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Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations
The days and weeks preceding hospitalization are poorly understood because they transpire before patients are seen in conventional clinical care settings. Home health sensors offer opportunities to learn signatures of impending hospitalizations and facilitate early interventions, however the relevan...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936117/ https://www.ncbi.nlm.nih.gov/pubmed/35313571 http://dx.doi.org/10.1101/2022.03.10.22272238 |
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author | Harrington, Nicholas Barba, David Torres Bui, Quan M. Wassell, Andrew Khurana, Sukhdeep Rubarth, Rodrigo B. Sung, Kevin Owens, Robert L. Agnihotri, Parag King, Kevin R. |
author_facet | Harrington, Nicholas Barba, David Torres Bui, Quan M. Wassell, Andrew Khurana, Sukhdeep Rubarth, Rodrigo B. Sung, Kevin Owens, Robert L. Agnihotri, Parag King, Kevin R. |
author_sort | Harrington, Nicholas |
collection | PubMed |
description | The days and weeks preceding hospitalization are poorly understood because they transpire before patients are seen in conventional clinical care settings. Home health sensors offer opportunities to learn signatures of impending hospitalizations and facilitate early interventions, however the relevant biomarkers are unknown. Nocturnal respiratory rate (NRR) is an activity-independent biomarker that can be measured by adherence-independent sensors in the home bed. Here, we report automated longitudinal monitoring of NRR dynamics in a cohort of high-risk recently hospitalized patients using non-contact mechanical sensors under patients’ home beds. Since the distribution of nocturnal respiratory rates in populations is not well defined, we first quantified it in 2,000 overnight sleep studies from the NHLBI Sleep Heart Health Study. This revealed that interpatient variability was significantly greater than intrapatient variability (NRR variances of 11.7 brpm(2) and 5.2 brpm(2) respectively, n=1,844,110 epochs), which motivated the use of patient-specific references when monitoring longitudinally. We then performed adherence-independent longitudinal monitoring in the home beds of 34 high-risk patients and collected raw waveforms (sampled at 80 Hz) and derived quantitative NRR statistics and dynamics across 3,403 patient-nights (n= 4,326,167 epochs). We observed 23 hospitalizations for diverse causes (a 30-day hospitalization rate of 20%). Hospitalized patients had significantly greater NRR deviations from baseline compared to those who were not hospitalized (NRR variances of 3.78 brpm(2) and 0.84 brpm(2) respectively, n= 2,920 nights). These deviations were concentrated prior to the clinical event, suggesting that NRR can identify impending hospitalizations. We analyzed alarm threshold tradeoffs and demonstrated that nominal values would detect 11 of the 23 clinical events while only alarming 2 times in non-hospitalized patients. Taken together, our data demonstrate that NRR dynamics change days to weeks in advance of hospitalizations, with longer prodromes associating with volume overload and heart failure, and shorter prodromes associating with acute infections (pneumonia, septic shock, and covid-19), inflammation (diverticulitis), and GI bleeding. In summary, adherence-independent longitudinal NRR monitoring has potential to facilitate early recognition and management of pre-symptomatic disease. |
format | Online Article Text |
id | pubmed-8936117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-89361172022-03-22 Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations Harrington, Nicholas Barba, David Torres Bui, Quan M. Wassell, Andrew Khurana, Sukhdeep Rubarth, Rodrigo B. Sung, Kevin Owens, Robert L. Agnihotri, Parag King, Kevin R. medRxiv Article The days and weeks preceding hospitalization are poorly understood because they transpire before patients are seen in conventional clinical care settings. Home health sensors offer opportunities to learn signatures of impending hospitalizations and facilitate early interventions, however the relevant biomarkers are unknown. Nocturnal respiratory rate (NRR) is an activity-independent biomarker that can be measured by adherence-independent sensors in the home bed. Here, we report automated longitudinal monitoring of NRR dynamics in a cohort of high-risk recently hospitalized patients using non-contact mechanical sensors under patients’ home beds. Since the distribution of nocturnal respiratory rates in populations is not well defined, we first quantified it in 2,000 overnight sleep studies from the NHLBI Sleep Heart Health Study. This revealed that interpatient variability was significantly greater than intrapatient variability (NRR variances of 11.7 brpm(2) and 5.2 brpm(2) respectively, n=1,844,110 epochs), which motivated the use of patient-specific references when monitoring longitudinally. We then performed adherence-independent longitudinal monitoring in the home beds of 34 high-risk patients and collected raw waveforms (sampled at 80 Hz) and derived quantitative NRR statistics and dynamics across 3,403 patient-nights (n= 4,326,167 epochs). We observed 23 hospitalizations for diverse causes (a 30-day hospitalization rate of 20%). Hospitalized patients had significantly greater NRR deviations from baseline compared to those who were not hospitalized (NRR variances of 3.78 brpm(2) and 0.84 brpm(2) respectively, n= 2,920 nights). These deviations were concentrated prior to the clinical event, suggesting that NRR can identify impending hospitalizations. We analyzed alarm threshold tradeoffs and demonstrated that nominal values would detect 11 of the 23 clinical events while only alarming 2 times in non-hospitalized patients. Taken together, our data demonstrate that NRR dynamics change days to weeks in advance of hospitalizations, with longer prodromes associating with volume overload and heart failure, and shorter prodromes associating with acute infections (pneumonia, septic shock, and covid-19), inflammation (diverticulitis), and GI bleeding. In summary, adherence-independent longitudinal NRR monitoring has potential to facilitate early recognition and management of pre-symptomatic disease. Cold Spring Harbor Laboratory 2022-03-14 /pmc/articles/PMC8936117/ /pubmed/35313571 http://dx.doi.org/10.1101/2022.03.10.22272238 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Harrington, Nicholas Barba, David Torres Bui, Quan M. Wassell, Andrew Khurana, Sukhdeep Rubarth, Rodrigo B. Sung, Kevin Owens, Robert L. Agnihotri, Parag King, Kevin R. Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations |
title | Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations |
title_full | Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations |
title_fullStr | Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations |
title_full_unstemmed | Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations |
title_short | Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations |
title_sort | nocturnal respiratory rate dynamics enable early recognition of impending hospitalizations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936117/ https://www.ncbi.nlm.nih.gov/pubmed/35313571 http://dx.doi.org/10.1101/2022.03.10.22272238 |
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