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PubMed2025

Personalizing CA125 Levels Using Tumor Marker Variants: A Case-Control Analysis of Diagnostic Performance for Pancreatic Cancer.

BACKGROUND: Cancer antigen 125 (CA125) is widely recognized as a useful biomarker for the surveillance of patients with ovarian and other cancers. Prior genome-wide association studies have identified variants that influence CA125 levels. We evaluated the utility of stratifying CA125 levels by such variants and evaluated diagnostic performance in control subjects and patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: We measured CA125 levels in 807 control subjects and 450 patients with PDAC and genotyped 10 variants involving four genes (GAL3ST2, MSLN, D2HGDH, and MUC16). We compared CA125 levels in controls by variant and generated variant-defined CA125 cutoffs and then classified cases and controls into functional groups based on their variant profile. We used this variant classification to evaluate the diagnostic performance of CA125 in patients with PDAC. RESULTS: Six variants associated with CA125 levels were used to group controls into one of four groups. Mean CA125 levels in the highest variant group were approximately fourfold higher than in the lowest group. African Americans were more likely to have a variant group associated with low CA125 levels. After setting diagnostic cutoffs by variant group, the diagnostic sensitivity of CA125 for PDAC was 20.2% at 98% specificity (areas under the ROC curve, 0.702), not significantly different from a uniform CA125 diagnostic cutoff (areas under the ROC curve, 0.700). CONCLUSIONS: Gene variants can be used to generate personalized CA125 reference ranges. This approach did not significantly improve CA125's diagnostic performance for pancreatic cancer, but it merits evaluation in other diagnostic settings, such as detecting ovarian cancer. IMPACT: Gene variants can be used to personalize CA125 levels.

Humans↗

PubMed2026

Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.

Rare diseases collectively affect 1 in 10 individuals, yet current genetic testing fails to identify a causal variant for most cases. At present, cytogenetic methods and/or sequencing approaches such as exome (ES) or short-read genome sequencing (srGS) represent the state-of-the-art for comprehensive clinical discovery of sequence and structural variants (SVs), including copy number variants, balanced SVs, complex SVs, and tandem repeats (TRs). Recently, long-read genome sequencing (lrGS), coupled with multiomics data, has presented great promise to resolve variation in genomic regions recalcitrant to characterization by srGS such as highly repetitive simple repeat sequences and segmental duplications. However, there are few guidelines to enable clinical interpretation of genetic variation in these highly repetitive genomic regions, and the enthusiasm of the field in adopting lrGS has made it difficult to assess the true added diagnostic yield of this technology due to widely variable and inconsistently applied analytic pipelines and variable degrees of pre-screening by ES or srGS. Here, we investigated the contribution of SVs to rare diseases using srGS as a front-line strategy when paired with highly sensitive SV discovery and evaluate the added diagnostic yield of incorporating lrGS for a subset of cases. Our srGS analysis encompassed 1,462 families (3,450 individuals) recruited through the Broad Institute Center for Mendelian Genetics and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) programs. Diagnostic SVs were identified in 5.4% of cases (79/1,462), of which 80% were uniquely detectable by srGS compared to standard cytogenetic techniques. For 96 families (including 10 families with a heterozygous variant observed in a known recessive gene of clinical relevance), we performed lrGS with methylation profiling, as well as long-read transcriptomic analyses in a subset of 20 trios. Analyses with lrGS yielded over 25,000 SVs per genome, 63% of which were not captured by srGS, along with an additional ~200 rare SNV/indels per genome not previously captured and 12 differentially methylated regions per genome. Among these, we identified only one diagnostic variant not interpreted by srGS, an apparently mosaic de novo SNV in CASK that was absent in the srGS callset due to allelic imbalance. No new diagnoses were supported by long-read transcriptomics or episignatures. In this well characterized rare disease cohort, the added diagnostic yield was thus 1.04% (1/96 families). Following a systematic literature review of prior lrGS studies, we find that most reported diagnoses were detectable by srGS and that our added diagnostic yield is consistent with those prior studies. These studies emphasize the significant impact of comprehensive SV discovery in rare disease cases and further demonstrate the power for increased discovery of novel genomic variation and episignatures from lrGS. Nonetheless, they also serve to temper expectations of dramatic diagnostic advances in rare disease patients until there is more extensive annotation of the functional and clinical impact of all coding and noncoding variation uniquely accessible to lrGS with extensive reference databases spanning highly repetitive genomic sequencing that could be enabled by this transformative technology.

