Positive Likelihood Ratio Values Research Articles

Accuracy of the international growth charts to diagnose obesity according to the body composition analysis in US children and adolescents.

This study verified the accuracy of the international BMI references and the allometric BMI reference to diagnose obesity in children and adolescents from the USA. Data from 17313 subjects were obtained from the National Health and Nutrition Examination Survey between the years 1999-2006 and 2011-2018. Fat Mass Index, Allometric Fat Mass Index and fat mass/fat-free mass were calculated. Receiver operating characteristic curve, AUC, sensitivity, specificity, positive likelihood ratio and negative likelihood ratio were estimated to evaluate the accuracy of the growth references for diagnosing obesity. The International Obesity Task Force, MULT BMI 17 years, MULT BMI 18 years and allometric BMI 19 years achieved the best sensitivity-specificity trade-off for boys, with sensitivities ranging from 0·92 to 0·96 and specificities of 0·94, with positive likelihood ratio of 15·51, 16·17, 13·46 and 18·01, respectively. The negative likelihood ratios were notably low, ranging from 0·04 to 0·08. In girls, the International Obesity Task Force, MULT BMI 17 years and MULT allometric BMI 17 years also demonstrated high sensitivity (0·95-0·97) and specificity (0·92), with positive likelihood ratio values of 11·54, 11·82 and 11·77, respectively and low negative likelihood ratio values (0·03-0·05). In summary, these international growth references presented satisfactory performance to diagnose obesity. However, the MULT growth reference performed better, and the MULT allometric BMI was the only indicator capable of detecting that girls have a higher proportion of fat mass than boys for the same index values. These findings suggest that the MULT growth reference may be a better tool to assess the nutritional status of children and adolescents internationally.

Assessing the precision of machine learning for diagnosing pulmonary arterial hypertension: a systematic review and meta-analysis of diagnostic accuracy studies.

Pulmonary arterial hypertension (PAH) is a severe cardiovascular condition characterized by pulmonary vascular remodeling, increased resistance to blood flow, and eventual right heart failure. Right heart catheterization (RHC) is the gold standard diagnostic technique, but due to its invasiveness, it poses risks such as vessel and valve injury. In recent years, machine learning (ML) technologies have offered non-invasive alternatives combined with ML for improving the diagnosis of PAH. The study aimed to evaluate the diagnostic performance of various methods, such as electrocardiography (ECG), echocardiography, blood biomarkers, microRNA, chest x-ray, clinical codes, computed tomography (CT) scan, and magnetic resonance imaging (MRI), combined with ML in diagnosing PAH. The outcomes of interest included sensitivity, specificity, area under the curve (AUC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). This study employed the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool for quality appraisal and STATA V.12.0 for the meta-analysis. A comprehensive search across six databases resulted in 26 articles for examination. Twelve articles were categorized as low-risk, nine as moderate-risk, and five as high-risk. The overall diagnostic performance analysis demonstrated significant findings, with sensitivity at 81% (95% CI = 0.76-0.85, p < 0.001), specificity at 84% (95% CI = 0.77-0.88, p < 0.001), and an AUC of 89% (95% CI = 0.85-0.91). In the subgroup analysis, echocardiography displayed outstanding results, with a sensitivity value of 83% (95% CI = 0.72-0.91), specificity value of 93% (95% CI = 0.89-0.96), PLR value of 12.4 (95% CI = 6.8-22.9), and DOR value of 70 (95% CI = 23-231). ECG demonstrated excellent accuracy performance, with a sensitivity of 82% (95% CI = 0.80-0.84) and a specificity of 82% (95% CI = 0.78-0.84). Moreover, blood biomarkers exhibited the highest NLR value of 0.50 (95% CI = 0.42-0.59). The implementation of echocardiography and ECG with ML for diagnosing PAH presents a promising alternative to RHC. This approach shows potential, as it achieves excellent diagnostic parameters, offering hope for more accessible and less invasive diagnostic methods. PROSPERO (CRD42024496569).

