Diagnostic accuracy, reliability, and construct validity of the German quick mild cognitive impairment screen.

BACKGROUND: Early detection of cognitive impairment is among the top research priorities aimed at reducing the global burden of dementia. Currently used screening tools have high sensitivity but lack specificity at their original cut-off, while decreasing the cut-off was repeatedly shown to improve specificity, but at the cost of lower sensitivity. In 2012, a new screening tool was introduced that aims to overcome these limitations - the Quick mild cognitive impairment screen (Qmci). The original English Qmci has been rigorously validated and demonstrated high diagnostic accuracy with both good sensitivity and specificity. We aimed to determine the optimal cut-off value for the German Qmci, and evaluate its diagnostic accuracy, reliability (internal consistency) and construct validity. METHODS: We retrospectively analyzed data from healthy older adults (HOA; n = 43) and individuals who have a clinical diagnosis of 'mild neurocognitive disorder' (mNCD; n = 37) with a biomarker supported characterization of the etiology of mNCD of three studies of the 'Brain-IT' project. Using Youden's Index, we calculated the optimal cut-off score to distinguish between HOA and mNCD. Receiver operating characteristic (ROC) curve analysis was performed to evaluate diagnostic accuracy based on the area under the curve (AUC). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Reliability (internal consistency) was analyzed by calculating Cronbach's α. Construct validity was assessed by analyzing convergent validity between Qmci-G subdomain scores and reference assessments measuring the same neurocognitive domain. RESULTS: The optimal cut-off score for the Qmci-G was ≤ 67 (AUC = 0.96). This provided a sensitivity of 91.9% and a specificity of 90.7%. The PPV and NPV were 89.5% and 92.9%, respectively. Cronbach's α of the Qmci-G was 0.71 (CI95% [0.65 to 0.78]). The Qmci-G demonstrated good construct validity for subtests measuring learning and memory. Subtests that measure executive functioning and/or visuo-spatial skills showed mixed findings and/or did not correlate as strongly as expected with reference assessments. CONCLUSION: Our findings corroborate the existing evidence of the Qmci's good diagnostic accuracy, reliability, and construct validity. Additionally, the Qmci shows potential in resolving the limitations of commonly used screening tools, such as the Montreal Cognitive Assessment. To verify these findings for the Qmci-G, testing in clinical environments and/or primary health care and direct comparisons with standard screening tools utilized in these settings are warranted.

Diagnostic ability of [18F]FDG PET/CT for distinguishing benign from malignant spleen lesions.

OBJECTIVES: [18F]Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is a non-invasive imaging modality used in the differential diagnosis of splenic lesions, although ideal parameters and thresholds remain unclear. The present study evaluated the ability of [18F]FDG PET/CT, including its visual and quantitative parameters, to differentiate between benign and malignant splenic lesions. METHODS: Patients who underwent [18F]FDG PET/CT following the detection of splenic lesions on contrast-enhanced CT were retrospectively analysed. Visual parameters assessed on [18F]FDG PET/CT included whole spleen uptake intensity, lesion multiplicity, and lesion uptake, and quantitative parameters included maximum standardised uptake value (SUVmax), lesion-to-background ratio (LBR), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and lesion size. Parameters differentiating between benign and malignant lesions were evaluated by Pearson's chi-square test, Mann-Whitney U-test, and receiver operating characteristics (ROC) curve analysis. RESULTS: Splenic lesion uptake (p = 0.001) was the only visual parameter significantly distinguishing between benign and malignant lesions. ROC curve analysis demonstrated that SUVmax had the largest area under the ROC, 0.91 (p < 0.001), with an optimal cut-off > 5.3 having a sensitivity of 90.3% and a specificity of 80.6%. Subgroup analysis of malignant lesions showed that SUVmax (p = 0.013), LBR (p = 0.012), and TLG (p = 0.034) were significantly higher in splenic lymphomas than in splenic metastases. CONCLUSION: Of the [18F]FDG PET/CT parameters investigated, SUVmax had the highest accuracy in diagnosing malignant splenic lesions and was significantly higher in splenic lymphomas than in splenic metastases. Visual determination of [18F]FDG uptake by splenic lesions may be an easily evaluated parameter. CLINICAL RELEVANCE STATEMENT: SUVmax and visual grade of [18F]FDG PET/CT help to differentiate spleen lesions. [18F]FDG PET/CT is useful for discriminating between benign and malignant spleen lesions. KEY POINTS: Many splenic lesions are difficult to diagnose on anatomical imaging, with histopathologic analyses are required. SUVmax of PET/CT provided the diagnostic ability to differentiate between benign and malignant splenic lesions. More than normal spleen uptake can be a convenient parameter to diagnose malignant spleen lesions.