Journal Article↗

PubMed1975

Diagnostic value of routine liver tests.

In 131 patients on a medical service and 97 patients on a surgical service, in whom a diagnosis of hepatobiliary disease was verified in the hospital, the diagnostic value of routine liver tests performed soon after admission was evaluated by stepwise discriminant analysis. By measurements of alanine aminotransferase, alkaline phosphatases, gamma globulin, prothrombin time, bilirubin, and albumin, half of the medical patients were correctly classified into one of seven diagnostic categories. Aminotransferase contributed most to the classification, being twice as effective as random allocation. Decreasing the number of diagnostic categories to three (hepatitis, fatty liver, and chronic liver disease) increased the frequency of correct allocation to 80%. The allocation of all the patients to seven medical and four surgical diagnostic categories by means of four tests (aminotransferase, alkaline phosphatases, prothrombin time, and bilirubin) was significantly improved by each step with a misclassification rate of 55% when all tests were used. A reduction of the diagnostic groups to five (hepatitis, fatty liver, chronic liver disease, duct obstruction and tumor) increased the frequency of correct allocation to 63%. The analysis demonstrates the limited diagnostic effectiveness of routine liver tests when used alone. The absolute discrimination values depend on the a priori frequencies of the diagnostic groups investigated, and therefore may vary from time to time and from place to place.

Alanine Transaminase↗

PubMed2025

Bacteriophages as a modern diagnostic tool: innovations, applications and challenges.

Bacteriophages, viruses that specifically infect bacteria, have emerged as a valuable tool in diagnostics due to their unique specificity and adaptability. This review explores the diverse applications of bacteriophages in diagnostic methods, from traditional phage typing to advanced molecular techniques such as phage display and PCR-based diagnostics. It highlights their use in identifying bacterial strains, monitoring fermentation processes, and diagnosing critical conditions like tuberculosis, MRSA infections, and cancer. Innovations such as phage-based biosensors and reporter phages enhance the speed and precision of diagnostics, offering significant advantages over traditional methods. Challenges, including bacterial resistance and immune responses to phages, are also discussed alongside strategies for mitigation, such as phage cocktails and engineering. Integrating phage technology with modern bioscience holds promise for addressing antibiotic resistance and revolutionizing clinical and industrial diagnostics. This comprehensive analysis underscores the potential of bacteriophages to transform the diagnostic landscape while identifying areas requiring further research and development.

Bacteriophages↗

PubMed2023

Phenotypic presentation of Mendelian disease across the diagnostic trajectory in electronic health records.

PURPOSE: To investigate the phenotypic presentation of Mendelian disease across the diagnostic trajectory in the electronic health record (EHR). METHODS: We applied a conceptual model to delineate the diagnostic trajectory of Mendelian disease to the EHRs of patients affected by 1 of 9 Mendelian diseases. We assessed data availability and phenotype ascertainment across the diagnostic trajectory using phenotype risk scores and validated our findings via chart review of patients with hereditary connective tissue disorders. RESULTS: We identified 896 individuals with genetically confirmed diagnoses, 216 (24%) of whom had fully ascertained diagnostic trajectories. Phenotype risk scores increased following clinical suspicion and diagnosis (P < 1 × 10-4, Wilcoxon rank sum test). We found that of all International Classification of Disease-based phenotypes in the EHR, 66% were recorded after clinical suspicion, and manual chart review yielded consistent results. CONCLUSION: Using a novel conceptual model to study the diagnostic trajectory of genetic disease in the EHR, we demonstrated that phenotype ascertainment is, in large part, driven by the clinical examinations and studies prompted by clinical suspicion of a genetic disease, a process we term diagnostic convergence. Algorithms designed to detect undiagnosed genetic disease should consider censoring EHR data at the first date of clinical suspicion to avoid data leakage.

