Comparing Continuous with Periodic Vital Sign Scoring for Clinical Deterioration Using a Patient Data Model.

To evaluate a minute-by-minute monitoring algorithm against a periodic early warning score (EWS) in detecting clinical deterioration and workload. Periodic EWSs suffer from large measurement intervals, causing late detection of deterioration. This might be prevented by continuous vital sign monitoring with a real-time algorithm such as the Visensia Safety Index (VSI). This prospective comparative data modeling cohort study (NCT04189653) compares continuous algorithmic alerts against periodic EWS in continuous monitored medical and surgical inpatients. We evaluated sensitivity, frequency, number of warnings needed to evaluate (NNE) and time of initial alert till escalation of care (EOC): Rapid Response Team activation, unplanned ICU admission, emergency surgery, or death. Also, the percentage of VSI alerting minutes was compared between patients with or without EOC. In 1529 admissions continuous VSI warned for 55% of EOC (95% CI: 45-64%) versus 51% (95% CI: 41-61%) by periodic EWS. NNE for VSI was 152 alerts per detected EOC (95% CI: 114-190) compared to 21 (95% CI: 17-28). It generated 0.99 warnings per day per patient compared to 0.13. Time from detection score till escalation was 8.3 hours (IQR: 2.6-24.8) with VSI versus 5.2 (IQR: 2.7-12.3) hours with EWS (P=0.074). The percentage of warning VSI minutes was higher in patients with EOC than in stable patients (2.36% vs 0.81%, P<0.001). Although sensitivity of detection was not significantly improved continuous vital sign monitoring shows potential for earlier alerts for deterioration compared to periodic EWS. A higher percentage of alerting minutes may indicate risk for deterioration.

The Effect of Continuous Versus Periodic Vital Sign Monitoring on Disease Severity of Patients with an Unplanned ICU Transfer.

Continuous vital sign monitoring (CM) may detect ward patient's deterioration earlier than periodic monitoring. This could result in timely ICU transfers or in a transfer delay due to misperceived higher level of care on the ward. The primary objective of this study was to compare patient's disease severity upon unplanned ICU transfer, before and after CM implementation. We included a one-year period before and after CM implementation between August 1, 2017 - July 31, 2019. Before implementation, surgical and internal medicine patients' vital signs were periodically monitored, compared to continuous monitoring with wireless linkage to hospital systems after implementation. In both periods the same early warning score (EWS) protocol was in place. Primary outcome was disease severity scores upon ICU transfer. Secondary outcomes were ICU and hospital length of stay, incidence of mechanical ventilation and ICU mortality. In the two one-year periods 93 and 59 unplanned ICU transfer episodes were included, respectively. Median SOFA (3 (2-6) vs 4 (2-7), p = .574), APACHE II (17 (14-20) vs 16 (14-21), p = .824) and APACHE IV (59 (46-67) vs 50 (36-65), p = .187) were comparable between both periods, as were the median ICU LOS (3.0 (1.7-5.8) vs 3.1 (1.6-6.1), p.962), hospital LOS (23.6 (11.5-38.0) vs 19 (13.9-39.2), p = .880), incidence of mechanical ventilation (28 (47%) vs 22 (54%), p.490), and ICU mortality (11 (13%) vs 10 (19%), p.420). This study shows no difference in disease severity upon unplanned ICU transfer after CM implementation for patients who have deteriorated on the ward.

Effect of continuous wireless vital sign monitoring on unplanned ICU admissions and rapid response team calls: a before-and-after study.

BACKGROUND: Continuous vital sign monitoring may potentially be improved through the use of wearable monitors linked wirelessly to hospital electronic patient records. By improving early detection of physiological deterioration this approach may save lives. METHODS: We performed a single-centre before-and-after study including surgical and medical patients at a university hospital in The Netherlands. The study intervention was continuous vital sign monitoring using wearable monitors linked wirelessly to hospital systems. The co-primary outcomes were unplanned ICU admission and rapid response team calls. Secondary outcomes were length of hospital stay and in-patient death. RESULTS: Our baseline cohort included 2466 admissions and our intervention cohort included 2303 admissions recruited from August 2017 to July 2019. Patients in the intervention cohort experienced fewer unplanned ICU admissions (84 [3.4%] vs 54 [2.3%]; P=0.03) and fewer rapid response team calls (107 [4.3%] vs 71 [3.1%]; P=0.02). The number of rapid response team calls that did not result in ICU admission also declined (70 [2.8%] vs 45 [2.0%]; P=0.05). The number of rapid response team calls that did result in ICU admission was not significantly different (52 [2.1%] vs 36 [1.6%]; P=0.16). There were no differences in hospital stay or in-patient deaths between the two study periods. CONCLUSIONS: Continuous monitoring of patient vital signs using wearable monitoring technology linked wirelessly to hospital systems was associated with a reduction in unplanned ICU admissions and rapid response team calls. Further research is necessary to confirm the impact of this approach on patient survival.

