Cancer remains a global health challenge, necessitating continuous advancements in diagnostic and treatment strategies. This review focuses on the utility of non-invasive biomarkers in cancer diagnosis and treatment, their role in early detection, disease monitoring, and personalized therapeutic interventions. Through a systematic review of the literature, we identified 45 relevant studies that highlight the potential of these biomarkers across various cancer types, such as breast, prostate, lung, and colorectal cancers. The non-invasive biomarkers discussed include liquid biopsies, epigenetic markers, non-coding RNAs, exosomal cargo, and metabolites. Notably, liquid biopsies, particularly those based on circulating tumour DNA (ctDNA), have emerged as the most promising method for early, non-invasive cancer detection due to their ability to provide comprehensive genetic and epigenetic information from easily accessible blood samples. This review demonstrates how non-invasive biomarkers can facilitate early cancer detection, accurate subtyping, and tailored treatment strategies, thereby improving patient outcomes. It underscores the transformative potential of non-invasive biomarkers in oncology, highlighting their application for enhancing early detection, survival rates, and treatment precision in cancer care.
UNASSIGNED: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023474749 PROSPERO, identifier CRD42023474749.

OBJECTIVE: This study aimed to summarize validity estimates of International Classification of Diseases (ICD) codes in identifying opioid overdose (OOD) among patient data from emergency rooms, emergency medical services, inpatient, outpatient, administrative, medical claims, and mortality, and estimate the sensitivity and specificity of the algorithms in the absence of a perfect reference standard.
METHODS: We systematically reviewed studies published before December 8, 2023, and identified with Medline and Embase. Studies reporting sufficient details to recreate a 2 × 2 table comparing the ICD algorithms to a reference standard in diagnosing OOD-related events were included. We used Bayesian latent class models (BLCM) to estimate the posterior sensitivity and specificity distributions of five ICD-10 algorithms and of the imperfect coroner\'s report review (CRR) in detecting prescription opioid-related deaths (POD) using one included study.
RESULTS: Of a total of 1990 studies reviewed, three were included. The reported sensitivity estimates of ICD algorithms for OOD were low (range from 25.0% to 56.8%) for ICD-9 in diagnosing non-fatal OOD-related events and moderate (72% to 89%) for ICD-10 in diagnosing POD. The last included study used ICD-9 for non-fatal and fatal and ICD-10 for fatal OOD-related events and showed high sensitivity (i.e. above 97%). The specificity estimates of ICD algorithms were good to excellent in the three included studies. The misclassification-adjusted ICD-10 algorithm sensitivity estimates for POD from BLCM were consistently higher than reported sensitivity estimates that assumed CRR was perfect.
CONCLUSIONS: Evidence on the performance of ICD algorithms in detecting OOD events is scarce, and the absence of bias correction for imperfect tests leads to an underestimation of the sensitivity of ICD code estimates.
RéSUMé: OBJECTIFS: Cette étude avait pour objectifs de recenser les estimations de la validité des codes de Classification Internationale des Maladies (CIM) à diagnostiquer les cas de surdose aux opioïdes (SDO) chez des patients en utilisant les données de salles d’urgence, services médicaux d’urgence, hospitalisations, soins ambulatoires, services administratifs, demandes de remboursement de frais médicaux, ainsi que de mortalité, et d’estimer la sensibilité et la spécificité d’algorithmes utilisant la CIM en l’absence d’un test de référence parfait. MéTHODES: Nous avons examiné systématiquement les études publiées avant le 8 décembre 2023, et identifiées dans Medline et Embase. Les études rapportant suffisamment de détails permettant de recréer un tableau 2 × 2 comparant les algorithmes de la CIM à un test de référence pour le diagnostic d’événements liés aux SDO ont été incluses. Les données d’une étude éligible ont été utilisées pour estimer, avec des modèles Bayésiens de classes latentes (MBCL), les distributions a posteriori de la sensibilité et de la spécificité de cinq algorithmes de la CIM-10 et du test imparfait de révision du rapport du coroner (RRC) dans la détection des décès liés aux opioïdes de prescription (DOP). RéSULTATS: Trois parmi les 1 990 études examinées ont été retenues. Les estimations rapportées de la sensibilité des codes CIM étaient faibles (variant de 25,0 % à 56,8 %) pour CIM-9 dans le diagnostic des événements liés aux SDO non-fatales dans une étude, et modérées (72 % à 89 %) pour CIM-10 dans le diagnostic des DOP dans une autre étude. La dernière étude incluse combinait des codes CIM-9 pour les cas non-fatals et fatals et CIM-10 pour les cas fatals et démontrait des estimations de sensibilité élevées (c.à.d. supérieures à 97 %). Les estimations de la spécificité étaient bonnes à excellentes dans les trois études. Les estimations de la sensibilité des algorithmes de la CIM-10 corrigées pour les erreurs de classification pour les décès liés aux opioïdes, obtenues à partir de nos MBCL, étaient systématiquement plus élevées que celles rapportées et qui supposaient que RRC était un test parfait. CONCLUSION: Les évidences sur la performance des algorithmes de la CIM dans la détection des cas de SDO sont rares, et l’absence de correction de biais pour des tests diagnostiques imparfaits conduit à une sous-estimation de la sensibilité des codes de la CIM.

