Sander W.M. Keet

Reproducibility of non-standardised autonomic function testing in the pre-operative assessment screening clinic*

By convention, autonomic function tests are undertaken under standard test conditions that limit their implementation during routine pre‐operative assessment. We therefore evaluated the comparability of autonomic function tests under both non‐standardised and standardised test conditions in 20 healthy male subjects. Autonomic function was assessed using an ECG monitor and a continuous non‐invasive blood pressure measurement device. Under non‐standardised conditions, intraclass correlation for heart rate variability analysis was good for the low and high frequency bands (0.87; 95% CI 0.58–0.96 and 0.83; 95% CI 0.56–0.94, respectively), but moderate (0.65; 95% CI 0.14–0.86) for the very low frequency band; reproducibility was high for the expiration/inspiration ratio (0.89; 95% CI 0.71–0.96), Valsalva ratio (0.76; 95% CI 0.37–0.91) and handgrip test (0.76; 95% CI 0.35–0.91) (all p < 0.05) but was low for the response to quick standing. Reproducibility under standardised conditions was comparable to the above values. We demonstrated that reproducibility for most autonomic tests under non‐standardised conditions is acceptable and suggest that implementation of these tests during pre‐operative assessment may be feasible.

Level of agreement between heart rate variability and pulse rate variability in healthy individuals.

Background and objective According to international standards, autonomic function is assessed by heart rate variability (HRV) calculated from R–R intervals obtained with an electrocardiogram (ECG). However, intra-operative movement artefacts and electrical interference may complicate R-wave detection. Pulse rate variability (PRV) derived from continuous blood pressure measurements may provide a feasible alternative for HRV. We aimed to investigate the level of agreement between PRV and traditional HRV using a novel beat-to-beat non-invasive blood pressure monitoring device. Methods In this prospective observational study, R–R intervals and non-invasive blood pressure waveforms were recorded simultaneously from 20 healthy male individuals at rest. HRV and PRV were analysed offline by spectral analysis, which divides the signal into its composing frequencies. Spearmans correlation coefficient, intra-class correlation coefficients and Bland–Altman analysis were used to study the level of agreement between HRV and PRV. Results The correlation coefficient between HRV and PRV was 0.99 (P < 0.001). Level of agreement was excellent with a mean difference of 1% in the very low frequency and low-frequency band and 14% in the high-frequency band. Reliability of both HRV and PRV was moderate to high. Conclusion Our data show that PRV derived from non-invasive blood pressure waveforms corresponds well with traditional HRV derived from ECG. These results indicate that under standard conditions, blood pressure waveforms may replace HRV in healthy individuals and that the use of PRV in the peri-operative setting should be further evaluated.

The impact of autonomic dysfunction on peri-operative cardiovascular complications

Cardiovascular autonomic neuropathy is frequently observed in patients with diabetes mellitus. As anaesthesia has a marked effect on peri‐operative autonomic function, the interplay between diabetic neuropathy and anaesthesia may result in unexpected haemodynamic instability during surgery. The objective of this literature review was to examine the association of cardiovascular autonomic neuropathy with peri‐operative cardiovascular complications. We searched PubMed for articles with search elements of autonomic dysfunction [MeSH] AND anaesthesia [MeSH] AND complications [MeSH]. Depending on the type of anaesthesia, the presence of cardiovascular autonomic neuropathy in surgical patients can markedly affect peri‐operative haemodynamics and postoperative recovery. Pre‐operative testing of the extent of autonomic dysfunction in particular populations, like diabetics, may contribute to a reduction in haemodynamic instability and cardiovascular complications. Non‐invasive diagnostic methods assessing autonomic function may be an important tool during pre‐operative risk assessment.

Cardiovascular autonomic function testing under non-standardised and standardised conditions in cardiovascular patients with type-2 diabetes mellitus†

Autonomic function tests require standardised test conditions. We compared testing under non‐standardised and standardised conditions and investigated the agreement between heart and pulse rate variability in 30 subjects with diabetes mellitus. Deep breathing, Valsalva manoeuvre and quick standing tests showed non‐standardised reproducibility intraclass correlations (95% CI) of 0.96 (0.82–0.99), 0.96 (0.81–0.99) and 0.75 (−0.98 to 0.94), respectively. Intraclass correlations for sustained handgrip and quick standing were poor. Heart and pulse rate variability showed high‐frequency band intraclass correlations (95% CI) of 0.65 (−0.07 to 0.89) and 0.47 (−0.88 to 0.85) for the very low‐frequency band, respectively, 0.68 (0.00−0.90) and 0.70 (−0.09 to 0.91) for the low‐frequency band, and 0.86 (0.57−0.95) and 0.82 (0.39−0.95) for the high‐frequency band. Reproducibility under standardised conditions was comparable. The mean difference (95% limits of agreement) between heart and pulse rate variability was 0.99 (0.80−1.22) for very low frequency, 1.03 (0.88−1.21) for low frequency and 1.35 (0.84−2.16) for high frequency, with a Spearmans correlation coefficient of 1.00, 0.99 and 0.98, respectively. We demonstrated a high agreement between heart and pulse rate variability and acceptable reproducibility with most autonomic function tests, heart and pulse rate variability.