Racial Composition of Social Environments Over the Life Course Using the Pictorial Racial Composition Measure: Development and Validation Study.

Studies investigating the impact of racial segregation on health have reported mixed findings and tended to focus on the racial composition of neighborhoods. These studies use varying racial composition measures, such as census data or investigator-adapted questions, which are currently limited to assessing one dimension of neighborhood racial composition. This study aims to develop and validate a novel racial segregation measure, the Pictorial Racial Composition Measure (PRCM). The PRCM is a 10-item questionnaire of pictures representing social environments across adolescence and adulthood: neighborhoods and blocks (adolescent and current), schools and classrooms (junior high and high school), workplace, and place of worship. Cognitive interviews (n=13) and surveys (N=549) were administered to medically underserved patients at a primary care clinic at the Barnes-Jewish Hospital. Development of the PRCM occurred across pilot and main phases. For each social environment and survey phase (pilot and main), we computed positive versus negative pairwise comparisons: mostly Black versus all other categories, half Black versus all other categories, and mostly White versus all other categories. We calculated the following validity metrics for each pairwise comparison: sensitivity, specificity, correct classification rate, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, false positive rate, and false negative rate. For each social environment, the mostly Black and mostly White dichotomizations generated better validity metrics relative to the half Black dichotomization. Across all 10 social environments in the pilot and main phases, mostly Black and mostly White dichotomizations exhibited a moderate-to-high sensitivity, specificity, correct classification rate, positive predictive value, and negative predictive value. The positive likelihood ratio values were >1, and the negative likelihood ratio values were close to 0. The false positive and negative rates were low to moderate. These findings support that using either the mostly Black versus other categories or the mostly White versus other categories dichotomizations may provide accurate and reliable measures of racial composition across the 10 social environments. The PRCM can serve as a uniform measure across disciplines, capture multiple social environments over the life course, and be administered during one study visit. The PRCM also provides an added window into understanding how structural racism has impacted minoritized communities and may inform equitable intervention and prevention efforts to improve lives.

Unlocking the potential of HB/RDW ratio as a simple marker for predicting mortality in acute ischemic stroke patients after thrombolysis

BackgroundSystemic inflammation impairs outcomes in acute ischemic stroke (AIS). There is limited knowledge regarding the prognostic value of inflammatory biomarkers derived from complete blood count in predicting in-hospital mortality (IHM) in AIS patients treated with recombinant tissue plasminogen activator (rt-PA). Our study aims to compare the predictive performance of various inflammatory biomarkers for predicting IHM in AIS patients. MethodsThis retrospective study included AIS patients treated with rt-PA between January 2015 and July 2022. We identified the following inflammatory biomarkers: white blood cell counts (WBCs), absolute neutrophil count, absolute lymphocyte count, neutrophil to lymphocyte count ratio, platelet to neutrophil ratio, platelet to lymphocyte ratio, red cell distribution width (RDW), RDW to platelet ratio (RPR), and hemoglobin to RDW (HB/RDW) at admission before rt-PA administration. We assessed the predictive value of these biomarkers for IHM by plotting receiver operating characteristic (ROC) curves. The associations between inflammatory biomarkers and IHM were analyzed using multivariable logistic regression (MVLR) analyses. ResultsOf 345 AIS patients, IHM occurred in 65 patients (18.84%). HB/RDW and RDW showed better predictive performance compared to other inflammatory biomarkers. In ROC curve analysis, HB/RDW and RDW had an area under ROC of 0.668. HB/RDW outperformed RDW in terms of the positive likelihood ratio (2.733 vs 1.575), accuracy (0.757 vs 0.585), specificity (0.814 vs 0.560), and positive predictive values (0.388 vs 0.267). In MVLR analysis, RDW, RPR, and HB/RDW remained significantly associated with IHM (per 1-unit increases: odds ratios (ORs) = 1.450, 95% CI: [1.178-1.784]; per 1-unit increases: ORs = 1.329, 95% CI [1.103-1.602]; and per 0.1-unit decreases: ORs = 1.412, 95% CI [1.089-1.831], respectively). ConclusionsThe association between HB/RDW and IHM in AIS patients treated with rt-PA was significant. HB/RDW exhibited superior predictive performance compared to other inflammatory biomarkers in predicting IHM.

