Remote Vital Sign Monitoring in Admission Avoidance Hospital at Home: A Systematic Review.

OBJECTIVES: To examine randomized controlled trials (RCTs) of "hospital at home" (HAH) for admission avoidance in adults presenting with acute physical illness to identify the use of vital sign monitoring approaches and evidence for their effectiveness. DESIGN: Systematic review. SETTING AND PARTICIPANTS: This review compared strategies for vital sign monitoring in admission avoidance HAH for adults presenting with acute physical illness. Vital sign monitoring can support HAH acute multidisciplinary care by contributing to safety, determining requirement of further assessment, and guiding clinical decisions. There are a wide range of systems currently available, including reliable and automated continuous remote monitoring using wearable devices. METHODS: Eligible studies were identified through updated database and trial registries searches (March 2, 2016, to February 15, 2023), and existing systematic reviews. Risk of bias was assessed using the Cochrane risk of bias 2 tool. Random effects meta-analyses were performed, and narrative summaries provided stratified by vital sign monitoring approach. RESULTS: Twenty-one eligible RCTs (3459 participants) were identified. Two approaches to vital sign monitoring were characterized: manual and automated. Reporting was insufficient in the majority of studies for classification. For HAH compared to hospital care, 6-monthly mortality risk ratio (RR) was 0.94 (95% CI 0.78-1.12), 3-monthly readmission to hospital RR 1.02 (0.77-1.35), and length of stay mean difference 1.91 days (0.71-3.12). Readmission to hospital was reduced in the automated monitoring subgroup (RR 0.30 95% CI 0.11-0.86). CONCLUSIONS AND IMPLICATIONS: This review highlights gaps in the reporting and evidence base informing remote vital sign monitoring in alternatives to admission for acute illness, despite expanding implementation in clinical practice. Although continuous vital sign monitoring using wearable devices may offer added benefit, its use in existing RCTs is limited. Recommendations for the implementation and evaluation of remote monitoring in future clinical trials are proposed.

Rapid implementation of blood pressure self-monitoring in pregnancy at a UK NHS Trust during the COVID-19 pandemic: a quality improvement evaluation.

BACKGROUND: This service evaluation describes the rapid implementation of self-monitoring of blood pressure (SMBP) into maternity care at a tertiary referral centre during the COVID-19 pandemic. It summarises findings, identifies knowledge gaps and provides recommendations for further research and practice. INTERVENTION: Pregnant and postpartum women monitored their blood pressure (BP) at home, with instructions on actions to take if their BP exceeded pre-determined thresholds. Some also conducted proteinuria self-testing. DATA COLLECTION AND ANALYSIS: Maternity records, app data and staff feedback were used in interim evaluations to assess process effectiveness and guide adjustments, employing a Plan-Do-Study-Act and root cause analysis approach. RESULTS: Between March 2020 and August 2021, a total of 605 women agreed to self-monitor their BP, including 10 women with limited English. 491 registered for telemonitoring (81.2%). 21 (3.5%) took part in urine self-testing. Engagement was high and increased over time with no safety issues. Biggest concerns related to monitor supply and postnatal monitoring. In December 2020, SMBP was integrated into the standard maternity care pathway. CONCLUSIONS: This project demonstrated successful integration of SMBP into maternity care. Early stakeholder engagement and clear guidance were crucial and community midwifery support essential. Supplying BP monitors throughout pregnancy and post partum could improve the service and fully digitised maternity records would aid data collection. More research is needed on SMBP in the postnatal period and among non-English speakers. These findings support efforts to implement app-supported self-monitoring and guide future research.

Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts.

