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Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count
OBJECTIVE: To subdivide the antiretroviral therapy (ART) human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) patients by modeling the CD4 cell count variable, with an aim to reduce the medical burden from lifelong ART. MATERIALS AND METHODS: The data of outpatients at the r...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114561/ https://www.ncbi.nlm.nih.gov/pubmed/37091020 http://dx.doi.org/10.4103/jfmpc.jfmpc_1765_22 |
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author | Min, Li Qunwei, Wang |
author_facet | Min, Li Qunwei, Wang |
author_sort | Min, Li |
collection | PubMed |
description | OBJECTIVE: To subdivide the antiretroviral therapy (ART) human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) patients by modeling the CD4 cell count variable, with an aim to reduce the medical burden from lifelong ART. MATERIALS AND METHODS: The data of outpatients at the research unit between August 2009 and December 2020 were exported and mined. A recency-frequency (RF) model was established for data subdivision, and data of non-churn ART patients were preserved. Common factor analysis (CFA) was conducted on the three indicators of the baseline/mean/last CD4 cell counts to obtain critical variables; then, k-means modeling was used to subdivide ART patients and their medical burden was analyzed. RESULTS: A total of 12,106 samples of non-churn ART patients were preserved by RF modeling. The baseline/mean/last CD4 cell counts served as important variables employed for modeling. The patients were divided into 15 types, including two types with poor compliance and poor immune reconstitution, two types with good compliance but poor immune reconstitution, four types with poor compliance but good immune reconstitution, and seven types with good compliance and good immune reconstitution. The frequency of visits was 5.25–9.95 visits/person/year, and the percentage of examination fees was 44.24%–59.05%, with a medical burden of 4114.24–12,676.66 yuan/person/year, of which 42.62%–70.09% was reduced. CONCLUSION: The CD4 cell count is not only an important indicator for judging post-ART immune recovery, but also a major modeling variable in subdividing ART patients with varying medical burdens. Poor compliance and poor immune reconstitution lead to excessive visits and frequent examinations, which were the leading causes of the heavy medical burden of ART. |
format | Online Article Text |
id | pubmed-10114561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-101145612023-04-20 Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count Min, Li Qunwei, Wang J Family Med Prim Care Original Article OBJECTIVE: To subdivide the antiretroviral therapy (ART) human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) patients by modeling the CD4 cell count variable, with an aim to reduce the medical burden from lifelong ART. MATERIALS AND METHODS: The data of outpatients at the research unit between August 2009 and December 2020 were exported and mined. A recency-frequency (RF) model was established for data subdivision, and data of non-churn ART patients were preserved. Common factor analysis (CFA) was conducted on the three indicators of the baseline/mean/last CD4 cell counts to obtain critical variables; then, k-means modeling was used to subdivide ART patients and their medical burden was analyzed. RESULTS: A total of 12,106 samples of non-churn ART patients were preserved by RF modeling. The baseline/mean/last CD4 cell counts served as important variables employed for modeling. The patients were divided into 15 types, including two types with poor compliance and poor immune reconstitution, two types with good compliance but poor immune reconstitution, four types with poor compliance but good immune reconstitution, and seven types with good compliance and good immune reconstitution. The frequency of visits was 5.25–9.95 visits/person/year, and the percentage of examination fees was 44.24%–59.05%, with a medical burden of 4114.24–12,676.66 yuan/person/year, of which 42.62%–70.09% was reduced. CONCLUSION: The CD4 cell count is not only an important indicator for judging post-ART immune recovery, but also a major modeling variable in subdividing ART patients with varying medical burdens. Poor compliance and poor immune reconstitution lead to excessive visits and frequent examinations, which were the leading causes of the heavy medical burden of ART. Wolters Kluwer - Medknow 2023-02 2023-02-28 /pmc/articles/PMC10114561/ /pubmed/37091020 http://dx.doi.org/10.4103/jfmpc.jfmpc_1765_22 Text en Copyright: © 2023 Journal of Family Medicine and Primary Care https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Min, Li Qunwei, Wang Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count |
title | Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count |
title_full | Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count |
title_fullStr | Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count |
title_full_unstemmed | Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count |
title_short | Subdividing ART patients and analyzing the medical burden by modeling of CD4 cell count |
title_sort | subdividing art patients and analyzing the medical burden by modeling of cd4 cell count |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114561/ https://www.ncbi.nlm.nih.gov/pubmed/37091020 http://dx.doi.org/10.4103/jfmpc.jfmpc_1765_22 |
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