Evaluation of MicroScan Bacterial Identification Panels for Low-Resource Settings.
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ABSTRACT:
SUBMITTER: Ombelet S
PROVIDER: S-EPMC7922174 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Medical diagnosis in low-resource settings is confronted by the lack of suitable guidelines, protocols and checklists. Online-accessible procedural documents are difficult to find, might be mistranslated or interpreted and usually do not address the needs of developing countries. Urinalysis, one of the most frequently performed diagnostic examinations worldwide, involves a series of tests aiming to detect particular disorders, such as urinary tract infections, kidney disease and diabetes. In this guideline, we present an alternative approach for clinical laboratories with limited resources to identify common bacterial uropathogens. We propose dividing the identification plan into two levels. The implicated pathogen will first be assigned into a bacterial group, basic identification, against which a suitable panel of antimicrobial agents shall be selected for the antimicrobial susceptibility testing (AST). Characterization of the pathogen to the genus or species level, advanced identification, will then be performed to ensure correct reading of the AST results and determine the epidemiology of clinically significant pathogens. Most of the proposed steps in our guideline are tailored to meet the needs of clinical laboratories in low-resource settings. Such guidelines are needed to strengthen the capacity of regional pathology laboratories and to enhance international initiatives on antimicrobial resistance and health equity.
| S-EPMC7602787 | biostudies-literature
Project description:BACKGROUND:Globally, preterm birth is the leading cause of neonatal death with estimated prevalence and associated mortality highest in low- and middle-income countries (LMICs). Accurate identification of preterm infants is important at the individual level for appropriate clinical intervention as well as at the population level for informed policy decisions and resource allocation. As early prenatal ultrasound is commonly not available in these settings, gestational age (GA) is often estimated using newborn assessment at birth. This approach assumes last menstrual period to be unreliable and birthweight to be unable to distinguish preterm infants from those that are small for gestational age (SGA). We sought to leverage machine learning algorithms incorporating maternal factors associated with SGA to improve accuracy of preterm newborn identification in LMIC settings. METHODS AND FINDINGS:This study uses data from an ongoing obstetrical cohort in Lusaka, Zambia that uses early pregnancy ultrasound to estimate GA. Our intent was to identify the best set of parameters commonly available at delivery to correctly categorize births as either preterm (<37 weeks) or term, compared to GA assigned by early ultrasound as the gold standard. Trained midwives conducted a newborn assessment (<72 hours) and collected maternal and neonatal data at the time of delivery or shortly thereafter. New Ballard Score (NBS), last menstrual period (LMP), and birth weight were used individually to assign GA at delivery and categorize each birth as either preterm or term. Additionally, machine learning techniques incorporated combinations of these measures with several maternal and newborn characteristics associated with prematurity and SGA to develop GA at delivery and preterm birth prediction models. The distribution and accuracy of all models were compared to early ultrasound dating. Within our live-born cohort to date (n = 862), the median GA at delivery by early ultrasound was 39.4 weeks (IQR: 38.3-40.3). Among assessed newborns with complete data included in this analysis (n = 468), the median GA by ultrasound was 39.6 weeks (IQR: 38.4-40.3). Using machine learning, we identified a combination of six accessible parameters (LMP, birth weight, twin delivery, maternal height, hypertension in labor, and HIV serostatus) that can be used by machine learning to outperform current GA prediction methods. For preterm birth prediction, this combination of covariates correctly classified >94% of newborns and achieved an area under the curve (AUC) of 0.9796. CONCLUSIONS:We identified a parsimonious list of variables that can be used by machine learning approaches to improve accuracy of preterm newborn identification. Our best-performing model included LMP, birth weight, twin delivery, HIV serostatus, and maternal factors associated with SGA. These variables are all easily collected at delivery, reducing the skill and time required by the frontline health worker to assess GA. TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT02738892.
| S-EPMC6392324 | biostudies-literature
Project description:Differences in definitions of acute pediatric diarrhea result in variable estimates of morbidity and mortality, treatment coverage, and associations with risk factors and outcomes. We reviewed published literature and guidelines focused on acute pediatric diarrhea in low- and middle-income countries. Clinical guidelines most commonly defined diarrhea in terms of quantity of loose or watery stool with consideration of normal stool patterns, whereas research studies often relied exclusively on a quantitative definition. The most commonly used quantitative definition, ?3 loose or watery stools in a 24-hour period, has been compared to gold standards of caregiver perception and visual inspection of stool, with variable agreement. Age, breast-feeding status, and setting (facility vs household-based) influence the performance of quantitative diarrhea definitions in children. Universal adoption of a set of valid gold standard definitions specifically aligned with various programmatic and research goals will lead to more accurate coverage estimates and better-informed resource prioritization.
