Resource-limited Settings Research Articles

Short- and long-term stability of SARS-CoV-2 antibodies on dried blood spots under different storage conditions.

Dried blood spots (DBS) are broadly used for different serological analyses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody assessment. In order to biobank DBS samples, an understanding of the preservation of SARS-CoV-2 antibodies is needed. Therefore, we assessed the stability of SARS-CoV-2 antibodies on DBS during short- and long-term storage under different storage temperatures. Seven sample donors were enrolled, each donating twenty 6 mm DBS to assess anti-spike (S1) SARS-CoV-2 IgG antibodies (EUROIMMUN). Baseline samples were analyzed on the day of collection. The remainder of the samples was stored in grip seal bags kept in a cryobox at room temperature/4°C until 2 months after collection and at -20°C until 2 years after collection. Samples were analyzed at regular intervals within the total storage duration and after one and five freeze-thaw cycles. A pooled coefficient of variation was calculated for each storage temperature. We found that anti-S1 SARS-CoV-2 antibodies collected on DBS saver cards remain stable during short-term storage at RT, 4°C, and -20°C (at least to 2 months) and long-term storage at -20°C (at least 2 years). Moreover, up to five freeze-thaw cycles can occur without impacting the anti-S1 SARS-CoV-2 antibody level. The inter-assay coefficient of variation lies between 10 and 15%. As DBS can be preserved for both shorter periods of time at RT and longer periods of time at -20°C, they are a perfect application for studies that require sample shipment by mail, self-sampling studies, studies in limited resource settings and biobanking.IMPORTANCEDried blood spots (DBS) are currently widely used as a microsampling technique for different qualitative and quantitative serological assessments. Yet, there is a lack of long-term stability and storage condition studies. In our study, first, we assessed the stability of SARS-CoV-2 antibodies on DBS up to 2 years post-collection. We believe that our data are not only important for future COVID-19 research but also for studies on other infections/diseases using DBS-based serology.

Fibreoptic intubation in children and young people in resource-limited settings: A case series during a humanitarian aid operation in Guinea.

Fibreoptic intubation in children and young people in resource-limited settings: A case series during a humanitarian aid operation in Guinea.

Immunotherapeutic Strategies as Potential Treatment Options for Cutaneous Leishmaniasis.

Cutaneous leishmaniasis (CL), caused by protozoan parasites of the Leishmania genus, is prevalent in tropical and subtropical regions, with important morbidity, particularly in low- to middle-income countries. Current systemic treatments, including pentavalent antimonials and miltefosine, are associated with significant toxicity, reduced efficacy, and are frequently ineffective in cases of severe or chronic CL. Immunotherapies leverage the immune system to combat microbial infection and offer a promising adjunct or alternative approach to the current standard of care for CL. However, the heterogeneous clinical presentation of CL, which is dependent on parasite species and host immunity, may require informed clinical intervention with immunotherapies. This review explores the clinical and immunological characteristics of CL, emphasising the current landscape of immunotherapies in in vivo models and clinical studies. Such immune-based interventions aim to modulate immune responses against Leishmania, with additive therapeutic effects enabling the efficacy of lower drug doses and decreasing the associated toxicity. Understanding the mechanisms that underlie immunotherapy for CL provides critical insights into developing safer and more effective treatments for this neglected tropical disease. Identifying suitable therapeutic candidates and establishing their safety and efficacy are essential steps in this process. However, the feasibility and utility of these treatments in resource-limited settings must also be considered, taking into account factors such as cost of production, temperature stability, and overall patient access.

Rapid Molecular Diagnostics in Vulvovaginal Candidosis.

