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Factors that influence recruitment to COVID-19 vaccine trials: a qualitative evidence synthesis.
BACKGROUND: The COVID-19 pandemic marked a unique period characterised by an extraordinary global virus spread. The collective effort to halt the transmission of the virus led to various public health initiatives, including a variety of COVID-19 vaccine trials. Many of these trials used adaptive methods to address the pandemic's challenges, such as the need for rapid recruitment. These adaptive methods allow for modifications to the trial procedures without undermining the trial's integrity, making the research process more flexible and efficient. However, recruiting participants for vaccine trials remains a considerable challenge. The aim of this qualitative evidence synthesis (QES) is to explore the factors that influence a person's decision to participate in a COVID-19 vaccine trial. Lessons learned from this could help shape future trials' design and conduct, particularly those conducted within a pandemic. METHODS: We conducted a systematic search for qualitative studies and mixed methods studies with a qualitative component in the WHO COVID-19 Research Database, MEDLINE, CINAHL, PsycINFO, Epistemomikos, Online Resource for Research in Clinical Trials (ORCCA), and the Cochrane COVID-19 Study Register. We used the best-fit framework synthesis approach and the Social Ecological Model as an a priori framework. We used the GRADE-CERQual approach to assess our confidence in the review findings. RESULTS: Five studies involving 539 participants were included. One of these studies included participants in a COVID-19 vaccine trial. In three of the studies, participants were asked hypothetically about their attitudes. Another study included people who had either not responded to or declined an invitation to participate in a COVID-19 vaccine trial. We developed six themes outlining the factors that influence a person's decision to participate in a COVID-19 vaccine trial: (1) personal gains, (2) perceived risk, (3) influence of family and community, (4) contributing for others, (5) institutional trust and mistrust, and (6) accessibility of the trial. CONCLUSION: This review sheds light on how people perceive the potential personal, family, and community advantages of trial participation and how these perceptions may be weighed against concerns about vaccine safety. The findings also point toward specific aspects of trial methodology to consider when designing COVID-19 vaccine trials.
Effect of tropical climates on the quality of commonly used antibiotics: the protocol for a systematic review and meta-analysis.
INTRODUCTION: Medicine quality can be influenced by environmental factors. In low- and middle-income countries (LMICs) with tropical climates, storage facilities of medicines in healthcare settings and homes may be suboptimal. However, knowledge of the effects of temperature and other climatic and environmental factors on the quality of medicines is limited. A better understanding of the effects of climates may assist in the development of control strategies to help reduce factors contributing to poor-quality medicines. Therefore, this systematic review aims to synthesise data from published studies describing the effects of storage conditions on the quality of antibiotic medicines commonly used in LMICs. METHODS AND ANALYSIS: We will search literature from databases, including the PubMed, Web of Science, Scopus and Google Scholar, and grey literature between 1987 and 2022. Experimental studies that evaluate the influence of temperature, humidity and sunlight on the quality of antibiotics applicable to Africa and South Asia will be included. Experimental studies that assess naturally occurring and simulated storage conditions and medicines prepared from powder with water and stored in hospitals or at home to be used across several doses will be also included. The key search terms related to the tropical climate, quality and commonly used antibiotics, such as temperature, storage condition, humidity, sunlight and moisture; quality, assay, purity, dissolution, disintegration, hardness, friability, weight variation, weight uniformity, degradation, impurities and stability; and amoxicillin, ceftriaxone, azithromycin, ciprofloxacin, doxycycline, metronidazole, trimethoprim-sulfamethoxazole, erythromycin, ampicillin and gentamicin, respectively, will be connected using the appropriate Boolean operators (OR, AND). The search terms will be used in correspondence with Medical Subject Heading terms by keyword arrangement. The available evidence for the poor quality of commonly used antibiotics is summarised by the type of diagnosis, type of drug and region. Meta-analysis using random effects will be performed using RevMan software to determine the pooled effects of environmental exposures. The degree of heterogeneity will be evaluated by the inverse of variance (I2). Forest plots will be used to present the meta-analysis data. ETHICS AND DISSEMINATION: Ethical approval is not required as the study is a systematic review. This review will be disseminated through open-access peer-reviewed publication. PROSPERO REGISTRATION NUMBER: CRD42023432848.
Impact of HIV exposure without infection on hospital course and mortality among young children in sub-Saharan Africa: a multi-site cohort study.
