Sensory block duration after spinal anaesthesia supplemented with intravenous dexamethasone: a randomised controlled double-blinded trial.

BACKGROUND: Intravenous dexamethasone prolongs duration of analgesia or sensory block after injection of local anaesthetics close to peripheral nerves by an average of 8 h. Uncertainty remains on the potential increase in the duration of sensory block after spinal anaesthesia. The objective of this randomised controlled double-blinded trial was to investigate whether dexamethasone i.v. prolongs the sensory block of spinal anaesthesia with bupivacaine when compared with a control group. METHODS: Of 50 patients undergoing lower limb osteoarticular surgery under spinal anaesthesia with isobaric bupivacaine 15 mg i.t. with morphine 100 µg i.t. were randomised to receive either dexamethasone 0.15 mg kg-1 i.v. or normal saline 3 ml i.v. The primary outcome was duration of sensory block defined as the time elapsed between injection of the local anaesthetic in the intrathecal space and the regression of sensory block by two dermatomes compared with the highest dermatome blocked. Secondary outcomes included intravenous morphine consumption, pain scores at rest and on movement, postoperative nausea and vomiting, and blood glucose at 2, 24, and 48 h. RESULTS: Median duration of sensory block was 135 (105-225) min in the dexamethasone group and 158 (135-240 min) in the control group (P=0.19). Patients in the dexamethasone group received less morphine at 24 h, had significantly less postoperative nausea and vomiting at 2 h and 24 h, and had increased blood glucose at 24 h. Other secondary outcomes were similar between groups. CONCLUSION: Intravenous dexamethasone did not prolong the sensory block of spinal anaesthesia with isobaric bupivacaine. However, it reduced morphine consumption and rate of postoperative nausea and vomiting at 24 h, at the expense of an increased blood glucose. CLINICAL TRIAL REGISTRATION: NCT03527576 (Clinicaltrials.gov).

Accuracy of blood pressure measurement across BMI categories using the OptiBP™ mobile application.

PURPOSE: Obesity is a clear risk factor for hypertension. Blood pressure (BP) measurement in obese patients may be biased by cuff size and upper arm shape which may affect the accuracy of measurements. This study aimed to assess the accuracy of the OptiBP smartphone application for three different body mass index (BMI) categories (normal, overweight and obese). MATERIALS AND METHODS: Participants with a wide range of BP and BMI were recruited at Lausanne University Hospital's hypertension clinic in Switzerland. OptiBP estimated BP by recording an optical signal reflecting light from the participants' fingertips into a smartphone camera. Age, sex and BP distribution were collected to fulfil the AAMI/ESH/ISO universal standards. Both auscultatory BP references and OptiBP BP were measured and compared using the simultaneous opposite arms method, as described in the 81060-2:2018 ISO norm. Subgroup analyses were performed for each BMI category. RESULTS: We analyzed 414 recordings from 95 patients: 34 were overweight and 15 were obese. The OptiBP application had a performance acceptance rate of 82%. The mean and standard deviation (SD) differences between the optical BP estimations and the auscultatory reference rates (criterion 1) were respected in all subgroups: SBP mean value was 2.08 (SD 7.58); 1.32 (6.44); -2.29 (5.62) respectively in obese, overweight and normal weight subgroup. For criterion 2, which investigates the precision errors on an individual level, the threshold for systolic BP in the obese group was slightly above the requirement for this criterion. CONCLUSION: This study demonstrated that the OptiBP application is easily applicable to overweight and obese participants. Differences between the reference measure and the OptiBP estimation were within ISO limits (criterion 1). In obese participants, the SD of mean error was outside criterion 2 limits. Whether auscultatory measurement, due to arm morphology or the OptiBP is associated with increasing bias in obese still needs to be studied.