Vulvovaginal candidosis (VVC) is a common condition among women, with current diagnostic methods relying on clinical evaluation and laboratory testing. These traditional methods are often limited by the need for specialized training, variable performance, and lengthy diagnostic processes, leading to delayed treatment and inappropriate antifungal use. This review evaluates the efficacy of molecular diagnostic tools for VVC and provides guidance on their application in clinical practice. A literature search was conducted using PubMed to identify studies evaluating rapid diagnostic tests specifically for vulvovaginal Candida isolates. Inclusion criteria focused on studies utilizing molecular diagnostics for the detection of Candida species in VVC. Articles discussing non-vaginal Candida infections, non-English studies, and animal or in vitro research were excluded. Twenty-three studies met the inclusion criteria, predominantly evaluating nucleid acid amplification tests/polymerase chain reaction (NAAT/PCR) assays and DNA probes. PCR/NAAT assays demonstrated high sensitivity and specificity (>86%) for VVC diagnosis, outperforming conventional diagnostic methods. Comparatively, DNA probes, while simpler, exhibited lower sensitivity. The included studies were mostly observational, with only one randomized controlled trial. Emerging diagnostic technologies, including artificial intelligence and integrated testing models, show promise for improving diagnostic precision and clinical outcomes. Molecular diagnostics offer a significant improvement in VVC management, though traditional methods remain valuable in resource-limited settings.

Reducing harm associated with prehospital tourniquet application in resource-limited settings.

Reducing harm associated with prehospital tourniquet application in resource-limited settings.

Management of high dose olanzapine poisoning in a young child under limited resource setting: a case report from Nepal

Introduction: Olanzapine, an atypical antipsychotic, is widely used for treating psychiatric conditions such as schizophrenia and bipolar disorder. Accidental overdose in children is rare but can lead to severe clinical effects. This case report discusses the management of a five-year-old male who accidently ingested 180 mg of olanzapine, the highest reported dose in a child under five years. Case Presentation: A five-year-old boy accidentally ingested 180 mg of Olanzapine, resulting in loss of consciousness and central nervous system depression. He exhibited hyperglycemia, elevated lactate, and prolonged prothrombin time, but no significant cardiovascular issues. Following intubation and supportive care, including intravenous medications and mechanical ventilation, the child gradually improved. He was discharged in stable condition with follow-up instructions. Discussion: Olanzapine toxicity in children presents with a variety of symptoms, including somnolence, hypotension, and neurological impairments, which are dose-dependent. Even in case of an exceptionally high overdose, the absence of cardiovascular toxicity supports safety profile of olanzapine. Common laboratory findings include hyperglycemia, elevated liver enzymes, and metabolic disturbances. Management involves airway protection, supportive care, and monitoring, as no specific antidote exists. Prompt and appropriate care, even in severe cases under limited resource settings, can lead to favorable outcomes. Conclusion: In cases of high dose accidental olanzapine poisoning in children, it is essential to begin quick intervention and comprehensive supportive care to achieve successful outcomes and can be managed even in limited resource settings. Preventive measures are crucial to avoid such incidents and careful monitoring is essential in managing pediatric olanzapine overdose.

Clinical diagnosis and management of spinocerebellar Ataxia in a resource-constrained setting: a case report from Eastern Nepal

Introduction: Spinocerebellar ataxias (SCA) are a diverse group of neurodegenerative disorders with autosomal dominant inheritance, primarily affecting the cerebellum and its connections. Diagnosis typically involves genetic testing, but in resource-limited settings, clinical and neuroimaging assessments become critical. This case report highlights the role of non-genetic methods in diagnosing SCA and outlines management strategies in such settings. Case Presentation: A 41-year-old male presented with a two-year history of progressive gait imbalance, headache, and abnormal speech. He had a family history of similar symptoms in two siblings, but no significant past medical history. Clinical examination revealed scanning speech, dysmetria, and a broad-based gait. Clinical and neuroimaging findings, including cerebellar atrophy, led to a diagnosis of SCA in the absence of genetic testing. Patient management with speech, occupational, and physical therapies, showed gradual improvement. Discussion: SCA, characterized by cerebellar atrophy and a range of clinical symptoms, is typically diagnosed through genetic testing, but clinical and imaging assessments are crucial when genetic resources are limited. This case illustrates that a comprehensive clinical evaluation, including neuroimaging, can support the diagnosis of SCA even without genetic testing. Strategic management emphasizing symptomatic relief and functional improvement through a multidisciplinary approach, including regular follow-up and personalized therapy, are crucial, as evidenced by the timely improvement observed in our case. Conclusion: In resource-limited settings, a comprehensive clinical and neuroimaging assessment is essential for diagnosing Spinocerebellar Ataxia when genetic testing is not feasible. Effective management through multidisciplinary therapies can improve patient outcomes, underscoring the need for innovative strategies to enhance diagnostic and treatment capabilities in such environments.

