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Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach
BACKGROUND: Vaso‐occlusive crises (VOCs) are the hallmark of sickle cell disease (SCD), with higher severity among hospitalized patients. Clustering hospitalizations with similar pain trajectories could identify vulnerable patient subgroups. Aims were to (a) identify clusters of hospitalizations bas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941740/ https://www.ncbi.nlm.nih.gov/pubmed/33709084 http://dx.doi.org/10.1002/jha2.114 |
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author | Rodday, Angie Mae Esham, Kimberly S. Savidge, Nicole Parsons, Susan K. |
author_facet | Rodday, Angie Mae Esham, Kimberly S. Savidge, Nicole Parsons, Susan K. |
author_sort | Rodday, Angie Mae |
collection | PubMed |
description | BACKGROUND: Vaso‐occlusive crises (VOCs) are the hallmark of sickle cell disease (SCD), with higher severity among hospitalized patients. Clustering hospitalizations with similar pain trajectories could identify vulnerable patient subgroups. Aims were to (a) identify clusters of hospitalizations based on pain trajectories; (b) identify factors associated with these clusters; and (c) determine the association between these clusters and 30‐day readmissions. METHODS: We retrospectively included 350 VOC hospitalizations from 2013 to 2016 among 59 patients. Finite mixture modeling identified clusters of hospitalizations from intercepts and slopes of pain trajectories during the hospitalization. Generalized estimating equations for multinomial and logistic models were used to identify factors associated with clusters of hospitalizations and 30‐day readmissions, respectively, while accounting for multiple hospitalizations per patient. RESULTS: Three clusters of hospitalizations based on pain trajectories were identified: slow (n = 99), moderate (n = 207), and rapid (n = 44) decrease in pain scores. In multivariable analysis, SCD complications, female gender, and affective disorders were associated with clusters with slow or moderate decrease in pain scores (compared to rapid decrease). Although univariate analysis found that the cluster with moderate decrease in pain scores was associated with lower odds of 30‐day readmissions compared to the cluster with slow decrease, it was nonsignificant in multivariable analysis. SCD complications were associated with higher odds of 30‐day readmissions and older age was associated with lower odds of 30‐day readmissions. CONCLUSIONS: Our results highlight variability in pain trajectories among patients with SCD experiencing VOC and provide a novel approach for identifying subgroups of patients that could benefit from more intensive follow‐up. |
format | Online Article Text |
id | pubmed-7941740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79417402021-11-01 Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach Rodday, Angie Mae Esham, Kimberly S. Savidge, Nicole Parsons, Susan K. EJHaem Sickle Cell, Thrombosis, and Haematology BACKGROUND: Vaso‐occlusive crises (VOCs) are the hallmark of sickle cell disease (SCD), with higher severity among hospitalized patients. Clustering hospitalizations with similar pain trajectories could identify vulnerable patient subgroups. Aims were to (a) identify clusters of hospitalizations based on pain trajectories; (b) identify factors associated with these clusters; and (c) determine the association between these clusters and 30‐day readmissions. METHODS: We retrospectively included 350 VOC hospitalizations from 2013 to 2016 among 59 patients. Finite mixture modeling identified clusters of hospitalizations from intercepts and slopes of pain trajectories during the hospitalization. Generalized estimating equations for multinomial and logistic models were used to identify factors associated with clusters of hospitalizations and 30‐day readmissions, respectively, while accounting for multiple hospitalizations per patient. RESULTS: Three clusters of hospitalizations based on pain trajectories were identified: slow (n = 99), moderate (n = 207), and rapid (n = 44) decrease in pain scores. In multivariable analysis, SCD complications, female gender, and affective disorders were associated with clusters with slow or moderate decrease in pain scores (compared to rapid decrease). Although univariate analysis found that the cluster with moderate decrease in pain scores was associated with lower odds of 30‐day readmissions compared to the cluster with slow decrease, it was nonsignificant in multivariable analysis. SCD complications were associated with higher odds of 30‐day readmissions and older age was associated with lower odds of 30‐day readmissions. CONCLUSIONS: Our results highlight variability in pain trajectories among patients with SCD experiencing VOC and provide a novel approach for identifying subgroups of patients that could benefit from more intensive follow‐up. John Wiley and Sons Inc. 2020-10-22 /pmc/articles/PMC7941740/ /pubmed/33709084 http://dx.doi.org/10.1002/jha2.114 Text en © 2020 The Authors. eJHaem published by British Society for Haematology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Sickle Cell, Thrombosis, and Haematology Rodday, Angie Mae Esham, Kimberly S. Savidge, Nicole Parsons, Susan K. Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach |
title | Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach |
title_full | Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach |
title_fullStr | Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach |
title_full_unstemmed | Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach |
title_short | Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach |
title_sort | clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: a data‐driven approach |
topic | Sickle Cell, Thrombosis, and Haematology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941740/ https://www.ncbi.nlm.nih.gov/pubmed/33709084 http://dx.doi.org/10.1002/jha2.114 |
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