BACKGROUND: Although mortality risk associated with HIV is well described, HIV-exposed uninfected (HEU) young children are also at increased risk of hospitalization and death as compared to HIV-unexposed uninfected (HUU) children. The drivers of poor outcomes among HEU children remain unknown, limiting the development of interventions to support this vulnerable population. METHODS: We performed a secondary analysis of data from a large multi-country prospective cohort [Childhood Acute Illness and Nutrition (CHAIN) Network] study. Data from 5 sites in Uganda, Kenya, and Malawi were included. Hospitalized children aged 2-23 months were followed from an index admission for 6 months after discharge to determine acute and long-term outcomes. Using perinatal HIV exposure (HEU and HUU) as the primary exposure and adjusting for child, caregiver, and household characteristics, we compared inpatient and 30-day survival outcomes, nutritional status, hospital length of stay, illness severity, and utilization of inpatient resources. RESULTS: We included 1486 children: 217 HEU and 1269 HUU. HEU children had an increased risk of mortality both during hospitalization [adjusted OR 1.96, 95% CI (1.14-3.37)] and in the 30 days following hospital admission [adjusted hazard ratio 2.20, 95% CI (1.10-4.42)]. Wasting and stunting were more frequent in HEU than HUU children, with adjusted OR 1.41, 95% CI (1.03-1.95) and adjusted OR 1.91, 95% CI (1.34-2.70), respectively. HEU children were also more likely to have a prolonged hospital stay compared to HUU children [adjusted OR 1.58, 95% CI (1.08-2.29)], although admission diagnoses, illness severity at admission, and use of inpatient resources (supplemental oxygen, nasogastric tube, and second-line antibiotics) did not differ significantly between groups. CONCLUSIONS: HEU children are more likely to die during hospitalization and within 30 days of admission, to be wasted and stunted upon hospital admission, and to require a prolonged hospital stay, as compared to HUU children. Hospitals in settings with a high prevalence of women-living-with-HIV should ensure that maternal HIV status is established among children requiring admission and build capacity to provide additional hospital monitoring and early post-discharge support for HEU children.
Implementation of evidence-based foot screening in people with diabetes: A scoping review.
BACKGROUND: Recommendations to prevent diabetes ulceration and amputation include an annual foot check, primarily screening for sensation and circulation. Using these simple, evidence-based components is vital to identifying complications early, assessing risk, and managing care to prevent or delay amputations. However, routine implementation of these assessments is suboptimal and approaches to their integration remain poorly understood. AIM: We aimed to identify and synthesize information on the factors affecting implementation of simple evidence-based diabetes foot screening. METHODS: We reviewed published and grey literature using a blinded two-stage process by two independent reviewers. Included studies were primary research that implemented or improved foot screening for adults with type 1 or 2 diabetes, assessing at least one of the following: 10-g monofilament sensitivity, pedal pulse palpation, or history of ulceration or amputation. A thematic synthesis approach was used. RESULTS: We screened 5133 titles and abstracts, reviewed 102 full-text articles, and included 26 studies in the final analysis. We identified four key themes: (1) Existing diabetes screening (i.e. retinal screening) or treatment interventions (i.e. medication collection) provide opportunities for synergistic integration; (2) Annual event-based foot screening (e.g. on World Diabetes Day) in lower resource settings provides community-focused preventative care; (3) Further opportunities to increase access to foot screening include self-administered screening and screening in complex residential settings; (4) Healthcare provider champions are essential for local foot screening implementation in primary and secondary care. CONCLUSION: Further research should evaluate the issues identified in these four themes, in different contexts, and with support of implementation frameworks.
Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers.
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information. Our study provides a snapshot of global researchers' perception of current trends and future impacts of LLMs in research. Using a cross-sectional design, we surveyed 226 medical and paramedical researchers from 59 countries across 65 specialties, trained in the Global Clinical Scholars' Research Training certificate program of Harvard Medical School between 2020 and 2024. Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p
A comprehensive scoping review on machine learning-based fetal echocardiography analysis.
Fetal echocardiography (ultrasound of the fetal heart) plays a vital role in identifying heart defects, allowing clinicians to establish prenatal and postnatal management plans. Machine learning-based methods are emerging to support the automation of fetal echocardiographic analysis; this review presents the findings from a literature review in this area. Searches were queried at leading indexing platforms ACM, IEEE Xplore, PubMed, Scopus, and Web of Science, including papers published until July 2023. In total, 343 papers were found, where 48 papers were selected to compose the detailed review. The reviewed literature presents research on neural network-based methods to identify fetal heart anatomy in classification and segmentation modelling. The reviewed literature uses five categorical technical analysis terms: attention and saliency, coarse to fine, dilated convolution, generative adversarial networks, and spatio-temporal. This review offers a technical overview for those already working in the field and an introduction to those new to the topic.
Diagnostic accuracy of a non-invasive spot-check hemoglobin meter, Masimo Rad-67® pulse CO-Oximeter®, in detection of anemia in antenatal care settings in Kenya.
