Asthma control and its predictors in Ethiopia: Systematic review and meta-analysis

Prevalence and predictors of medication adherence among adolescents and adults with asthma in Ethiopia: a systematic review and meta-analysis

OBJECTIVE

This review aimed to estimate the pooled prevalence and predictors of medication adherence among adolescents and adults with asthma in Ethiopia.

DATA SOURCES

Primary studies were searched from PubMed, Scopus, HINARI, and Google Scholar from January 1, 2010 to December 10, 2023. In addition, we have used citation tracking.

STUDY SELECTIONS

Observational studies (cross sectional, case control, and cohort) conducted among asthmatic patients ≥15 years old in Ethiopia, published in English language were included. After screening, the studies were assessed using Joanna Briggs Institute (JBI) critical appraisal tool and data were extracted using a checklist. Heterogeneity was assessed using forest plot, Q-statistics and I2.

RESULTS

The review was performed among 13 institution-based studies with a total of 2901 participants with asthma. About 1058 participants had comorbid disease and 354 were cigarette smokers. The pooled prevalence of adherence to medications among patients with asthma was 40.50% (95% CI: 28.05, 52.96; p value < 0.001) with high heterogeneity (I2 = 98.25%, p < 0.001). Getting health education about asthma and having comorbid disease were predictors of medication adherence among adolescents and adults with asthma in Ethiopia.

CONCLUSIONS

The pooled prevalence of medication adherence among adolescents and adults with asthma in Ethiopia is low and indicated that three out of five adolescents and adults with asthma were non-adherent to medications. This implies the Ministry of Health should develop different strategies to improve medication adherence including patient education and strengthening the health care system. Multicenter longitudinal studies should be further conducted by using objective methods of adherence measurement and large sample size.

Medication Non-adherence and predictor factors among adult Asthmatic patients in Ethiopia: a Systematic review and Meta-Analysis

Objective: A pronounced burden is evident in individuals with asthma, with approximately half of them not adhering to their prescribed medication. Therefore this study aimed to assess the pooled prevalence of anti-asthma medications non-adherence in Ethiopia.Data sources: A comprehensive search was conducted across multiple electronic databases including PubMed, Africa Index Medicus, Science Direct, Hinari, and a search engine, Google Scholar from October 5 to 20, 2023. In addition, digital research repositories from Addis Ababa and Bahir Dar University were accessed.Data selection: The eligibility criteria was employed to screen studies after uploading search results to EndNote software to remove duplicates first. Then, two investigators, CT and BBT, independently assessed titles, abstracts, and the full text of all retrieved references to identify potentially eligible studies.Result: This meta-analysis, which was conducted in Ethiopia, and included 11 full-text articles, revealed a pooled asthma medication non-adherence level of 51.20% (95% CI, 35.20%, 67.20%) with substantial heterogeneity (I2 = 99.08%). The review has also identified factors predicting non-adherence among asthmatic patients: free (health service) (AOR: 0.31, 95% CI; 0.18-0.54), poor knowledge (AOR: 2.85, 95% CI; 1.61-5.05), absence of formal education (AOR: 3.01, 95% CI; 1.72-5.25), history of Previous ADR(AOR: 8.57, 95% CI; 1.12-65.3), and the presence of Co- morbidity(AOR: 3.28, 95% CI; 2.014-5.68), had shown association with asthma medication non-adherence.Conclusion: Asthma medication non-adherence is notably high in Ethiopia. Addressing medication non-adherence requires a comprehensive approach, including clear communication between healthcare providers, patient education and addressing financial barriers to ensure better adherence in asthma patients.

Prevalence of medication adherence among adult asthmatic patients in four African countries: A systematic review and meta-analysis

Non-adherence to medications has many deleterious effects including poor treatment outcomes, increased economic burden, increased morbidity, hospitalization rate, health care utilization, productivity loss, and mortality. Therefore, this review aimed to estimate the pooled prevalence of medication adherence among asthmatic adults in 4 African countries. Primary studies were extensively searched from databases such as PubMed, HINARI, Cochrane Library, CINHALand, Google Scholar, and Google search engines. After screening and assessing the quality of studies, data were extracted using a checklist. Heterogeneity was assessed using forest plot, Chocran's Q Test and I2. The random effects meta-analysis model was employed to pool the prevalence of medication adherence among adult asthmatic patients in Africa. Sub-group analysis and meta-regression were performed to identify the sources of heterogeneity. Publication bias was assessed using funnel plots with Egger's test. A sensitivity analysis was performed to assess the influence of individual studies on the overall estimate. The review was performed among 16 studies of which 14 were cross-sectional with a total of 4019 participants. The pooled random effects prevalence of adherence to medications among adult patients with asthma in Africa was 39% (95% CI: 32, 47; p < 0.001) with a heterogeneity (I2 = 94.82, p < 0.001). The pooled prevalence of medication adherence among adult asthmatic patients in Africa is low. Researchers should conduct further multicenter longitudinal studies by using objective methods of adherence measurement.