Effect of Hypoglycemia on Heart Rate Variability in People with Type 1 Diabetes and Impaired Awareness of Hypoglycemia.

BACKGROUND: People with impaired awareness of hypoglycemia (IAH) are at elevated risk of severe, potentially hazardous, hypoglycemia and would benefit from a device alerting to hypoglycemia. Heart rate variability (HRV) changes with hypoglycemia due to sympathetic activity. Since IAH is associated with suppressed sympathetic activity, we investigated whether hypoglycemia elicits a measurable change in HRV in patients with T1D and IAH. METHOD: Eligible participants underwent a modified hyperinsulinemic euglycemic hypoglycemic clamp (glucose nadir, 43.1 ± 0.90 mg/dl), while HRV was measured by a VitalConnect HealthPatch. Measurements of HRV included Root Mean Square of the Successive Differences (RMSSD) and low to high frequency (LF:HF) ratio. Wilcoxon rank-sum test was used for testing within-subject HRV changes. RESULTS: We included 12 participants (8 female, mean age 57 ± 12 years, mean HbA1c 57 ± 5 mmol/mol (7.4 ± 0.4%)). Symptoms increased from 4.0 (1.5-7.0) at euglycemia to 7.5 (5.0-11.0) during hypoglycemia (P = .003). In response to hypoglycemia, the LF:HF ratio and RMSSD increased when normalized for data obtained during euglycemia (both P < .01). The LF:HF ratio increased in 6 participants (50%) and declined in one other participant (8%). The RMSSD decreased in 3 (25%) and increased in 4 (33%) participants. In 2 patients, no change in HRV could be detected in response to hypoglycemia. CONCLUSIONS: This study reveals that hypoglycemia-induced changes in HRV are retained in the majority of people with T1D and IAH, and that these changes can be detected by a wearable device. Real-time HRV seems usable for detection of hypoglycemia in patients with IAH.

Algorithms for Prediction of Clinical Deterioration on the General Wards: A Scoping Review.

OBJECTIVE: The primary objective of this scoping review was to identify and describe state-of-the-art models that use vital sign monitoring to predict clinical deterioration on the general ward. The secondary objective was to identify facilitators, barriers, and effects of implementing these models. DATA SOURCES: PubMed, Embase, and CINAHL databases until November 2020. STUDY SELECTION: We selected studies that compared vital signs-based automated real-time predictive algorithms to current track-and-trace protocols in regard to the outcome of clinical deterioration in a general ward population. DATA EXTRACTION: Study characteristics, predictive characteristics and barriers, facilitators, and effects. RESULTS: We identified 1741 publications, 21 of which were included in our review. Two of the these were clinical trials, 2 were prospective observational studies, and the remaining 17 were retrospective studies. All of the studies focused on hospitalized adult patients. The reported area under the receiver operating characteristic curves ranged between 0.65 and 0.95 for the outcome of clinical deterioration. Positive predictive value and sensitivity ranged between 0.223 and 0.773 and from 7.2% to 84.0%, respectively. Input variables differed widely, and predicted endpoints were inconsistently defined. We identified 57 facilitators and 48 barriers to the implementation of these models. We found 68 reported effects, 57 of which were positive. CONCLUSION: Predictive algorithms can detect clinical deterioration on the general ward earlier and more accurately than conventional protocols, which in one recent study led to lower mortality. Consensus is needed on input variables, predictive time horizons, and definitions of endpoints to better facilitate comparative research.

Wearable Patch Heart Rate Variability Is an Early Marker of Systemic Inflammation During Experimental Human Endotoxemia.

INTRODUCTION: Early diagnosis and treatment can reduce the risk of organ failure and mortality in systemic inflammatory conditions. Heart rate variability (HRV) has potential for early identification of the onset of systemic inflammation, as it may detect changes in sympathetic nervous system activity resulting from the developing inflammatory response before clinical signs appear. With the use of new methodologies, we investigated the onset and kinetics of HRV changes as well as several inflammatory parameters and symptoms during experimental human endotoxemia, a model of systemic inflammation in humans in vivo. PATIENTS AND METHODS: Healthy volunteers were intravenously administered LPS (n = 15) or placebo (n = 15). HRV was determined using a wireless wearable device, and parameters low to high frequency (LF:HF) ratio, root mean square of the successive differences (RMSSD), and standard deviation of normal-to-normal R-R intervals (SDNN)were calculated through 1-min-rolling 6-min windows. Plasma cytokine levels and flu-like symptoms and vital signs were serially assessed. RESULTS: The increase in LF:HF ratio, reflecting sympathetic predominance, was more pronounced in the LPS group compared to the placebo group, with the difference becoming statistically significant 65 min following LPS administration (1.63 [1.42-1.83] vs. 1.28 [1.11-1.44], P = 0.005). Significant between-group differences in RMSSD and SDNN were observed from 127 to 140 min post-LPS administration onwards, respectively. Plasma cytokine levels showed significant between-group differences staring 60 min post-LPS. For symptom score, heart rate, temperature, and diastolic blood pressure, significant differences compared with the placebo group were observed at 90, 118, 120, and 124 min post-LPS, respectively. CONCLUSION: In a controlled human model of systemic inflammation, elevations in the LF:HF ratio followed very shortly after elevations in plasma cytokine levels and preceded onset of flu-like symptoms and alterations in vital signs. HRV may represent a promising non-invasive tool for early detection of a developing systemic inflammatory response.

