Finger volume pulse waveforms facilitate reliable assessment of heart rate variability, but not blood pressure variability or baroreflex function.

BACKGROUND: We sought to determine whether heart rate variability (HRV), blood pressure (BP) variability, and baroreceptor-heart rate reflex sensitivity can be reliably assessed using finger volume pulse waveforms obtained from the commercially available EndoPAT device. METHODS: Non-invasive BP (Finometer Pro as a non-invasive standard) and finger volume (EndoPAT) waveforms were recorded in 65 adults (37 ± 14 years; 60% female) and systolic BP and heart rate (HR) time series were derived after calibrating the EndoPAT signal based on systolic and diastolic BP values obtained by a sphygomomanometer. Transfer function analyses were performed to test for coherence between systolic BP and HR time series derived from the Finometer and EndoPAT devices. Time-domain HRV parameters, frequency domain HR and systolic BP variability parameters, and baroreflex sensitivity (sequence technique) were computed from Finometer- and EndoPAT-derived time series and intraclass correlation coefficients (ICC) were calculated. RESULTS: Squared coherence between systolic BP time series derived from the Finometer and EndoPAT devices was low, suggesting poor correlation. In contrast, squared coherence between HR time series derived from the two devices was excellent [High Frequency (HF) = 0.80, Low Frequency (LF) = 0.81], with gain values close to 1.0. ICC values for time- and frequency-domain HRV parameters were excellent (>0.9 except for relative HF HRV, which was 0.77), while ICC values for frequency-domain BP variability parameters and baroreceptor-HR reflex sensitivity were low. CONCLUSIONS: Finger volume pulse waveforms can be used to reliably assess both time-domain and frequency-domain HR variability. However, frequency domain BP variability parameters cannot be reliably assessed from finger volume pulse waveforms using the simple calibration technique used in this study.

Effects of antipsychotic drugs on cardiovascular variability in participants with bipolar disorder.

OBJECTIVE: The risk for cardiovascular diseases is elevated in persons with bipolar disorder. However, it remains unknown how much of this excess risk is secondary to pharmacologic treatment. We tested the hypothesis that current and cumulative antipsychotic drug exposure is associated with increased cardiovascular risk as indicated by lower heart rate variability (HRV) and increased blood pressure variability (BPV). METHODS: Fifty-five individuals with bipolar disorder (33 ± 7 years; 67% female) underwent noninvasive electrocardiogram assessment of time-domain and frequency-domain HRV, as well as BPV analysis. Medication histories were obtained through systematic review of pharmacy records for the past 5 years. RESULTS: Current antipsychotic exposure was associated with lower standard deviation of NN intervals. Second-generation antipsychotics were associated with lower standard deviation of NN intervals and root mean square of successive differences. There was no significant relationship between 5-year antipsychotic exposure and HRV in subjects with bipolar disorder. Exploratory analysis revealed a possible link between selective serotonin reuptake inhibitor exposure and increased low-frequency spectral HRV. CONCLUSIONS: Current antipsychotic use (particularly second-generation antipsychotics with high affinities for the D2S receptor) is associated with reduced autonomic-mediated variability of the HR. The absence of an association with cumulative exposure suggests that the effects are acute in onset and may therefore relate more to altered autonomic function than structural cardiovascular abnormalities. Future studies should prospectively examine effects of these antipsychotics on autonomic function.

Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration.

BACKGROUND: HealthImpact is a novel algorithm using administrative health care data to stratify patients according to risk for incident diabetes. OBJECTIVES: To (a) independently assess the predictive validity of HealthImpact and (b) explore its utility in diabetes screening within a nationally integrated health care system. METHODS: National Veterans Health Administration data were used to create 2 cohorts. The replication cohort included patients without diagnosed diabetes as of October 1, 2012, to determine if HealthImpact scores were significantly associated with diabetes (type 1 or 2) incidence within the subsequent 3 years. The utility cohort included patients without diagnosed diabetes as of August 1, 2015, and assessed diabetes screening rates in the 2 years surrounding this index date, stratified by HealthImpact scores. RESULTS: The 3-year incidence of diabetes in the replication cohort (n = 3,287,240) was 9.1%. Of 100,617 (3.1%) patients with HealthImpact scores > 90, 30,028 developed diabetes, yielding a positive predictive value of 29.8%. These patients accounted for 9.9% of all incident diabetes cases (sensitivity). Sensitivity and negative predictive value improved with descending HealthImpact threshold scores (e.g., > 75, > 50), whereas specificity and positive predictive value declined. Of 3,499,406 patients in the utility cohort, 85.3% received either a blood glucose or hemoglobin A1c test during the 2-year observation period. Among 101,355 patients with a HealthImpact score > 90, nearly all (98.3%) were screened, and 86.3% had an A1c test. CONCLUSIONS: Our independent analysis corroborates the validity of HealthImpact in stratifying patients according to diabetes risk. However, its practical utility to enhance diabetes screening in a real-world clinical environment will be strongly dependent on the pattern and frequency of existing screening practices. DISCLOSURES: This work was supported by the Iowa City VA Health Care System and by the Department of Veterans Affairs, Office of Research and Development, Health Services Research and Development Service (Lund, CIN 13-412). The authors have no conflicts of interest. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the U.S. government.