AI Article Synopsis

Article Abstract

Background: Various integrated care models have been used to improve treatment completion of medications for chronic hepatitis B virus (HBV), chronic hepatitis C virus (HCV), Mycobacterium tuberculosis (TB), and Human immunodeficiency virus (HIV) among people with substance use disorders (SUD). We have conducted a systematic review to evaluate whether integrated models have impacts of the treatment of infectious diseases among marginalized people with SUD.

Methods: We searched MEDLINE/PubMed (1946 to 2018, on July 26, 2018) and Embase (from 1974 to 2018, on July 26, 2018) for randomized controlled trials (RCTs) and cohort studies evaluating diverse integrated models' effects on sustained virological response (SVR), HIV suppression, HBV curation or suppression, completion of TB treatment regimen among people with SUD. The included studies were assessed qualitatively.

Results: Altogether, 1640 studies, and references to 1135 related reviews and RCTs were considered, and only seven RCTs and three cohort studies fulfilled the inclusion criteria. We identified nine integrated care models. Two studies, one RCT and one cohort study, showed a significant effect of their integrated models. The RCT evaluated psychosocial treatment, opioid agonist treatment (OAT) and directly observed TB treatment, and found a significant increase in TB treatment completions among intervention group compared to control group (60% versus 13%, p < 0.01). The cohort study including OAT and TB treatments had an effect on TB treatment completion in hospitalized patients (89% versus 73%, p = 0.03). Eight out of ten studies showed no significant effects of their integrated care models on defined outcomes. One of which having included 363 participants in a RCT showed no effect on SVR compared to the control group when the results adjusted for active substance use and alcohol dependence in a post-hoc analysis (11% versus 7%, p = 0.49).

Conclusions: The findings indicate uncertainty on the effects of integrated care models' on treatment for severe infectious diseases among people with SUD. Some studies point toward that integrated models could improve care of people with SUD, yet high-quality studies and preferably, sufficiently sized clinical trials are needed to conclude on the degree of impact.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449980PMC
http://dx.doi.org/10.1186/s12879-019-3918-2DOI Listing

Publication Analysis

Top Keywords

integrated care
12
infectious diseases
8
people substance
8
substance disorders
8
systematic review
8
care models
8
chronic hepatitis
8
hepatitis virus
8
integrated models
8
2018 july
8

Similar Publications

Loneliness, social isolation, and living alone: a comprehensive systematic review, meta-analysis, and meta-regression of mortality risks in older adults.

Aging Clin Exp Res

January 2025

Research Laboratory Psychology of Patients, Families, and Health Professionals, Department of Nursing, School of Health Sciences, University of Ioannina, Ioannina, Greece.

Loneliness, social isolation, and living alone are significant risk factors for mortality, particularly in older adults. This systematic review and meta-analysis aimed to quantify their associations with all-cause and cause-specific mortality in older adults, broadening previous research by including more social factors. Comprehensive searches were conducted in PubMed, APA PsycINFO, and CINAHL until December 31, 2023, following PRISMA 2020 and MOOSE guidelines.

View Article and Find Full Text PDF

Introduction: Cesarean deliveries account for approximately one-third of all births in Germany, prompting ongoing discussions on cesarean section rates and their connection to medical staffing and birth volume. In Germany, the majority of departments integrate obstetric and gynecological care within a single department.

Methods: The analysis utilized quality reports from German hospitals spanning 2015 to 2019.

View Article and Find Full Text PDF

Infrared absorption spectroscopy and surface-enhanced Raman spectroscopy were integrated into three data fusion strategies-hybrid (concatenated spectra), mid-level (extracted features from both datasets) and high-level (fusion of predictions from both models)-to enhance the predictive accuracy for xylazine detection in illicit opioid samples. Three chemometric approaches-random forest, support vector machine, and -nearest neighbor algorithms-were employed and optimized using a 5-fold cross-validation grid search for all fusion strategies. Validation results identified the random forest classifier as the optimal model for all fusion strategies, achieving high sensitivity (88% for hybrid, 92% for mid-level, and 96% for high-level) and specificity (88% for hybrid, mid-level, and high-level).

View Article and Find Full Text PDF

Background: Cisgender women living with HIV (WLWH) are disproportionately impacted by cervical cancer. Nevertheless, disparities in uptake and implementation of cervical cancer services persist in sub-Saharan Africa, where population-level estimates of screening coverage remain scarce.

Methods: We pooled data from nationally representative Population-based HIV Impact Assessment (PHIA) surveys conducted in Ethiopia, Malawi, Rwanda, Tanzania, Zambia, and Zimbabwe (2015-2019).

View Article and Find Full Text PDF

Non-destructive color sensors are widely applied for rapid analysis of various biological and healthcare point-of-care applications. However, existing red, green, blue (RGB)-based color sensor systems, relying on the conversion to human-perceptible color spaces like hue, saturation, lightness (HSL), hue, saturation, value (HSV), as well as cyan, magenta, yellow, key (CMYK) and the CIE L*a*b* (CIELAB) exhibit limitations compared to spectroscopic methods. The integration of machine learning (ML) techniques presents an opportunity to enhance data analysis and interpretation, enabling insights discovery, prediction, process automation, and decision-making.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!