Short-term heart rate variability in healthy adults.

Introduction: Standardised heart rate variability (HRV) analysis is used as a diagnostic and prognostic tool for cardiovascular as well as perioperative risk stratification. The lack of reference values for young and middle-aged subjects however limits implementation of HRV analysis in the clinical setting. With this study we aimed to define reference values, and to define the influences of gender and age for short-term heart rate variability in the young and middle-aged population. Methods: Ninety-three healthy subjects (18-50 years) were studied during standard test conditions. Short-term HRV was assessed using an ECG monitor. Data represent mean ±SD or median with 10th and 90th centiles. To determine gender and age differences Student’s t-test or Mann-Whitney U-test were used. Pearson and Spearman’s rank correlation coefficients were used to determine correlations between age and HRV parameters Results: All parameters for heart rate variability, except for the LF/ (LF+HF), showed significantly higher values for men then for woman (mean normal-to-normal (1014 ±183 vs 896 ±121 ms), standard deviation of normal-to-normal (65.3 (36.6-97.6) vs 49.4 (29.9-91.3) ms), root mean square of successive differences between normal-to-normal (55.8 (24.2-98.7) vs 41.5 (21.5-87.0) ms), very low frequency (1282 (438-4390) vs 785 (259-2090) ms2), low frequency (1025 (361-2983) vs 487 (206-1365) ms2), high frequency (1311 (405-3491) vs 763 (203-3981) ms2) and total spectral power, respectively). Age showed no influence on the baseline characteristics and HRV parameters and showed no significant correlations in a range between -0.21 and 0.27. Conclusions: This study provided reference values for short-term heart rate variability in healthy adults, which may support further implementation of this tool in patient risk stratification.

Health risk factors in the anesthesia population

STUDY OBJECTIVE We investigated the prevalence of lifestyle risk factors in patients admitted to our preoperative assessment outpatient clinic, and compared patient self-reports and anesthetist reports of health risk factors to evaluate the patient self-image of preoperative health status. DESIGN Cross-sectional survey. SETTING The study was performed in an academic teaching hospital in Amsterdam, the Netherlands, during 3 consecutive months at the preoperative screening clinic. PATIENTS A total of 1227 adult patients scheduled for surgery were screened, and 1111 were included (patients being excluded where data were incomplete). INTERVENTIONS AND MEASUREMENTS Before health risk screening by an anesthetist, patients filled out a lifestyle risk factor questionnaire including overweight, hypertension, diabetes mellitus, smoking, physical activity, and alcohol use. These were compared with risk factors stated in the preoperative assessment report of the anesthetist. MAIN RESULTS The study population was aged 51 ± 17 years with a body mass index of 25.6 ± 4.7 kg/m(2). The most frequent lifestyle risk factors reported by the anesthetist were overweight and obesity (47.5%), smoking (25.3%), and hypertension (23.7%). The prevalence of no, 1, or 2 lifestyle risk factors in the preoperative assessment outpatient clinic population was, respectively, 30.1%, 35.6%, and 18.5% reported by the anesthetist and 36.4%, 36.7%, and 18.6% reported by the patients. Patients with more lifestyle risk factors were older with a higher body mass index and American Society of Anesthesiologists classification. Differences in reporting of lifestyle risk factors between patients and anesthetist occurred especially with overweight (26.5% vs 47.5%). CONCLUSIONS The prevalence of lifestyle risk factors in perioperative patients is high, and differences in reporting between patients and anesthetists may suggest that patients are unaware of or ignore their unhealthy state. Further studies are warranted to investigate the association between the lifestyle risk factors and outcome in the anesthesiology setting.

Acute kidney injury: Finding a needle in a haystack

An 80-year-old woman with a history of venous thromboembolism and ischemic stroke was admitted with headache and confusion. Examination revealed fever and an alteredmental status, butwas otherwise unremarkable. Laboratory tests showed normal electrolytes and kidney function and no signs of inflammation. Urine analysis, chest X-ray and imaging of the brain with CT scan showed no explanation for the fever or confusion. Intravenous treatment with cefuroxime 1500 mg and gentamycin 350 mg was immediately started at admission. Cerebrospinal fluid analysis showed a slightly elevated leukocyte

Can nonstandardised, simplified autonomic function tests be used for risk profiling in the anaesthesia population?

Local as well as general anaesthesia have marked effects on autonomic function, which may lead to unexpected haemodynamic instability during surgery. Moreover, in patients with preexisting autonomic dysfunction (e.g. because of health risk factors and/or diseases such as diabetes mellitus or heart failure) anaesthesia is a prominent risk factor for perioperative complications. This letter discusses the implementation of simplified cardiovascular autonomic function tests in preoperative patient risk assessment to identify patients at risk of intraoperative hypotension and periand postoperative cardiovascular complications.