Resource-limited Environments Research Articles

Point-of-care ultrasound in resource-limited environments: a review

Ultrasound is a standard assessment modality in hospital and prehospital settings. It is becoming more accessible in remote, austere and resource-limited environments. Aim: This article aims to review the literature on the use of point-of-care ultrasound (POCUS) imaging in low- to medium-income countries (LMICs) and by practitioners working in remote and austere out-of-hospital environments. Methods: Fifteen articles published between 2019 and 2023 found via PubMed were identified and analysed. Results: The 15 papers present the use of ultrasound imaging by practitioners in LMICs: six were systemic reviews; five were narrative reviews; two were randomised clinical trials; and two were case studies. Conclusions: Few articles focusing on POCUS use in LMICs were published over the five-year period. However, the number of publications increased over the years. Of the 15 studies in this review, six (40%) were systematic reviews, five (33%) were narrative reviews, two (13%) were random clinical trials and two (13%) were case studies. All studies were conducted in district hospitals or other resource-limited environments. The studies have revealed a significant increase in POCUS use over the past few years, with the majority of the devices now being smartphone-based. This is a promising development in POCUS use in austere environments.

A lightweight visual mamba network for image recognition under resource-limited environments

The Vision Transformers (ViTs) models show great potential in recognition due to their excellent self-attention mechanisms. However, they often need more computational complexity, making achieving high performance in resource-constrained environments challenging. This paper proposes a lightweight visual model (called LightViM) to tackle these challenges, specifically devised for recognition challenges under resource-constrained environments. Considering the imperative of reducing the model’s computational complexity and resource consumption , we propose lightweight local–global feature fusion modules based on Mamba (LGF-Mamba) aimed at integrating spatially detailed local information with globally contextualized features while maintaining lower linear time complexity. In LGF-Mamba, Mamba sub-blocks are first designed to extract global information; then, for the rapid extraction of local features, LocalE module is designed and integrated into LGF-Mamba, exploring more comprehensive feature representation. This mechanism efficiently directs the network to integrate features from different spatial scales, thereby improving the recognition performance in resource-constrained environments. Experimental results indicate that, in comparison to other leading-edge lightweight methods, the proposed procedure simultaneously achieves superior recognition performance and minimal resource consumption.

Managing Patients With COVID-19 in Armenia Using a Remote Monitoring System: Descriptive Study.

The COVID-19 pandemic has imposed immense stress on global health care systems, especially in low- and middle-income countries (LMICs). Armenia, a middle-income country in the Caucasus region, contended with the pandemic and a concurrent war, resulting in significant demand on its already strained health care infrastructure. The COVID@home program was a multi-institution, international collaboration to address critical hospital bed shortages by implementing a home-based oxygen therapy and remote monitoring program. The objective of this study was to describe the program protocol and clinical outcomes of implementing an early discharge program in Armenia through a collaboration of partner institutions, which can inform the future implementation of COVID-19 remote home monitoring programs, particularly in LMICs or low-resource settings. Seven hospitals in Yerevan participated in the COVID@home program. A web app based on OpenMRS was developed to facilitate data capture and care coordination. Patients meeting eligibility criteria were enrolled during hospitalization and monitored daily while on oxygen at home. Program evaluation relied on data extraction from (1) eligibility and enrollment forms, (2) daily monitoring forms, and (3) discharge forms. Over 11 months, 439 patients were screened, and 221 patients were managed and discharged. Around 94% (n=208) of participants safely discontinued oxygen therapy at home, with a median home monitoring duration of 26 (IQR 15-45 days; mean 32.33, SD 25.29) days. Women (median 28.5, mean 35.25 days) had similar length of stay to men (median 26, mean 32.21 days; P=.75). Despite challenges in data collection and entry, the program demonstrated feasibility and safety, with a mortality rate below 1% and low re-admission rate. Opportunities for operational and data quality improvements were identified. This study contributes practical evidence on the implementation and outcomes of a remote monitoring program in Armenia, offering insights into managing patients with COVID-19 in resource-constrained settings. The COVID@home program's success provides a model for remote patient care, potentially alleviating strain on health care resources in LMICs. Policymakers can draw from these findings to inform the development of adaptable health care solutions during public health crises, emphasizing the need for innovative approaches in resource-limited environments.

