Development of population research at Mayo Clinic

Risk of Autoimmune Disease in Research-Identified Cases of Autism Spectrum Disorder: A Longitudinal, Population-Based Birth Cohort Study

OBJECTIVE

Determine the risk of autoimmune disease in research-identified cases of autism spectrum disorder (ASD) compared with referents using a longitudinal, population-based birth cohort.

METHODS

ASD incident cases were identified from a population-based birth cohort of 31,220 individuals. Inclusive ASD definition based on DSM-IV-TR autistic disorder, Asperger syndrome, and pervasive developmental disorder, not otherwise specified, was used to determine ASD cases. For each ASD case, 2 age- and sex-matched referents without ASD were identified. Diagnosis codes assigned between birth and December 2017 were electronically obtained. Individuals were classified as having an autoimmune disorder if they had at least 2 diagnosis codes more than 30 days apart. Cox proportional hazards models were fit to estimate the hazard ratio (HR) between ASD status and autoimmune disorder.

RESULTS

Of 1014 ASD cases, 747 (73.7%) were male. Fifty ASD cases and 59 of the 1:2 matched referents were diagnosed with first autoimmune disorder at the median age of 14 and 17.1 years, respectively. ASD cases had increased risk of autoimmune disease compared with matched referents (HR 1.74; 95% confidence interval [CI], 1.21-2.52). The increased risk was statistically significant among male patients (HR 2.01; 95% CI, 1.26-3.21) but not among the smaller number of female subjects (HR 1.38; 95% CI, 0.76-2.50).

CONCLUSION

This study provides evidence from a longitudinal, population-based birth cohort for co-occurrence of ASD and autoimmune disorders. Thus, children with ASD should be monitored for symptoms of autoimmune disease and appropriate workup initiated.

Performance of the ACC/AHA Pooled Cohort Cardiovascular Risk Equations in Clinical Practice

BACKGROUND

The performance of the American College of Cardiology/American Heart Association pooled cohort equation (PCE) for atherosclerotic cardiovascular disease (ASCVD) in real-world clinical practice has not been evaluated extensively.

OBJECTIVES

The goal of this study was to test the performance of PCE to predict ASCVD risk in the community, and determine if including individuals with values outside the PCE range (ie, age, blood pressure, cholesterol) or statin therapy initiation over follow-up would significantly affect PCE predictive capabilities.

METHODS

The PCE was validated in a community-based cohort of consecutive patients who sought primary care in Olmsted County, Minnesota, between 1997 and 2000, followed-up through 2016. Inclusion criteria were similar to those of PCE derivation. Patient information was ascertained by using the record linkage system of the Rochester Epidemiology Project. ASCVD events (nonfatal and fatal myocardial infarction and ischemic stroke) were validated in duplicate. Calculated and observed ASCVD risk and c-statistics were compared across predefined groups.

RESULTS

This study included 30,042 adults, with a mean age of 48.5 ± 12.2 years; 46% were male. Median follow-up was 16.5 years, truncated at 10 years for this analysis. Mean ASCVD risk was 5.6% ± 8.73%. There were 1,555 ASCVD events (5.2%). The PCE revealed good performance overall (c-statistic 0.78) and in sex and race subgroups; it was highest among non-White female subjects (c-statistic 0.81) and lowest in White male subjects (c-statistic 0.77). Out-of-range values and initiation of statin medication did not affect model performance.

CONCLUSIONS

The PCE performed well in a community cohort representing real-world clinical practice. Values outside PCE ranges and initiation of statin medication did not affect performance. These results have implications for the applicability of current strategies for the prevention of ASCVD.

Association of Bipolar Disorder With Major Adverse Cardiovascular Events: A Population-Based Historical Cohort Study

OBJECTIVE

This study aimed to assess the association of bipolar disorder (BD) with risk of major adverse cardiac events (MACEs) after adjusting for established cardiovascular disease (CVD) risk factors.

METHODS

We conducted a population-based historical cohort study using the Rochester Epidemiology Project. Patients older than 30 years with a clinical encounter from 1998 to 2000 with no prior MACE, atrial fibrillation, or heart failure were followed up through March 1, 2016. BD diagnosis was validated by chart review. Cox proportional hazards regression models were adjusted for established CVD risk factors, alcohol use disorder, other substance use disorders (SUDs), and major depressive disorder (MDD).

RESULTS

The cohort included 288 individuals with BD (0.81%) and 35,326 individuals without BD as the reference group (Ref). Median (interquartile range) follow-up was 16.5 (14.6-17.5) years. A total of 5636 MACE events occurred (BD, 59; Ref, 5577). Survival analysis showed an association between BD and MACE (median event-free-survival rates: BD, 0.80; Ref, 0.86; log-rank p = .018). Multivariate regression adjusting for age and sex also yielded an association between BD and MACE (hazard ratio [HR] = 1.93; 95% confidence interval [CI] = 1.43-2.52; p < .001). The association remained significant after further adjusting for smoking, diabetes mellitus, hypertension, high-density lipoprotein cholesterol, and body mass index (HR = 1.66; 95% CI = 1.17-2.28; p = .006), and for alcohol use disorder, SUD, and MDD (HR = 1.56; 95% CI = 1.09-2.14; p = .010).