RATIONALE: Intensive care units (ICUs) admit the most severely ill patients. Once these patients are discharged from the ICU to a step-down ward, they continue to have their vital signs monitored by nursing staff, with Early Warning Score (EWS) systems being used to identify those at risk of deterioration. OBJECTIVES: We report the development and validation of an enhanced continuous scoring system for predicting adverse events, which combines vital signs measured routinely on acute care wards (as used by most EWS systems) with a risk score of a future adverse event calculated on discharge from the ICU. DESIGN: A modified Delphi process identified candidate variables commonly available in electronic records as the basis for a 'static' score of the patient's condition immediately after discharge from the ICU. L1-regularised logistic regression was used to estimate the in-hospital risk of future adverse event. We then constructed a model of physiological normality using vital sign data from the day of hospital discharge. This is combined with the static score and used continuously to quantify and update the patient's risk of deterioration throughout their hospital stay. SETTING: Data from two National Health Service Foundation Trusts (UK) were used to develop and (externally) validate the model. PARTICIPANTS: A total of 12 394 vital sign measurements were acquired from 273 patients after ICU discharge for the development set, and 4831 from 136 patients in the validation cohort. RESULTS: Outcome validation of our model yielded an area under the receiver operating characteristic curve of 0.724 for predicting ICU readmission or in-hospital death within 24 hours. It showed an improved performance with respect to other competitive risk scoring systems, including the National EWS (0.653). CONCLUSIONS: We showed that a scoring system incorporating data from a patient's stay in the ICU has better performance than commonly used EWS systems based on vital signs alone. TRIAL REGISTRATION NUMBER: ISRCTN32008295.

Supporting people with type 2 diabetes in effective use of their medicine through mobile health technology integrated with clinical care (SuMMiT-D pilot): results of a feasibility randomised trial.

BACKGROUND: The purpose of this 6-month intervention pilot feasibility randomised trial was to test sending brief messages using mobile phones to promote self-management through taking medication as prescribed to people with type 2 diabetes. This was to inform the design and conduct of a future large-scale United Kingdom-based clinical trial and establish the feasibility of recruitment, the technology used, follow-up, and data collection. METHODS: A multicentre individually randomised, controlled parallel group trial in primary care, recruiting adults (≥ 35 years) with type 2 diabetes in England. Consenting participants were randomly allocated to receive short message system text messages up to four times a week, or usual care, for a period of 6 months; messages contained behavioural change techniques targeting medication use. The primary outcome was the rate of recruitment to randomisation of participants to the trial with a planned rate of 22 participants randomised per month. The study also aimed to establish the feasibility of follow-up at 6 months, with an aim of retaining more than 80% of participants. Data, including patient-reported measures, were collected at baseline and the end of the 6-month follow-up period, and a notes review was completed at 24 months. RESULTS: The trial took place between 26 November 2018 and 30 September 2019. In total 209 participants were randomly allocated to intervention (n = 103) or usual care (n = 106). The maximum rate of monthly recruitment to the trial was 60-80 participants per month. In total, 12,734 messages were sent to participants. Of these messages, 47 were identified as having failed to be sent by the service provider. Participants sent 2,864 messages to the automated messaging system. Baseline data from medical records were available for > 90% of participants with the exception of cholesterol (78.9%). At 6 months, a further HbA1c measurement was reported for 67% of participants. In total medical record data were available at 6 months for 207 (99.0%) of participants and completed self-report data were available for 177 (84.7%) of participants. CONCLUSION: The feasibility of a large-scale randomised evaluation of brief message intervention for people with type 2 diabetes appears to be high using this efficient design. Failure rate of sending messages is low, rapid recruitment was achieved among people with type 2 diabetes, clinical data is available on participants from routine medical records and self-report of economic measures was acceptable. TRIAL REGISTRATION: ISCTRN ISRCTN13404264. Registered on 10 October 2018.

Using a novel ambulatory monitoring system to support patient safety on an acute infectious disease ward during an unfolding pandemic.