Prediction accuracy of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer: A systematic review and meta-analysis.

e14652 Background: To compare the predictive accuracy of PD-L1 IHC, tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profiling (GEP), driver gene mutation, and combined marker for immunotherapy response of advanced non-small cell lung cancer (NSCLC). Methods: Systematic searches of PubMed, Cochrane CENTRAL, and Embase were conducted from inception to July 6, 2023. Clinical trials involved with predictive biomarkers exploration for immune checkpoint inhibitors (ICIs) in advanced NSCLC were eligible. The response according to the biomarkers were extracted. The primary outcome was the area under the curve (AUC) of the summary receiver operating characteristic (SROC). Sensitivity, specificity, likelihood ratios and predictive values were evaluated. The subgroup analysis of different PD-L1 cut-off, TMB test and driver gene mutation were performed. Results: 36 articles of 59 biomarker tests were included. The AUC of combined marker (0.75; 95%CI, 0.71-0.78) was higher than PD-L1 (0.64; 95%CI, 0.60-0.68), tTMB (0.64; 95%CI, 0.60-0.68), bTMB (0.68; 95%CI, 0.64-0.72), GEP (0.67; 95%CI, 0.63-0.71), and driver gene mutation (0.51; 95%CI, 0.47-0.55). Combined marker also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers (Table). In subgroup analysis, PD-L1 with cut-off 50% had higher AUC (0.67; 95%CI, 0.63-0.71) than cut-off 1% (0.62; 95%CI, 0.58-0.66); EGFR mutation had higher AUC (0.69; 95%CI, 0.65-0.73) than KRAS (0.53; 95%CI, 0.49-0.58); tTMB measured by Whole Exosome Sequencing (WES) had approximate AUC to that measure by targeted gene panel. The predictive accuracy of the biomarkers was further compared for patients receiving ICI-based combination therapy. The AUC of combined marker (0.70; 95%CI, 0.66-0.74) remained the highest for combination therapy. Conclusions: Combined marker (PD-L1+tTMB/bTMB/GEP) has superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. bTMB is a promising liquid biopsy biomarker. The prescription of ICI for patients with EGFR mutation should be cautious. Further investigation is warranted to precisely identify biomarkers in various clinical settings. [Table: see text]

Abstract LB276: qPCR in the diagnosis of papillary thyroid cancer: Assessment of BRAF V600E mutation in FNA biopsies of thyroid nodules