Model development for bespoke large language models for digital triage assistance in mental health care

Contemporary large language models (LLMs) may have utility for processing unstructured, narrative free-text clinical data contained in electronic health records (EHRs) — a particularly important use-case for mental health where a majority of routinely-collected patient data lacks structured, machine-readable content.A significant problem for the United Kingdom’s National Health Service (NHS) are the long waiting lists for specialist mental healthcare. According to NHS data (NHS Digital, 2024), in each month of 2023, there were between 370,000 and 470,000 individual new referrals into secondary mental healthcare services. Referrals must be triaged by clinicians, using clinical information contained in the patient’s EHR to arrive at a decision about the most appropriate mental healthcare team to assess and potentially treat these patients.The ability to efficiently recommend a relevant team by ingesting potentially voluminous clinical notes could help services both reduce referral waiting times and with the right technology, improve the evidence available to justify triage decisions.We present and evaluate three different approaches for LLM-based, end-to-end ingestion of variable-length clinical EHR data to assist clinicians when triaging referrals. Our model is able to deliver triage recommendations consistent with existing clinical practices and its architecture was implemented on a single GPU, making it practical for implementation in resource-limited NHS environments where private implementations of LLM technology will be necessary to ensure confidential clinical data are appropriately controlled and governed. Code available at: https://github.com/NtaylorOX/BespokeLLM_Triage.

Development of instructional design principles for using ICT in resource-limited learning environments: a case of Bangladesh

The integration of ICT in education in developing countries has become a significant focus in various ODA projects and educational research. With the increasing demand for teachers to incorporate ICT in their classrooms, the precise methods for effectively integrating ICT resources have not been thoroughly explored. Therefore, this research aimed to develop the most optimal instructional design principles that may systematically guide teachers in planning their lessons using ICT, specifically in the context of Bangladesh. By employing the design and development research method, this research developed an initial set of instructional design principles based on literature review and field research, then elaborated on the principles through three sets of internal validation tests and a usability test by conducting in-depth interviews to confirm the applicability of the principles in real classroom settings in Bangladesh. The final version of instructional design principles is composed of five components, ten principles, and 22 specific guidelines. Two distinct features of the principles are discussed for further research. In discussion, this research underscores the necessity of providing practical instructional design principles to guide teachers in effectively utilizing ICT, particularly within a resource-limited learning environment like Bangladesh.

Characterizing the soil microbial community associated with the fungal pathogen Coccidioides immitis.

Coccidioidomycosis is a fungal disease affecting humans and other mammals, caused by environmental pathogens of the genus Coccidioides . Understanding the ecological factors that shape the distribution of Coccidioides in soils is important for minimizing the risk of human exposure, though this remains challenging due to the pathogen's highly variable spatial distribution. Here, we examined associations between the soil microbial community and Coccidioides immitis presence within the Carrizo Plain National Monument-a minimally disturbed grassland ecosystem, and the site of a longitudinal study examining the effects of rodents and their burrows on C. immitis presence in soils. Using internal transcribed spacer 2 (ITS2) and 16S sequencing to characterize the soil fungal and bacterial communities, we found over 30 fungal species, including several other members of the Onygenales order, that co-occurred with Coccidioides more frequently than expected by chance. Coccidioides -positive samples were significantly higher in microbial diversity than negative samples, an association partly driven by higher Coccidioides presence within rodent burrows compared to surface soils. Soil source ( i.e., rodent burrow versus surface soil) explained the largest amount of variation in bacterial and fungal community diversity and composition, with soils collected from rodent burrows having higher microbial diversity than those collected from adjacent surface soils. While prior evidence is mixed regarding associations between Coccidioides and microbial diversity, our study suggests that favorable microhabitats such as rodent burrows can lead to a positive association between soil diversity and Coccidioides presence, particularly in otherwise resource-limited natural environments.

Detecting emerald ash borer boring vibrations using an encoder-decoder and improved DenseNet model.

Forest ecosystems are under constant threat from wood-boring pests such as the Emerald ash borer (EAB), which remain elusive owing to their hidden life cycles within tree trunks. Early detection is vital to mitigate economic and ecological damage. The main current monitoring method is manual detection which is ineffective at early stages of infestation. This study introduces VibroEABNet, a deep learning-based joint recognition network designed to enhance the detection of EAB boring vibration signals, with a novel approach integrating denoising and recognition modules. The proposed VibroEABNet model demonstrated exceptional performance, achieving an average accuracy of 98.98% across multiple signal-to-noise ratios (SNRs) in test datasets and a remarkable 97.5% accuracy in real forest datasets, surpassing traditional models and other deep learning networks evaluated in this study. These findings were supported by rigorous noise resistance analysis and real dataset evaluation, indicating the model's robustness and reliability in practical applications. Furthermore, the model's efficiency was highlighted by its inference time of 26 ms and a compact model size of 8.43 MB, underscoring its suitability for deployment in resource-limited environments. The development of VibroEABNet marks a significant advancement in pest detection methodologies, offering a scalable, accurate and efficient solution for early monitoring of wood-boring pests. The integration of a denoising module within the network structure addresses the challenge of environmental noise, one of the primary limitations in acoustic monitoring of pests. Currently, this research is limited to a specific pest. Future work will focus on the applicability of this network to other wood-boring pests. © 2024 Society of Chemical Industry.