Evaluation of adherence to STARD for Abstracts in a diverse sample of diagnostic accuracy abstracts published in 2012 and 2019 reveals suboptimal reporting practices.

OBJECTIVE: To evaluate the completeness of reporting in a sample of abstracts on diagnostic accuracy studies before and after the release of STARD for Abstracts in 2017. METHODS: We included 278 diagnostic accuracy abstracts published in 2012 (N=138) and 2019 (N=140) and indexed in EMBASE. We analyzed their adherence to 10 items of the 11-item STARD for Abstracts checklist and explored variability in reporting across abstract characteristics using multivariable Poisson modeling. RESULTS: Most of the 278 abstracts (75%) were published in discipline-specific journals, with a median impact factor of 2.9 (IQR: 1.9-3.7). The majority (41%) of abstracts reported on imaging tests. Overall, a mean of 5.4/10 (SD: 1.4) STARD for Abstracts items was reported (range: 1.2-9.7). Items reported in less than one-third of abstracts included 'eligible patient demographics' (24%), 'setting of recruitment' (30%), 'method of enrolment' (18%), 'estimates of precision for accuracy measures' (26%), and 'protocol registration details' (4%). We observed substantial variability in reporting across several abstract characteristics, with higher adherence associated with the use of a structured abstract, no journal limit for abstract word count, abstract word count above the median, one-gate enrolment design, and prospective data collection. There was no evidence of an increase in the number of reported items between 2012 and 2019 (5.2 vs. 5.5 items; adjusted reporting ratio 1.04 [95%CI: 0.98-1.10]). CONCLUSION: This sample of diagnostic accuracy abstracts revealed suboptimal reporting practices, without improvement between 2012 and 2019. The test evaluation field could benefit from targeted knowledge translation strategies to improve completeness of reporting in abstracts.

Sample size calculation for data reliability and diagnostic performance: a go-to review.

Sample size, namely the number of subjects that should be included in a study to reach the desired endpoint and statistical power, is a fundamental concept of scientific research. Indeed, sample size must be planned a priori, and tailored to the main endpoint of the study, to avoid including too many subjects, thus possibly exposing them to additional risks while also wasting time and resources, or too few subjects, failing to reach the desired purpose. We offer a simple, go-to review of methods for sample size calculation for studies concerning data reliability (repeatability/reproducibility) and diagnostic performance. For studies concerning data reliability, we considered Cohen's κ or intraclass correlation coefficient (ICC) for hypothesis testing, estimation of Cohen's κ or ICC, and Bland-Altman analyses. With regards to diagnostic performance, we considered accuracy or sensitivity/specificity versus reference standards, the comparison of diagnostic performances, and the comparisons of areas under the receiver operating characteristics curve. Finally, we considered the special cases of dropouts or retrospective case exclusions, multiple endpoints, lack of prior data estimates, and the selection of unusual thresholds for α and ß errors. For the most frequent cases, we provide example of software freely available on the Internet.Relevance statement Sample size calculation is a fundamental factor influencing the quality of studies on repeatability/reproducibility and diagnostic performance in radiology.Key points• Sample size is a concept related to precision and statistical power.• It has ethical implications, especially when patients are exposed to risks.• Sample size should always be calculated before starting a study.• This review offers simple, go-to methods for sample size calculations.

Identifying early language predictors: A replication of Gasparini et al. (2023) confirming applicability in a general population cohort.