AIM: To gain staff feedback on the implementation and impact of a novel ambulatory monitoring system to support coronavirus patient management on an isolation ward. DESIGN: Qualitative service evaluation. METHODS: Semi-structured interviews were conducted with 15 multidisciplinary isolation ward staff in the United Kingdom between July 2020 and May 2021. Interviews were audio-recorded, transcribed and analysed using thematic analysis. FINDINGS: Adopting Innovation to Assist Patient Safety was identified as the overriding theme. Three interlinked sub-themes represent facets of how the system supported patient safety. Patient Selection was developed throughout the pandemic, as clinical staff became more confident in choosing which patients would benefit most. Trust In the System described how nurses coped with discrepancies between the ambulatory system and ward observation machines. Finally, Resource Management examined how, once trust was built, staff perceived the ambulatory system assisted with caseload management. This supported efficient personal protective equipment resource use by reducing the number of isolation room entries. Despite these reported benefits, face-to-face contact was still highly valued, despite the risk of coronavirus exposure. CONCLUSION: Hospital wards should consider using ambulatory monitoring systems to support caseload management and patient safety. Patients in isolation rooms or at high risk of deterioration may particularly benefit from this additional monitoring. However, these systems should be seen as an adjunct to nursing care, not a replacement. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Nurses valued ambulatory monitoring as a means of ensuring the safety of patients at risk of deterioration and prioritizing their workload. IMPACT: The findings of this research will be useful to all those developing or considering implementation of ambulatory monitoring systems in hospital wards. REPORTING METHOD: This manuscript follows the Consolidated criteria for Reporting Qualitative Research (COREQ) guidelines with inclusion of relevant SQUIRE guidelines for reporting quality improvement. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Identification of motor progression in Parkinson's disease using wearable sensors and machine learning.

Wearable devices offer the potential to track motor symptoms in neurological disorders. Kinematic data used together with machine learning algorithms can accurately identify people living with movement disorders and the severity of their motor symptoms. In this study we aimed to establish whether a combination of wearable sensor data and machine learning algorithms with automatic feature selection can estimate the clinical rating scale and whether it is possible to monitor the motor symptom progression longitudinally, for people with Parkinson's Disease. Seventy-four patients visited the lab seven times at 3-month intervals. Their walking (2-minutes) and postural sway (30-seconds,eyes-closed) were recorded using six Inertial Measurement Unit sensors. Simple linear regression and Random Forest algorithms were utilised together with different routines of automatic feature selection or factorisation, resulting in seven different machine learning algorithms to estimate the clinical rating scale (Movement Disorder Society- Unified Parkinson's Disease Rating Scale part III; MDS-UPDRS-III). Twenty-nine features were found to significantly progress with time at group level. The Random Forest model revealed the most accurate estimation of the MDS-UPDRS-III among the seven models. The model estimations detected a statistically significant progression of the motor symptoms within 15 months when compared to the first visit, whereas the MDS-UPDRS-III did not capture any change. Wearable sensors and machine learning can track the motor symptom progression in people with PD better than the conventionally used clinical rating scales. The methods described in this study can be utilised complimentary to the clinical rating scales to improve the diagnostic and prognostic accuracy.

Features from the photoplethysmogram and the electrocardiogram for estimating changes in blood pressure.

There is a growing emphasis being placed on the potential for cuffless blood pressure (BP) estimation through modelling of morphological features from the photoplethysmogram (PPG) and electrocardiogram (ECG). However, the appropriate features and models to use remain unclear. We investigated the best features available from the PPG and ECG for BP estimation using both linear and non-linear machine learning models. We conducted a clinical study in which changes in BP ([Formula: see text]BP) were induced by an infusion of phenylephrine in 30 healthy volunteers (53.8% female, 28.0 (9.0) years old). We extracted a large and diverse set of features from both the PPG and the ECG and assessed their individual importance for estimating [Formula: see text]BP through Shapley additive explanation values and a ranking coefficient. We trained, tuned, and evaluated linear (ordinary least squares, OLS) and non-linear (random forest, RF) machine learning models to estimate [Formula: see text]BP in a nested leave-one-subject-out cross-validation framework. We reported the results as correlation coefficient ([Formula: see text]), root mean squared error (RMSE), and mean absolute error (MAE). The non-linear RF model significantly ([Formula: see text]) outperformed the linear OLS model using both the PPG and the ECG signals across all performance metrics. Estimating [Formula: see text]SBP using the PPG alone ([Formula: see text] = 0.86 (0.23), RMSE = 5.66 (4.76) mmHg, MAE = 4.86 (4.29) mmHg) performed significantly better than using the ECG alone ([Formula: see text] = 0.69 (0.45), RMSE = 6.79 (4.76) mmHg, MAE = 5.28 (4.57) mmHg), all [Formula: see text]. The highest ranking features from the PPG largely modelled increasing reflected wave interference driven by changes in arterial stiffness. This finding was supported by changes observed in the PPG waveform in response to the phenylephrine infusion. However, a large number of features were required for accurate BP estimation, highlighting the high complexity of the problem. We conclude that the PPG alone may be further explored as a potential single source, cuffless, blood pressure estimator. The use of the ECG alone is not justified. Non-linear models may perform better as they are able to incorporate interactions between feature values and demographics. However, demographics may not adequately account for the unique and individualised relationship between the extracted features and BP.