What is the context? • Hypertension and obesity have a major impact on population health and costs. • Obesity is a chronic disease characterized by abnormal or excessive fat accumulation. • Obesity, in combination with other diseases like hypertension, is a major risk factor for cardiovascular and total death. • In Europe, the obesity rate is 21.5% for men and 24.5% for women. • Hypertension, which continues to increase in the population, is a factor that can be modified when well managed. • Blood pressure measurement by the usual method may be complicated in obese patients due to fat accumulation and the shape of the arm and can lead to measurement errors. In addition, the non-invasive blood pressure measurement can be constraining and uncomfortable.What is new? • Smartphone apps are gradually appearing and allow the measurement of blood pressure without a pressure cuff using photoplethysmography. • OptiBP is a smartphone application that provides an estimate of blood pressure that has been evaluated in the general population. • The objective of this study is to assess whether OptiBP is equally effective in obese and overweight patients.What is the impact? • The use of smartphones to estimate BP in overweight and obese patients may be a solution to the known bias associated with cuff measurement. • The acquisition of more and more data with a larger number of patients will allow the continuous improvement of the application's algorithm.

Photoplethysmography-Based Blood Pressure Monitoring Could Improve Patient Outcome during Anesthesia Induction.

During anesthesia, noncritical patients are routinely monitored via noninvasive cuff-based blood pressure (BP) monitors. Due to the noncontinuous nature of the monitoring, the BP values of the patient remain unavailable between consecutive cuff measurements, carrying the risk of missing rapid and sudden variations in BP. We evaluated the added value of using a photoplethysmography (PPG)-based continuous BP measurement device in addition to the standard cuff-based monitoring in a cohort of 40 patients in comparison with the current approach, in which only intermittent cuff-based measurements are available. When using a three-minute cuff measurement interval, using the PPG-based BP measurement in addition to the cuff-based monitor reduced the error (mean ± SD) of systolic (SBP) and mean (MBP) BP from 2.6 ± 19.6 mmHg and 1.2 ± 13.2 mmHg to 0.5 ± 11.2 mmHg and 0.0 ± 8.1 mmHg, respectively. Error grid analysis was also used to assess the improvement in patient safety. The additional use of the PPG-based BP measurement reduced the amount of data falling into higher risk categories. For SBP, points falling in the significant-, moderate-, and low-risk categories decreased from 1.1%, 8.7%, and 19.3% to 0.0%, 2.3%, and 9.6%, respectively. Similar results were obtained for MBP. These results suggest that using a PPG-based BP monitor-in addition to the standard cuff-based monitor-can improve patient safety during anesthesia induction, with no additional sensor needed.

Smartphone based blood pressure measurement: accuracy of the OptiBP mobile application according to the AAMI/ESH/ISO universal validation protocol.

OBJECTIVE: The aim of this study was to assess the accuracy of the OptiBP mobile application based on an optical signal recorded by placing the patient's fingertip on a smartphone's camera to estimate blood pressure (BP). Measurements were carried out in a general population according to existing standards of the Association for the Advancement of Medical Instrumentation (AAMI), the European Society of Hypertension (ESH) and the International Organization for Standardization (ISO). METHODS: Participants were recruited during a scheduled appointment at the hypertension clinic of Lausanne University Hospital in Switzerland. Age, gender and BP distribution were collected to fulfill AAMI/ESH/ISO universal standards. Both auscultatory BP references and OptiBP were measured and compared using the opposite arm simultaneous method as described in the 81060-2:2018 ISO norm. RESULTS: A total of 353 paired recordings from 91 subjects were analyzed. For validation criterion 1, the mean ± SD between OptiBP and reference BP recordings was respectively 0.5 ± 7.7 mmHg and 0.4 ± 4.6 mmHg for SBP and DBP. For validation criterion 2, the SD of the averaged BP differences between OptiBP and reference BP per subject was 6.3 mmHg and 3.5 mmHg for SBP and DBP. OptiBP acceptance rate was 85%. CONCLUSION: The smartphone embedded OptiBP cuffless mobile application fulfills the validation requirements of AAMI/ESH/ISO universal standards in a general population for the measurement of SBP and DBP.