BACKGROUND: Identifying language disorders earlier can help children receive the support needed to improve developmental outcomes and quality of life. Despite the prevalence and impacts of persistent language disorder, there are surprisingly no robust predictor tools available. This makes it difficult for researchers to recruit young children into early intervention trials, which in turn impedes advances in providing effective early interventions to children who need it. AIMS: To validate externally a predictor set of six variables previously identified to be predictive of language at 11 years of age, using data from the Longitudinal Study of Australian Children (LSAC) birth cohort. Also, to examine whether additional LSAC variables arose as predictive of language outcome. METHODS & PROCEDURES: A total of 5107 children were recruited to LSAC with developmental measures collected from 0 to 3 years. At 11-12 years, children completed the Clinical Evaluation of Language Fundamentals, 4th Edition, Recalling Sentences subtest. We used SuperLearner to estimate the accuracy of six previously identified parent-reported variables from ages 2-3 years in predicting low language (sentence recall score ≥ 1.5 SD below the mean) at 11-12 years. Random forests were used to identify any additional variables predictive of language outcome. OUTCOMES & RESULTS: Complete data were available for 523 participants (52.20% girls), 27 (5.16%) of whom had a low language score. The six predictors yielded fair accuracy: 78% sensitivity (95% confidence interval (CI) = [58, 91]) and 71% specificity (95% CI = [67, 75]). These predictors relate to sentence complexity, vocabulary and behaviour. The random forests analysis identified similar predictors. CONCLUSIONS & IMPLICATIONS: We identified an ultra-short set of variables that predicts 11-12-year language outcome with 'fair' accuracy. In one of few replication studies of this scale in the field, these methods have now been conducted across two population-based cohorts, with consistent results. An imminent practical implication of these findings is using these predictors to aid recruitment into early language intervention studies. Future research can continue to refine the accuracy of early predictors to work towards earlier identification in a clinical context. WHAT THIS PAPER ADDS: What is already known on the subject There are no robust predictor sets of child language disorder despite its prevalence and far-reaching impacts. A previous study identified six variables collected at age 2-3 years that predicted 11-12-year language with 75% sensitivity and 81% specificity, which warranted replication in a separate cohort. What this study adds to the existing knowledge We used machine learning methods to identify a set of six questions asked at age 2-3 years with ≥ 71% sensitivity and specificity for predicting low language outcome at 11-12 years, now showing consistent results across two large-scale population-based cohort studies. What are the potential or clinical implications of this work? This predictor set is more accurate than existing feasible methods and can be translated into a low-resource and time-efficient recruitment tool for early language intervention studies, leading to improved clinical service provision for young children likely to have persisting language difficulties.

A prospective evaluation of the diagnostic accuracy of the point-of-care VISITECT CD4 Advanced Disease test in seven countries.

BACKGROUND: CD4 measurement is pivotal in the management of advanced HIV disease. VISITECT® CD4 Advanced Disease (AccuBio Limited, Alva, UK; VISITECT) is an instrument-free, point-of-care, semi-quantitative test allowing visual identification of a CD4 ≤200 cells/µl, or >200 cells/µl from finger-prick or venous blood. METHODS: As part of a diagnostic accuracy study of FUJIFILM SILVAMP TB LAM (clinicaltrials.gov: NCT04089423), people living with HIV of ≥18 years old were prospectively recruited in seven countries from outpatient departments if a tuberculosis symptom was present, and from inpatient departments. Participants provided venous blood for CD4 measurement using flow cytometry (reference standard) and finger-prick blood for VISITECT (index text), performed at point-of-care. Sensitivity, specificity, and positive and negative predictive values of VISITECT to determine a CD4 ≤200 cells/µl were evaluated. RESULTS: Among 1604 participants, the median flow cytometry CD4 was 367 (IQR 128-626) cells/µl and 521 (32.5%) had a CD4 ≤200 cells/µl. VISITECT sensitivity was 92.7% (483/521, 95% CI 90.1-94.7%) and specificity was 61.4% (665/1083, 95% CI 58.4-64.3%). For participants with a CD4 between 0-100, 101-200, 201-300, 301-500, and >500 cells/µl, VISITECT misclassified 4.5% (95% CI 2.5-7.2%), 12.5 (95% CI 8.0-18.2%), 74.1% (95% CI 67.0-80.5%), 48.0% (95% CI 42.5-53.6%), and 22.6% (95% CI 19.3-26.3%), respectively. CONCLUSIONS: VISITECT's sensitivity, but not specificity, met the World Health Organization's minimal sensitivity and specificity threshold of 80% for point-of-care CD4 tests. VISITECT's quality needs to be assessed and its accuracy optimized. VISITECT´s utility as CD4 triage test should be investigated.

Diagnostic performance of the CellaVision preclassification neutrophil count - time to bypass the reclassification?

