 911 center. A separate analysis was performed on patients identified by dispatchers with a chief complaint of stroke (n = 85) or MI (n = 372). Results. Comparing stroke and MI patients identified by ICD-9 codes, mean EMS transport times in minutes did not meaningfully differ with respect to dispatch to scene arrival time (8.3 vs 8.9, p = 0.61), scene time (19.5 vs 21.4, p = 0.23), and transport time (13.7 vs 16.2, p = 0.10). Mean total call times in minutes from dispatch to hospital arrival were similar between stroke and MI patients (41.5 vs 46.4, p = 0.22). Results were similar when comparing patients identified by dispatchers with a chief complaint indicative of stroke or MI. Conclusion. In this single county, EMS response times were not different between stroke and MI patients. Replication in other EMS settings is needed to confirm these findings.