Humans↗

PubMed2024

Diagnostic delay in monogenic disease: A scoping review.

PURPOSE: Diagnostic delay in monogenic disease is reportedly common. We conducted a scoping review investigating variability in study design, results, and conclusions. METHODS: We searched the academic literature on January 17, 2023, for original peer reviewed journals and conference articles that quantified diagnostic delay in monogenic disease. We abstracted the reported diagnostic delay, relevant study design features, and definitions. RESULTS: Our search identified 259 articles quantifying diagnostic delay in 111 distinct monogenetic diseases. Median reported diagnostic delay for all studies collectively in monogenetic diseases was 5.0 years (IQR 2-10). There was major variation in the reported delay within individual monogenetic diseases. Shorter delay was associated with disorders of childhood metabolism, immunity, and development. The majority (67.6%) of articles that studied delay reported an improvement with calendar time. Study design and definitions of delay were highly heterogenous. Three gaps were identified: (1) no studies were conducted in the least developed countries, (2) delay has not been studied for the majority of known, or (3) most prevalent genetic diseases. CONCLUSION: Heterogenous study design and definitions of diagnostic delay inhibit comparison across studies. Future efforts should focus on standardizing delay measurements, while expanding the research to low-income countries.

Humans↗

PubMed2026

Vitamin B12 Deficiency in Sickle Cell Disease: Method-Driven Estimates and Systematic Diagnostic Misclassification.

OBJECTIVES: To determine whether the reported 0%-70% prevalence of vitamin B12 deficiency in sickle cell disease (SCD) reflects true population variation or diagnostic misclassification. METHODS: We conducted a PRISMA 2020-compliant systematic review of observational studies (January 1, 2000-May 13, 2026; PROSPERO CRD420251087800) assessing B12 status in SCD. PubMed, AJOL, and Google Scholar were searched with citation tracking and dual screening. Diagnostic validity was assessed across biomarker strategy, analytical platform, thresholds, and confounder control using a proposed context-integrated framework to classify methodological robustness and discordance. RESULTS: Fourteen studies were included (57% high-income; 43% LMIC). The evidence base was dominated by limited diagnostic approaches: 71% used immunoassays, over one-third relied on circulating B12 alone, and functional biomarkers were inconsistently applied without systematic confounder adjustment. Prevalence estimates were strongly influenced by diagnostic methods rather than underlying population biology, ranging from 0% to 70% in single-marker studies (mostly 0%-7.1%, with outliers ~50%-70%) and 6.9%-53% in multi-marker studies. Discordance was substantial and greater in LMIC settings than HIC. CONCLUSION: Current diagnostic approaches in SCD appear method-dependent, generating heterogeneous prevalence estimates with uncertain clinical validity. These findings challenge existing estimates and have implications for clinical practice, research design, and diagnostic equity. TRIAL REGISTRATION: ClinicalTrials.gov identifier: CRD420251087800.

Humans↗

PubMed2026

Respiratory-onset peripartum cardiomyopathy: a systematic review of diagnostic pitfalls and clinical outcomes.