OBJECTIVES: The objective of this study was to perform a method comparison between the CellaVision preclassification neutrophil count and the reclassification neutrophil count performed by trained laboratory technicians, and to evaluate the diagnostic performance of the preclassification neutrophil count at clinical decision levels. METHODS: We retrospectively identified patient samples through 2019-2022 in which the differential count was performed on Cellavision (n = 4,354). Data on sample characteristics and leukocyte- and differential counts was extracted from the electronic medical journal. For each sample, data containing the pre- and reclassification leukocyte classification, respectively, was extracted from the Cellavision software. Method comparison between the pre-and reclassification neutrophil count was performed using Bland Altman analysis. Diagnostic performance of the preclassification neutrophil count was evaluated according to four pre-specified categories of results with the reclassification as reference method. RESULTS: The median difference between the pre- and reclassification neutrophil count was 0.044 x 109/L. The preclassification neutrophil count categorised 95.6% of all samples correctly according to the four categories. The sensitivity, specificity, positive predictive value and negative predictive value for detecting neutrophilia > 7.00 x 109/L was 98.8%, 97.2%, 95.8%, and 99.2%, respectively. In samples with leukopenia (n = 543), the sensitivity, specificity, positive predictive value and negative predictive value for detecting severe neutropenia (< 0.50 x 109/L) was 97.7%, 99.1%, 98.6%, and 98.5%, respectively. CONCLUSION: The diagnostic performance of the CellaVision preclassification neutrophil count was satisfactory. The preclassification neutrophil count may be released to the electronic medical journal to improve turnaround time and benefit laboratory management.

Mayo Normative Studies: Amyloid and Neurodegeneration Negative Normative Data for the Auditory Verbal Learning Test and Sex-Specific Sensitivity to Mild Cognitive Impairment/Dementia.

Background: Conventional normative samples include individuals with undetected Alzheimer's disease neuropathology, lowering test sensitivity for cognitive impairment. Objective: We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A-N-) for Rey's Auditory Verbal Learning Test (AVLT). We compared these MNS A-N- norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments. Methods: The A-N- sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A-N- norms in two independent samples of CU (n = 261) and mild cognitive impairment (MCI)/dementia participants (n = 392) > 55 years of age. Results: Variability associated with age decreased by almost half in the A-N- norm sample relative to the conventional norm sample. Fully-adjusted MNS A-N- norms showed approximately 7- 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1- 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men. Conclusions: A-N- norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A-N- norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.

Assessment of the diagnostic efficacy of radiological and functional evaluation of primary adrenal mass and its' surgical outcomes.

INTRODUCTION: Objective of this study was to assess the diagnostic efficacy of the most commonly used radiological evaluation in form of contrast enhanced computed tomography of abdomen with adrenal protocol, basic functional evaluation and surgical outcomes of primary adrenal masses. MATERIAL AND METHODS: We have retrospectively analysed the institutional records of 108, patients admitted from August 2017 to September 2023, who had underwent surgical intervention for their adrenal mass after thorough evaluation and stabilization. RESULTS: Flank pain was the most common symptoms in 44 (40.74%) patients. Non-functional adrenal adenoma was found in 36 (33.33%) patients. Pheochromocytoma was the most the common functional adrenal mass found in 24 (22.22%) patients. CECT abdomen had suggested features of malignancy in 16(14.81%) patients. In final histopathological report 26(24.07%) patients had pheochromocytoma and 12 (11.11%) patients had adrenocortical carcinoma. CECT abdomen had sensitivity of 75%, specificity of 95.6%. Plasma free metanephrines and normetanephrine analysis had shown sensitivity of 90%, specificity of 92.86%, aldosterone to renin ratio had sensitivity of 92%, specificity of 100%. Sensitivity and specificity of the low-dose dexamethasone suppression test and plasma dehydroepiandrosterone was 100% in our study. Eighty patients (74.07%) were operated with laparoscopic adrenalectomy, 20 (18.52%) patients with open adrenalectomy. Eight patients (7.41%) were converted from laparoscopic to open. Laparoscopic approach had significantly lesser mean operating time, lesser blood loss, lesser hospitalization and lesser post-operative complications. CONCLUSION: Radiological analysis and functional analysis has shown good sensitivity and high specificity. Laparoscopic approach has advantage of lesser operative time, lesser hospitalization and lesser post-operative complications.

Accuracy of contrast-enhanced CT in liver neoplasms in children under 2 years age.

