LITERATURE UPDATE
timely intervention because turnaround time (TAT) decreases with these devices. They can also be operated by non-medical personnel and patients with minimum expertise as these devices are easy to handle and interpret. This increases patient awareness regarding their diseases and benefits doctors in giving more patient-centred care. POCT devices require minimum setup and can be utilised even in remote places. The present review focuses on POCT
devices employed specifically in clinical biochemistry, (eg glucose, HbA1c, cardiac biomarkers, fertility tests, haematological analysis, electrolytes, enzymes, urine dipstick tests, etc.). This introductory review delves into comprehending the fundamentals of POCT technologies, their guidelines, applications, advantages, and disadvantages. It covers a broad overview of the tests done and the samples required to process these tests. It also compares the pros and cons of POCT devices over centralised laboratory testing. The review also aims to emphasise the relevance of its use in today’s era, current trends regarding POCT in urban and rural setups, challenges faced in the field during its implementation, and the potential areas of improvement in the future. However, it is advisable to seek references for more detailed and critical information regarding all the specific topics given in this review article.
Point-of-care testing for diagnosing hypofibrinogenemia in postpartum hemorrhage: Systematic review and meta- analysis Nakamura E, Mihara T, Kondo Y, Noma H, Shimizu S. Thromb Res. 2025 Jul; 251: 109339. doi: 10.1016/
j.thromres.2025.109339.
Postpartum haemorrhage (PPH) can rapidly cause hyperfibrinogenaemia, requiring prompt coagulation factor replacement. Point-of-care testing (POCT) is gaining interest for early diagnosis for hyperfibrinogenaemia, despite limited evidence. This systematic review evaluated the diagnostic accuracy of POCT for hyperfibrinogenaemia in PPH. A literature search was conducted using MEDLINE, Embase, Cochrane, and Web of Science. Studies using POCT for PPH diagnosis, both observational and interventional, were included. Risk of bias was assessed using the QUADAS-2 tool. A meta-analysis was performed using the Reitsma bivariate random- effects model for three POCT types: dry haematology, thromboelastography, and thromboelastometry. The diagnostic accuracy was evaluated using a summary Receiver Operating Characteristic (ROC) curve and area under the curve (AUC).
Nine articles, including 16 studies with
a total of 2902 patients, were analysed. The dry haematology group had only two studies, preventing data pooling. Thromboelastography (four articles, including 10 studies with 1386 patients) showed a sensitivity of 0.80 (95% CI: 0.75– 0.84), specificity of 0.90 (0.85–0.93), and AUC of 0.81 (0.77–0.85). Thromboelastometry (four articles, including four studies with 1394 patients) showed a sensitivity of 0.89 (0.74–0.96), specificity of 0.84 (0.63–0.94), and AUC of 0.93 (0.83–0.95). Thromboelastography and
thromboelastometry demonstrated high diagnostic accuracy for hyperfibrinogenaemia in PPH. However, evidence for dry haematology was insufficient. POCT may enable rapid and accurate diagnosis of hyperfibrinogenaemia in PPH.
Artificial intelligence (AI) in point-of-care testing Pillay TS, Khan AI, Yenice S. Clin Chim Acta. 2025 Jun 15; 574: 120341. doi: 10.1016/
j.cca.2025.120341.
The integration of artificial intelligence (AI) into point-of-care testing (POCT) represents a transformative leap in modern healthcare, addressing critical challenges in diagnostic accuracy, workflow efficiency, and equitable access. While POCT has revolutionised decentralised care through rapid results, its potential is hindered by variability in accuracy, integration hurdles, and resource constraints. AI technologies – encompassing machine learning, deep learning, and natural language processing – offer robust solutions: convolutional neural networks improve malaria detection in sub-Saharan Africa to 95% sensitivity, while predictive analytics reduce device downtime by 20% in resource-limited setings. AI- driven decision support systems curtail antibiotic misuse by 40% through real-time data synthesis, and portable AI devices enable anaemia screening in rural India with 94% accuracy, slashing diagnostic delays from weeks to hours. Despite these advancements, challenges persist, including data privacy risks, algorithmic opacity, and infrastructural gaps in low- and middle-income countries. Explainable AI frameworks and
blockchain encryption are critical to building clinician trust and ensuring regulatory compliance. Future directions emphasise the convergence of AI with Internet of Things (IoT) and blockchain for predictive diagnostics, as demonstrated by AI-IoT systems forecasting dengue outbreaks 14 days in advance. Personalised medicine, powered by genomic and wearable data integration, further
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underscores AI potential to tailor therapies, reducing cardiovascular events by 25%. Realising this vision demands
interdisciplinary collaboration, ethical governance, and equitable implementation to bridge global health disparities. By harmonising innovation with accessibility, AI-enhanced POCT emerges as a cornerstone of proactive, patient- centred healthcare, poised to democratise diagnostics and drive sustainable health equity worldwide.
Bioluminescence in Clinical and Point-of- Care Testing Reyes S, Rodriguez R, Dikici E, Daunert S, Deo S. Biosensors (Basel). 2025 Jul 2; 15 (7): 422. doi: 10.3390/bios15070422.
Point-of-care testing (POCT) offers a transformative approach to diagnostics by enabling rapid and accurate results at or near the site of patient care. This is especially valuable in critical care, emergency setings, and resource- limited areas. However, one major limitation of POCT remains its analytical sensitivity, particularly in detecting low concentrations of analytes. To address this, various innovations
are being explored, including advanced sensors, signal amplification, and sensitive labels. Among these, bioluminescent proteins have gained atention for their high sensitivity, fast readout, minimal background interference, and simplified instrumentation. Bioluminescence – light emission from biochemical reactions – presents an ideal platform for enhancing POCT sensitivity. In parallel, metal-organic frameworks (MOFs), especially structures like ZIF-8, are emerging as valuable materials in biosensing. Their high porosity, tunable surface properties, and ability to host biomolecules make them excellent candidates for improving analyte capture and signal transduction. When integrated with bioluminescent systems, MOFs can stabilise proteins, concentrate targets, and enhance overall assay performance. This review highlights the role of bioluminescent proteins in medical diagnostics and their application in POCT platforms. The authors also discuss the potential synergy between MOFs and bioluminescence to overcome current sensitivity limitations. Finally, they examine existing challenges and strategies to optimise these technologies for robust, field-deployable diagnostic tools. By leveraging both the natural
sensitivity of bioluminescence and the structural advantages of MOFs, next- generation POCT systems can achieve superior performance, driving forward diagnostic accessibility and patient care outcomes.
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