| S-EPMC5907861 | biostudies-other
Project description:PurposeIdiopathic clubfoot affects approximately 1/1000 alive-born infants, of whom 80-91% are born in low- or middle-income countries (LMICs). This retrospective study aimed to evaluate the morphological, functional, and social outcomes in patients with neglected clubfoot in rural Bangladesh, after receiving surgical treatment.MethodsPatients received a posteromedial release (PMR) with or without an additional soft tissue intervention (group 1), a PMR with an additional bony intervention (group 2), or a triple arthrodesis (group 3) according to our surgical algorithm. Patients were followed until two year post-intervention. Evaluation was done using a modified International Clubfoot Study Group Outcome evaluation score and the Laaveg-Ponseti score.ResultsTwenty-two patients with 32 neglected clubfeet (ages 2-24 years) received surgical treatment. Nineteen patients with 29 clubfeet attended follow-up. At two year follow-up an excellent, good, or fair Laaveg-Ponseti score was obtained in 81% (group 1), 80% (group 2), and 0% (group 3) of the patients (p value 0.0038). Age at intervention is inversely correlated with the Laaveg-Ponseti score at two year follow-up (p < 0.0001). All patients attended school or work and were able to wear normal shoes.ConclusionOur treatment algorithm is in line with other surgical algorithms used in LMICs. Our data reconfirms that excellent results can be obtained with a PMR regardless of age. Our algorithm follows a pragmatic approach that takes into account the reality on the ground in many LMICs. Good functional outcomes can be achieved with PMR for neglected clubfoot. Further research is needed to investigate the possible role of triple arthrodesis.
| S-EPMC8752568 | biostudies-literature
Project description:IntroductionZika virus (ZIKV) is a re-emerging flavivirus that poses a significant public health threat. ZIKV exhibits a wide array of non-vector borne human transmission routes, such as sexual transmission, transplacental transmission and blood transfusion. Detection and surveillance of ZIKV is considered paramount in prevention of major outbreaks. With the majority of cases reported in low-resource locations, simple, low-cost detection methods are considered highly desirable.Materials and methodsHere we have developed a sensitive and specific ZIKV diagnostic using reverse transcription recombinase-aided amplification (RT-RAA) coupled with lateral flow detection (LFD) targeting a highly conserved region of the ZIKV NS1 gene.ResultsWe show our rapid, isothermal-ZIKV-diagnostic (Iso-ZIKV-Dx) can detect 500 copies of synthetic ZIKV RNA/μL in under 30 min at a constant 39°C. Using simulated urine samples, we observed that Iso-ZIKV-Dx also detects as low as 34.28 RNA copies/reaction of ZIKV (MR766 strain). Specificity testing confirmed that our test does not detect any co-circulating flaviviruses (dengue, West Nile, Japanese encephalitis, Murray Valley encephalitis and yellow fever viruses) or chikungunya virus. Sample processing results show complete inactivation of ZIKV (MR766 strain) in 5 min at room temperature using our novel viral RNA sample preparation reagent. Furthermore, lateral flow strips testing demonstrates positive diagnoses in as little as 5 min in running buffer.DiscussionContrary to conventional RT-qPCR, our Iso-ZIKV-Dx does not require expensive machinery, specialised laboratory settings or extensively trained personnel. Pre-clinical evaluation demonstrates that our test exhibits robust, in-field capabilities without compromising sensitivity or specificity. When compared to the gold-standard RT-qPCR, our Iso-ZIKV-Dx test offers an array of applications that extend beyond diagnostics alone, including potential for surveillance and monitoring of ZIKV vector competency.
| S-EPMC10694267 | biostudies-literature
Project description:Objective:Evaluate a novel continuous temperature monitor in a low-resource neonatal ward. Design:We developed a low-cost continuous neonatal temperature monitor (NTM) for use in low-resource settings. Accuracy of NTM was initially assessed in the laboratory. Clinical evaluation then was performed in a neonatal ward in a central hospital in Malawi; eligible neonates (<1?week of age) were recruited for continuous temperature monitoring with NTM and a Philips Intellivue MP30 Patient Monitor. Interventions and outcome measures:The temperature probes of NTM and the reference patient monitor were attached to the infant's abdomen, and core temperature was continuously recorded for up to 3?hours. Axillary temperatures were taken every hour. We compared temperatures measured using NTM, the patient monitor and the axillary thermometer. Results:Laboratory temperature measurements obtained with NTM were within 0.059°C (range: -0.035°C to 0.195°C) of a reference thermometer. A total of 39 patients were recruited to participate in the clinical evaluation of NTM; data from four patients were excluded due to faulty hardware connections. The mean difference in measured temperatures between the NTM and the Intellivue MP30 was -0.04°C (95%?CI -0.52°C to 0.44°C). Conclusion:NTM meets ISO 80601-2-56 standards for accuracy and is an appropriate, low-cost continuous temperature monitor for neonatal wards in low-resource settings. Trial registration numbers:NCT03965312 and NCT03866122.