Abstract Papillary thyroid carcinoma (PTC) accounts for up to 90% of thyroid cancer cases, and its differentiation from benign conditions presents a challenge in clinical practice. Fine needle aspiration biopsy (FNAB) has become a recommended practice for evaluating thyroid nodules (TN) with imaging features suspicious of malignancy. Although FNAB demonstrates high accuracy in discriminating TN, a significant number are classified as malignant indeterminate (MTI), which can only be fully diagnosed by post-surgical histologic evaluation. Up to 30% of FNAB findings are expected to be MTI, leading to a high rate of unnecessary hemithyroidectomies in about 75% of patients. In PTC, the most common mutation is c.T1799A in the BRAF gene (rs113488022), resulting in V600E in the B-raf protein, leading to an increase expression by altering the MAPK pathway. The aim of this study was to evaluate the efficacy of discriminating patients with malignant and benign TNs by detecting BRAF V600E in tissue from FNAB for molecular diagnosis of PTC. The qPCR technique with allele-specific probes was used to detect the BRAF c.1799T&amp;gt;A mutation in somatic DNA samples extracted by FNAB from TN (n=99) with suspected malignancy by ultrasonography. Cytologic diagnosis of biopsies was performed using the Bethesda System (TBSRTC). Diagnostic accuracy measures for evaluation of BRAF c.1799T&amp;gt;A as a diagnostic tool were performed with MedCalc software. Of the 99 patients, it was determined by cytology that 50 patients (50.51%) had PTC and 49 benign neoplasms (49.49%). The mutation was detected in 28 of the PTC samples (56%) (AA homozygotes [n=12, 24%] and AT heterozygotes [n=16, 32%). No mutation carriers were found among patients with benign neoplasms. Regarding accuracy measures were 56% for sensitivity of 56% and 100% specificity. The positive predictive value was 100% and the negative predictive value was 69.01%, with an accuracy of 77.78%. Finally, the negative likelihood ratio (LR-) value was 0.44 (95% CI: 0.32 to 0.60), while the positive likelihood ratio (LR+) value could not be calculated as there were no patients with the mutation in the group of patients with benign TN. In conclusion, our results suggest that the presence of BRAF c.1799T&amp;gt;A mutation could be indicative of PTC, confirming its usefulness in the differentiation between malignant and benign tumors. BRAF V600E detection may be valuable as an adjunct to conventional cytology, improving diagnostic accuracy and reducing the need for unnecessary surgical procedures. While highlighting the potential utility of this technique as a diagnostic tool, further analysis and consideration of other metrics is recommended for a full evaluation of its clinical relevance. Citation Format: Anette R. Gastelum-Quiroz, Andrea Ross-Orozco, Marco A. Álvarez-Arrazola, Eliakym Arambula-Meraz, Karla L. Morales-Hernández, Hanna M. Tolosa-Lerma, Fred Luque-Ortega, Paola Y. Sánchez-Aboytes, Noemí García-Magallanes. qPCR in the diagnosis of papillary thyroid cancer: Assessment of BRAF V600E mutation in FNA biopsies of thyroid nodules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB276.

Prediction performance comparison of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer.

The aim of the present study was to compare the predictive accuracy of PD-L1 immunohistochemistry (IHC), tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profile (GEP), driver gene mutation, and combined biomarkers for immunotherapy response of advanced non-small cell lung cancer (NSCLC). In part 1, clinical trials involved with predictive biomarker exploration for immunotherapy in advanced NSCLC were included. The area under the curve (AUC) of the summary receiver operating characteristic (SROC), sensitivity, specificity, likelihood ratio and predictive value of the biomarkers were evaluated. In part 2, public datasets of immune checkpoint inhibitor (ICI)-treated NSCLC involved with biomarkers were curated (N = 871). Odds ratio (OR) of the positive versus negative biomarker group for objective response rate (ORR) was measured. In part 1, the AUC of combined biomarkers (0.75) was higher than PD-L1 (0.64), tTMB (0.64), bTMB (0.68), GEP (0.67), and driver gene mutation (0.51). Combined biomarkers also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers. In part 2, the OR of combined biomarkers of PD-L1 plus TMB (PD-L1 cutoff 1%, 0.14; cutoff 50% 0.13) was lower than that of PD-L1 (cutoff 1%, 0.33; cutoff 50% 0.24), tTMB (0.28), bTMB (0.48), EGFR mutation (0.17) and KRAS mutation (0.47), for distinguishing ORR of patients after immunotherapy. Furthermore, positive PD-L1, tTMB-high, wild-type EGFR, and positive PD-L1 plus TMB were associated with prolonged progression-free survival (PFS). Combined biomarkers have superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. Further investigation is warranted to select optimal biomarkers for various clinical settings.

Long noncoding RNAs and circular RNAs as potential diagnostic biomarkers of inflammatory bowel diseases: a systematic review and meta-analysis.

