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. 2023 Apr:21:21-27.
doi: 10.1016/j.ijpddr.2022.11.006. Epub 2022 Dec 5.

Poor adherence is a major barrier to the proper treatment of cutaneous leishmaniasis: A case-control field assessment in Iran

Mehdi Bamorovat  1 , Iraj Sharifi  2 , Setareh Agha Kuchak Afshari  3 , Ali Karamoozian  4 , Amirhossein Tahmouresi  5 , Amireh Heshmatkhah  6 , Ehsan Salarkia  5 , Ahmad Khosravi  5 , Maryam Hakimi Parizi  5 , Maryam Barghi  7
Affiliations

Poor adherence is a major barrier to the proper treatment of cutaneous leishmaniasis: A case-control field assessment in Iran

Mehdi Bamorovat et al. Int J Parasitol Drugs Drug Resist. 2023 Apr.

Abstract

Leishmaniasis is an overlooked, poverty-stricken, and complex disease with growing social and public health problems. In general, leishmaniasis is a curable disease; however, there is an expansion of unresponsive cases to treatment in cutaneous leishmaniasis (CL). One of the effective and ignored determinants in the treatment outcome of CL is poor treatment adherence (PTA). PTA is an overlooked and widespread phenomenon to proper Leishmania treatment. This study aimed to explore the effect of poor adherence in unresponsiveness to treatment in patients with anthroponotic CL (ACL) by comparing conventional statistical modalities and machine learning analyses in Iran. Overall, 190 cases consisting of 50 unresponsive patients (case group), and 140 responsive patients (control group) with ACL were randomly selected. The data collecting form that included 25 queries (Q) was recorded for each case and analyzed by R software and genetic algorithm (GA) approaches. Complex treatment regimens (Q11), cultural and lay views about the disease and therapy (Q8), life stress, hopelessness and negative feelings (Q22), adverse effects of treatment (Q13), and long duration of the lesion (Q12) were the most prevalent significant variables that inhibited effective treatment adherence by the two methods, in decreasing order of significance. In the inherent algorithm approach, similar to the statistical approach, the most significant feature was complex treatment regimens (Q11). Providing essential knowledge about ACL and treatment of patients with chronic diseases and patients with misconceptions about chemical drugs are important issues directly related to the disease's unresponsiveness. Furthermore, early detection of patients to prevent the long duration of the disease and the process of treatment, efforts to minimize side effects of treatment, induction of positive thinking, and giving hope to patients with stress and anxiety by medical staff, and family can help patients adhere to the treatment.

Keywords: Cutaneous leishmaniasis; Iran; Major barrier; Poor adherence; Treatment.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Confusion matrix and receiver operating characteristic (ROC) curve in statistical approach.
Fig. 2
Fig. 2
The confusion matrix of the selected features with support vector machine (SVM) classifier, class 1: Responsive, and class 2: Unresponsive.
Fig. 3
Fig. 3
The receiver operating characteristic (ROC) plot curve of selected features via support vector machine (SVM) classifier and indicated area under the curve (AUC).
Fig. 4
Fig. 4
Factors affecting adherence to treatment for CL.
See this image and copyright information in PMC

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