Diagnosing hypertension in primary care: a retrospective cohort study to investigate the importance of night-time blood pressure assessment.

BACKGROUND: Ambulatory blood-pressure monitoring (ABPM) has become less frequent in primary care since the COVID-19 pandemic, with home blood-pressure monitoring (HBPM) often the preferred alternative; however, HBPM cannot measure night-time blood pressure (BP), and patients whose night-time BP does not dip, or rises (reverse dipping), have poorer cardiovascular outcomes. AIM: To investigate the importance of measuring night-time BP when assessing individuals for hypertension. DESIGN AND SETTING: Retrospective cohort study of two patient populations - namely, hospital patients admitted to four UK acute hospitals located in Oxfordshire, and participants of the BP in different ethnic groups (BP-Eth) study, who were recruited from 28 UK general practices in the West Midlands. METHOD: Using BP data collected for the two cohorts, three systolic BP phenotypes (dipper, non-dipper, and reverse dipper) were studied. RESULTS: Among the hospital cohort, 48.9% (n = 10 610/21 716) patients were 'reverse dippers', with an average day-night systolic BP difference of +8.0 mmHg. Among the community (BP-Eth) cohort, 10.8% (n = 63/585) of patients were reverse dippers, with an average day-night systolic BP difference of +8.5 mmHg. Non-dipper and reverse-dipper phenotypes both had lower daytime systolic BP and higher night-time systolic BP than the dipper phenotype. Average daytime systolic BP was lowest in the reverse-dipping phenotype (this was 6.5 mmHg and 6.8 mmHg lower than for the dipper phenotype in the hospital and community cohorts, respectively), thereby placing them at risk of undiagnosed, or masked, hypertension. CONCLUSION: Not measuring night-time BP puts all groups, other than dippers, at risk of failure to identify hypertension. As a result of this study, it is recommended that GPs should offer ABPM to all patients aged ≥60 years as a minimum when assessing for hypertension.

Predicting Isolated Nocturnal Hypertension Using Dawn and Dusk Home Blood Pressure Monitoring.

Hypertension is a major global cause of morbidity and mortality. Home Blood Pressure Monitoring (HBPM) has the potential to help diagnose patients experiencing isolated nocturnal hypertension who may otherwise be missed. This paper investigates potential diagnostic thresholds for diagnosing isolated nocturnal hypertension using dawn and dusk HBPM measurements in the BP-Eth ambulatory blood pressure monitoring (ABPM) database. Depending on whether European or American diagnostic guidelines for hypertension were used, incidence of isolated nocturnal hypertension in the BP-Eth database was 17.1% or 16.8%, respectively. Using averaged dawn and dusk HBPM measurements to diagnose isolated nocturnal hypertension yielded an AUROC of 0.79 (European guidelines) or 0.84 (American guidelines). The SBP and DBP diagnostic thresholds required to detect 80% of cases of isolated nocturnal hypertension were found to be 125.4 mmHg and 75.7 mmHg, respectively (European guidelines) or 117.6 mmHg and 74.3 mmHg, respectively (American guidelines). These thresholds corresponded to a sensitivity of 80% and specificity of 63% (European guidelines) or sensitivity of 83% and specificity of 65% (American guidelines). These results demonstrate the potential for HBPM to function as an intermediate step in screening patients, determining which patients require more intensive ABPM monitoring for detection of isolated nocturnal hypertension. Clinical Relevance - This study investigates the incidence of isolated nocturnal hypertension, and the possibility of using home blood pressure monitoring (HBPM) to screen for it. Isolated nocturnal hypertension is otherwise only detectable using more expensive and burdensome ambulatory blood pressure monitoring (ABPM).

Study protocol: use of a smartphone application to support the implementation of a complex physical activity intervention (+Stay Active) in women with gestational diabetes mellitus-protocol for a non-randomised feasibility study.

