Implementation of point-of-care testing of C-reactive protein concentrations to improve antibiotic targeting in respiratory illness in Vietnamese primary care: a pragmatic cluster-randomised controlled trial

Background In previous trials, point-of-care testing of C-reactive protein (CRP) concentrations safely reduced antibiotic use in non-severe acute respiratory infections in primary care. However, these trials were done in a research-oriented context with close support from research staff, which could have influenced prescribing practices. To better inform the potential for scaling up point-of-care testing of CRP in respiratory infections, we aimed to do a pragmatic trial of the intervention in a routine care setting. Methods We did a pragmatic, cluster-randomised controlled trial at 48 commune health centres in Viet Nam between June 1, 2020, and May 12, 2021. Eligible centres served populations of more than 3000 people, handled 10–40 respiratory infections per week, had licensed prescribers on site, and maintained electronic patient databases. Centres were randomly allocated (1:1) to provide point-of-care CRP testing plus routine care or routine care only. Randomisation was stratified by district and by baseline prescription level (ie, the proportion of patients with suspected acute respiratory infections to whom antibiotics were prescribed in 2019). Eligible patients were aged 1–65 years and visiting the commune health centre for a suspected acute respiratory infection with at least one focal sign or symptom and symptoms lasting less than 7 days. The primary endpoint was the proportion of patients prescribed an antibiotic at first attendance in the intention-to-treat population. The per-protocol analysis included only people who underwent CRP testing. Secondary safety outcomes included time to resolution of symptoms and frequency of hospitalisation. This trial is registered with ClinicalTrials.gov, NCT03855215. Findings 48 commune health centres were enrolled and randomly assigned, 24 to the intervention group (n=18 621 patients) and 24 to the control group (n=21 235). 17 345 (93·1%) patients in the intervention group were prescribed antibiotics, compared with 20 860 (98·2%) in the control group (adjusted relative risk 0·83 [95% CI 0·66–0·93]). Only 2606 (14%) of 18 621 patients in the intervention group underwent CRP testing and were included in the per-protocol analysis. When analyses were restricted to this population, larger reductions in prescribing were noted in the intervention group compared with the control group (adjusted relative risk 0·64 [95% CI 0·60–0·70]). Time to resolution of symptoms (hazard ratio 0·70 [95% CI 0·39–1·27]) and frequency of hospitalisation (nine in the intervention group vs 17 in the control group; adjusted relative risk 0·52 [95% CI 0·23–1·17]) did not differ between groups. Interpretation Use of point-of-care CRP testing efficaciously reduced prescription of antibiotics in patients with non-severe acute respiratory infections in primary health care in Viet Nam without compromising patient recovery. The low uptake of CRP testing suggests that barriers to implementation and compliance need to be addressed before scale-up of the intervention. Funding Australian Government, UK Government, and the Foundation for Innovative New Diagnostics

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Outpatient antibiotic prescribing for acute respiratory infections in Vietnamese primary care settings by the WHO AWaRe (Access, Watch and Reserve) classification: An analysis using routinely collected electronic prescription data

Background: This study aims to investigate patterns of antibiotic prescribing and to determine patient-specific factors associated with the choice of antibiotics by the World Health Organization's Access-Watch-Reserve (WHO AWaRe) class for acute respiratory infections (ARIs) in rural primary care settings in northern Vietnam. Methods: We retrospectively reviewed health records for outpatients who were registered with the Vietnamese Health Insurance Scheme, visited one of 112 commune health centres in 6 rural districts of Nam Dinh province, Vietnam during 2019, and were diagnosed with ARIs. Patient-level prescription data were collected from the electronic patient databases. We used descriptive statistics to investigate patterns of antibiotic prescribing, with the primary outcomes including total antibiotic prescriptions and prescriptions by WHO AWaRe group. We identified patient-specific factors associated with watch-group antibiotic prescribing through multivariable logistic regression analysis. Findings: Among 193,010 outpatient visits for ARIs observed in this study, 187,144 (97.0%) resulted in an antibiotic prescription, of which 172,976 (92.5%) were access-antibiotics, 10,765 (5.6%) were watch-antibiotics, 3366 (1.8%) were not-recommended antibiotics. No patients were treated with reserve-antibiotics. The proportion of watch-antibiotic prescription was highest amongst children under 5-years old (18.1%, compared to 9.5% for 5–17-years, 4.9% for 18–49-years, 4.3% for 50–64-years, and 3.7% for 65-and-above-years). In multivariable logistic regression, children, district, ARI-type, comobid chronic respiratory illness, and follow-up visit were associated with higher likelihood of prescribing watch-group antibiotics. Interpretation: The alarmingly high proportion of antibiotic prescriptions for ARIs in primary care, and the frequent use of watch-antibiotics for children, heighten concerns around antibiotic overuse at the community level. Antimicrobial stewardship interventions and policy attention are needed in primary care settings to tackle the growing threat of antibiotic resistance