Making gene editing accessible in resource limited environments: recommendations to guide a first-time user.

The designer nuclease, CRISPR-Cas9 system has advanced the field of genome engineering owing to its programmability and ease of use. The application of these molecular scissors for genome engineering earned the developing researchers the Nobel prize in Chemistry in the year 2020. At present, the potential of this technology to improve global challenges continues to grow exponentially. CRISPR-Cas9 shows promise in the recent advances made in the Global North such as the FDA-approved gene therapy for the treatment of sickle cell anaemia and β-thalassemia and the gene editing of porcine kidney for xenotransplantation into humans affected by end-stage kidney failure. Limited resources, low government investment with an allocation of 1% of gross domestic production to research and development including a shortage of skilled professionals and lack of knowledge may preclude the use of this revolutionary technology in the Global South where the countries involved have reduced science and technology budgets. Focusing on the practical application of genome engineering, successful genetic manipulation is not easily accomplishable and is influenced by the chromatin landscape of the target locus, guide RNA selection, the experimental design including the profiling of the gene edited cells, which impacts the overall outcome achieved. Our assessment primarily delves into economical approaches of performing efficient genome engineering to support the first-time user restricted by limited resources with the aim of democratizing the use of the technology across low- and middle-income countries. Here we provide a comprehensive overview on existing experimental techniques, the significance for target locus analysis and current pitfalls such as the underrepresentation of global genetic diversity. Several perspectives of genome engineering approaches are outlined, which can be adopted in a resource limited setting to enable a higher success rate of genome editing-based innovations in low- and middle-income countries.

Amino acid sensitive latent fingermark detection formulations based upon improvised carrier solvents for resource-limited environments: A proof-of-concept study

HFE-7100 and petroleum ether (bp 40–60 °C) are routine carrier solvents used in amino acid sensitive fingermark reagents such as 1,2-indanedione/zinc chloride (IND-Zn) and ninhydrin. However, limited resource jurisdictions face major challenges in sourcing laboratory-grade reagents due to budgetary and geographical restrictions. Common hydrocarbon solvents, available from hardware stores and similar outlets, may offer a more readily available and inexpensive alternative for such jurisdictions. This study assessed the range of improvised carrier solvents for their suitability in the IND-Zn formulation and found that eight different hydrocarbon solvents were able to develop fingermarks when substituted into the formulation. The formulation based on shellite solvent outperformed all other improvised formulations tested, providing high-quality fingermarks and similar sensitivity to a petroleum ether (bp 40–60 °C) based formulation across six porous substrates using six donors. A similar approach was applied to ninhydrin, where it was discovered that formulations using kerosene, white spirits and shellite as carrier solvents performed comparably to a formulation based on petroleum ether (bp 40–60 °C). By chemically characterising each solvent using gas chromatography-mass spectrometry, this study also provided a greater understanding of how the chemical composition of a carrier solvent impacts the efficacy of the resulting IND-Zn formulation, emphasising that hydrocarbon solvents should contain short-chain alkanes and minimal aromatic content to give a more volatile formulation. Additionally, the identity of the solvent was found to cause slight differences in the colour and luminescence intensity of ink diffusion on porous substrates. These results indicate that improvised hydrocarbon solvents are suitable alternatives to common carrier solvents with their operational use offering major benefits for limited resource jurisdictions by reducing costs and supply chain risks. A thorough risk assessment must be conducted by each jurisdiction that intends to use this method as health and safety considerations are concerns with these improvised solvents.

Effects of periodic bottlenecks on the dynamics of adaptive evolution in microbial populations.

