TY - JOUR
T1 - Cluster modelling of longitudinal disease data
T2 - asthma and potential clinical phenotypes
AU - Wesonga, Ronald
AU - Bakheit, Charles
AU - Ababneh, Faisal
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. The internal grant number IG/SCI/DOMS/17/01 of the College of Science, Sultan Qaboos University;Sultan Qaboos University [IG/SCI/DOMS/17/01]; We would like to thank Dr Abraham Owino and Professor Fabian Nabugoomu for their helpful discussions that improved the quality of this paper.
Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - Asthma and chronic obstructive pulmonary diseases are assiduous inflammatory diseases with substantial effects on health and well-being of individuals, and are known to pose great financial implications. This study aimed to explore a possibility of potential clusters of these diseases based on the reported incidences by the Ministry of Health, Sultanate of Oman. Maternal asthma has been found to be a major risk factor for asthma in infants. However, the clustering of asthma morbidity has not been explained fully. In our study, we developed five potential clusters and mapped them onto asthma clinical phenotypes using the complete linkage hierarchical agglomerative cluster models. Accordingly, the majority (92%) who had relatively easy to control symptoms of asthma were the younger male, while the much older female patients experienced difficult to control asthma symptoms. Asthma disease clustering facilitates targeted efforts to prioritize medical response, control and management of the disease. Further research is sought to develop cost of illness optimization models for healthcare resource allocation so as to combat the scourge.
AB - Asthma and chronic obstructive pulmonary diseases are assiduous inflammatory diseases with substantial effects on health and well-being of individuals, and are known to pose great financial implications. This study aimed to explore a possibility of potential clusters of these diseases based on the reported incidences by the Ministry of Health, Sultanate of Oman. Maternal asthma has been found to be a major risk factor for asthma in infants. However, the clustering of asthma morbidity has not been explained fully. In our study, we developed five potential clusters and mapped them onto asthma clinical phenotypes using the complete linkage hierarchical agglomerative cluster models. Accordingly, the majority (92%) who had relatively easy to control symptoms of asthma were the younger male, while the much older female patients experienced difficult to control asthma symptoms. Asthma disease clustering facilitates targeted efforts to prioritize medical response, control and management of the disease. Further research is sought to develop cost of illness optimization models for healthcare resource allocation so as to combat the scourge.
KW - Asthma
KW - clinical phenotypes
KW - hierarchical agglomerative clustering
KW - k-means
KW - statistics
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U2 - 10.1080/02286203.2021.1873221
DO - 10.1080/02286203.2021.1873221
M3 - Article
AN - SCOPUS:85100610971
SN - 0228-6203
VL - 42
SP - 227
EP - 239
JO - International Journal of Modelling and Simulation
JF - International Journal of Modelling and Simulation
IS - 2
ER -