INTRODUCTION: Physical activity (PA) interventions have a promising role in the management of gestational diabetes mellitus (GDM). Digital technologies can support PA at scale and remotely. The protocol describes a study designed to determine the feasibility and acceptability of a complex intervention; known as +Stay Active. +Stay Active combines motivational interviewing with a bespoke behaviour change informed smartphone application (Stay-Active) to augment PA levels in women with GDM. METHODS AND ANALYSIS: This is a non-randomised feasibility study using a mixed methods approach. Participants will be recruited from the GDM antenatal clinic at the Women Centre, John Radcliffe Hospital, Oxford. Following baseline assessments (visit 1) including self-reported and device determined PA assessment (wearing a wrist accelerometer), women will be invited to participate in an online motivational interview, then download and use the Stay-Active app (Android or iOS) (visit 2). Women will have access to Stay-Active until 36 weeks gestation, when engagement and PA levels will be reassessed (visit 3). The target sample size is 60 women. Primary outcomes are recruitment and retention rates, compliance and assessment of participant engagement and acceptability with the intervention. Secondary outcomes are assessment of blood glucose control, self-reported and device determined assessment of PA, usage and structured feedback of participant's attitudes to +Stay Active, assessment of health costs and description of maternal and neonatal outcomes. This study will provide key insights into this complex intervention regarding engagement in smartphone technology and the wearing of accelerometers. These data will inform the development of a randomised controlled trial with refinements to intervention implementation. ETHICS AND DISSEMINATION: The study has received a favourable opinion from South Central-Hampshire B Research Ethics Committee; REC reference: 20/SC/0342. Written informed consent will be obtained from all participants. Findings will be disseminated through peer-reviewed journals, conferences and seminar presentations. TRIAL REGISTRATION NUMBER: ISRCTN11366562.

Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors.

BACKGROUND: We have previously shown that wearable technology and machine learning techniques can accurately discriminate between progressive supranuclear palsy (PSP), Parkinson's disease, and healthy controls. To date these techniques have not been applied in longitudinal studies of disease progression in PSP. OBJECTIVES: We aimed to establish whether data collected by a body-worn inertial measurement unit (IMU) network could predict clinical rating scale scores in PSP and whether it could be used to track disease progression. METHODS: We studied gait and postural stability in 17 participants with PSP over five visits at 3-month intervals. Participants performed a 2-minute walk and an assessment of postural stability by standing for 30 seconds with their eyes closed, while wearing an array of six IMUs. RESULTS: Thirty-two gait and posture features were identified, which progressed significantly with time. A simple linear regression model incorporating the three features with the clearest progression pattern was able to detect statistically significant progression 3 months in advance of the clinical scores. A more complex linear regression and a random forest approach did not improve on this. CONCLUSIONS: The reduced variability of the models, in comparison to clinical rating scales, allows a significant change in disease status from baseline to be observed at an earlier stage. The current study sheds light on the individual features that are important in tracking disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Classifying nocturnal blood pressure patterns using photoplethysmogram features.

Circadian rhythms in blood pressure (BP) may in some cases be indicative of an increased risk of adverse cardiovascular events. However, current methods for assessing these rhythms can be disruptive to sleep, work, and daily activities. Features of the photoplethysmogram (PPG), which can be non-invasively and unobtrusively recorded, have been suggested as surrogate measures of BP. This work investigates the presence of a circadian rhythm in these features and evaluates their potential to classify nocturnal BP patterns. 742 patients who were discharged home from the ICU were selected from the MIMIC-III database. Our results show that a number of PPG features exhibit a clear and observable circadian rhythm. Of the 19 features evaluated, the circadian rhythms of 5 features outperformed heart rate (HR) in terms of correlation with the circadian rhythm of SBP ( ). We also present evidence that a metric combining the PPG features significantly improves BP phenotype classification accuracy. Clinical Relevance-This work suggests that a combined metric of PPG features may be able to accurately assess an individual's circadian rhythm of BP.

Ambulatory blood pressure monitoring using telemedicine: proof-of-concept cohort and failure modes and effects analyses.