Rapid detection of human adenovirus by multiple cross displacement amplification combined with nanoparticle-based biosensor platform

Human adenoviruses (HAdV), particularly serotypes 3 and 7 (HAdV-3 and HAdV-7), are significant respiratory pathogens that contribute to high morbidity rates and severe pneumonia in infants and children. The lack of distinct clinical presentations and effective treatments highlights the urgent need for rapid and reliable diagnostic methods for HAdV-3 and HAdV-7. This study devises a novel detection assay, termed HAdV-MCDA-LFB, which combines isothermal multiple cross displacement amplification (MCDA) with a nanoparticle-based lateral flow biosensor (LFB). Targeting the conserved hexon gene, HAdV-MCDA-LFB demonstrated high sensitivity, detecting low to 10 fg of hexon-containing plasmid per reaction without cross-reaction under the optimized conditions. Moreover, HAdV-MCDA-LFB exhibited comparable diagnostic accuracy to real-time PCR in clinical sample analysis, indicating its practical applicability. The whole procedure, including rapid template preparation (15 min), MCDA reaction (40 min at 67 °C) and result interpretation (<5 min), can be completed within one hour. Together, this rapid turnaround time, coupled with its simplicity and accuracy, makes HAdV-MCDA-LFB a promising point-of-care diagnostic tool for HAdV-3 and HAdV-7, particularly in resource-limited settings.

VERMICULTURE AND VERMICOMPOSTING: TWIN EARTHWORM TECHNOLOGIES, SUITABLE FOR HOUSEHOLDS AND SMALLHOLDER FARMERS TO CONVERT WASTES TO WEALTH – A NARRATIVE REVIEW

Many smallholder farmers in developing countries face interconnected challenges, including poor soil fertilisation, low agricultural output, and inefficient conversion of agricultural wastes into biofertilisers, all of which can be sustainably addressed through vermiculture and vermicomposting—twin earthworm-based technologies. This review aims to explore vermiculture and vermicomposting, their interconnections, and key optimisation factors, while also guiding smallholder farmers on setting up simple vermiculture and vermicomposting units using locally sourced materials. A wide literature search was conducted across databases such as Google Scholar, Scopus, and Web of Science, focusing on vermiculture, vermicomposting and earthworm utilisation in waste management. From an initial pool of articles, 35 studies were selected for their relevance, empirical data, and rigorous methodology. Findings show that earthworms' natural behaviours, such as burrowing, soil ingestion, excretion and rapid reproduction, are exploited by vermiculture and vermicomposting to produce both earthworm mass and vermicompost, a sustainable and efficient biofertilizer. Vermiculture focuses on maximising earthworm harvest, with vermicompost as a secondary product, while vermicomposting aims to maximise vermicompost production, often resulting in increased earthworm mass. Vermicomposting units can be constructed from locally available materials, including wood, organic and agricultural wastes, and earthworm food sources, like fermented cow and sheep dung. The review assesses the potential of these technologies for small-scale farms, emphasising their feasibility and benefits in resource-limited settings. Since low agricultural output by smallholder farmers is partly traceable to unaffordable costs of chemical fertilisers, this review will draw attention to the use of vermicompost as a cheap and sustainable alternative

An exploratory study on the potential of ChatGPT as an AI-assisted diagnostic tool for visceral leishmaniasis

Visceral leishmaniasis (VL) is a severe parasitic disease that poses significant diagnostic challenges due to its complex presentation and the necessity for comprehensive diagnostic methods. This exploratory study investigates the potential of Chat Generative Pre-trained Transformer (ChatGPT)/GPT-4, an artificial intelligence (AI) chatbot, in assisting the diagnostic process for VL. We evaluated the diagnostic accuracy of ChatGPT/GPT-4 in generating differential diagnosis lists for eight clinical vignette cases of VL, authored by a Brazilian infectious disease doctor. Our findings reveal that ChatGPT/GPT-4 included VL in the top five differential diagnoses in 75% of the cases (95% confidence interval [CI]: 40.1 &amp;ndash; 93.7%) and identified VL as the top diagnosis in 50% of the cases (95% CI: 30.3 &amp;ndash; 86.5%). These results underscore the high potential of ChatGPT/GPT-4 as an AI-assisted diagnostic tool, which is capable of providing accurate differential diagnoses and assisting healthcare professionals in resource-limited settings. The study highlights the broader applicability of AI chatbots in medical diagnostics, not only for common conditions but also for specialized and less prevalent diseases like VL. By integrating AI tools into the diagnostic workflow, healthcare providers can enhance their diagnostic accuracy and efficiency, ultimately improving patient outcomes. This research contributes to the growing body of evidence supporting the utility of AI in healthcare and underscores the need for further studies to validate these findings across larger and more diverse clinical scenarios.