BACKGROUND: The assessment of deep venous thrombosis (DVT) is clinically difficult diagnosis. The \"gold standard test\" for DVT diagnosis is venography; however, various point-of-care ultrasound (POCUS) protocols have been suggested for DVT evaluation in the emergency department.
OBJECTIVE: This review evaluated the role of different POCUS protocols in diagnosing DVT in the emergency department.
METHODS: A systematic review and meta-analysis was conducted based of PRISMA guideline and registered on PROSEPRO (CRD42023398871). An electronic database search in Embase, PubMed, ScienceDirect, and Google scholar and a manual search were performed to identify eligible studies till February 2023. Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) was used to assess the risk of bias in included studies. Quantitative analysis was carried out using STATA 16 and Review Manager software (RevMan 5.4.1). Sensitivity, specificity of POCUS protocols for DVT diagnosis compared to reference standard test was calculated.
RESULTS: Heterogeneity was identified between 26 included studies for review. The pooled sensitivity, specificity, PPV, and NPV for the 2-point POCUS protocol were 92.32% (95% CI: 87.58-97.06), 96.86% (95% CI: 95.09-98.64), 88.41% (95% CI: 82.24-94.58) and 97.25% (95% CI: 95.51-98.99), respectively. Similarly, the pooled sensitivity, specificity, PPV, and NPV for 3-point POCUS were 89.15% (95% CI: 83.24-95.07), 92.71% (95% CI: 89.59-95.83), 81.27% (95% CI: 73.79-88.75), and 95.47% (95% CI: 92.93-98). The data pooled for complete compression ultrasound, and whole-leg duplex ultrasound also resulted in a sensitivity and specificity of 100% (95% CI: 98.21-100) and 97.05% (95% CI: 92.25-100), respectively. On the other hand, the time from triage to DVT diagnosis was significantly shorter for emergency physician-performed POCUS than diagnostic tests performed by radiologists.
CONCLUSIONS: The diagnostic performance of POCUS protocols performed by emergency physicians was excellent. Combined with the significant reduction in time to diagnosis. POCUS can be used as the first-line imaging tool for DVT diagnosis in the emergency department. We also recommended that attending emergency physicians with POCUS training are present during DVT diagnosis to improve diagnostic performance even though high diagnostic performance is observed even with the minimum training.

Gastrointestinal diseases are increasing in global prevalence. As a result, the contribution to both mortality and healthcare costs is increasing. While interventions utilizing scoping techniques or ultrasound are crucial to both the timely diagnosis and management of illness, a few limitations are associated with these techniques. Artificial intelligence, using computerized diagnoses, deep learning systems, or neural networks, is increasingly being employed in multiple aspects of medicine to improve the characteristics and outcomes of these tools. Therefore, this review aims to discuss applications of artificial intelligence in endoscopy, colonoscopy, and endoscopic ultrasound.