BACKGROUND: Multiple differentials exist for pediatric liver tumors under 2 years. Accurate imaging diagnosis may obviate the need for tissue sampling in most cases. OBJECTIVE: To evaluate the imaging features and diagnostic accuracy of computed tomography (CT) in liver tumors in children under 2 years. METHODS: Eighty-eight children under 2 years with treatment naive liver neoplasms and baseline contrast-enhanced CT were included in this institutional review board approved retrospective study. Two blinded onco-radiologists assessed these tumors in consensus. Findings assessed included enhancement pattern, lobulated appearance, cystic change, calcifications, central scar-like appearance, and metastases. The radiologists classified the lesion as hepatoblastoma, infantile hemangioma, mesenchymal hamartoma, rhabdoid tumor, or indeterminate, first based purely on imaging and then after alpha-fetoprotein (AFP) correlation. Multivariate analysis and methods of comparing means and frequencies were used for statistical analysis wherever applicable. Diagnostic accuracy, sensitivity, and positive predictive values were analyzed. RESULTS: The mean age of the sample was 11.4 months (95% CI, 10.9-11.8) with 50/88 (57%) boys. The study included 72 hepatoblastomas, 6 hemangiomas, 4 mesenchymal hamartomas, and 6 rhabdoid tumors. Presence of calcifications, multilobular pattern of arterial enhancement, lobulated morphology, and central scar-like appearance was significantly associated with hepatoblastomas (P-value < 0.05). Fourteen out of eighty-eight lesions were called indeterminate based on imaging alone; six lesions remained indeterminate after AFP correlation. Pure radiology-based diagnostic accuracy was 81.8% (95% CI, 72.2-89.2%), which increased to 92.1% (95% CI, 84.3-96.7%) (P-value > 0.05) after AFP correlation, with one hepatoblastoma misdiagnosed as a rhabdoid tumor. If indeterminate lesions were excluded for biopsy, the accuracy would be 98.8% (95% CI, 93.4-99.9%). CONCLUSION: CT had high accuracy for diagnosing liver neoplasms in the under 2-year age population after AFP correlation. Certain imaging features were significantly associated with the diagnosis of hepatoblastoma. A policy of biopsying only indeterminate lesions after CT and AFP correlation would avoid sampling in the majority of patients.

Ocular Signs and Testing Most Compatible with Sarcoidosis-Associated Uveitis: A Latent Class Analysis.

Purpose: This study aims to explore the potential subgroups of sarcoidosis-associated uveitis (SAU) within a multicenter cohort of uveitis participants. Design: Cross-sectional study. Participants: A cohort of 826 uveitis patients from a uveitis registry from 19 clinical centers in 12 countries between January 2011 and April 2015. Methods: We employed a latent class analysis (LCA) incorporating recommended tests and clinical signs from the revised International Workshop on Ocular Sarcoidosis (IWOS) to identify potential SAU subgroups within the multicenter uveitis cohort. Additionally, we assessed the performance of the individual tests and clinical signs in classifying the potential subclasses. Main Outcome Measures: Latent subtypes of SAU. Results: Among 826 participants included in this analysis, the 2-class LCA model provided a best fit, with the lowest Bayesian information criteria of 7218.7 and an entropy of 0.715. One class, consisting of 548 participants, represented the non-SAU, whereas the second class, comprised of 278 participants, was most representative of SAU. Snowballs/string of pearls vitreous opacities had the best test performance for classification, followed by bilaterality and bilateral hilar lymphadenopathy (BHL). The combination of 4 tests with the highest classification importance, including snowballs/string of pearls vitreous opacities, periphlebitis and/or macroaneurysm, bilaterality, and BHL, demonstrated a sensitivity of 84.8% and a specificity of 95.4% in classifying the SAU subtypes. In the exploratory analysis of the 3-class LCA model, which had comparable fit indices as the 2-class model, we identified a candidate non-SAU subtype, candidate SAU subtype with pulmonary involvement, and a candidate SAU with less pulmonary involvement. Conclusions: Latent class modeling, incorporating tests and clinical signs from the revised IWOS criteria, effectively identified a subset of participants with clinical features indicative of SAU. Though the sensitivity of individual ocular signs or tests was not perfect, using a combination of tests provided a satisfactory performance in classifying the SAU subclasses identified by the 2-class LCA model. Notably, the classes identified by the 3-class LCA model, including a non-SAU subtype, an SAU subtype with pulmonary involvement, and an SAU subtype with less pulmonary involvement, may have potential implication for clinical practice, and hence should be validated in further research. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Robust AI-Driven Segmentation of Glioblastoma T1c and FLAIR MRI Series and the Low Variability of the MRIMath© Smart Manual Contouring Platform.

Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen-Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists' scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists' ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists' scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists' scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland-Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform's low inter-user variability and the high accuracy of its T1c and FLAIR AI models.

Comparative evaluation of screening tools for sarcopenia in patients with axial spondyloarthritis.