Population bottlenecks can impact the rate of adaptation in evolving populations. On the one hand, each bottleneck reduces the genetic variation that fuels adaptation. On the other hand, each founder that survives a bottleneck can undergo more generations and leave more descendants in a resource-limited environment, which allows surviving beneficial mutations to spread more quickly. A theoretical model predicted that the rate of fitness gains should be maximized using ~8-fold dilutions. Here we investigate the impact of repeated bottlenecks on the dynamics of adaptation using numerical simulations and experimental populations of Escherichia coli. Our simulations confirm the model's prediction when populations evolve in a regime where beneficial mutations are rare and waiting times between successful mutations are long. However, more extreme dilutions maximize fitness gains in simulations when beneficial mutations are common and clonal interference prevents most of them from fixing. To examine these predictions, we propagated 48 E. coli populations with 2-, 8-, 100-, and 1000-fold dilutions for 150 days. Adaptation began earlier and fitness gains were greater with 100- and 1000-fold dilutions than with 8-fold dilutions, consistent with the simulations when beneficial mutations are common. However, the selection pressures in the 2-fold treatment were qualitatively different from the other treatments, violating a critical assumption of the model and simulations. Thus, varying the dilution factor during periodic bottlenecks can have multiple effects on the dynamics of adaptation caused by differential losses of diversity, different numbers of generations, and altered selection.

From passion to profit: the growth of Mambokadzi Bath and Body

Learning outcomes By the end of the lesson, students should be able to identify and think critically about common business problems and come up with possible solutions, explain how a business owner’s attributes can influence the business decisions they make, use available information to assess the viability and sustainability of a business model/strategy, determine the strengths and weaknesses of a particular marketing strategy and suggest ways to improve it and use the information provided to evaluate the risks and benefits of business growth strategies and determine their appropriateness for specified circumstances. Case overview/synopsis Mambokadzi is a small business with considerable potential in Zimbabwe’s beauty and personal care industry. The case study spans several years, highlighting Sharon Chingwaro’s journey as she navigates the difficulties of starting and growing a business with limited resources. The case study delves into various aspects of running a small business, such as production, marketing, distribution, human resources and intellectual property. It also discusses the value of resilience and endurance, as well as the need for resourcefulness when starting and growing a business under difficult circumstances. This case study is intended to teach entrepreneurship and marketing strategies to both under- and postgraduate students, with a particular emphasis on the difficulties of starting and growing a business in a limited-resource environment. It has applications in a variety of fields, including entrepreneurship, strategic management and marketing. Complexity academic level This case study is suitable for undergraduate and postgraduate students. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

LVD-YOLO: An efficient lightweight vehicle detection model for intelligent transportation systems

Vehicle detection is a fundamental component of intelligent transportation systems. However, current algorithms often encounter issues such as high computational complexity, long execution times, and significant resource demands, making them unsuitable for resource-limited environments. To overcome these challenges, we propose LVD-YOLO, a Lightweight Vehicle Detection Model based on YOLO. This model incorporates the EfficientNetv2 network structure as its backbone, which reduces parameters and enhances feature extraction capabilities. By utilizing a bidirectional feature pyramid structure along with a dual attention mechanism, we enable efficient information exchange across feature layers, thereby improving multiscale feature fusion. Additionally, we refine the model's loss function with SIoU loss to boost regression and prediction performance. Experimental results on the PASCAL VOC and MS COCO datasets show that LVD-YOLO outperforms YOLOv5s, achieving a 0.5% increase in accuracy while reducing FLOPs by 64.6% and parameters by 48.6%. These improvements highlight its effectiveness for use in resource-constrained environments.

Technical nuance

Background. Colloid cyst treatment with purely endoscopic surgery is considered to be safe and effective. Complete capsule removal for gross total resection is usually recommended to prevent recurrence but may not always be safely feasible. Our objective was to go for complete endoscopic surgery using mainly aspiration, manipulation and coagulation with complete capsule resection and discuss the rationale for the procedure. Methods and materials. A case report with a third ventricle colloid cyst was surgically treated with a complete endoscopic excision using the proper technique. Results. Our patient underwent Transforaminal endoscopic surgery and the cyst was excised completely and the capsule was removed intentionally. Cyst remnants were absent on postoperative MRI. Mild Intraventricular haemorrhage was an intraoperative complication. Surgery was statistically associated with cyst volume and ventricular size reduction. There were no serious complications postoperatively. Follow-up did not show any recurrence or remnant growth that needed further treatment. Conclusion. Gross total resection may be the main objective for selected cases and seems to be safer while preserving good results, especially in a limited resource environment. Surgical planning allows the surgeon to choose among the different resection routes and techniques available. Decisions are predominantly based on preoperative imaging and intraoperative findings. Full-endoscopic approach for third ventricle colloid cyst removal is a feasible technique. Cyst aspiration followed by grasping and rotational manoeuvre for the cyst wall provides total removal with the resolution of the obstruction if present and relief of symptoms.

