Sickle cell diseases (SCD) are the most common genetic disorders with significant morbidity and mortality worldwide, including in India. The high prevalence of this disorder in many geographical regions calls for the use of a point-of-care rapid diagnostic test (RDT) for early screening and management of the diagnosed cases to reduce the allied clinical severity. In view of this, the present study was undertaken for the validation of a point-of-care RDT kit (SICKLECHECKTM) for the screening of SCD. This validation and diagnostic accuracy study was conducted among the cases advised for screening of SCD. For validation, all the recruited cases were investigated for both the SICKLECHECKTM RDT kit and HPLC (Variant-II) considering HPLC as a gold standard. A total of 400 cases were screened for both tests. For the presence and absence of sickle cell hemoglobin in the samples, SICKLECHECKTM RDT kit results showed a sensitivity and specificity of 99.39% and 98.73% respectively with references to HPLC findings. For the detection of the \'AS\' pattern, the SICKLECHECKTM RDT kit has shown a sensitivity and specificity of 99.07% and 98.81% respectively. For the detection of the \'SS\' pattern, the SICKLECHECKTM RDT kit has shown a sensitivity and specificity of 97.92% and 100.0% respectively. Cases with β thalassemia trait, hemoglobin E trait, hemoglobin Lepore trait and trait for hereditary-persistence-of-fetal-hemoglobin (high HbF %) diagnosed in HPLC were resulted with \'AA\' pattern in SICKLECHECKTM RDT kit. The high sensitivity and specificity of the SICKLECHECKTM RDT kit insist on its use as a point-of-care screening tool for SCD especially where there is a lack of laboratory facilities as well as in hospital-based set-up requiring immediate diagnosis and management of SCD. However, for further confirmation, the samples should be analyzed with other gold standard techniques like HPLC.

OBJECTIVE: The purpose of this study was to define the utility of CT scans for detecting articular extension in tibial shaft fractures and determine whether radiographic parameters can predict the presence of operative distal tibial articular fractures (DTAFs).
METHODS:
METHODS: Retrospective cohort study.
METHODS: Single level I trauma center.
UNASSIGNED: Patients age 18 years and older who were treated operatively for tibial shaft fractures occurring at or below the tibial isthmus were included. Patients were excluded for extension of the main tibial shaft fracture into the tibial plafond (AO/OTA 43 B/C), ballistic injuries, and absence of a preoperative CT scan.
UNASSIGNED: The primary outcome was CT utility, defined as the presence of a DTAF or DTAF displacement on CT that was not recognized on plain radiographs on secondary analysis at the time of the study by a senior-level resident. Secondary outcome was the association between radiographic parameters and operative DTAFs. Variables with P ≤ 0.2 on univariate testing were included in a multiple binary logistic regression model to determine independent predictors of operative DTAFs.
RESULTS: One hundred forty-four patients were included, with a mean age of 52 years. Seventy-six patients (53%) were men. CT utility was 41% for the identification of unrecognized DTAFs. CT utility was 79% for isolated pDTAF, 57% for medial DTAF, 83% for isolated anterolateral DTAF, and 100% for multiple DTAFs. Operative DTAFs were independently associated with spiral tibial shaft fracture type (P < 0.001) and low fibular fracture (P = 0.04). In patients who had both spiral tibial shaft fracture type and low fibula fracture, the rate of operative DTAF was 46% (22/48).
CONCLUSIONS: CT scans identified DTAFs that were unrecognized on plain radiographs in 41% of cases. CT scans were most useful in identifying nonposterior DTAFs. CT scans may be considered for all distal third tibial fractures, but especially those with spiral tibial shaft patterns and low fibular fractures, to avoid missing operative articular injury.
METHODS: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Brucellosis represents a major public health concern worldwide. Human transmission is mainly due to the consumption of unpasteurized milk and dairy products of infected animals. The gold standard for the diagnosis of Brucella spp in ruminants is the bacterial isolation, but it is time-consuming. Polymerase Chain Reaction (PCR) is a quicker and more sensitive technique than bacterial culture. Droplet digital PCR (ddPCR) is a novel molecular assay showing high sensitivity in samples with low amount of DNA and lower susceptibility to amplification inhibitors. Present study aimed to develop a ddPCR protocol for the detection of Brucella abortus in buffalo tissue samples. The protocol was validated using proficiency test samples for Brucella spp by real time qPCR. Furthermore, 599 tissue samples were examined. Among reference materials, qPCR and ddPCR demonstrated same performance and were able to detect up to 225 CFU/mL. Among field samples, ddPCR showed higher sensitivity (100%), specificity and accuracy of 93.4% and 94.15%, respectively. ddPCR could be considered a promising technique to detect B. abortus in veterinary specimens, frequently characterized by low amount of bacteria, high diversity in matrices and species and poor storage conditions.