Sarcopenia is linked to chronic inflammation and muscle wasting. This research aims to compare the screening accuracy of tools for sarcopenia in axial spondyloarthritis (axSpA). A cross-sectional study involving 104 axSpA patients was conducted at Phramongkutklao Hospital between January 2020 and February 2021. Sarcopenia was diagnosed according to the AWGS 2019 criteria. Appendicular skeletal muscle mass was measured using DXA. SARC-F, SARC-CalF, and SARC-F+EBM, muscle strength, and physical performance were assessed. The screening tests were evaluated using ROC curves. The optimal cutoffs were identified with the Youden index. Most patients were male (74%), with a mean (SD) age and disease duration of 42.6 (12.22) and 8.3 (8.5), respectively. The prevalence of sarcopenia was 22.1%. The AUCs (95% CI) for calf circumference, SARC-F, SARC-CalF, SARC-F+EBM, handgrip strength, chair stand time, gait speed, and time and go test were 0.830 (0.734, 0.925), 0.509 (0.373-0.645), 0.782 (0.670-0.894), 0.856 (0.758-0.954), 0.710 (0.594-0.825), 0.640 (0.508-0.772), 0.689 (0.539-0.839), and 0.711 (0.576-0.846), respectively. The optimal cutoffs for SARC-F, SARC-CalF, and SARC-F+EBM were 1, 10, and 10, with sensitivity/specificity of 81.0%/29.7%, 90.5%/68.9%, and 77.3%/87.2%, respectively. Calf circumference, SARC-CalF, and SARC-F+EBM had the best performance to screen for sarcopenia in axSpA patients. Lowering the thresholds would potentially enhance the performances of SARC-CalF and SARC-F+EBM.

Excellent accuracy of magnetic resonance imaging for diagnosis of discoid meniscus tears: A systematic review and meta-analysis.

Purpose: The discoid meniscus (DM) is distinguished by its thickened, disc-shaped formation, which extends over the tibial plateau. The likelihood of developing osteoarthritis escalates if a DM tear remains undiagnosed and untreated. While DM tears can be diagnosed through arthroscopy, the high cost, invasive nature and limited availability of this procedure highlight the need for a better diagnostic modality. This study aims to determine the accuracy of magnetic resonance imaging (MRI) in diagnosing DM tears. Methods: A systematic review was conducted to gather articles with at least 10 cases on the comparison of MRI and arthroscopy as the gold standard for DM tear diagnosis. Stata and MetaDisc were used to conduct the statistical analysis. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Results: Five diagnostic performance studies, derived from four original research papers involving 305 patients, were evaluated. Based on the pooled data, the sensitivity, specificity, diagnostic odds ratio, positive limit of detection and negative limit of detection were found to be 0.87 (95% confidence interval [CI], 0.82-0.91) and 0.84 (95% CI, 0.75-0.90), 32.88 (95% CI, 5.81-186.02), 5.22 (95% CI, 1.71-15.92) and 0.18 (95% CI, 0.09-0.38), respectively. A hierarchical summary receiver operating characteristic curve with an area under the curve of 0.92 was generated. Conclusion: This meta-analysis demonstrates that MRI has excellent sensitivity and specificity for diagnosing DM tears. Despite its lower accuracy compared to arthroscopy, MRI can be used in symptomatic patients as a viable alternative to arthroscopy due to its inherent advantages. Level of Evidence: Level IV.

Diagnostic Efficacy Study Comparing Tzanakis Scoring System With Alvarado Scoring System in Effective Diagnosis of Acute Appendicitis.

Objective Among the common causes of abdominal emergencies, acute appendicitis ranks at the top, particularly in the young population. While negative appendectomy is not uncommon, the risk of appendicular perforation is substantial if the diagnosis is missed or delayed. This study evaluated the diagnostic efficacy of the Tzanakis scoring system for acute appendicitis, comparing it with the Alvarado scoring system, considering the histopathological finding as the gold standard. Materials and methods This prospective observational study, conducted in the General Surgery department in a tertiary care hospital in India, included clinically diagnosed acute appendicitis cases posted for open or laparoscopic appendicectomy. Results The mean age for the 60 participants included in the study was 30.97±13.44, and the median was 24.5 yrs. The sensitivity of ultrasonography (USG) in diagnosing histopathological positive acute appendicitis was 89%, and the specificity was 50%. The sensitivity, specificity, positive, and negative predictive values of the Tzanakis score were 87%, 50%, 96%, and 22%, respectively, and those of the Alvarado score were 54%, 75%, 96%, and 10%, respectively. Conclusion The receiver operator characteristic (ROC) curve for the Alvarado and Tzanakis scores showed that the area under the curve (AUC) was greater for the Tzanakis scoring system (0.670) than for the Alvarado scoring system (0.598). Differences between the AUCs were not statistically significant. Although the Tzanakis scoring system is more sensitive than the Alvarado scoring system in diagnosing acute appendicitis, studies with larger samples are needed to show the superiority of this scoring system over the Alvarado scoring system.