INTRODUCTION: Peripartum cardiomyopathy (PPCM) may initially present with prominent respiratory symptoms that resemble primary pulmonary disease, particularly in late pregnancy and the early postpartum period. In clinical practice, this presentation often triggers alternative diagnostic pathways, introducing delay at a time when rapid cardiac assessment is critical. Although respiratory-dominant presentations are repeatedly described across case-based and observational reports, they have not been systematically examined as a distinct diagnostic pathway within the PPCM literature. CONTENT: This PRISMA-guided systematic review synthesized evidence relating to respiratory-onset presentations of PPCM. Major databases and registers were searched comprehensively. Following screening of 589 records and full-text assessment of 145 reports, 49 studies met inclusion criteria. Twenty studies were qualitatively prioritized for narrative synthesis using ROBIS-informed methodological appraisal. Evidence was examined across diagnostic misclassification patterns, cardiopulmonary mechanisms, differential diagnoses, investigative strategies, and acute and longitudinal management considerations. SUMMARY: Respiratory-led presentations were commonly misattributed to asthma, pneumonia, pulmonary embolism, or perioperative causes, with diagnostic delay frequently reported. Across heterogeneous study designs, cardiogenic pulmonary edema with left-ventricular systolic dysfunction emerged as a recurring unifying mechanism. Early use of echocardiography, natriuretic peptides, and targeted imaging consistently aided differentiation from primary respiratory pathology. Severe clinical deterioration was often described in the context of delayed recognition. OUTLOOK: Respiratory-onset PPCM represents a high-risk diagnostic pathway rather than a discrete disease entity. Prospective registries, standardized diagnostic algorithms, and closer integration of obstetric and cardiopulmonary care are needed to refine early recognition and improve maternal outcomes.

Humans↗

PubMed2026

A narrative systematic review of definitions and diagnostic criteria for disordered eating and eating disorders in type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes and disordered eating (T1DE) affects 8-37.1% of adults and is associated with high rates of morbidity and mortality. The absence of a standardised case definition of T1DE and its severity hinders effective screening, diagnosis and treatment. This systematic review aimed to (1) synthesise existing case definitions and diagnostic criteria for T1DE in adults and (2) identify key characteristics to inform consensus for future diagnostic criteria. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies involved adults (≥18 years) with type 1 diabetes assessing disordered eating; paediatric studies, mixed samples without disaggregated data, non-empirical designs and non-English publications were excluded. PubMed, MEDLINE, EMBASE, CINAHL and PsycINFO were searched up to November 2025 for peer-reviewed studies involving adults with T1DE. Qualitative and quantitative data on definitions, diagnostic criteria and assessment tools were extracted. Study quality was appraised using a modified Graphical Appraisal Tool for Epidemiological studies (GATE) checklist. Due to heterogeneity of data, a narrative synthesis of findings was performed to describe current definitions of T1DE. RESULTS: Sixty-one studies met the inclusion criteria, with a pooled sample of 111,208 participants (76% women) from over 22 countries. T1DE was defined using a heterogeneous array of terms, diagnostic frameworks and assessment tools (29 distinct methods). The Diabetes Eating Problem Survey-Revised (DEPS-R) was the most used questionnaire, but many studies relied on criteria adapted from general eating disorder classifications or generic questionnaires. Approximately three-quarters of the studies assessed insulin omission behaviours, but the operationalisation of the cognitions for insulin omission varied widely. Beyond physiological markers such as HbA1c and BMI, studies explored various diabetes-related and psychological constructs, although often considering diabetes and disordered eating separately rather than as an integrated condition. CONCLUSIONS/INTERPRETATION: This systematic review highlights the lack of a unified, evidence-based definition of T1DE, resulting in inconsistent screening, diagnostic and reporting practices. Establishing clear, consistent, evidence-based diagnostic criteria and screening questionnaires for T1DE is critical to improving early detection and developing targeted interventions. These findings provide a foundation for refining T1DE definitions as a stepping stone to an international consensus definition. STUDY REGISTRATION: PROSPERO registration no. CRD420250223622 FUNDING: King's College London and King's College Hospital through the KMRT KCH Joint Research Committee studentship. This work was also conducted as part of the National Institute for Health Research (NIHR; CS-2017-17-023)-funded STEADY project (Safe management of people with Type 1 diabetes and EAting Disorders studY). NZ's salary was part-funded by the NIHR via the NIHR Clinician Scientist award to MS; JT and KI are part-funded by the NIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. MS was funded through her NIHR Clinician Scientist Fellowship (CS-2017-17-023).