BACKGROUND: Reverse transcription polymerase chain reaction (RT-PCR) is the main technique used to identify COVID-19 from respiratory samples. It has been suggested in several articles that chest CTs could offer a possible alternate diagnostic tool for COVID-19; however, no professional medical body recommends using chest CTs as an early COVID-19 detection modality. This literature review examines the use of CT scans as a diagnostic tool for COVID-19.
METHODS: A comprehensive search of research works published in peer-reviewed journals was carried out utilizing precisely stated criteria. The search was limited to English-language publications, and studies of COVID-19-positive patients diagnosed using both chest CT scans and RT-PCR tests were sought. For this review, four databases were consulted: these were the Cochrane and ScienceDirect catalogs, and the CINAHL and Medline databases made available by EBSCOhost.
RESULTS: In total, 285 possibly pertinent studies were found during an initial search. After applying inclusion and exclusion criteria, six studies remained for analysis. According to the included studies, chest CT scans were shown to have a 44 to 98% sensitivity and 25 to 96% specificity in terms of COVID-19 diagnosis. However, methodological limitations were identified in all studies included in this review.
CONCLUSIONS: RT-PCR is still the suggested first-line diagnostic technique for COVID-19; while chest CT is adequate for use in symptomatic patients, it is not a sufficiently robust diagnostic tool for the primary screening of COVID-19.

The versatile basic structure of piperazine allows for the development and production of newer bioactive molecules that can be used to treat a wide range of diseases. Piperazine derivatives are unique and can easily be modified for the desired pharmacological activity. The two opposing nitrogen atoms in a six-membered piperazine ring offer a large polar surface area, relative structural rigidity, and more acceptors and donors of hydrogen bonds. These properties frequently result in greater water solubility, oral bioavailability, and ADME characteristics, as well as improved target affinity and specificity. Various synthetic protocols have been reported for piperazine and its derivatives. In this review, we focused on recently published synthetic protocols for the synthesis of the piperazine and its derivatives. The structure-activity relationship concerning different biological activities of various piperazine-containing drugs has also been highlighted to provide a good understanding to researchers for future research on piperazines.

Basophil activation test (BAT) or the mast cell activation test (MAT) are two in vitro tests that are currently being studied in food allergy as diagnostic tools as an alternative to oral food challenges (OFCs). We conducted a meta-analysis on BAT and MAT, assessing their specificity and sensitivity in diagnosing peanut allergy. Six databases were searched for studies on patients suspected of having peanut allergy. Studies using BAT or MAT to peanut extract and/or component as diagnostic tools with results given in percentage of CD63 activation were included in this meta-analysis. Study quality was evaluated with the QUADAS-2 tool. On the 11 studies identified, eight focused exclusively on children, while three included a mixed population of adults and children. Only one study provided data on MAT, precluding us from conducting a statistical analysis. The diagnostic accuracy of BAT was higher when stimulated with peanut extract rather than Ara h 2 with a pooled specificity of 96% (95% CI: 0.89-0.98) and sensitivity of 0.86 (95% CI: 0.74-0.93). The sensitivity and specificity of BATs in discriminating between allergic and sensitized patients were studied as well, with pooled analysis revealing a sensitivity of 0.86 (95% CI: 0.74; 0.93) and a specificity of 0.97 (95% CI: 0.94, 0.98). BATs, when stimulated with peanut extracts, exhibit a satisfactory sensitivity and specificity for the diagnosis of peanut allergy and can help to discriminate between allergic individuals and those only sensitized to peanuts. More investigations on the potential for MATs diagnostic methods are warranted.

BACKGROUND: Burkholderia pseudomallei, a Gram-negative pathogen, causes melioidosis. Although various clinical laboratory identification methods exist, culture-based techniques lack comprehensive evaluation. Thus, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of culture-based automation and non-automation methods.
METHODS: Data were collected via PubMed/MEDLINE, EMBASE, and Scopus using specific search strategies. Selected studies underwent bias assessment using QUADAS-2. Sensitivity and specificity were computed, generating pooled estimates. Heterogeneity was assessed using I2 statistics.
RESULTS: The review encompassed 20 studies with 2988 B. pseudomallei samples and 753 non-B. pseudomallei samples. Automation-based methods, particularly with updating databases, exhibited high pooled sensitivity (82.79%; 95% CI 64.44-95.85%) and specificity (99.94%; 95% CI 98.93-100.00%). Subgroup analysis highlighted superior sensitivity for updating-database automation (96.42%, 95% CI 90.01-99.87%) compared to non-updating (3.31%, 95% CI 0.00-10.28%), while specificity remained high at 99.94% (95% CI 98.93-100%). Non-automation methods displayed varying sensitivity and specificity. In-house latex agglutination demonstrated the highest sensitivity (100%; 95% CI 98.49-100%), followed by commercial latex agglutination (99.24%; 95% CI 96.64-100%). However, API 20E had the lowest sensitivity (19.42%; 95% CI 12.94-28.10%). Overall, non-automation tools showed sensitivity of 88.34% (95% CI 77.30-96.25%) and specificity of 90.76% (95% CI 78.45-98.57%).
CONCLUSIONS: The study underscores automation\'s crucial role in accurately identifying B. pseudomallei, supporting evidence-based melioidosis management decisions. Automation technologies, especially those with updating databases, provide reliable and efficient identification.