Background: The COVID-19 pandemic has accelerated adoption of remote consulting in healthcare. Despite opportunities posed by telemedicine, most hypertension services in Europe have suspended ambulatory blood pressure monitoring (ABPM). Methods: We examined the process and performance of remotely delivered ABPM using two methodologies: firstly, a Failure Modes and Effects Analysis (FMEA) and secondly, a quantitative analysis comparing ABPM data from a subgroup of 65 participants of the Screening for Hypertension in the INpatient Environment (SHINE) diagnostic accuracy study. The FMEA was performed over seven sessions from February to March 2021, with a multidisciplinary team comprising a patient representative, a research coordinator with technical expertise and four research clinicians. Results: The FMEA identified a single high-risk step in the remote ABPM process. This was cleaning of monitoring equipment in the context of the COVID-19 pandemic, unrelated to the remote setting. A total of 14 participants were scheduled for face-to-face ABPM appointments, before the UK March 2020 COVID-19 lockdown; 62 were scheduled for remote ABPM appointments since emergence of the COVID-19 pandemic between November 2020 and August 2021. A total of 65 (88%) participants completed ABPMs; all obtained sufficient successful measurements for interpretation. For the 10 participants who completed face-to-face ABPM, there were 402 attempted ABPM measurements and 361 (89%) were successful. For the 55 participants who completed remote ABPM, there were 2516 attempted measurements and 2214 (88%) were successful. There was no significant difference in the mean per-participant error rate between face-to-face (0.100, SD 0.009) and remote (0.143, SD 0.132) cohorts (95% CI for the difference -0.125 to 0.045 and two-tailed P-value 0.353). Conclusions: We have demonstrated that ABPM can be safely and appropriately provided in the community remotely and without face-to-face contact, using video technology for remote fitting appointments, alongside courier services for delivery of equipment to participants.

Effect of Self-monitoring of Blood Pressure on Blood Pressure Control in Pregnant Individuals With Chronic or Gestational Hypertension: The BUMP 2 Randomized Clinical Trial.

Importance: Inadequate management of elevated blood pressure is a significant contributing factor to maternal deaths. The role of blood pressure self-monitoring in pregnancy in improving clinical outcomes for the pregnant individual and infant is unclear. Objective: To evaluate the effect of blood pressure self-monitoring, compared with usual care alone, on blood pressure control and other related maternal and infant outcomes, in individuals with pregnancy hypertension. Design, Setting, and Participants: Unblinded, randomized clinical trial that recruited between November 2018 and September 2019 in 15 hospital maternity units in England. Individuals with chronic hypertension (enrolled up to 37 weeks' gestation) or with gestational hypertension (enrolled between 20 and 37 weeks' gestation). Final follow-up was in May 2020. Interventions: Participants were randomized to either blood pressure self-monitoring using a validated monitor and a secure telemonitoring system in addition to usual care (n = 430) or to usual care alone (n = 420). Usual care comprised blood pressure measured by health care professionals at regular antenatal clinics. Main Outcomes and Measures: The primary maternal outcome was the difference in mean systolic blood pressure recorded by health care professionals between randomization and birth. Results: Among 454 participants with chronic hypertension (mean age, 36 years; mean gestation at entry, 20 weeks) and 396 with gestational hypertension (mean age, 34 years; mean gestation at entry, 33 weeks) who were randomized, primary outcome data were available from 444 (97.8%) and 377 (95.2%), respectively. In the chronic hypertension cohort, there was no statistically significant difference in mean systolic blood pressure for the self-monitoring groups vs the usual care group (133.8 mm Hg vs 133.6 mm Hg, respectively; adjusted mean difference, 0.03 mm Hg [95% CI, -1.73 to 1.79]). In the gestational hypertension cohort, there was also no significant difference in mean systolic blood pressure (137.6 mm Hg compared with 137.2 mm Hg; adjusted mean difference, -0.03 mm Hg [95% CI, -2.29 to 2.24]). There were 8 serious adverse events in the self-monitoring group (4 in each cohort) and 3 in the usual care group (2 in the chronic hypertension cohort and 1 in the gestational hypertension cohort). Conclusions and Relevance: Among pregnant individuals with chronic or gestational hypertension, blood pressure self-monitoring with telemonitoring, compared with usual care, did not lead to significantly improved clinic-based blood pressure control. Trial Registration: ClinicalTrials.gov Identifier: NCT03334149.

