Postoperative circadian patterns in wearable sensor measured heart rate: a prospective observational study.

PURPOSE: This study aimed to describe the 24-hour cycle of wearable sensor-obtained heart rate in patients with deterioration-free recovery and to compare it with patients experiencing postoperative deterioration. METHODS: A prospective observational trial was performed in patients following bariatric or major abdominal cancer surgery. A wireless accelerometer patch (Healthdot) continuously measured postoperative heart rate, both in the hospital and after discharge, for a period of 14 days. The circadian pattern, or diurnal rhythm, in the wearable sensor-obtained heart rate was described using peak, nadir and peak-nadir excursions. RESULTS: The study population consisted of 137 bariatric and 100 major abdominal cancer surgery patients. In the latter group, 39 experienced postoperative deterioration. Both surgery types showed disrupted diurnal rhythm on the first postoperative days. Thereafter, the bariatric group had significantly lower peak heart rates (days 4, 7-12, 14), lower nadir heart rates (days 3-14) and larger peak-nadir excursions (days 2, 4-14). In cancer surgery patients, significantly higher nadir (days 2-5) and peak heart rates (days 2-3) were observed prior to deterioration. CONCLUSIONS: The postoperative diurnal rhythm of heart rate is disturbed by different types of surgery. Both groups showed recovery of diurnal rhythm but in patients following cancer surgery, both peak and nadir heart rates were higher than in the bariatric surgery group. Especially nadir heart rate was identified as a potential prognostic marker for deterioration after cancer surgery.

Lessons Learned from Telemonitoring in an Outpatient Bariatric Surgery Pathway-Secondary Outcomes of a Patient Preference Clinical Trial.

BACKGROUND: Remote monitoring is increasingly used to support postoperative care. This study aimed to describe the lessons learned from the use of telemonitoring in an outpatient bariatric surgery pathway. MATERIALS AND METHODS: Patients were assigned based on their preference to an intervention cohort of same-day discharge after bariatric surgery. In total, 102 patients were monitored continuously for 7 days using a wearable monitoring device with a Continuous and Remote Early Warning Score-based notification protocol (CREWS). Outcome measures included missing data, course of postoperative heart and respiration rate, false positive notification and specificity analysis, and vital sign assessment during teleconsultation. RESULTS: In 14.7% of the patients, data for heart rate was missing for > 8 h. A day-night-rhythm of heart rate and respiration rate reappeared on average on postoperative day 2 with heart rate amplitude increasing after day 3. CREWS notification had a specificity of 98%. Of the 17 notifications, 70% was false positive. Half of them occurred between day 4 and 7 and were accompanied with surrounding reassuring values. Comparable postoperative complaints were encountered between patients with normal and deviated data. CONCLUSION: Telemonitoring after outpatient bariatric surgery is feasible. It supports clinical decisions, however does not replace nurse or physician care. Although infrequent, the false notification rate was high. We suggested additional contact may not be necessary when notifications occur after restoration of circadian rhythm or when surrounding reassuring vital signs are present. CREWS supports ruling out serious complications, what may reduce in-hospital re-evaluations. Following these lessons learned, increased patients' comfort and decreased clinical workload could be expected. TRIAL REGISTRATION: ClinicalTrials.gov. Identifier: NCT04754893.

Machine Learning for Postoperative Continuous Recovery Scores of Oncology Patients in Perioperative Care with Data from Wearables.

Assessing post-operative recovery is a significant component of perioperative care, since this assessment might facilitate detecting complications and determining an appropriate discharge date. However, recovery is difficult to assess and challenging to predict, as no universally accepted definition exists. Current solutions often contain a high level of subjectivity, measure recovery only at one moment in time, and only investigate recovery until the discharge moment. For these reasons, this research aims to create a model that predicts continuous recovery scores in perioperative care in the hospital and at home for objective decision making. This regression model utilized vital signs and activity metrics measured using wearable sensors and the XGBoost algorithm for training. The proposed model described continuous recovery profiles, obtained a high predictive performance, and provided outcomes that are interpretable due to the low number of features in the final model. Moreover, activity features, the circadian rhythm of the heart, and heart rate recovery showed the highest feature importance in the recovery model. Patients could be identified with fast and slow recovery trajectories by comparing patient-specific predicted profiles to the average fast- and slow-recovering populations. This identification may facilitate determining appropriate discharge dates, detecting complications, preventing readmission, and planning physical therapy. Hence, the model can provide an automatic and objective decision support tool.

The Accuracy of Wrist-Worn Photoplethysmogram-Measured Heart and Respiratory Rates in Abdominal Surgery Patients: Observational Prospective Clinical Validation Study.

BACKGROUND: Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established. OBJECTIVE: This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients. METHODS: The accuracy of the wrist-worn PPG sensor was assessed in 62 post-abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m2). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy. RESULTS: Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis. CONCLUSIONS: The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained. TRIAL REGISTRATION: ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127.

Prognostic Value of Combined Biomarkers in Patients With Heart Failure: The Heartmarker Score.