Humans↗

PubMed2026

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans↗

PubMed2025

Diagnostic and phylogenetic perspectives of the 2023 Murray Valley encephalitis virus outbreak in Australia: an observational study.

BACKGROUND: An outbreak of Murray Valley encephalitis virus (MVEV), the largest since 1974, was observed in Australia between Jan 1 and July 31, 2023. This study aims to characterise the utility of diagnostic platforms, testing algorithms, and genomic characteristics of MVEV to facilitate a comprehensive framework for MVEV testing and surveillance in the outbreak setting. METHODS: In this observational study, we assessed flavivirus diagnostics for all patients with suspected Murray Valley encephalitis in Australia from Jan 1 to July 31, 2023. We included all patients with confirmed Murray Valley encephalitis, probable Murray Valley encephalitis, or acute unspecified flavivirus infection using the Communicable Diseases Network Australia case definition. Cases were excluded if an alternative diagnosis was identified. We collected blood, serum, cerebrospinal fluid, brain tissue, urine, or a combination of these samples, as appropriate and at the discretion of the treating clinician. We conducted multimodal diagnostic testing, which included flavivirus-specific serological and nucleic acid amplification testing. Metagenomic next-generation sequencing, including next-generation deep sequencing, target-enrichment, and targeted amplification, was conducted on human and representative mosquito-derived samples obtained from established mosquito population surveillance programmes for phylogenetic analysis. FINDINGS: 27 patients with encephalitis were assessed for MVEV between Jan 1, 2023, and July 31, 2023, 23 (85%) of whom fulfilled national case definitions for confirmed Murray Valley encephalitis. Patient ages ranged from 6 weeks to 83 years (median 62·0 years [IQR 31·0-67·5]) and patients were mostly male (21 [78%] male patients and six [22%] female patients). Incidence varied widely by geographical region and was highest in the Northern Territory (32·0 per 1 000 000 population). Diagnostic specimen collection generally occurred promptly (median 6·0 days [IQR 4·0-14·5] from symptom onset to diagnostic specimen collection). In seven patients, case assignation relied on convalescent serum samples to assess for seroconversion or an appropriate rise in antibody titre (to four times the initial value or greater), or both. MVEV-specific IgM was detectable in serum samples of 17 (81%) of 21 patients tested by day 7 and MVEV IgG or total antibody (TAb) were detected in 18 (100%) of 18 patients tested by day 30. MVEV-specific IgM (or TAb) and MVEV RNA were detected in cerebrospinal fluid collected within 14 days of symptom onset in nine (39%) of 23 patients and seven (28%) of 25 patients, respectively. Phylogenetic analysis revealed two circulating MVEV genotypes, G1A and G2, in mosquitoes and humans in 2023. In southeast Australia, only G1A was detected and probably introduced from enzootic foci in northern Australia. INTERPRETATION: This study provides a comprehensive overview of the diagnostic workflows and phylogenetic evaluations used during the 2023 MVEV outbreak in Australia, emphasising the importance of a multimodal approach for accurate and timely confirmation of flavivirus infection. Further One Health surveillance for MVEV and other zoonotic flaviviruses is key, given potential expanded ecological niches in the context of episodic climatic events. FUNDING: None.

Humans↗

PubMed1976

[Liver metastases: diagnostic value of blood tests, scintiscanning, and laparoscopy (author's transl)].