Effect of Self-monitoring of Blood Pressure on Diagnosis of Hypertension During Higher-Risk Pregnancy: The BUMP 1 Randomized Clinical Trial.

Importance: Inadequate management of elevated blood pressure (BP) is a significant contributing factor to maternal deaths. Self-monitoring of BP in the general population has been shown to improve the diagnosis and management of hypertension; however, little is known about its use in pregnancy. Objective: To determine whether self-monitoring of BP in higher-risk pregnancies leads to earlier detection of pregnancy hypertension. Design, Setting, and Participants: Unblinded, randomized clinical trial that included 2441 pregnant individuals at higher risk of preeclampsia and recruited at a mean of 20 weeks' gestation from 15 hospital maternity units in England between November 2018 and October 2019. Final follow-up was completed in April 2020. Interventions: Participating individuals were randomized to either BP self-monitoring with telemonitoring (n = 1223) plus usual care or usual antenatal care alone (n = 1218) without access to telemonitored BP. Main Outcomes and Measures: The primary outcome was time to first recorded hypertension measured by a health care professional. Results: Among 2441 participants who were randomized (mean [SD] age, 33 [5.6] years; mean gestation, 20 [1.6] weeks), 2346 (96%) completed the trial. The time from randomization to clinic recording of hypertension was not significantly different between individuals in the self-monitoring group (mean [SD], 104.3 [32.6] days) vs in the usual care group (mean [SD], 106.2 [32.0] days) (mean difference, -1.6 days [95% CI, -8.1 to 4.9]; P = .64). Eighteen serious adverse events were reported during the trial with none judged as related to the intervention (12 [1%] in the self-monitoring group vs 6 [0.5%] in the usual care group). Conclusions and Relevance: Among pregnant individuals at higher risk of preeclampsia, blood pressure self-monitoring with telemonitoring, compared with usual care, did not lead to significantly earlier clinic-based detection of hypertension. Trial Registration: ClinicalTrials.gov Identifier: NCT03334149.

Supporting People With Type 2 Diabetes in the Effective Use of Their Medicine Through Mobile Health Technology Integrated With Clinical Care to Reduce Cardiovascular Risk: Protocol for an Effectiveness and Cost-effectiveness Randomized Controlled Trial.

BACKGROUND: Type 2 diabetes is a common lifelong condition that affects over 400 million people worldwide. The use of effective medications and active self-management can reduce the risk of serious complications. However, people often have concerns when starting new medications and face difficulties in taking their medications regularly. Support provided by brief messages delivered through mobile phone-based SMS text messages can be effective in some long-term conditions. We have identified promising behavior change techniques (BCTs) to promote medication adherence in this population via a systematic review and developed SMS text messages that target these BCTs. Feasibility work has shown that these messages have fidelity to intended BCTs, are acceptable to patients, and are successful in changing the intended determinants of medication adherence. We now plan to test this intervention on a larger scale in a clinical trial. OBJECTIVE: The aim of this trial is to determine the effectiveness and cost-effectiveness of this intervention for reducing cardiovascular risk in people with type 2 diabetes by comparing it with usual care. METHODS: The trial will be a 12-month, multicenter, individually randomized controlled trial in primary care and will recruit adults (aged ≥35 years) with type 2 diabetes in England. Consenting participants will be randomized to receive short SMS text messages intended to affect a change in medication adherence 3 to 4 times per week in addition to usual care. The aim is to test the effectiveness and cost-effectiveness of the intervention when it is added to usual care. The primary clinical outcome will be a composite cardiovascular risk measure. Data including patient-reported measures will be collected at baseline, at 13 and 26 weeks, and at the end of the 12-month follow-up period. With 958 participants (479 in each group), the trial is powered at 92.5% to detect a 4-percentage point difference in cardiovascular risk. The analysis will follow a prespecified plan. A nested quantitative and qualitative process analysis will be used to examine the putative mechanisms of behavior change and wider contextual influences. A health economic analysis will be used to assess the cost-effectiveness of the intervention. RESULTS: The trial has completed the recruitment phase and is in the follow-up phase. The publication of results is anticipated in 2024. CONCLUSIONS: This trial will provide evidence regarding the effectiveness and cost-effectiveness of this intervention for people with type 2 diabetes. TRIAL REGISTRATION: ISRCTN Registry ISRCTN15952379; https://www.isrctn.com/ISRCTN15952379. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32918.