Background: Heart failure (HF) biomarkers have prognostic value. The aim of this study was to combine HF biomarkers into an objective classification system for risk stratification of patients with HF. Methods: HF biomarkers were analyzed in a population of HF outpatients and expressed relative to their cut-off values (N-terminal pro-B-type natriuretic peptide [NT-proBNP] >1,000 pg/mL, soluble suppression of tumorigenesis-2 [ST2] >35 ng/mL, growth differentiation factor-15 [GDF-15] >2,000 pg/mL, and fibroblast growth factor-23 [FGF-23] >95.4 pg/mL). Biomarkers that remained significant in multivariable analysis were combined to devise the Heartmarker score. The performance of the Heartmarker score was compared to the widely used New York Heart Association (NYHA) classification based on symptoms during ordinary activity. Results: HF biomarkers of 245 patients were analyzed, 45 (18%) of whom experienced the composite endpoint of HF hospitalization, appropriate implantable cardioverter-defibrillator shock, or death. HF biomarkers were elevated more often in patients that reached the composite endpoint than in patients that did not reach the endpoint. NT-proBNP, ST2, and GDF-15 were independent predictors of the composite endpoint and were thus combined as the Heartmarker score. The event-free survival and distance covered in 6 minutes of walking decreased with an increasing Heartmarker score. Compared with the NYHA classification, the Heartmarker score was better at discriminating between different risk classes and had a comparable relationship to functional capacity. Conclusions: The Heartmarker score is a reproducible and intuitive model for risk stratification of outpatients with HF, using routine biomarker measurements.

A wearable patch based remote early warning score (REWS) in major abdominal cancer surgery patients.

INTRODUCTION: The shift toward remote patient monitoring methods to detect clinical deterioration requires testing of wearable devices in real-life clinical settings. This study aimed to develop a remote early warning scoring (REWS) system based on continuous measurements using a wearable device, and compare its diagnostic performance for the detection of deterioration to the diagnostic performance of the conventional modified early warning score (MEWS). MATERIALS AND METHODS: The study population of this prospective, single center trial consisted of patients who underwent major abdominal cancer surgery and were monitored using routine in-hospital spotcheck measurements of the vital parameters. Heart and respiratory rates were measured continuously using a wireless accelerometer patch (HealthDot). The prediction by MEWS of deterioration toward a complication graded Clavien-Dindo of 2 or higher was compared to the REWS derived from continuous measurements by the wearable patch. MAIN RESULTS: A total of 103 patients and 1909 spot-check measurements were included in the analysis. Postoperative deterioration was observed in 29 patients. For both EWS systems, the sensitivity (MEWS: 0.20 95% CI: [0.13-0.29], REWS: 0.20 95% CI: [0.13-0.29]) and specificity (MEWS: 0.96 95% CI: [0.95-0.97], REWS: 0.96 95% CI: [0.95-0.97]) were assessed. CONCLUSIONS: The diagnostic value of the REWS method, based on continuous measurements of the heart and respiratory rates, is comparable to that of the MEWS in patients following major abdominal cancer surgery. The wearable patch could detect the same amount of deteriorations, without requiring manual spot check measurements.

Left atrial reservoir strain as a predictor of cardiac outcome in patients with heart failure: the HaFaC cohort study.

BACKGROUND: The left atrium (LA) is a key player in the pathophysiology of systolic and diastolic heart failure (HF). Speckle tracking derived LA reservoir strain (LASr) can be used as a prognostic surrogate for elevated left ventricular filling pressure similar to NT-proBNP. The aim of the study is to investigate the correlation between LASr and NT-proBNP and its prognostic value with regards to the composite endpoint of HF hospitalization and all-cause mortality within 1 year. METHODS: Outpatients, sent to the echocardiography core lab because of HF, were enrolled into this study. Patients underwent a transthoracic echocardiographic examination, commercially available software was used to measure LASr. Blood samples were collected directly after the echocardiographic examination to determine NT-proBNP. RESULTS: We included 174 HF patients, 43% with reduced, 36% with mildly reduced, and 21% with preserved ejection fraction. The study population showed a strong inverse correlation between LASr and log-transformed NT-proBNP (r = - 0.75, p < 0.01). Compared to NT-proBNP, LASr predicts the endpoint with a comparable specificity (83% vs. 84%), however with a lower sensitivity (70% vs. 61%). CONCLUSION: LASr is inversely correlated with NT-proBNP and a good echocardiographic predictor for the composite endpoint of hospitalization and all-cause mortality in patients with HF. TRIAL REGISTRATION: https://www.trialregister.nl/trial/7268.

Accuracy of vital parameters measured by a wearable patch following major abdominal cancer surgery.

INTRODUCTION: Recent advances in wearable technology allow for the development of wirelessly connected sensors to continuously measure vital parameters in the general ward or even at home. The present study assesses the accuracy of a wearable patch (Healthdot) for continuous monitoring of heartrate (HR) and respiration rate (RR). MATERIALS AND METHODS: The Healthdot measures HR and RR by means of chest accelerometry. The study population consisted of patients following major abdominal oncological surgery. The analysis focused on the agreement between HR and RR measured by the Healthdot and the gold standard patient monitor in the intensive and post-anesthesia care unit. RESULTS: For HR, a total of 112 h of measurements was collected in 26 patients. For RR, a total of 102 h of measurements was collected in 21 patients. On second to second analysis, 97% of the HR and 87% of the RR measurements were within 5 bpm and 3 rpm of the reference monitor. Assessment of 5-min averaged data resulted in 96% of the HR and 95% of the RR measurements within 5 bpm and 3 rpm of the reference monitor. A Clarke error grid analysis showed that 100% of the HR and 99.4% of the 5-min averaged data was clinically acceptable. CONCLUSION: The Healthdot accurately measured HR and RR in a cohort of patients recovering from major abdominal surgery, provided that good quality data was obtained. These results push the Healthdot forward as a clinically acceptable tool in low acuity settings for unobtrusive, automatic, wireless and continuous monitoring.