Beyond Dialysis: Reshaping CKD Paradigms in Developing Nations

Dear Sir / Madam, Respected Editor, I am writing to bring attention to the critical need for increased research on conservative kidney management (CKM) in the context of patients with advanced chronic kidney disease (CKD). The recent advancements in developed nations have demonstrated that CKM is a novel and effective approach to caring for CKD patients, particularly those who choose not to pursue maintenance dialysis. Historically, medical care for individuals with CKD has adhered to a paternalistic model, where clinicians make treatment decisions independent of patient preferences. JS Scherer et al observed that a provider's assessment of a patient's frailty and response exerted a more substantial influence on the treatment provided than the patient’s comorbidities, functional status, and stated preferences. 2 Furthermore, another study showed that some individuals exhibited a preference for conservative care after shared-decision making, irrespective of the potential survival benefits offered by dialysis if it entailed frequent hospital visits or travel restrictions. 3 This underscores the significance of patient autonomy, where the pursuit of freedom can sometimes outweigh the emphasis on clinical outcomes. However, contemporary CKD management in the 21st century emphasizes shared decision-making and patient empowerment. While research suggests CKM can improve quality of life, reduce hospitalizations, and minimize invasive procedures, offering a valuable alternative to dialysis, its impact on survival becomes less clear for patients over 80 or those with multiple comorbidities.4 Additionally, the inclusion of patients and their families in collaborative decision-making processes has proven advantageous, supported by specialized decision aids that promote well-informed discussions regarding CKM with healthcare providers.5 Nephrologists face significant challenges in implementing effective conservative kidney management (CKM) due to a lack of clinical guidelines, training, evidence, and system-level infrastructure. This has resulted in limited awareness and discussion of CKM among patients and healthcare providers, hindering its adoption. With the global burden of chronic kidney disease (CKD) increasing significantly over the past three decades, particularly affecting low- and middle-income countries, there is a pressing need for innovative, cost-effective solutions. CKM emerges as a viable alternative where dialysis is often inaccessible or unaffordable, with the potential to significantly impact CKD management, especially in resource-limited settings such as Pakistan. I urge the scientific community and policymakers to recognize the importance of supporting and conducting research on conservative kidney management. ---Continue

ESPressoscope: A small and powerful approach for in situ microscopy.

Microscopy is essential for detecting, identifying, analyzing, and measuring small objects. Access to modern microscopy equipment is crucial for scientific research, especially in the biomedical and analytical sciences. However, the high cost of equipment, limited availability of parts, and challenges associated with transporting equipment often limit the accessibility and operational capabilities of these tools, particularly in field sites and other remote or resource-limited settings. Thus, there is a need for affordable and accessible alternatives to traditional microscopy systems. We address this challenge by investigating the feasibility of using a simple microcontroller board not only as a portable and field-ready digital microscope, but furthermore as a versatile platform which can easily be adapted to a variety of imaging applications. By adding a few external components, we demonstrate that a low-cost ESP32 camera board can be used to build an autonomous in situ platform for digital time-lapse imaging of cells. Our prototype of this approach, which we call ESPressoscope, can be adapted to applications ranging from monitoring incubator cell cultures in the lab to observing ecological phenomena in the sea, and it can be adapted for other techniques such as microfluidics or spectrophotometry. Our prototype of the ESPressoscope concept achieves a low power consumption and small size, which makes it ideal for field research in environments and applications where microscopy was previously infeasible. Its Wi-Fi connectivity enables integration with external image processing and storage systems, including on cloud platforms when internet access is available. Finally, we present several web browser-based tools to help users operate and manage our prototype's software. Our findings demonstrate the potential for low-cost, portable microscopy solutions to enable new and more accessible experiments for biological and analytical applications.