In 90 patients with known extra-hepatic malignancy the liver was examined for metastases. The diagnostic value of clinical information, blood examinations, 99mTc scintiscan, and laparoscopy for the diagnosis of the liver metastases was evaluated. Clinical data (age, sex, time since onset of symptoms and localisation of primary tumor) are of no diagnostic value. The most reliable blood tests are alkaline phosphatase (AP) and GOT. The probability of liver metastastases rises with increasingly abnormal values of AP and GOT. However, the probability is not much greater in cases with highly abnormal values than in cases with only moderate elevation of AP and GOT. Diagnostic accuracy of AP is optimal by using a cutoff point of 76 U/l (sensitivity 79%, specificity 64%). Bilirubin, prothrombin time, haemoglobin and blood sedimentation rate are of very little value. Combinations of AP with these blood tests does not improve diagnostic accuracy. Therefore, it is not useful to determine more blood tests than AP alone. Informed reading of liver scans has a specificity of 75% and a sensitivity of 91%. Blind reading of scans has a sensitivity of 94% and a specificity of 95%. This diagnostic accuracy cannot be improved by additional blood tests. Laparscopy has a sensitivity of 85% and a specificity of 95%. Scanning and laparoscopy are complementary methods. When optimal diagnostic accuracy is required both methods should be used.

Adult↗

PubMed2025

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University Münster.

Journal Article↗

PubMed2026

MIC-based tuberculosis drug susceptibility testing using Sensititre MYCOTB: a diagnostic accuracy meta-analysis.

Accurate drug susceptibility testing (DST) is crucial for designing effective regimens for multidrug-resistant (MDR) and pre-extensively drug-resistant tuberculosis (pre-XDR TB). Sensititre MYCOTB enables simultaneous determination of minimum inhibitory concentrations (MICs) for multiple drugs, but its diagnostic performance varies across studies. This meta-analysis evaluated the diagnostic performance of Sensititre MYCOTB for key MDR and pre-XDR TB drugs. The protocol was registered in PROSPERO (CRD420251230599). PubMed, Cochrane, Google Scholar, Scopus, ONOS, Web of Science, ScienceDirect, and registries were systematically searched for studies published between 2010 and 2025. Studies comparing the Sensititre MYCOTB with reference DST for Mycobacterium tuberculosis complex (MTBC) were included. Bias assessment and pooled diagnostic accuracy estimates were generated. Fourteen studies, including 1,728 isolates, were analyzed. Rifampicin and isoniazid demonstrated high sensitivity (0.976 [95% CI: 0.94-0.99] and 0.977 [95% CI: 0.95-0.99]) and specificity (0.958 [95% CI: 0.84-0.98] and 0.957 [95% CI: 0.83-0.99], respectively) with low heterogeneity. Amikacin, kanamycin, and ofloxacin demonstrate good diagnostic accuracy, with high specificity (>0.98 [95% CI]). Moderate diagnostic accuracy was observed for ethambutol, streptomycin, ethionamide, and rifabutin. Cycloserine, moxifloxacin, and para-aminosalicylic acid showed inconsistent performance despite excellent specificity (>0.97 [95% CI]). Sensitivity analysis partially improved pooled sensitivity for moxifloxacin 0.801 (95% CI: 0.585-0.924) and para-aminosalicylic acid 0.76 (95% CI: 0.518-0.894), whereas cycloserine remained at 0.436 (95% CI: 0.190-0.725), although heterogeneity persisted. Sensititre MYCOTB DST demonstrates high diagnostic accuracy for MDR-TB and pre-XDR-TB drugs, while caution is required with cycloserine, moxifloxacin, and para-aminosalicylic acid. These findings support the integration of MIC-based testing into clinical decision-making.

Microbial Sensitivity Tests↗

PubMed2025

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

Journal Article↗

PubMed1977

Barium enema as a diagnostic aid in children with abdominal pain.

Diagnostic barium enema is not a substitution for well executed physical examination, and its use should be reserved only for obscure situations. An abnormal roentgenogram provides valuable information, since the fear of missing acute appendicitis in these children is minimized. When normal, this diagnostic test may bring to early operation those with minimal symptoms or unusual presentations, thus avoiding the possibility of prolonged observation and perforation. In children with known associated severe medical maladies, diagnostic barium enema can serve to reaffirm the diagnosis prior to the hazardous operative intervention. It may also eliminate the need for operation in those conditions which mimic acute appendicitis. The use of diagnostic barium enema in the past three and a half years significantly improved our diagnostic capabilities in children with abdominal pain. There was a corresponding reduction in the number of normal appendixes removed. The efficancy and, above all, the safety of this procedure make it a valuable diagnostic aid in the care of children.

