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Review 1: "Prediction of deterioration from COVID-19 in patients in skilled nursing facilities using wearable and contact-free devices: a feasibility study"

This preprint aims to use wearable devices to predict deterioration from COVID-19 in skilled nursing facility patients. Reviewers suggested improvements in determining statistical significance, clarifying the data collection period, and discussing viral transmission implications.

Published onMay 24, 2022
Review 1: "Prediction of deterioration from COVID-19 in patients in skilled nursing facilities using wearable and contact-free devices: a feasibility study"
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key-enterThis Pub is a Review of
Prediction of deterioration from COVID-19 in patients in skilled nursing facilities using wearable and contact-free devices: a feasibility study

AbstractBackground and RationaleApproximately 35% of all COVID-19 deaths occurred in Skilled Nursing Facilities (SNFs). In a healthy general population, wearables have shown promise in providing early alerts for actionable interventions during the pandemic. We tested this promise in a cohort of SNFs patients diagnosed with COVID-19 and admitted for post-acute care under quarantine. We tested if 1) deployment of wearables and contact-free biosensors is feasible in the setting of SNFs and 2) they can provide early and actionable insights into deterioration.MethodsThis prospective clinical trial has been IRB-approved (NCT04548895). We deployed two commercially available devices detecting continuously every 2-3 minutes heart rate (HR), respiratory rate (RR) and uniquely providing the following biometrics: 1) the wrist-worn bracelet by Biostrap yielded continuous oxygen saturation (O2Sat), 2) the under-mattress ballistocardiography sensor by Emfit tracked in-bed activity, tossing, and sleep disturbances. Patients also underwent routine monitoring by staff every 2-4 h. For death outcomes, cases are reported due to the small sample size. For palliative care versus at-home discharges, we report mean±SD at p<0.05.ResultsFrom 12/2020 - 03/2021, we approached 26 PCR-confirmed SarsCoV2-positive patients at two SNFs: 5 declined, 21 were enrolled into monitoring by both sensors (female=13, male=8; age 77.2±9.1). We recorded outcomes as discharged to home (8, 38%), palliative care (9, 43%) or death (4, 19%). The O2Sat threshold of 91% alerted for intervention. Biostrap captured hypoxic events below 91% nine times as often as the routine intermittent pulse oximetry. In the patient deceased, two weeks prior we observed a wide range of O2Sat values (65-95%) captured by the Biostrap device and not noticeable with the routine vital sign spot checks. In this patient, the Emfit sensor yielded a markedly reduced RR (7/min) in contrast to 18/min from two routine spot checks performed in the same period of observation as well as compared to the seven patients discharged home over a total of 86 days of monitoring (RR 19± 4). Among the patients discharged to palliative care, a total of 76 days were monitored, HR did not differ compared to the patients discharged home (68±8 vs 70±7 bpm). However, we observed a statistically significant reduction of RR at 16±4/min as well as the variances in RR (10±6 vs 19±4/min vs16±13) and activity of palliative care patients vs. patients discharged home.Conclusion/DiscussionWe demonstrate that wearables and under-mattress sensors can be integrated successfully into the SNF workflows and are well tolerated by the patients. Moreover, specific early changes of oxygen saturation fluctuations and other biometrics herald deterioration from COVID-19 two weeks in advance and evaded detection without the devices. Wearable devices and under-mattress sensors in SNFs hold significant potential for early disease detection.

RR:C19 Evidence Scale rating by reviewer:

  • Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.



This manuscript describes the feasibility of the use of two devices for early detection of deterioration in patients with COVID-19 admitted to two skilled nursing facilities (SNF). The data collected from the devices were compared to the current study facilities’ standard of care which included intermittent measurement of clinical parameters. The authors concluded that it is feasible to employ the use of these devices in the SNF setting.

The manuscript provides important data to support the imperative for the use of continuous monitoring in this patient population and the benefits of both the wearable and environmental devices studied. The authors also discuss significant differences in values obtained using manual versus an electronic collection of physiologic parameters in the early detection of deterioration in the COVID-19 patient but did not include significance values (e.g., p-values).

In summary, I recommend publication with the RR: C19 Journal with the following recommended improvements:

  1. Enhancing the background information to describe the successful use of similar devices in the early detection of deterioration in other patient populations.

  2. Relying on primary sources for statistical data (example: on page 4 the authors cite the NY Times COVID-19 statistics in the narrative, but the graph is from the CDC and the numbers do not match).

  3. Including statistical significance values to support their findings.

  4. Providing key demographic data related to ethnicity has been shown to be a significant risk factor in COVID-19 outcomes.

  5. Addressing limitations of the study.

  6. Reviewing punctuation and grammar/sentence structure which was a bit awkward throughout the manuscript.


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