Highly sensitive detection of carbendazim in agricultural products using colorimetric and photothermal lateral flow immunoassay based on plasmonic gold nanostars

The wide use and high toxicity of carbendazim (CBD) in agriculture pose unprecedented demands for convenient, sensitive, and cost-effective on-site monitoring. Herein, we propose a novel colorimetric and photothermal dual-mode lateral flow immunoassay (LFIA) based on plasmonic gold nanostars (AuNSs) for CBD detection in agricultural products. The AuNSs were synthesized via a rapid seed-mediated growth method (with growth time of ∼5 s). A stable immunoprobe was formed by adsorbing CBD antibodies onto AuNSs. This immunoprobe exhibited high conversion efficiency and sensitivity in photothermal detection with a low limit of detection (LOD) of 0.28 ng mL−1. The LOD of the colorimetric mode was higher (0.48 ng mL−1). The results of CBD detection in various agricultural products aligned well with ultra-performance liquid chromatography tandem mass spectrometry. Overall, our LFIA shows excellent sensitivity, specificity, reproducibility, and rapidness in CBD detection, and thus is a highly potential on-site platform in resource-limited environments.

External Support and Demographic Factors as Differentials of Achievement Goal Orientation among Adolescent Students in Resource-Limited Environments

External Support and Demographic Factors as Differentials of Achievement Goal Orientation among Adolescent Students in Resource-Limited Environments

Magnetic Hydrogel Microbots for Efficient Pollutant Decontamination and Self-Catalyzed Regeneration in Continuous Flow Systems.

The efficient removal of organic pollutants from water is crucial for protecting human health and the ecosystem. While adsorbent-based approaches offer advantages over traditional chemical and thermal methods, they still suffer from slow adsorption kinetics, high energy demand, and limited material lifespan. Herein, an efficient decontamination platform is introduced, using magnetic hydrogel microbots (MHMs) made from picolitre-sized hydrogel droplets coated with multifunctional magnetic nanoparticles. This approach includes 1) dividing a droplet into smaller microbots to enhance their interaction with sample solution and 2) dynamically spinning these MHMs to generate hydrodynamic flows that actively draw pollutants toward the embedded hydrogel for capture. The MHMs show high decontamination effectiveness in both bulk and continuous flow setups, achieving ≈95% removal efficiency within 3min. Further integrating MHMs with a non-pressurized fluidic platform enables energy-efficient continuous flow decontamination, removing ≥95% total organic carbon from a complex pollutant mixture at a flow rate surpassing other recent designs. Additionally, the MHMs facilitate self-catalyzed regeneration using an environmentally friendly H2O2 precursor, allowing for long-term and repeated usage. By enabling the unique divide-and-arrest decontamination of toxic pollutants, the multifunctional design holds tremendous promise for on-site wastewater treatment to ensure safe water access for everyone, even in resource-limited environments.

Establishment of a Real-Time Fluorescence Isothermal Recombinase-Aided Amplification Method for the Detection of H9 Avian Influenza Virus.

The H9 subtype of avian influenza virus (AIV) has been characterized by its rapid spread, wide range of prevalence, and continuous evolution in recent years, leading to an increasing ability for cross-species transmission. This not only severely impacts the economic benefits of the aquaculture industry, but also poses a significant threat to human health. Therefore, developing a rapid and sensitive detection method is crucial for the timely diagnosis and prevention of H9 AIVs. In this study, a real-time fluorescent reverse transcription recombinase-aided isothermal amplification (RT-RAA) technique targeting the hemagglutinin (HA) of H9 AIVs was established. This technique can be used for detection in just 30 min at a constant temperature of 42 °C, and it exhibits good specificity without cross-reactivity with other viruses. Sensitivity tests revealed that the detection limit of RT-RAA was 163 copies per reaction, and the visual detection limit was 1759 copies per reaction at a 95% confidence interval, both of which are capable of detecting low concentrations of standards. Furthermore, RT-RAA was applied to detect 155 clinical samples, and compared to real-time fluorescent quantitative PCR (RT-qPCR), RT-RAA demonstrated high accuracy, with a specificity of 100% and a kappa value of 0.96, indicating good correlation. Additionally, with the assistance of a portable blue imaging device, we can visually observe the amplification products, greatly facilitating rapid detection in resource-limited environments. The RT-RAA detection method developed in this study does not require expensive equipment or highly skilled staff, making it beneficial for the accurate and low-cost detection of H9 AIVs.