BACKGROUND: Clostridioides difficile infection (CDI) is a clinical and laboratory diagnosis. Populations at higher risk of developing disease require a high clinical index of suspicion for laboratory testing to avoid incorrect assumptions of colonization. Common risk factors include recent antibiotic use, elderly (>65 years old), and immunocompromised patients. C. difficile assays should be ordered in an algorithm approach to diagnose an infection rather than colonization. Screening tests are widely available in hospital systems, but novel molecular testing may aid in diagnosis in patients with inconclusive or discordant antigen and toxin test results.  Methods: Data was extracted from PubMed, Scopus, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) databases based on the keywords \"clostridioides difficile\", \"toxin assay\", and \"toxic megacolon\". The data extracted is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A total of 27 reports were included in this systematic review.
RESULTS: Testing patients with a significant gastrointestinal surgical history, hypogammaglobulinemia, inflammatory bowel disease, intensive care unit, and immunocompromised patients for CDI is highly recommended. Diarrhea in these subsets of patients requires correlation of clinical context and an understanding of assay results to avoid over- and under-treating.
CONCLUSIONS: CDI should be considered in all patients with traditional risk factors. Heightened clinical suspicion of CDI is required in patients with hypogammaglobulinemia, transplant recipients, patients with gastrointestinal surgical history, and inflammatory bowel disease. Testing should be limited to patients with clinical manifestations of CDI to ensure a high pretest probability for test interpretation. Healthcare workers should adhere to testing algorithms to optimize yield in the appropriate clinical context. Diagnostic assays should follow a sequential, stepwise approach to categorize the toxin expression status of the bacteria accurately.

UNASSIGNED: Pulmonary hypertension (PH) is a life-threatening disease, especially in paediatric population. Symptoms of paediatric PH are non-specific. Accurate detection of paediatric PH is helpful for early treatment and mortality reduction. Therefore, we assessed the overall performance of brain natriuretic peptide (BNP) and N-terminal brain natriuretic peptide (NT-proBNP) for diagnosing PH in paediatric population.
UNASSIGNED: PubMed, Web of Science, Cochrane Library and Embase databases were screened since their respective inceptions until August 2023. A bivariate random model and a hierarchical summary receiver operating characteristic model were used together to evaluate and summarize the overall performance of BNP and NT-proBNP for diagnosing paediatric PH.
UNASSIGNED: Eighteen studies using BNP/NT-proBNP were assessed, comprising 1127 samples. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and area under the curve (AUROC) of BNP/NT-proBNP were separately as 0.81, 0.87, 6.33, 0.21, 29.50 and 0.91, suggesting a good diagnostic performance of BNP/NT-proBNP for detecting PH in paediatric population. For BNP, the pooled sensitivity, specificity, PLR, NLR, DOR and AUROC were 0.83, 0.89, 7.76, 0.19, 40.90 and 0.93, indicating the diagnostic accuracy of BNP for paediatric PH patients was good. For NT-proBNP, the pooled sensitivity, specificity, PLR, NLR, DOR and AUROC were 0.81, 0.86, 5.59, 0.22, 24.96 and 0.90, showing that NT-proBNP could provide a good value for detecting paediatric PH.
UNASSIGNED: Both BNP and NT-proBNP are good markers for differentiating paediatric PH patients from non-PH individuals.
Accurate detection of paediatric PH is helpful for early treatment and mortality reduction. This study shows that both BNP and NT-proBNP are good markers for detecting paediatric PH. In clinical practice, we recommend that BNP and NT-proBNP are auxiliary biomarkers in diagnosing paediatric PH.