Malnutrition screening tool and nutritional screening tool for classification of nutritional risk in patients with cancer upon hospital admission: Comparison of diagnostic performance using Global Leadership Initiative on malnutrition criteria as reference.

BACKGROUND & AIMS: Tools for screening of nutrition risk in patients with cancer are usually validated against other screening instruments. Here with the performance of Malnutrition Screening Tool (MST) and Nutritional Screening Tool (NUTRISCORE) to identify the risk of malnutrition was assessed. A full nutritional evaluation and diagnosis following criteria from the Global Leadership Initiative of Malnutrition (GLIM) was the reference standard for the classification of malnutrition. METHODS: Diagnostic test prospective analysis of adult patients with a confirmed diagnosis of cancer. MST, NUTRISCORE and nutritional evaluation and diagnosis by GLIM criteria were independently performed within 24 h of admission to a 4th tier hospital in Bogotá, Colombia. RESULTS: From 439 patients the sensitivity and specificity of MST was 75% and 94% and of NUTRISCORE 45% and 97% respectively. The area under receiver operating characteristic (ROC) curves were 0.90 for MST and 0.85 for NUTRISCORE (p = 0.003). CONCLUSION: The MST showed a significantly better diagnostic performance over NUTRISCORE for detection of malnutrition risk at admission to hospital of patients with cancer.

Distinguishing thymic cysts from low-risk thymomas via [18F]FDG PET/CT.

BACKGROUND: Thymic cysts are a rare benign disease that needs to be distinguished from low-risk thymoma. [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is a non-invasive imaging technique used in the differential diagnosis of thymic epithelial tumours, but its usefulness for thymic cysts remains unclear. Our study evaluated the utility of visual findings and quantitative parameters of [18F]FDG PET/CT for differentiating between thymic cysts and low-risk thymomas. METHODS: Patients who underwent preoperative [18F]FDG PET/CT followed by thymectomy for a thymic mass were retrospectively analyzed. The visual [18F]FDG PET/CT findings evaluated were PET visual grade, PET central metabolic defect, and CT shape. The quantitative [18F]FDG PET/CT parameters evaluated were PET maximum standardized uptake value (SUVmax), CT diameter (cm), and CT attenuation in Hounsfield units (HU). Findings and parameters for differentiating thymic cysts from low-risk thymomas were assessed using Pearson's chi-square test, the Mann-Whitney U-test, and receiver operating characteristics (ROC) curve analysis. RESULTS: Seventy patients (18 thymic cysts and 52 low-risk thymomas) were finally included. Visual findings of PET visual grade (P < 0.001) and PET central metabolic defect (P < 0.001) showed significant differences between thymic cysts and low-risk thymomas, but CT shape did not. Among the quantitative parameters, PET SUVmax (P < 0.001), CT diameter (P < 0.001), and CT HU (P = 0.004) showed significant differences. In ROC analysis, PET SUVmax demonstrated the highest area under the curve (AUC) of 0.996 (P < 0.001), with a cut-off of equal to or less than 2.1 having a sensitivity of 100.0% and specificity of 94.2%. The AUC of PET SUVmax was significantly larger than that of CT diameter (P = 0.009) and CT HU (P = 0.004). CONCLUSIONS: Among the [18F]FDG PET/CT parameters examined, low FDG uptake (SUVmax ≤ 2.1, equal to or less than the mediastinum) is a strong diagnostic marker for a thymic cyst. PET visual grade and central metabolic defect are easily accessible findings.

Exploring complement biomarkers in suspected axial spondyloarthritis.