Low compliance to a vital sign safety protocol on general hospital wards: A retrospective cohort study.

BACKGROUND: Periodic vital sign monitoring is commonly used to detect clinical deterioration. Incomplete assessment of Early Warning Score (EWS) and poor protocol compliance may negatively impact nurses' responsiveness to critical situations. OBJECTIVE: This study assesses the quality of recorded EWSs and the degree of overall protocol compliance and protocol compliance in adverse event patients, in a centre that is an early adopter of an EWS safety protocol. DESIGN: Retrospective single-centre cohort study. SETTING: General hospital wards of a tertiary referral university medical centre. PARTICIPANTS: 48,864 patients admitted to general wards between 2015 and 2018. METHODS: Vital sign and Modified EWS (MEWS) data were collected from the electronic health record. MEWS completeness was evaluated by determining the proportion of missing values for each vital sign. To evaluate protocol compliance, we assessed whether the elapsed time between consecutive MEWSs was within the protocollary time as dictated by the MEWS protocol. Outcome measures were overall MEWS completeness, and both overall protocol compliance and protocol compliance specifically in the 24 h before adverse events. RESULTS: All required items to calculate a MEWS were present in 76 percent of the 1,663,743 vital sign measurements. Overall protocol compliance was 62 percent. For the low, mid-range and high MEWS groups, protocol compliances were 67, 47 and 30 percent, respectively. Time-to-next-MEWS exceeded protocol-recommended timing by up to 9 h for a substantial amount of MEWSs in the mid- and high-range MEWS groups. In patients with adverse events, compliance to the MEWS protocol during the 24 h prior to the events was 66 percent in aggregate, ranging from 80% in low MEWS groups, 74% in the mid-range, and 49% in the high MEWS groups. In the high MEWS group, improvements in protocol compliance were primarily noted in five hours immediately preceding the event. CONCLUSIONS: EWS assessments were incomplete in one-quarter of measurements. Compliance to a MEWS safety protocol was generally low, specifically when the protocol mandated more frequent MEWS assessments. Although more MEWSs were recorded in patients with adverse events, the increase in vital sign measurements' frequency mostly occurred shortly before the event manifested. This finding suggests missed opportunities to detect clinical deterioration.

Continuous Monitoring of Vital Signs in the General Ward Using Wearable Devices: Randomized Controlled Trial.

BACKGROUND: Wearable devices can be used for continuous patient monitoring in the general ward, increasing patient safety. Little is known about the experiences and expectations of patients and health care professionals regarding continuous monitoring with these devices. OBJECTIVE: This study aimed to identify positive and negative effects as well as barriers and facilitators for the use of two wearable devices: ViSi Mobile (VM) and HealthPatch (HP). METHODS: In this randomized controlled trial, 90 patients admitted to the internal medicine and surgical wards of a university hospital in the Netherlands were randomly assigned to continuous vital sign monitoring using VM or HP and a control group. Users' experiences and expectations were addressed using semistructured interviews. Nurses, physician assistants, and medical doctors were also interviewed. Interviews were analyzed using thematic content analysis. Psychological distress was assessed using the State Trait Anxiety Inventory and the Pain Catastrophizing Scale. The System Usability Scale was used to assess the usability of both devices. RESULTS: A total of 60 patients, 20 nurses, 3 physician assistants, and 6 medical doctors were interviewed. We identified 47 positive and 30 negative effects and 19 facilitators and 36 barriers for the use of VM and HP. Frequently mentioned topics included earlier identification of clinical deterioration, increased feelings of safety, and VM lines and electrodes. No differences related to psychological distress and usability were found between randomization groups or devices. CONCLUSIONS: Both devices were well received by most patients and health care professionals, and the majority of them encouraged the idea of monitoring vital signs continuously in the general ward. This comprehensive overview of barriers and facilitators of using wireless devices may serve as a guide for future researchers, developers, and health care institutions that consider implementing continuous monitoring in the ward. TRIAL REGISTRATION: Clinicaltrials.gov NCT02933307; http://clinicaltrials.gov/ct2/show/NCT02933307.