Blood pressure measurements with the OptiBP smartphone app validated against reference auscultatory measurements.

Mobile health diagnostics have been shown to be effective and scalable for chronic disease detection and management. By maximizing the smartphones' optics and computational power, they could allow assessment of physiological information from the morphology of pulse waves and thus estimate cuffless blood pressure (BP). We trained the parameters of an existing pulse wave analysis algorithm (oBPM), previously validated in anaesthesia on pulse oximeter signals, by collecting optical signals from 51 patients fingertips via a smartphone while simultaneously acquiring BP measurements through an arterial catheter. We then compared smartphone-based measurements obtained on 50 participants in an ambulatory setting via the OptiBP app against simultaneously acquired auscultatory systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean blood pressure (MBP) measurements. Patients were normotensive (70.0% for SBP versus 61.4% for DBP), hypertensive (17.1% vs. 13.6%) or hypotensive (12.9% vs. 25.0%). The difference in BP (mean ± standard deviation) between both methods were within the ISO 81,060-2:2018 standard for SBP (- 0.7 ± 7.7 mmHg), DBP (- 0.4 ± 4.5 mmHg) and MBP (- 0.6 ± 5.2 mmHg). These results demonstrate that BP can be measured with accuracy at the finger using the OptiBP smartphone app. This may become an important tool to detect hypertension in various settings, for example in low-income countries, where the availability of smartphones is high but access to health care is low.

Automated Pulse Oximeter Waveform Analysis to Track Changes in Blood Pressure During Anesthesia Induction: A Proof-of-Concept Study.

BACKGROUND: Intraoperative hypotension is associated with postoperative complications and death. Oscillometric brachial cuffs are used to measure arterial pressure (AP) in most surgical patients but may miss acute changes in AP. We hypothesized that pulse oximeter waveform analysis may help to detect changes in systolic AP (SAP) and mean AP (MAP) during anesthesia induction. METHODS: In 40 patients scheduled for an elective surgery necessitating general anesthesia and invasive AP monitoring, we assessed the performance of a pulse oximeter waveform analysis algorithm (optical blood pressure monitoring [oBPM]) to estimate SAP, MAP, and their changes during the induction of general anesthesia. Acute AP changes (>20%) in SAP and MAP assessed by the reference invasive method and by oBPM were compared using 4-quadrant and polar plots. The tracking ability of the algorithm was evaluated on changes occurring over increasingly larger time spans, from 30 seconds up to 5 minutes. The second objective of the study was to assess the ability of the oBPM algorithm to cope with the Association for the Advancement of Medical Instrumentation (AAMI) standards. The accuracy and precision of oBPM in estimating absolute SAP and MAP values compared to the invasive method was evaluated at various instants after algorithm calibration, from 30 seconds to 5 minutes. RESULTS: Rapid changes (occurring over time spans of ≤60 seconds) in SAP and MAP assessed by oBPM were strongly correlated and showed excellent concordance with changes in invasive AP (worst-case Pearson correlation of 0.94 [0.88, 0.97] [95% confidence interval], concordance rate of 100% [100%, 100%], and angular concordance rate at ±30° of 100% [100%, 100%]). The trending ability tended to decrease progressively as the time span over which the changes occurred increased, reaching 0.89 (0.85, 0.91) (Pearson correlation), 97% (95%, 100%) (concordance rate), and 90% (85%, 94%) (angular concordance rate) in the worst case. Regarding accuracy and precision, oBPM-derived SAP values were shown to comply with AAMI criteria up to 2 minutes after calibration, whereas oBPM-derived MAP values were shown to comply with criteria at all times. CONCLUSIONS: Pulse oximeter waveform analysis was useful to track rapid changes in SAP and MAP during anesthesia induction. A good agreement with reference invasive measurements was observed for MAP up to at least 5 minutes after initial calibration. In the future, this method could be used to track changes in AP between intermittent oscillometric measurements and to automatically trigger brachial cuff inflation when a significant change in AP is detected.