One size does not fit all: an application of stochastic modeling to estimating primary healthcare needs in Ethiopia at the sub-national level

BACKGROUND

Primary healthcare systems require adequate staffing to meet the needs of their local population. Guidelines typically use population ratio targets for healthcare workers, such as Ethiopia's goal of two health extension workers for every five thousand people. However, fixed ratios do not reflect local demographics, fertility rates, disease burden (e.g., malaria endemicity), or trends in these values. Recognizing this, we set out to estimate the clinical workload to meet the primary healthcare needs in Ethiopia by region.

METHODS

We utilize the open-source R package PACE-HRH for our analysis, which is a stochastic Monte Carlo simulation model that estimates workload for a specified service package and population. Assumptions and data inputs for region-specific fertility, mortality, disease burden were drawn from literature, DHS, and WorldPop. We project workload until 2035 for seven regions and two charted cities of Ethiopia.

RESULTS

All regions and charted cities are expected to experience increased workload between 2021 and 2035 for a starting catchment of five thousand people. The expected (mean) annual clinical workload varied from 2,930 h (Addis) to 3,752 h (Gambela) and increased by 19-28% over fifteen years. This results from a decline in per capita workload (due to declines in fertility and infectious diseases), overpowered by total population growth. Pregnancy, non-communicable diseases, sick child care, and nutrition remain the largest service categories, but their priority shifts substantially in some regions by 2035. Sensitivity analysis shows that fertility assumptions have major implications for workload. We incorporate seasonality and estimate monthly variation of up to 8.9% (Somali), though most services with high variability are declining.

CONCLUSIONS

Regional variation in demographics, fertility, seasonality, and disease trends all affect the workload estimates. This results in differences in expected clinical workload, the level of uncertainty in those estimates, and relative priorities between service categories. By showing these differences, we demonstrate the inadequacy of a fixed population ratio for staffing allocation. Policy-makers and regulators need to consider these factors in designing their healthcare systems, or they risk sub-optimally allocating workforce and creating inequitable access to care.

Characteristics of Severe Asthma Patients and Predictors of Asthma Control in the Swiss Severe Asthma Registry

BACKGROUND

Asthma is a chronic airway disease, affecting over 300 million people worldwide. 5-10% of patients suffer from severe asthma and account for 50% of asthma-related financial burden. Availability of real-life data about the clinical course of severe asthma is insufficient.

OBJECTIVES

The aims of this study were to characterize patients with severe asthma in Switzerland, enrolled in the Swiss Severe Asthma Registry (SSAR), and evaluate predictors for asthma control.

METHOD

A descriptive characterisation of 278 patients was performed, who were prospectively enrolled in the registry until January 2022. Socio-demographic variables, comorbidities, diagnostic values, asthma treatment, and healthcare utilisation were evaluated. Groups of controlled and uncontrolled asthma according to the asthma control test were compared.

RESULTS

Forty-eight percent of patients were female and the mean age was 55.8 years (range 13-87). The mean body mass index (BMI) was 27.4 kg/m2 (±6). 10.8% of patients were current smokers. Allergic comorbidities occurred in 54.3% of patients, followed by chronic rhinosinusitis (46.4%) and nasal polyps (34.1%). According to the ACT score, 54.7% had well controlled, 16.2% partly controlled and 25.9% uncontrolled asthma. The most common inhalation therapy was combined inhaled corticosteroids/long-acting β2-agonists (78.8%). Biologics were administered to 81.7% of patients and 19.1% received oral steroids. The multivariable analysis indicated that treatment with biologics was positively associated with asthma control whereas higher BMI, oral steroids, exacerbations, and COPD were negative predictors for asthma control.

CONCLUSION

Biologics are associated with improved control in severe asthma. Further studies are required to complete the picture of severe asthma in order to provide improved care for those patients.

Percent Recovery Index Predicts Poor Asthma Control and Exacerbation in Adults

Background

Previous studies indicate that the percent recovery index (PRI: the percentage increase from the maximally reduced FEV1 after bronchodilator inhalation), one of the indexes of methacholine bronchial provocation, may predict acute asthma exacerbations in childhood and elderly asthmatics. It is known that childhood (<12) and elder (>60) asthmatics may be different to adult patients in many aspect including prognosis. However, in adults, a research for predicting value of PRI to exacerbation is still absence. Besides exacerbation, predicting value of PRI to poor asthma control is also unknown. We try to detect whether PRI can predict poor asthma control and exacerbation in adults in this research. Meanwhile, we try to detect whether treatment can influence PRI.