Feasibility of a New Cuffless Device for Ambulatory Blood Pressure Measurement in Patients With Hypertension: Mixed Methods Study.

BACKGROUND: Frequent home blood pressure (BP) measurements result in a better estimation of the true BP. However, traditional cuff-based BP measurements are troublesome for patients. OBJECTIVE: This study aimed to evaluate the feasibility of a cuffless device for ambulatory systolic blood pressure (SBP) measurement. METHODS: This was a mixed method feasibility study in patients with hypertension. Performance of ambulatory SBPs with the device was analyzed quantitatively by intrauser reproducibility and comparability to a classic home BP monitor. Correct use by the patients was checked with video, and user-friendliness was assessed using a validated questionnaire, the System Usability Scale (SUS). Patient experiences were assessed using qualitative interviews. RESULTS: A total of 1020 SBP measurements were performed using the Checkme monitor in 11 patients with hypertension. Duplicate SBPs showed a high intrauser correlation (R=0.86, P<.001). SBPs measured by the Checkme monitor did not correlate well with those of the different home monitors (R=0.47, P=.007). However, the mean SBPs measured by the Checkme and home monitors over the 3-week follow-up were strongly correlated (R=0.75, P=.008). In addition, 36.4% (n=4) of the participants performed the Checkme measurements without any mistakes. The mean SUS score was 86.4 (SD 8.3). The most important facilitator was the ease of using the Checkme monitor. Most important barriers included the absence of diastolic BP and the incidental difficulties in obtaining an SBP result. CONCLUSIONS: Given the good intrauser reproducibility, user-friendliness, and patient experience, all of which facilitate patients to perform frequent measurements, cuffless BP monitoring may change the way patients measure their BP at home in the context of ambulant hypertension management.

Early Detection of Hypoglycemia in Type 1 Diabetes Using Heart Rate Variability Measured by a Wearable Device.

OBJECTIVE: Changes in heart rate variability (HRV) occur at the initiation of hypoglycemia due to sympathetic nervous system activity. We investigated the use of HRV detection by a wearable device as an early alert for hypoglycemia. RESEARCH DESIGN AND METHODS: This proof-of-principle study included 23 patients with type 1 diabetes (14 women, mean age 42 ± 11 years). Patients wore a VitalConnect HealthPatch for 5 days. Hypoglycemia was defined as glucose ≤70 mg/dL (≤3.9 mmol/L) by fingerstick measurement. HRV was analyzed in standardized periods before the hypoglycemic event. RESULTS: Sixty-six hypoglycemic events were recorded. Hypoglycemia caused a typical HRV pattern in 36 (55%) of the hypoglycemic events. Eighteen events (27%) showed an atypical pattern. Ten events were unclassified (15%), and two did not display a change in HRV (3%). CONCLUSIONS: Hypoglycemia causes early changes in HRV that can be detected by a wearable device. Measuring real-time HRV seems promising for early hypoglycemia detection.

Wireless and continuous monitoring of vital signs in patients at the general ward.

BACKGROUND: Clinical deterioration regularly occurs in hospitalized patients potentially resulting in life threatening events. Early warning scores (EWS), like the Modified Early Warning Score (MEWS), assist care givers in assessing patients' clinical situation, but cannot alert for deterioration between measurements. New devices, like the ViSi Mobile (VM) and HealthPatch (HP) allow for continuous monitoring and can alert deterioration in an earlier phase. VM and HP were tested regarding MEWS calculation compared to nurse measurements, and detection of high MEWS in periods between nurse observations. METHODS: This quantitative study was part of a randomized controlled trial. Sixty patients of the surgical and internal medicine ward with a minimal expected hospitalization time of three days were randomized to VM or HP continuous monitoring in addition to regular nurse MEWS measurements for 24-72 h. RESULTS: Median VM and HP MEWS were higher than nurse measurements (2.7 vs. 1.9 and 1.9 vs. 1.3, respectively), predominantly due to respiratory rate measurement differences. During 1282 h VM and 1886 h HP monitoring, 71 (14 patients) and 32 (7 patients) high MEWS periods were detected during the non-observed periods. Time between VM or HP based high MEWS and next regular nurse measurement ranged from 0 to 9 (HP) and 10 (VM) hours. CONCLUSIONS: Both VM and HP are promising for continuous vital sign monitoring and may be more accurate than nurses. High MEWS can be detected in hospitalized patients around the clock and clinical deterioration at an earlier phase during unobserved periods.