| S-EPMC7228652 | biostudies-literature
Project description:BackgroundMany modern molecular diagnostic assays targeting nucleic acids are typically confined to developed countries or to the national reference laboratories of developing-world countries. The ability to make technologies for the rapid diagnosis of infectious diseases broadly available in a portable, low-cost format would mark a revolutionary step forward in global health. Many molecular assays are also developed based on polymerase chain reactions (PCR), which require thermal cyclers that are relatively heavy (>20 pounds) and need continuous electrical power. The temperature ramping speed of most economical thermal cyclers are relatively slow (2 to 3 °C/s) so a polymerase chain reaction can take 1 to 2 hours. Most of all, these thermal cyclers are still too expensive ($2k to $4k) for low-resource setting uses.Methodology/principal findingsIn this article, we demonstrate the development of a low-cost and rapid water bath based thermal cycler that does not require active temperature control or continuous power supply during PCR. This unit costs $130 to build using commercial off-the-shelf items. The use of two or three vacuum-insulated stainless-steel Thermos food jars containing heated water (for denaturation and annealing/extension steps) and a layer of oil on top of the water allow for significantly stabilized temperatures for PCR to take place. Using an Arduino-based microcontroller, we automate the "archaic" method of hand-transferring PCR tubes between water baths.Conclusions/significanceWe demonstrate that this innovative unit can deliver high speed PCR (17 s per PCR cycle) with the potential to go beyond the 1,522 bp long amplicons tested in this study and can amplify from templates down to at least 20 copies per reaction. The unit also accepts regular PCR tubes and glass capillary tubes. The PCR efficiency of our thermal cycler is not different from other commercial thermal cyclers. When combined with a rapid nucleic acid detection approach, the thermos thermal cycler (TTC) can enable on-site molecular diagnostics in low-resource settings.
| S-EPMC4492969 | biostudies-literature
Project description:The rapid emergence and spread of numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants across the globe underscores the crucial need for continuous SARS-CoV-2 surveillance to ensure that potentially more pathogenic variants are detected early and contained. Whole genome sequencing (WGS) is currently the gold standard for COVID-19 surveillance; however, it remains cost-prohibitive and requires specialized technical skills. To increase surveillance capacity, especially in resource-scarce settings, supplementary methods that are cost- and time-effective are needed. Real-time multiplex PCR genotyping assays offer an economical and fast solution for screening circulating and emerging variants while simultaneously complementing existing WGS approaches. In this study we evaluated the AllplexTM SARS-CoV-2 Variants II multiplex real-time PCR genotyping assay, Seegene (South Korea), and implemented it in retrospectively characterizing circulating SARS-CoV-2 variants in a rural South African setting between April and October 2021, prior to the emergence of the Omicron variant in South Africa. The AllplexTM SARS-CoV-2 Variants II real-time PCR assay demonstrated perfect concordance with whole-genome sequencing in detecting Beta and Delta variants and exhibited high specificity, sensitivity and reproducibility. Implementation of the assay in characterization of SARS-CoV-2 variants between April and October 2021 in a rural South African setting revealed a rapid shift from the Beta to the Delta variant between April and June. All specimens successfully genotyped in April were Beta variants and the Delta variant was not detected until May. By June, 78% of samples genotyped were Delta variants and in July >95% of all genotyped samples were Delta variants. The Delta variant continued to predominate through to the end of our analysis in October 2021. Taken together, a commercial SARS-CoV-2 variant genotyping assay detected the rapid rate at which the Delta variant displaced the Beta variant in Limpopo, an under-monitored province in South Africa. Such assays provide a quick and cost-effective method of monitoring circulating variants and should be used to complement genomic sequencing for COVID-19 surveillance especially in resource-scarce settings.
| S-EPMC9231807 | biostudies-literature
Project description: Not available
| S-EPMC7333981 | biostudies-literature
Project description:BackgroundTo date (April 2021), medical device (MD) design approaches have failed to consider the contexts where MDs can be operationalised. Although most of the global population lives and is treated in Low- and Middle-Income Countries (LMCIs), over 80% of the MD market share is in high-resource settings, which set de facto standards that cannot be taken for granted in lower resource settings. Using a MD designed for high-resource settings in LMICs may hinder its safe and efficient operationalisation. In the literature, many criteria for frameworks to support resilient MD design were presented. However, since the available criteria (as of 2021) are far from being consensual and comprehensive, the aim of this study is to raise awareness about such challenges and to scope experts' consensus regarding the essentiality of MD design criteria.ResultsThis paper presents a novel application of Delphi study and Multiple Criteria Decision Analysis (MCDA) to develop a framework comprising 26 essential criteria, which were evaluated and chosen by international experts coming from different parts of the world. This framework was validated by analysing some MDs presented in the WHO Compendium of innovative health technologies for low-resource settings.ConclusionsThis novel holistic framework takes into account some domains that are usually underestimated by MDs designers. For this reason, it can be used by experts designing MDs resilient to low-resource settings and it can also assist policymakers and non-governmental organisations in shaping the future of global healthcare.
| S-EPMC8220789 | biostudies-literature