Methods

In 61 adults with asthma, baseline PRI was measured during enrollment. And then baseline PRI was evaluated as a predictor of exacerbation or poor asthma control at an upcoming 3-month follow-up. The covariates included age, sex, BMI, previous exacerbation, smoking status and baseline lung function. After treatment for 3 months, PRI was measured again and compared with baseline PRI.

Results

After the 3-month follow-up, we found that baseline PRI was significantly related to asthma exacerbation (P = 0.023), poor asthma control (ACT at 3 months, P = 0.014), decreased quality of life (decrease of MiniAQLQ, P = 0.010) and cumulative number of EDHO at 3 months (P = 0.039). Meanwhile, no significant correlation was observed between baseline PRI and inflammation factors (FENO, CaNO, and EOS). Finally, PRI was dramatically reduced after standard treatment for 3 months.

Conclusion

PRI is efficient in the prediction of poor asthma control and exacerbation in adults. The predictive value of PRI may rely on the inherent property of asthmatic airway smooth muscle (ASM) independent of inflammation factors. Effective treatment can alleviate PRI dramatically and that indicate PRI may also be valuable in evaluation of curative effect.

Identification of pyroptosis-related subtypes and establishment of prognostic model and immune characteristics in asthma

Background

Although studies have shown that cell pyroptosis is involved in the progression of asthma, a systematic analysis of the clinical significance of pyroptosis-related genes (PRGs) cooperating with immune cells in asthma patients is still lacking.

Methods

Transcriptome sequencing datasets from patients with different disease courses were used to screen pyroptosis-related differentially expressed genes and perform biological function analysis. Clustering based on K-means unsupervised clustering method is performed to identify pyroptosis-related subtypes in asthma and explore biological functional characteristics of poorly controlled subtypes. Diagnostic markers between subtypes were screened and validated using an asthma mouse model. The infiltration of immune cells in airway epithelium was evaluated based on CIBERSORT, and the correlation between diagnostic markers and immune cells was analyzed. Finally, a risk prediction model was established and experimentally verified using differentially expressed genes between pyroptosis subtypes in combination with asthma control. The cMAP database and molecular docking were utilized to predict potential therapeutic drugs.

Results

Nineteen differentially expressed PRGs and two subtypes were identified between patients with mild-to-moderate and severe asthma conditions. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes. Poor control subtypes were closely related to glucocorticoid resistance and airway remodeling. BNIP3 was identified as a diagnostic marker and associated with immune cell infiltration such as, M2 macrophages. The risk prediction model containing four genes has accurate classification efficiency and prediction value. Small molecules obtained from the cMAP database that may have therapeutic effects on asthma are mainly DPP4 inhibitors.

Conclusion

Pyroptosis and its mediated immune phenotype are crucial in the occurrence, development, and prognosis of asthma. The predictive models and drugs developed on the basis of PRGs may provide new solutions for the management of asthma.

Autophagy-Related Genes Are Involved in the Progression and Prognosis of Asthma and Regulate the Immune Microenvironment

Background

Autophagy has been proven to play an important role in the pathogenesis of asthma and the regulation of the airway epithelial immune microenvironment. However, a systematic analysis of the clinical importance of autophagy-related genes (ARGs) regulating the immune microenvironment in patients with asthma remains lacking.

Methods

Clustering based on the k-means unsupervised clustering method was performed to identify autophagy-related subtypes in asthma. ARG-related diagnostic markers in low-autophagy subtypes were screened, the infiltration of immune cells in the airway epithelium was evaluated by the CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. On the basis of the expression of ARGs and combined with asthma control, a risk prediction model was established and verified by experiments.

Results

A total of 66 differentially expressed ARGs and 2 subtypes were identified between mild to moderate and severe asthma. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes, and the low-autophagy subtype was closely associated with severe asthma, energy metabolism, and hormone metabolism. The autophagy gene SERPINB10 was identified as a diagnostic marker and was related to the infiltration of immune cells, such as activated mast cells and neutrophils. Combined with asthma control, a risk prediction model was constructed, the expression of five risk genes was supported by animal experiments, was established for ARGs related to the prediction model.

Conclusion

Autophagy plays a crucial role in the diversity and complexity of the asthma immune microenvironment and has clinical value in treatment response and prognosis.