Blood-rsCDM: a new rapid and simplified carbapenemase detection method for detecting carbapenemases in Enterobacterales directly from positive blood cultures

ObjectiveWe aim to validate and evaluate a new rapid and simplified method, called Blood-rsCDM, for the detection and characterization of carbapenemase using 3-aminophenylboronic acid (APBA) and ethylenediaminetetraacetic acid (EDTA) β-lactamase inhibitors from positive blood cultures.MethodWe utilized a panel of 172 Enterobacterales strains, including blaKPC (77), blaNDM (48), blaIMP (9), blaVIM (2), blaOXA-181 (2), blaKPC and blaNDM (6), as well as 28 carbapenem-susceptible Enterobacterales isolates, to assess the performance of Blood-rsCDM and the EDTA-carbapenem inactivation method (eCIM). Carbapenemase class was determined using specific inhibitors at 4 h and 6 h by Blood-rsCDM.ResultsBlood-rsCDM exhibited a sensitivity of 97.9% at both time points, with a specificity of 100%, regardless of the culture duration. The sensitivity of eCIM was 94.4%, with a specificity of 100%. Blood-rsCDM accurately characterized KPC-producing isolates as 77/77, metallo-β-lactamases (MBLs) as 58/59, and KPC and NDM carbapenemases as 6/6 at 4 h. There was no difference in results between the 4 h and 6 h time points. However, Blood-rsCDM could not differentiate OXA-181-producing strains. For eCIM, the characterization numbers for KPC-, OXA-181-, and MBLs-producing strains were 77/77, 2/2, and 57/59, respectively, but it failed to detect the coproduction of KPC and NDM isolates.ConclusionBlood-rsCDM accurately discriminates carbapenemase within 4 h and is capable of directly differentiating multi-enzyme (KPC and NDM) presence from positive blood culture broths. Therefore, Blood-rsCDM represents a rapid, simple, easy-to-read, and accurate tool that can be utilized in resource-limited settings.

AI in Psoriatic Disease: Scoping Review.

Artificial intelligence (AI) has many applications in numerous medical fields, including dermatology. Although the majority of AI studies in dermatology focus on skin cancer, there is growing interest in the applicability of AI models in inflammatory diseases, such as psoriasis. Psoriatic disease is a chronic, inflammatory, immune-mediated systemic condition with multiple comorbidities and a significant impact on patients' quality of life. Advanced treatments, including biologics and small molecules, have transformed the management of psoriatic disease. Nevertheless, there are still considerable unmet needs. Globally, delays in the diagnosis of the disease and its severity are common due to poor access to health care systems. Moreover, despite the abundance of treatments, we are unable to predict which is the right medication for the right patient, especially in resource-limited settings. AI could be an additional tool to address those needs. In this way, we can improve rates of diagnosis, accurately assess severity, and predict outcomes of treatment. This study aims to provide an up-to-date literature review on the use of AI in psoriatic disease, including diagnostics and clinical management as well as addressing the limitations in applicability. We searched the databases MEDLINE, PubMed, and Embase using the keywords "AI AND psoriasis OR psoriatic arthritis OR psoriatic disease," "machine learning AND psoriasis OR psoriatic arthritis OR psoriatic disease," and "prognostic model AND psoriasis OR psoriatic arthritis OR psoriatic disease" until June 1, 2023. Reference lists of relevant papers were also cross-examined for other papers not detected in the initial search. Our literature search yielded 38 relevant papers. AI has been identified as a key component in digital health technologies. Within this field, there is the potential to apply specific techniques such as machine learning and deep learning to address several aspects of managing psoriatic disease. This includes diagnosis, particularly useful for remote teledermatology via photographs taken by patients as well as monitoring and estimating severity. Similarly, AI can be used to synthesize the vast data sets already in place through patient registries which can help identify appropriate biologic treatments for future cohorts and those individuals most likely to develop complications. There are multiple advantageous uses for AI and digital health technologies in psoriatic disease. With wider implementation of AI, we need to be mindful of potential limitations, such as validation and standardization or generalizability of results in specific populations, such as patients with darker skin phototypes.