BACKGROUND: Valid and reliable instruments for measuring emotional development are critical for a proper diagnostic assignment in individuals with intellectual disabilities. This exploratory study examined the psychometric properties of the items on the Scale of Emotional Development-Short (SED-S).
METHODS: The sample included 612 adults with intellectual disabilities (Mage = 37.35, SDage = 13.27; 59.8% males). Item validity analysis comprising sensitivity and specificity rates and discriminatory power were determined.
RESULTS: The relative mean frequency of \'yes\' answers to all 200 items was 29.5%. The mean sensitivity rate was 67.5% and the mean specificity rate was 79.3%. Most items (85.0%) showed good discriminatory power with the adjacent stage(s), especially between SED-1, SED-2, SED-3 and SED-4. Particularly in SED-4 some items showed weaknesses in the differentiation between these stages.
CONCLUSIONS: This study adds to previous validation studies by showing that most SED-S items have psychometrically sound properties.

Yersinia enterocolitica (Ye) is a foodborne pathogen isolated from humans, food, animals, and the environment. Yersiniosis is the third most frequently reported foodborne zoonosis in the European Union. Ye species are divided into six biotypes 1A, 1B, 2, 3, 4, and 5, based on biochemical reactions and about 70 serotypes. Biotype 1A is non-pathogenic, 1B is highly pathogenic, and biotypes 2-5 have moderate or low pathogenicity. The reference analysis method for detecting pathogenic Ye species underestimates the presence of the pathogen due to similarities between Yersinia enterocolitica-like species and other Yersiniaceae and/or Enterobacteriaceae, low concentrations of distribution pathogenic strains and the heterogeneity of Yersinia enterocolitica species. In this study, the real-time PCR method ISO/TS 18867 to identify pathogenic biovars of Ye in bivalve molluscs was validated. The sensitivity, specificity and accuracy of the molecular method were evaluated using molluscs experimentally contaminated. The results fully agree with those obtained with the ISO 10273 method. Finally, we evaluated the presence of Ye in seventy commercial samples of bivalve molluscs collected in the Gulf of Naples using ISO/TS 18867. Only one sample tested resulted positive for the ail gene, which is considered the target gene for detection of pathogenic Ye according to ISO/TS 18867. Additionally, the presence of the ystB gene, used as target for Ye biotype 1A, was assessed in all samples using a real-time PCR SYBR Green platform. The results showed amplification ystB gene aim two samples.

OBJECTIVE: To assess the merit of clinical assessment tools in a neurocognitive screening following out-of-hospital cardiac arrest (OHCA).
METHODS: The neurocognitive screening that was evaluated included the performance-based Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT), the patient-reported Two Simple Questions (TSQ) and the observer-reported Informant Questionnaire on Cognitive Decline in the Elderly-Cardiac Arrest (IQCODE-CA). These instruments were administered at 6-months in the Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial. We used a comprehensive neuropsychological test battery from a TTM2 trial sub-study as a gold standard to evaluate the sensitivity and specificity of the neurocognitive screening.
RESULTS: In our cohort of 108 OHCA survivors (median age = 62, 88% male), the most favourable cut-off scores were: MoCA <26; SDMT z ≤-1; IQCODE-CA ≥3.04. The MoCA (sensitivity 0.64, specificity 0.85) and SDMT (sensitivity 0.59, specificity 0.83) had a higher classification accuracy than the TSQ (sensitivity 0.28, specificity 0.74) and IQCODE-CA (sensitivity 0.42, specificity 0.60). When using the cut-points for MoCA or SDMT in combination to identify neurocognitive impairment, sensitivity improved (0.74, specificity 0.81), area under the curve = 0.77, 95% CI [0.69, 0.85]. The most common unidentified impairments were within the episodic memory and executive functions domains, with fewer false negative cases on the MoCA or SDMT combined.
CONCLUSIONS: The MoCA and SDMT have acceptable diagnostic accuracy for screening for neurocognitive impairment in an OHCA population, and when used in combination the sensitivity improves. Patient and observer-reports correspond poorly with neurocognitive performance.
RESULTS: gov Identifier: NCT03543371.