CONCLUSIONS

In this study, BD was associated with an increased risk of MACE, which persisted after adjusting for established CVD risk factors, SUDs, and MDD. These results suggest that BD is an independent risk factor for major clinical cardiac disease outcomes.

The 12-lead electrocardiogram as a biomarker of biological age

Background

We have demonstrated that a neural network is able to predict a person's age from the electrocardiogram (ECG) [artificial intelligence (AI) ECG age]. However, some discrepancies were observed between ECG-derived and chronological ages. We assessed whether the difference between AI ECG and chronological age (Age-Gap) represents biological ageing and predicts long-term outcomes.

Methods and results

We previously developed a convolutional neural network to predict chronological age from ECGs. In this study, we used the network to analyse standard digital 12-lead ECGs in a cohort of 25 144 subjects ≥30 years who had primary care outpatient visits from 1997 to 2003. Subjects with coronary artery disease, stroke, and atrial fibrillation were excluded. We tested whether Age-Gap was correlated with total and cardiovascular mortality. Of 25 144 subjects tested (54% females, 95% Caucasian) followed for 12.4 ± 5.3 years, the mean chronological age was 53.7 ± 11.6 years and ECG-derived age was 54.6 ± 11 years (R ² = 0.79, P < 0.0001). The mean Age-Gap was small at 0.88 ± 7.4 years. Compared to those whose ECG-derived age was within 1 standard deviation (SD) of their chronological age, patients with Age-Gap ≥1 SD had higher all-cause and cardiovascular disease (CVD) mortality. Conversely, subjects whose Age-Gap was ≤1 SD had lower all-cause and CVD mortality. Results were unchanged after adjusting for CVD risk factors and other survival influencing factors.

Conclusion

The difference between AI ECG and chronological age is an independent predictor of all-cause and cardiovascular mortality. Discrepancies between these possibly reflect disease independent biological ageing.

External validation of the Ottawa subarachnoid hemorrhage clinical decision rule in patients with acute headache

We aim to externally validate the Ottawa subarachnoid hemorrhage (OSAH) clinical decision rule. This rule identifies patients with acute nontraumatic headache who require further investigation. We conducted a medical record review of all patients presenting to the emergency department (ED) with headache from January 2011 to November 2013. Per the OSAH rule, patients with any of the following predictors require further investigation: age 40 years or older, neck pain, stiffness or limited flexion, loss of consciousness, onset during exertion, or thunderclap. The rule was applied following the OSAH rule criteria. Patients were followed up for repeat visits within 7 days of initial presentation. Data were electronically harvested from the electronic medical record and manually abstracted from individual patient charts using a standardized data abstraction form. Calibration between trained reviewers was performed periodically. A total of 5034 ED visits with acute headache were reviewed for eligibility. There were 1521 visits that met exclusion criteria, and 3059 had headache of gradual onset or time to maximal intensity greater than or equal to 1 hour. The rule was applied to 454 patients (9.0%). There were 9 cases of subarachnoid hemorrhage (SAH), yielding an incidence of 2.0% (95% confidence interval [CI], 1.0%-3.9%) in the eligible cohort. The sensitivity for SAH was 100% (95% CI, 62.9%-100%); specificity, 7.6% (95% CI, 5.4%-10.6%); positive predictive value, 2.1% (95% CI 1.0%-4.2%); and negative predictive value, 100% (95% CI, 87.4%-100%). The OSAH rule was 100% sensitive for SAH in the eligible cohort. However, its low specificity and applicability to only a minority of ED patients with headache (9%) reduce its potential impact on practice.

Resting heart rate in first year survivors of myocardial infarction and long-term mortality: a community study

OBJECTIVE

To evaluate the long-term prognostic effect of resting heart rate (HR) at index myocardial infarction (MI) and during the first year after MI among 1-year survivors.

PATIENTS AND METHODS

The community-based cohort consisted of 1571 patients hospitalized with an incident MI from January 1, 1983, through December 31, 2007, in Olmsted County, Minnesota, who were in sinus rhythm at index MI and had HR measurements on electrocardiography at index and during the first year after MI. Outcomes were all-cause and cardiovascular deaths.

RESULTS

During a median follow-up of 7.0 years, 627 deaths and 311 cardiovascular deaths occurred. Using patients with HRs of 60/min or less as the referent, this study found that long-term all-cause mortality risk increased progressively with increasing HR at index (hazard ratio, 1.62; 95% CI, 1.25-2.09) and even more with increasing HR during the first year after MI (hazard ratio, 2.16; 95% CI, 1.64-2.84) for patients with HRs greater than 90/min, adjusting for clinical characteristics and β-blocker use. Similar results were observed for cardiovascular mortality (adjusted hazard ratio, 1.66; 95% CI, 1.14-2.42; and adjusted hazard ratio, 1.93; 95% CI, 1.27-2.94; for HR at index and within 1 year after MI, respectively).

CONCLUSION

These data from a large MI community cohort indicate that HR is a strong predictor of long-term all-cause and cardiovascular mortality not only at initial presentation of MI but also during the first year of follow-up.