Abstract P316: Beyond the Cuff: Revolutionizing Hypertension Care through Human-Centered Design and Tech-Driven Solutions in an Urban Community Health Center

Community Health Centers serve populations burdened with cardiovascular disease due to social determinants of health, necessitating innovative solutions in resource-limited environments. Wi-Fi/Bluetooth-enabled home blood pressure monitors have emerged as clinical tools for diagnosing, monitoring, and managing hypertension. The real time data enables timely interventions by care teams of patients being monitored. A multifaceted approach beyond clinic settings, supported by digital tools, can help reduce healthcare costs by preventing avoidable emergency room visits. We posited that implementing a self-monitored blood pressure (SMBP) program, supplemented by holistic, human-centered patient coaching and feedback, in a community health center setting would enhance patient engagement, medication adherence, and hypertension control. We designed and piloted a small SMBP program using Bluetooth-enabled blood pressure devices, targeting adult patients with documented uncontrolled blood pressure seen in our health centers in a 6- month window. This was further augmented by a holistic, human-centered individual and group-level coaching session. Patients enrolled in the SMBP program received comprehensive education on hypertension, including medication management and lifestyle changes, as well as data-driven feedback on their blood pressure profiles during virtual group and individual outreach sessions. The program's goals were to increase patient engagement in their care, adherence to interventions, leading to better blood pressure control. Results were significant: 22 of 32 participants graduated, achieving improved blood pressure control with medication and lifestyle changes. Average reductions of 17 mmHg in systolic and 6 mmHg in diastolic blood pressure were noted after being in the program for an average of three months. Among the graduates, 50% required medication intensification, and 60% adopted lifestyle changes, indicating the program's effectiveness. Our pilot affirmed the efficacy of utilizing digital solutions and integrated strategies to improve hypertension control and empower patients to make timely changes with data feedback. The key findings from our pilot led to the expansion of the SMBP program to serve a larger cohort of patients in our clinic. This underscores the critical role of patient engagement, technology integration, and an integrated approach to care in improving hypertension management, particularly in underserved communities.

Methodology for the Formulation of the Guidelines for the Management of Moderate to Severe Traumatic Brain Injury in Austere and Combat Environments

Care for the patient with traumatic brain injury (TBI) in austere or combat environments is challenging because resources are substantially limited as compared with care for these patients in a tertiary medical facility. Significant research has been and will continue to be performed on TBI care in these settings. This includes high-quality, evidence-based guidelines that are routinely updated to help guide the treating team as to best practices for a wide range of TBI presentations, complications, and outcomes. Much less is known regarding best practices for TBI care in a resource-limited environment, such as a facility in an austere environment without advanced imaging, dedicated neurointensive care, or definitive neurosurgical capabilities. The aim of this study was to identify the methodology that will be used for an upcoming in-person guideline conference, focusing on the care of patients with TBI in resource-limited austere and/or combat zones.

Clinical diagnosis of stroke patients using SIRIRAJ stroke score and Computed Tomography

Background & Objectives: Stroke is a significant cause of disability and death globally, with ischemic and hemorrhagic types. Rapid diagnosis is critical, particularly in resource-limited settings where access to neuroimaging is restricted. Thus, this study aimed to diagnose stroke patients usingthe Siriraj Stroke Score (SSS) and computed tomography at Janaki Medical College TeachingHospital.Materials and Methods: A total of 97 stroke patients presented within 72 hours of onset atJanaki Medical College Teaching Hospital, Nepal, were included in this study. Patients wereclinically assessed using the SSS and subsequently underwent CT brain scanning to confirm thestroke subtype. The SSS was calculated based on consciousness level, headache, vomiting,atheroma markers, and diastolic blood pressure. The results from SSS were compared with the CTscan findings to determine the clinical diagnosis.Results: The study found that 56.7% of the patients had hemorrhagic strokes, with intraparenchymal hematoma being the most common subtype. The SSS showed a strong correlation with CT scan results, particularly for hemorrhagic strokes, where most patients with a score above 1 were accurately diagnosed.Conclusion: The Siriraj Stroke Score is a valuable tool for initial stroke assessment, especially insettings where advanced neuroimaging is not immediately available. The study supports usingSSS in early stroke management, which could improve patient outcomes in resource-limited environments.