BACKGROUND:  The early diagnosis of Alzheimer\'s disease (AD) and mild cognitive impairment (MCI) remains a significant challenge in neurology, with conventional methods often limited by subjectivity and variability in interpretation. Integrating deep learning with artificial intelligence (AI) in magnetic resonance imaging (MRI) analysis emerges as a transformative approach, offering the potential for unbiased, highly accurate diagnostic insights.
OBJECTIVE:  A meta-analysis was designed to analyze the diagnostic accuracy of deep learning of MRI images on AD and MCI models.
METHODS:  A meta-analysis was performed across PubMed, Embase, and Cochrane library databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, focusing on the diagnostic accuracy of deep learning. Subsequently, methodological quality was assessed using the QUADAS-2 checklist. Diagnostic measures, including sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristic curve (AUROC) were analyzed, alongside subgroup analyses for T1-weighted and non-T1-weighted MRI.
RESULTS:  A total of 18 eligible studies were identified. The Spearman correlation coefficient was -0.6506. Meta-analysis showed that the combined sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.84, 0.86, 6.0, 0.19, and 32, respectively. The AUROC was 0.92. The quiescent point of hierarchical summary of receiver operating characteristic (HSROC) was 3.463. Notably, the images of 12 studies were acquired by T1-weighted MRI alone, and those of the other 6 were gathered by non-T1-weighted MRI alone.
CONCLUSIONS:  Overall, deep learning of MRI for the diagnosis of AD and MCI showed good sensitivity and specificity and contributed to improving diagnostic accuracy.
BACKGROUND:  O diagnóstico precoce da doença de Alzheimer (DA) e do comprometimento cognitivo leve (CCL) continua sendo um desafio significativo na neurologia, com métodos convencionais frequentemente limitados pela subjetividade e variabilidade na interpretação. A integração da aprendizagem profunda com a inteligência artificial (IA) na análise de imagens de ressonância magnética surge como uma abordagem transformadora, oferecendo o potencial para insights diagnósticos imparciais e altamente precisos.
OBJECTIVE:  Uma metanálise foi projetada para analisar a precisão diagnóstica do aprendizado profundo de imagens de ressonância magnética em modelos de DA e CCL. MéTODOS:  Uma metanálise foi realizada nos bancos de dados das bibliotecas PubMed, Embase e Cochrane seguindo as diretrizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), com foco na precisão diagnóstica do aprendizado profundo. Posteriormente, a qualidade metodológica foi avaliada por meio do checklist QUADAS-2. Medidas diagnósticas, incluindo sensibilidade, especificidade, razões de verossimilhança, razão de chances diagnósticas e área sob a curva característica de operação do receptor (area under the receiver operating characteristic curve [AUROC]) foram analisadas, juntamente com análises de subgrupo para ressonância magnética ponderada em T1 e não ponderada em T1.
RESULTS: Um total de 18 estudos elegíveis foram identificados. O coeficiente de correlação de Spearman foi de -0,6506. A metanálise mostrou que a sensibilidade e a especificidade combinadas, a razão de verossimilhança positiva, a razão de verossimilhança negativa e a razão de chances de diagnóstico foram 0,84, 0,86, 6,0, 0,19 e 32, respectivamente. A AUROC foi de 0,92. O ponto quiescente do resumo hierárquico da característica de operação do receptor (hierarchical summary of receiver operating characteristic [HSROC]) foi 3,463. Notavelmente, as imagens de 12 estudos foram adquiridas apenas por ressonância magnética ponderada em T1, e as dos outros 6 foram obtidas apenas por ressonância magnética não ponderada em T1. CONCLUSãO:  Em geral, a aprendizagem profunda da ressonância magnética para o diagnóstico de DA e CCL mostrou boa sensibilidade e especificidade e contribuiu para melhorar a precisão diagnóstica.

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Tongue swabs hold promise as a non-invasive sample for diagnosing tuberculosis (TB). However, their utility as replacements for sputum has been limited by their varied diagnostic performance in PCR assays compared to sputum. The use of silica-based DNA extraction methods may limit sensitivity due to incomplete lysis of Mycobacterium tuberculosis (MTB) cells and co-extraction of non-target nucleic acid, which may inhibit PCR. Specificity may also be compromised because these methods are labor-intensive and prone to cross-contamination. To address these limitations, we developed a sample preparation method that combines sonication for MTB lysis and a sequence-specific MTB DNA capture method using hybridization probes immobilized on magnetic beads. In spiked tongue swabs, our hybridization capture method demonstrated a 100-fold increase in MTB DNA yield over silica-based Qiagen DNA extraction and ethanol precipitation. In a study conducted on clinical samples from South Africa, our protocol had 74% (70/94) sensitivity and 98% (41/42) specificity for detecting active pulmonary TB with sputum Xpert MTB/RIF Ultra as the reference standard. While hybridization capture did not show improved sensitivity over Qiagen DNA extraction and ethanol precipitation, it demonstrated better specificity than previously reported methods and was easier to perform. With integration into point-of-care platforms, these strategies have the potential to help enable rapid non-sputum-based TB diagnosis across key underserved patient populations.