LC-MS/MS Method for Rapid Quantification of Progesterone in Rabbit Plasma and Its Application in a Pharmacokinetic Study of the Transdermal Formulation

A rapid and effective method using QuEChERS-based sample preparation procedure and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis has been developed and validated to determine progesterone in rabbit plasma. The analyte was extracted from plasma by acetonitrile with phase partitioning by a mixture of magnesium sulfate and sodium chloride. The supernatant was then directly injected into LC-MS/MS in a positive electrospray ionization mode and quantified using progesterone-d9 as the internal standard. The method linearity was in the range from 1 ng/mL (LOQ) to 200 ng/mL. Method recovery was from 86.0% to 103%, and repeatability was lower than 5.5%. The plasma sample was stable for 12 weeks stored at 18 ± 2°C. This method was applied to quantify progesterone in rabbit plasma in a pharmacokinetic study of two transdermal formulations: a reference drug and a eutectic-hydrogel system. The data indicate that the eutectic-hydrogel system’s bioavailability was 1.5 times better than that of the reference drug, and the transdermal system is a potential drug delivery system for progesterone

Assessment of the Role of Ginsenoside RB1 Active Substance in Alginate/Chitosan/Lovastatin Composite Films

This article reports the effect of ginsenoside Rb1 on some properties, morphology, and the drug release process of the chitosan (CS)/alginate (AG)/lovastatin (LOV) composite films prepared by a solution method using different contents of ginsenoside Rb1. The ratio of AG/CS was fixed at 4/1 (wt.%/wt.%), the content of LOV was 10 wt.%, and the content of ginsenoside Rb1 was changed from 1 to 5 wt.%. The results of scanning electron microscopy and Fourier transform infrared spectroscopy analysis showed that the composite films have a heterogeneous structure and the ginsenoside Rb1 content influenced on the structure of composite films. The presence of ginsenoside Rb1 did not influence on the melting temperature of these films but caused a significant difference in the melting enthalpy of the films. The ginsenoside Rb1 was also contributed positively on the LOV release from these films in different pH buffer solutions. The LOV release process from these films included two stages (fast/burst release and slow/control release). It was increased remarkably by the synergic effect of LOV and ginsenoside Rb1 in the drug release process. From the obtained results, we suggested that ginsenoside Rb1 plays an important role not only in the enhancement of health and immunity as general but also as an efficient agent in control of the LOV size as well as LOV drug release from the composite films

Robustness of Deep Transfer Learning-Based Crack Detection against Uncertainty in Hyperparameter Tuning and Input Data

Computer vision techniques can be applied to detect structural defects of different concrete structures. In this aspect, deep transfer learning algorithms play a key role in terms of automated crack identification. To the best of the authors’ knowledge, selecting appropriate models and tuning them for the classification of crack images, especially in adverse conditions, is a topic that has been neglected until now. Henceforth, to test the robustness and stability of deep transfer learning networks, eight popular pre-trained convolutional neural networks (CNN) models with different network architecture complexities were tasked with image classification challenges. This refinement was created by (i) varying a key hyperparameter used for tuning and (ii) feeding the networks with two variants of adverse conditions in image data. This chapter provides evidence of the optimal batch sizes that should be used and the best repurposed small and large deep learning networks that can achieve outstanding crack classification capabilities with compromised image data. According to the results, GoogleNet and Xception networks have been challenged and confirmed as high-performing networks on average, particularly when used with reasonable batch sizes