BACKGROUND: Point of care hemoglobin meters play key roles in increasing access to anemia screening in antenatal care especially in settings with limited access to laboratories. We aimed to determine the diagnostic accuracy of a non-invasive spot-check hemoglobin (SpHb) meter, Masimo Rad-67® Pulse CO-Oximeter®, in the diagnosis of anemia in pregnant women attending antenatal care clinics in Kilifi, Kenya. METHODS: This was a diagnostic accuracy study that retrospectively evaluated SpHb against a validated reference standard of laboratory assessed hemoglobin (Lab Hb) by a SYSMEX XN-330 automated hematology analyzer. The study was nested within a prospective pregnancy cohort study that recruited unselected pregnant women from antenatal care clinics in two public hospitals in Kilifi County, coastal Kenya. Records with both SpHb and Lab Hb were selected from pregnancy visits between May 2021 and December 2022. Linear regression and Bland-Altman analysis were performed to compare the two tests and diagnostic accuracy parameters obtained for the diagnosis of anemia. RESULTS: A total of 2,975 records (from 2,203 unique participants), with paired SpHb and Lab Hb were analyzed. Linear regression showed a significant but weak positive correlation, a proportional bias of 0.44 (95% CI 0.41-0.47) and a constant of 7.59 (95% CI 7.30-7.87, p
Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape
Background The WHO’s recommendations on antenatal care underscore the need for ultrasound assessment during pregnancy. Given that maternal and perinatal mortality remains unacceptably high in underserved regions, these guidelines are imperative for achieving better outcomes. In recent years, portable ultrasound devices have become increasingly popular in resource-constrained environments due to their cost-effectiveness, useability, and adoptability in resource-constrained settings. This desk review presents the capabilities and costs of currently available portable ultrasound devices, and is meant to serve as a resource for clinicians and researchers in the imaging community. Methods A list of ideal technical features for portable ultrasound devices was developed in consultation with subject matter experts (SMEs). Features included image acquisition modes, cost, portability, compatibility, connectivity, data storage and security, and regulatory certification status. Information on each of the devices was collected from publicly available information, input from SMEs and/or discussions with company representatives. Results 14 devices were identified and included in this review. The output is meant to provide objective information on ideal technical features for available ultrasound systems to researchers and clinicians working in obstetric ultrasound in low-resource settings. No product endorsements are provided. Conclusions This desk review provides an overview of the landscape of low-cost portable ultrasound probes for use in obstetrics in resource-constrained environments, and provides a description of key capabilities and costs for each. Methods could be applied to mapping the landscape of portable ultrasound devices for other clinical applications, or may be extended to reviewing other types of healthcare technologies. Further studies are recommended to evaluate portable ultrasound devices for usability and durability in global field settings.
SARS-CoV-2 seroprevalence in pregnant women in Kilifi, Kenya from March 2020 to March 2022.
BACKGROUND: Seroprevalence studies are an alternative approach to estimating the extent of transmission of SARS-CoV-2 and the evolution of the pandemic in different geographical settings. We aimed to determine the SARS-CoV-2 seroprevalence from March 2020 to March 2022 in a rural and urban setting in Kilifi County, Kenya. METHODS: We obtained representative random samples of stored serum from a pregnancy cohort study for the period March 2020 to March 2022 and tested for antibodies against the spike protein using a qualitative SARS-CoV-2 ELISA kit (Wantai, total antibodies). All positive samples were retested for anti-SARS-CoV-2 anti-nucleocapsid antibodies (Euroimmun, ELISA kits, NCP, qualitative, IgG) and anti-spike protein antibodies (Euroimmun, ELISA kits, QuantiVac; quantitative, IgG). RESULTS: A total of 2,495 (of 4,703 available) samples were tested. There was an overall trend of increasing seropositivity from a low of 0% [95% CI 0-0.06] in March 2020 to a high of 89.4% [95% CI 83.36-93.82] in Feb 2022. Of the Wantai test-positive samples, 59.7% [95% CI 57.06-62.34] tested positive by the Euroimmun anti-SARS-CoV-2 NCP test and 37.4% [95% CI 34.83-40.04] tested positive by the Euroimmun anti-SARS-CoV-2 QuantiVac test. No differences were observed between the urban and rural hospital but villages adjacent to the major highway traversing the study area had a higher seroprevalence. CONCLUSION: Anti-SARS-CoV-2 seroprevalence rose rapidly, with most of the population exposed to SARS-CoV-2 within 23 months of the first cases. The high cumulative seroprevalence suggests greater population exposure to SARS-CoV-2 than that reported from surveillance data.
Automated Myocardial Wall Motion Classification using Handcrafted Features vs a Deep CNN-based mapping.
Compared to other modalities such as computed tomography or magnetic resonance imaging, the appearance of ultrasound images is highly dependent on the expertise of the sonographer or clinician making the image acquisition, as well as the machine used, making it a challenge to analyze due to the frequent presence of artefacts, missing boundaries, attenuation, shadows, and speckle. In addition, manual contouring of the epicardial and endocardial walls exhibits large inconsistencies and variations as it is strongly dependent on the sonographer's training and expertise. Hence, in this paper we propose a fully automated image analysis framework to ultimately perform wall motion abnormality classification in 2D+T images. We explore both traditional Random Forests classification with handcrafted features and spatio-temporal hierarchical aggregation of information with a deep learning CNN-based approach. Regarding the later classifier, we also investigate the effect of local phase information retrieval through the use of Feature Asymmetry (FA), and demonstrate that pre-processing videos with FA enables the spatio-temporal CNN to better discover relevant left ventricle endocardial abstractions from low-level features to high-level representations automatically.