S. Lua, D. Lowe, A. Taylor, M. Sim, B. Henderson, C. Trueman, O. Meredith, S. Burns, P. McGuinness, C. Carlin
{"title":"P24 COVID-19高级呼吸生理学(CARP)可穿戴呼吸监测:早期见解","authors":"S. Lua, D. Lowe, A. Taylor, M. Sim, B. Henderson, C. Trueman, O. Meredith, S. Burns, P. McGuinness, C. Carlin","doi":"10.1136/thorax-2021-btsabstracts.134","DOIUrl":null,"url":null,"abstract":"P24 Figure 1CARP trial wearable respiratory rate, respiratory support and outcome data from 3 patients with severe COVID-19[Figure omitted. See PDF]Results156 patients were screened, with 77 recruited to the CARP trial. 32 patients required non-invasive respiratory support, of which 14 were escalated to mechanical intubation. 17 patients died within trial.Bland-Altman analyses of paired RR data confirmed that wearable sensor data shows good agreement with critical care RR monitoring (Phillips Intellivue MX700), and that ward-based intermittent clinician RR measurements were imprecise.From the initial utility review of CARP physiology data visualisations, rising hourly average RR >25/min is associated with subsequent patient deterioration. Improving and stable hourly average RR of <25/min associates with stable respiratory failure and improvement to hospital discharge (figure 1).ConclusionContinuous wearable respiratory rate remote monitoring in COVID-19 inpatients is feasible. Planned machine learning and time-series analyses of the detailed physiology and clinical endpoint data will determine appropriate cut-offs and feature importance for deteriorating patient risk predictions. The CARP clinical dashboard provides an infrastructure for future implementation and evaluation of these AI insights.","PeriodicalId":319670,"journal":{"name":"Virtual monitoring in COVID-19","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"P24 COVID-19 advanced respiratory physiology (CARP) wearable respiratory monitoring: early insights\",\"authors\":\"S. Lua, D. Lowe, A. Taylor, M. Sim, B. Henderson, C. Trueman, O. Meredith, S. Burns, P. McGuinness, C. Carlin\",\"doi\":\"10.1136/thorax-2021-btsabstracts.134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"P24 Figure 1CARP trial wearable respiratory rate, respiratory support and outcome data from 3 patients with severe COVID-19[Figure omitted. See PDF]Results156 patients were screened, with 77 recruited to the CARP trial. 32 patients required non-invasive respiratory support, of which 14 were escalated to mechanical intubation. 17 patients died within trial.Bland-Altman analyses of paired RR data confirmed that wearable sensor data shows good agreement with critical care RR monitoring (Phillips Intellivue MX700), and that ward-based intermittent clinician RR measurements were imprecise.From the initial utility review of CARP physiology data visualisations, rising hourly average RR >25/min is associated with subsequent patient deterioration. Improving and stable hourly average RR of <25/min associates with stable respiratory failure and improvement to hospital discharge (figure 1).ConclusionContinuous wearable respiratory rate remote monitoring in COVID-19 inpatients is feasible. Planned machine learning and time-series analyses of the detailed physiology and clinical endpoint data will determine appropriate cut-offs and feature importance for deteriorating patient risk predictions. The CARP clinical dashboard provides an infrastructure for future implementation and evaluation of these AI insights.\",\"PeriodicalId\":319670,\"journal\":{\"name\":\"Virtual monitoring in COVID-19\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Virtual monitoring in COVID-19\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/thorax-2021-btsabstracts.134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virtual monitoring in COVID-19","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/thorax-2021-btsabstracts.134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
P24 Figure 1CARP trial wearable respiratory rate, respiratory support and outcome data from 3 patients with severe COVID-19[Figure omitted. See PDF]Results156 patients were screened, with 77 recruited to the CARP trial. 32 patients required non-invasive respiratory support, of which 14 were escalated to mechanical intubation. 17 patients died within trial.Bland-Altman analyses of paired RR data confirmed that wearable sensor data shows good agreement with critical care RR monitoring (Phillips Intellivue MX700), and that ward-based intermittent clinician RR measurements were imprecise.From the initial utility review of CARP physiology data visualisations, rising hourly average RR >25/min is associated with subsequent patient deterioration. Improving and stable hourly average RR of <25/min associates with stable respiratory failure and improvement to hospital discharge (figure 1).ConclusionContinuous wearable respiratory rate remote monitoring in COVID-19 inpatients is feasible. Planned machine learning and time-series analyses of the detailed physiology and clinical endpoint data will determine appropriate cut-offs and feature importance for deteriorating patient risk predictions. The CARP clinical dashboard provides an infrastructure for future implementation and evaluation of these AI insights.