CT Imaging as a Single Modality for Clinical Staging of Gastric Cancer in Limited Resource Centers: A Retrospective Pilot Study.

Gastric cancer disproportionately impacts populations in resource-limited settings. Within a safety-net network, we assessed the utility of computed tomography (CT) as a single staging modality. We utilized a clinical database of gastric cancer patients treated within the Los Angeles County safety-net hospital system from 2016 to 2023 in conjunction with retrospective imaging review by certified radiologists. We assessed agreement between clinical and pathological staging for patients who underwent curative gastrectomy using the Kappa coefficient. Of 107 patients with available CT imaging, 43.9% (n = 47) were staged with CT as a single modality. Most tumors displayed infiltrating (75%) or diffuse (28%) morphology, 41% displayed adequate gastric distention and regional lymphadenopathy was common (68%). Twenty-nine patients underwent curative gastrectomy. Overall agreement was minimal (κ = 0.29, 95% CI [0.071-0.51], p = 0.022), weak for T3/T4 tumors (κ = 0.50, 95% CI [0.17-0.82], p < 0.01), and weak for Hispanic/Latino patients (κ = 0.47, 95% CI [0.19-0.76], p < 0.01). There was minimal agreement between clinical and pathologic staging when assessing clinical stage by CT imaging alone, suggesting that CT is not adequate as a single modality staging tool. While every effort should be made to obtain multimodal staging, larger studies are warranted to improve CT imaging protocols for staging in resource-limited settings.

Short-term associations of diarrhoeal diseases in children with temperature and precipitation in seven low- and middle-income countries from Sub-Saharan Africa and South Asia in the Global Enteric Multicenter Study.

Diarrhoeal diseases cause a heavy burden in developing countries. Although studies have described the seasonality of diarrhoeal diseases, the association of weather variables with diarrhoeal diseases has not been well characterized in resource-limited settings where the burden remains high. We examined short-term associations between ambient temperature, precipitation and hospital visits due to diarrhoea among children in seven low- and middle-income countries. Hospital visits due to diarrhoeal diseases under 5 years old were collected from seven sites in The Gambia, Mali, Mozambique, Kenya, India, Bangladesh, and Pakistan via the Global Enteric Multicenter Study from December 2007 to March 2011. Daily weather data during the same period were downloaded from the ERA5-Land. We fitted time-series regression models to examine the relationships of daily diarrhoea cases with daily ambient temperature and precipitation. Then, we used meta-analytic tools to examine the heterogeneity between the site-specific estimates. The cumulative relative risk (RR) of diarrhoea for temperature exposure (95th percentile vs. 1st percentile) ranged from 0.24 to 8.07, with Mozambique and Bangladesh showing positive associations, while Mali and Pakistan showed negative associations. The RR for precipitation (95th percentile vs. 1st percentile) ranged from 0.77 to 1.55, with Mali and India showing positive associations, while the only negative association was observed in Pakistan. Meta-analysis showed substantial heterogeneity in the association between temperature-diarrhoea and precipitation-diarrhoea across sites, with I2 of 84.2% and 67.5%, respectively. Child diarrhoea and weather factors have diverse and complex associations across South Asia and Sub-Saharan Africa. Diarrhoeal surveillance system settings should be conceptualized based on the observed pattern of climate change in these locations.

Critical Care in Resource-Limited Settings: Shedding Light and Providing Light…and Hope.

Critical Care in Resource-Limited Settings: Shedding Light and Providing Light…and Hope.

Integrating Genomic Data with the Development of CRISPR-Based Point-of-Care-Testing for Bacterial Infections

Abstract Purpose of Review Bacterial infections and antibiotic resistance contribute to global mortality. Despite many infections being preventable and treatable, the lack of reliable and accessible diagnostic tools exacerbates these issues. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-based diagnostics has emerged as a promising solution. However, the development of CRISPR diagnostics has often occurred in isolation, with limited integration of genomic data to guide target selection. In this review, we explore the synergy between bacterial genomics and CRISPR-based point-of-care tests (POCT), highlighting how genomic insights can inform target selection and enhance diagnostic accuracy. Recent Findings We review recent advances in CRISPR-based technologies, focusing on the critical role of target sequence selection in improving the sensitivity of CRISPR-based diagnostics. Additionally, we examine the implementation of these technologies in resource-limited settings across Asia and Africa, presenting successful case studies that demonstrate their potential. Summary The integration of bacterial genomics with CRISPR technology offers significant promise for the development of effective point-of-care diagnostics.

