Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease.
Patients with sickle cell disease (SCD) experience lifelong struggles with both chronic and acute pain, often requiring medical interventMaion. Pain can be managed with medications, but dosages must balance the goal of pain mitigation against the risks of tolerance, addiction and other adverse effec...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1008542 |
| _version_ | 1831716205792067584 |
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| author | Mark J Panaggio Daniel M Abrams Fan Yang Tanvi Banerjee Nirmish R Shah |
| author_facet | Mark J Panaggio Daniel M Abrams Fan Yang Tanvi Banerjee Nirmish R Shah |
| author_sort | Mark J Panaggio |
| collection | DOAJ |
| description | Patients with sickle cell disease (SCD) experience lifelong struggles with both chronic and acute pain, often requiring medical interventMaion. Pain can be managed with medications, but dosages must balance the goal of pain mitigation against the risks of tolerance, addiction and other adverse effects. Setting appropriate dosages requires knowledge of a patient's subjective pain, but collecting pain reports from patients can be difficult for clinicians and disruptive for patients, and is only possible when patients are awake and communicative. Here we investigate methods for estimating SCD patients' pain levels indirectly using vital signs that are routinely collected and documented in medical records. Using machine learning, we develop both sequential and non-sequential probabilistic models that can be used to infer pain levels or changes in pain from sequences of these physiological measures. We demonstrate that these models outperform null models and that objective physiological data can be used to inform estimates for subjective pain. |
| first_indexed | 2024-12-21T00:35:01Z |
| format | Article |
| id | doaj.art-f7efe4a068224b61891d0ec406aed44c |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-21T00:35:01Z |
| publishDate | 2021-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-f7efe4a068224b61891d0ec406aed44c2022-12-21T19:21:49ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-03-01173e100854210.1371/journal.pcbi.1008542Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease.Mark J PanaggioDaniel M AbramsFan YangTanvi BanerjeeNirmish R ShahPatients with sickle cell disease (SCD) experience lifelong struggles with both chronic and acute pain, often requiring medical interventMaion. Pain can be managed with medications, but dosages must balance the goal of pain mitigation against the risks of tolerance, addiction and other adverse effects. Setting appropriate dosages requires knowledge of a patient's subjective pain, but collecting pain reports from patients can be difficult for clinicians and disruptive for patients, and is only possible when patients are awake and communicative. Here we investigate methods for estimating SCD patients' pain levels indirectly using vital signs that are routinely collected and documented in medical records. Using machine learning, we develop both sequential and non-sequential probabilistic models that can be used to infer pain levels or changes in pain from sequences of these physiological measures. We demonstrate that these models outperform null models and that objective physiological data can be used to inform estimates for subjective pain.https://doi.org/10.1371/journal.pcbi.1008542 |
| spellingShingle | Mark J Panaggio Daniel M Abrams Fan Yang Tanvi Banerjee Nirmish R Shah Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease. PLoS Computational Biology |
| title | Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease. |
| title_full | Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease. |
| title_fullStr | Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease. |
| title_full_unstemmed | Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease. |
| title_short | Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease. |
| title_sort | can subjective pain be inferred from objective physiological data evidence from patients with sickle cell disease |
| url | https://doi.org/10.1371/journal.pcbi.1008542 |
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