The Use of Wearable Pulse Oximeters in the Prompt Detection of Hypoxemia and During Movement: Diagnostic Accuracy Study.

BACKGROUND: Commercially available wearable (ambulatory) pulse oximeters have been recommended as a method for managing patients at risk of physiological deterioration, such as active patients with COVID-19 disease receiving care in hospital isolation rooms; however, their reliability in usual hospital settings is not known. OBJECTIVE: We report the performance of wearable pulse oximeters in a simulated clinical setting when challenged by motion and low levels of arterial blood oxygen saturation (SaO2). METHODS: The performance of 1 wrist-worn (Wavelet) and 3 finger-worn (CheckMe O2+, AP-20, and WristOx2 3150) wearable, wireless transmission-mode pulse oximeters was evaluated. For this, 7 motion tasks were performed: at rest, sit-to-stand, tapping, rubbing, drinking, turning pages, and using a tablet. Hypoxia exposure followed, in which inspired gases were adjusted to achieve decreasing SaO2 levels at 100%, 95%, 90%, 87%, 85%, 83%, and 80%. Peripheral oxygen saturation (SpO2) estimates were compared with simultaneous SaO2 samples to calculate the root-mean-square error (RMSE). The area under the receiver operating characteristic curve was used to analyze the detection of hypoxemia (ie, SaO2<90%). RESULTS: SpO2 estimates matching 215 SaO2 samples in both study phases, from 33 participants, were analyzed. Tapping, rubbing, turning pages, and using a tablet degraded SpO2 estimation (RMSE>4% for at least 1 device). All finger-worn pulse oximeters detected hypoxemia, with an overall sensitivity of ≥0.87 and specificity of ≥0.80, comparable to that of the Philips MX450 pulse oximeter. CONCLUSIONS: The SpO2 accuracy of wearable finger-worn pulse oximeters was within that required by the International Organization for Standardization guidelines. Performance was degraded by motion, but all pulse oximeters could detect hypoxemia. Our findings support the use of wearable, wireless transmission-mode pulse oximeters to detect the onset of clinical deterioration in hospital settings. TRIAL REGISTRATION: ISRCTN Registry 61535692; http://www.isrctn.com/ISRCTN61535692. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-034404.

Non-contact physiological monitoring of post-operative patients in the intensive care unit.

Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

Experiences of current vital signs monitoring practices and views of wearable monitoring: A qualitative study in patients and nurses.

AIMS: To understand current experiences of vital signs monitoring of patients and clinical staff on a surgical ward, and views on the introduction of wearable ambulatory monitoring into the general ward environment. DESIGN: Qualitative study. METHODS: Semi-structured interviews using topic guides were conducted with 15 patients and 15 nurses on a surgical ward between July 2018 and August 2019. The concept of ambulatory wearable devices for clinical monitoring was introduced at the end of the interview. RESULTS: Three interconnected themes were identified. Vital sign data as evidence for escalation, examined nurses' use of data to support escalation of care and the implications for patients perceived to be deteriorating who have not reached the threshold for escalation. The second theme, Trustworthiness of vital sign data, described nurses' practice of using manual measurements to recheck or confirm automated vital signs readings when concerned. The final theme, finding a balance between continuous and intermittent monitoring, both patients and nurses agreed that although continuous monitoring may improve safety and reassurance, these needed to be balanced with multiple limitations. Factors to be considered included noise pollution, comfort, and impact on patient mobility and independence. Introduction of the concept of ambulatory wearable devices was viewed positively by both groups as offering solutions to some of the issues identified with traditional monitoring. However, most agreed that this would not be suitable for all patients and should not replace direct nurse/patient contact. CONCLUSION: Both patients and staff identified the benefits of continuous monitoring to improve patient safety but, due to limitations, use should be carefully considered and patient-centred. IMPACT: Feedback from nurses and patients suggests there is scope for ambulatory monitoring systems to be integrated into the hospital environment; however, both groups emphasized these should not add more noise to the ward nor replace direct nursing contact.