OBJECTIVES: To investigate lectin pathway proteins (LPPs) as biomarkers for axial spondyloarthritis (axSpA) in a cross-sectional cohort with a suspicion of axSpA, comprising newly diagnosed axSpA and chronic low back pain (cLBP) individuals. METHODS: Serum samples from 515 participants within the OptiRef cohort, including 151 axSpA patients and 364 cLBP patients, were measured using immunoassays for LPPs (mannan-binding lectin (MBL), collectin liver-1 (CL-L1), M-ficolin, H-ficolin and L-ficolin, MBL-associated serine proteases (MASP)-1, -2 and -3, MBL-associated proteins (MAp19 and MAp44) and the complement activation product C3dg). RESULTS: Serum levels of L-ficolin, MASP-2 and C3dg were elevated in axSpA patients, whereas levels of MASP-3 and CL-L1 were decreased, and this remained significant for C3dg and MASP-3 after adjustment for C reactive protein (CRP). A univariate regression analysis showed serum levels of CL-L1, MASP-2, MASP-3 and C3dg to predict the diagnosis of axSpA, and MASP-3 and C3dg remained significant in a multivariate logistic regression analysis. Assessment of the diagnostic potential showed that a combination of human leukocyte antigen B27 (HLA-B27) and measurements of L-ficolin, MASP-3 and C3dg increased the diagnostic specificity for axSpA, however, with a concomitant loss of sensitivity. CONCLUSIONS: Serum levels of complement activation, that is, C3dg, and MASP-3 differed significantly between axSpA and cLBP patients after adjustment for CRP. Although combining HLA-B27 with measurements of L-ficolin, MASP-3 and C3dg increased the diagnostic specificity for axSpA, this seems unjustified due to the concomitant loss of sensitivity. However, both C3dg and MASP-3 were associated with axSpA diagnosis in multivariate logistic regression, suggesting an involvement of complement in the inflammatory processes and possibly pathogenesis in axSpA.

Comparison of the Prognostic Accuracy of Full Outline of Unresponsiveness (FOUR) Score with Glasgow Coma Scale (GCS) Score among Patients with Traumatic Brain Injury in a Tertiary Care Center.

Objectives The Glasgow Coma Scale (GCS) is widely used and considered the gold standard in assessing the consciousness of patients with traumatic brain injury. However, some significant limitations, like the considerable variations in interobserver reliability and predictive validity, were the reason for developing the Full Outline of Unresponsiveness (FOUR) score. The current study aims to compare the prognostic accuracy of the FOUR score with the GCS score for in-hospital mortality and morbidity among patients with traumatic brain injury. Materials and Methods A prospective cohort study was conducted, where 237 participants were selected by consecutive sampling from a tertiary care center. These patients were assessed with the help of GCS and FOUR scores within 6 hours of admission, and other clinical parameters were also noted. The level of consciousness was checked every day with the help of GCS and FOUR scores until their last hospitalization day. Glasgow Outcome Scale was used to assess their outcome on the last day of hospitalization. The GCS and FOUR scores were compared, and data were analyzed by descriptive and inferential statistics. The chi-square test, independent Student's t -test, and receiver operating characteristic analysis were used for inferential analysis. Results The area under the curve (AUC) for the GCS score at the 6th hour for predicting mortality was 0.865 with a cutoff value of 5.5, and it yields a sensitivity of 87% and a specificity of 64%. The AUC for FOUR scores at the 6th hour for predicting the mortality was 0.893, with a cutoff value of 5.5, and it yields a sensitivity of 87% and a specificity of 73%. Conclusion The current study shows that, as per the AUC of GCS and FOUR scores, their sensitivity was equal, but specificity was higher in the FOUR score. So, the FOUR score has higher accuracy than the GCS score in the prediction of mortality among traumatic brain injury patients.

Value of turbo spin echo-based diffusion-weighted imaging in the differential diagnosis of benign and malignant solitary pulmonary lesions.

To quantitatively assess the diagnostic efficacy of multiple parameters derived from multi-b-value diffusion-weighted imaging (DWI) using turbo spin echo (TSE)-based acquisition techniques in patients with solitary pulmonary lesions (SPLs). A total of 105 patients with SPLs underwent lung DWI using single-shot TSE-based acquisition techniques and multiple b values. The apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) parameters, and lesion-to-spinal cord signal intensity ratio (LSR), were analyzed to compare the benign and malignant groups using the Mann-Whitney U test and receiver operating characteristic analysis. The Dstar values observed in lung cancer were slightly lower than those observed in pulmonary benign lesions (28.164 ± 31.950 versus 32.917 ± 34.184; Z = -2.239, p = 0.025). The LSR values were significantly higher in lung cancer than in benign lesions (1.137 ± 0.581 versus 0.614 ± 0.442; Z = - 4.522, p < 0.001). Additionally, the ADC800, ADCtotal, and D values were all significantly lower in lung cancer than in the benign lesions (Z = - 5.054, -5.370, and -6.047, respectively, all p < 0.001), whereas the f values did not exhibit any statistically significant difference between the two groups. D had the highest area under the curve (AUC = 0.887), followed by ADCtotal (AUC = 0.844), ADC800 (AUC = 0.824), and LSR (AUC = 0.789). The LSR, ADC800, ADCtotal, and D values did not differ statistically significantly in diagnostic effectiveness. Lung DWI using TSE is feasible for differentiating SPLs. The LSR method, conventional DWI, and IVIM have comparable diagnostic efficacy for assessing SPLs.