Dried blood spot improves global access to aquaporin-4-IgG testing for neuromyelitis optica.

This study aimed to evaluate the diagnostic accuracy of dried blood spot (DBS) compared with conventional serum Aquaporin-4-IgG (AQP4-IgG) testing. Prospective multicenter diagnostic study was conducted between April 2018 and October 2023 across medical centers in the United States, Uganda, and the Republic of Guinea. Neuromyelitis optica spectrum disorder (NMOSD) patients and controls collected blood on filter paper cards along with concurrent serum samples. These samples underwent analysis using flow cytometric live-cell-based assays (CBA) and enzyme-linked immunosorbent assay (ELISA) to determine AQP4 serostatus. The accuracy of AQP4-IgG detection between DBS and serum (gold standard) was compared. Among 150 participants (47 cases, 103 controls), there was a strong correlation between DBS and serum samples (Spearman's correlation coefficient of 0.82). The AUC was 0.97 (95% CI: 0.92-0.99). AQP4-IgG detection through DBS showed 87.0% sensitivity (95% CI: 0.74-0.95) and 100% specificity (95% CI: 0.96-1.00) using CBA, and 65.2% sensitivity (95% CI: 0.43-0.84) and 95.2% specificity (95% CI: 0.76-0.99) using ELISA. Serum ELISA demonstrated 69.6% sensitivity (95% CI: 0.47-0.87) and 98.4% specificity (95% CI: 0.91-0.99). The stability of DBS in detecting AQP4-IgG persisted over 24 months for most cases. The DBS represents a viable alternative for detecting AQP4-IgG in resource-limited settings to diagnose NMOSD, offering high sensitivity and specificity comparable to serum testing. Moreover, DBS has low shipping costs, is easy to administer, and is suitable for point-of-care testing.

Implementation of the WHO surgical safety checklist in resource-limited Somalia: a new standard in surgical safety

BackgroundSurgical safety remains a critical global health concern, with complications from surgical procedures resulting in significant morbidity and mortality, particularly in low- and middle-income countries. The World Health Organization (WHO) Surgical Safety Checklist (SSC) has been shown to reduce surgical complications and mortality rates. However, its implementation and impact in resource-limited settings like Somalia remain understudied. This study aimed to evaluate the implementation of the WHO SSC in selected hospitals in Mogadishu, Somalia, and assess its impact on surgical safety practices.MethodsA pre- and post-intervention study was conducted in 15 randomly selected hospitals in Mogadishu, Somalia. The intervention involved a comprehensive training program on the WHO SSC for surgical teams. Data on hospital characteristics, surgical details, and adherence to the SSC were collected over two periods: pre-intervention (April 12th to May 4th, 2024) and post-intervention (May 12th to June 3rd, 2024). The primary outcome was the adherence to the SSC, categorized as good (> 60%) or poor (≤ 60%). Descriptive statistics, McNemar’s test, and binary logistic regression were used for data analysis.ResultsAdherence to the WHO SSC significantly improved post-intervention, with 98.8% of surgical cases demonstrating good adherence compared to 37% pre-intervention (p < 0.001). The mean adherence score increased from 51.6% (SD = 29.6) to 94.1% (SD = 8.2). Significant improvements were observed for most individual checklist items, including patient identity confirmation, surgical site marking, anesthesia machine checks, and pulse oximeter use (p < 0.001). Team dynamics and communication also improved significantly post-intervention. Hospital type, size, years of service, funding source, surgical department, surgery type, urgency, and staff numbers were associated with checklist adherence pre-intervention.ConclusionThe implementation of a comprehensive training intervention significantly improved adherence to the WHO Surgical Safety Checklist in resource-limited hospitals in Mogadishu, Somalia. The findings highlight the feasibility and effectiveness of the SSC in enhancing surgical safety practices, team communication, and patient outcomes in challenging healthcare environments. Tailored implementation strategies, ongoing training, and cultural adaptation are crucial for the successful adoption of the SSC in resource-constrained settings.