Abdomen↗

PubMed2026

Artificial intelligence in molecular diagnostics for pandemic preparedness.

INTRODUCTION: Molecular diagnostics focusing on the detection and analysis of nucleic acids are indispensable tools for early pathogen identification, transmission monitoring, and genomic surveillance during pandemics. Recent technological advances have broadened the diagnostic landscape, incorporating PCR-based methods, isothermal amplification, high-CRISPR-based amplification detection, and sequencing. Despite their diagnostic potential, widespread implementation remains limited by high validation costs, time and logistical constraints, the need for specialized professional knowledge, and a lack of adaptability in resource-limited settings. Artificial intelligence (AI) is increasingly recognized as a promising but challenging approach, offering tools that streamline assay development, automate data interpretation, and optimize real-time diagnostic performance. AREAS COVERED: This review introduces recently published AI tools with potential to enhance the in-silico design validation process of oligonucleotides for molecular assays. These cover tools for initial assay design and optimization to validation and continuous assay updates. The limitations, including concerns regarding data accuracy, the lack of transparency in data processing ('black box' models), and unresolved licensing and regulatory issues, are highlighted for each tool and as expert opinion. EXPERT OPINION: Collectively, these challenges currently confine most AI-based approaches to research settings and prevent their routine implementation in clinical molecular diagnostics. Their widespread adoption depends on addressing remaining technical, regulatory, and practical challenges.

Humans↗

PubMed2025

Targeted next-generation sequencing for drug-resistant tuberculosis diagnosis: implementation considerations for bacterial load, regimen selection and diagnostic algorithm placement.

INTRODUCTION: Early and accurate diagnosis of drug-resistant tuberculosis (DR-TB) is essential for improving treatment outcomes. Phenotypic drug susceptibility testing (pDST) is comprehensive but slow, while rapid molecular assays provide resistance information for a limited number of drugs. Targeted next-generation sequencing (tNGS) offers the potential for broad and rapid resistance detection, but its integration into diagnostic algorithms has been hindered by uncertainty about its placement within existing workflows. METHODS: This study evaluated the extent to which two tNGS solutions-Deeplex Myc-TB (GenoScreen) and TB Drug Resistance Test (Oxford Nanopore Technologies, ONT)-provided interpretable drug resistance results that could inform regimen design, in comparison to other WHO-recommended molecular assays and pDST. Data were collected from three high-burden DR-TB settings under the Seq&Treat study. Sequencing success rates and drug resistance detection were analysed based on: (1) the initial Xpert MTB/RIF result (very low, low, medium, high), (2) resistance results for drugs in WHO-recommended regimens and (3) performance relative to other WHO-endorsed assays. The potential impact of different algorithms on the estimates was also considered. Key factors influencing successful tNGS adoption within diagnostic pathways were identified, leveraging insights from the Seq&Treat diagnostic accuracy study. RESULTS: Sequencing success rates were 88.5% (GenoScreen) and 93.1% (ONT) across 763 samples. While tNGS provided complete resistance data for 73%-86% of drugs in recommended regimens, pDST achieved 92%-93%. Both tNGS solutions matched or exceeded the sensitivity of WHO-recommended molecular assays. CONCLUSIONS: This study highlights the critical role of tNGS as a centralised tool for comprehensive drug resistance testing to inform DR-TB treatment decisions following initial screening assays. By complementing existing molecular tests with tNGS, diagnostic workflows can be optimised to ensure timely and comprehensive resistance detection. These findings support policy updates to integrate tNGS into global TB diagnostic algorithms. TRIAL REGISTRATION NUMBER: NCT04239326.

Humans↗