Inflammatory bowel disease (IBD) poses a growing global burden, necessitating the discovery of reliable biomarkers for early diagnosis. The clinical significance of dysregulated expression of long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) in diagnosing IBD has not been well established. Thus, our study aimed to investigate the diagnostic value of lncRNAs and circRNAs for IBD based on currently available studies. A comprehensive search was carried out in diverse electronic databases, such as PubMed, Embase, Scopus, Science Direct and Wiley Online Library to retrieve articles published until October 30, 2023. Stata 17.0 software was employed to determine pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR), and area under the curve (AUC). Heterogeneity, subgroup analysis, and meta-regression were explored, and publication bias was assessed using Deeks' funnel plot. Fagan's nomogram and likelihood ratio scattergram were employed to evaluate the clinical validity. A total of 11 articles encompassing 21 studies which involved 1239 IBD patients and 985 healthy controls were investigated. The findings revealed lncRNAs exhibit high level of pooled sensitivity 0.94 (95% CI: 0.87-0.97) and specificity 0.99 (95% CI: 0.89-1.00), along with PLR, NLR, DOR, and AUC values of 64.25 (95% CI: 7.39-558.66), 0.06 (95% CI: 0.03-0.13), 1055.25 (95% CI: 70.61-15770.77), and 0.99 (95% CI: 0.97-0.99), respectively. Conversely, CircRNAs showed moderate accuracy in IBD diagnosis, with sensitivity of 0.68 (95% CI: 0.61-0.73), specificity of 0.73 (95% CI: 0.65-0.79), PLR of 2.47 (95% CI: 1.94-3.16), NLR of 0.45 (95% CI: 0.38-0.53), DOR of 5.54 (95% CI: 3.88-7.93), and AUC value of 0.75 (95% CI: 0.71-0.79). Moreover, findings from subgroup analysis depicted heightened diagnostic efficacy when employing lncRNA H19 and a large sample size (≥100), with notable efficacy in diagnosing both ulcerative colitis (UC) and Crohn's disease (CD). LncRNAs exhibit high diagnostic accuracy in distinguishing patients with IBD from healthy controls signifying their possible use as potential biomarkers, while circRNAs showed moderate diagnostic accuracy. Nevertheless, to validate our findings and confirm the clinical utility of lncRNAs and circRNAs in IBD diagnosis, a large pool of prospective and multi-center studies should be undertaken. https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023491840.

Quantitative thresholds for variant enrichment in 13,845 cases: improving pathogenicity classification in genetic hearing loss

BackgroundThe American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines recommend using variant enrichment among cases as "strong" evidence for pathogenicity per the PS4 criterion. However, quantitative support for PS4 thresholds from real-world Mendelian case–control cohorts is lacking.MethodsTo address this gap, we evaluated and established PS4 thresholds using data from the Chinese Deafness Genetics Consortium. A total of 9,050 variants from 13,845 patients with hearing loss (HL) and 6,570 ancestry-matched controls were analyzed. Positive likelihood ratio and local positive likelihood ratio values were calculated to determine the thresholds corresponding to each strength of evidence across three variant subsets.ResultsIn subset 1, consisting of variants present in both cases and controls with an allele frequency (AF) in cases ≥ 0.0005, an odds ratio (OR) ≥ 6 achieved strong evidence, while OR ≥ 3 represented moderate evidence. For subset 2, which encompassed variants present in both cases and controls with a case AF < 0.0005, and subset 3, comprising variants found only in cases and absent from controls, we defined the PS4_Supporting threshold (OR > 2.27 or allele count ≥ 3) and the PS4_Moderate threshold (allele count ≥ 6), respectively. Reanalysis applying the adjusted PS4 criteria changed the classification of 15 variants and enabled diagnosis of an additional four patients.ConclusionsOur study quantified evidence strength thresholds for variant enrichment in genetic HL cases, highlighting the importance of defining disease/gene-specific thresholds to improve the precision and accuracy of clinical genetic testing.

Dynamic Susceptibility Contrast-Enhanced Perfusion-Weighted Imaging in Differentiation Between Recurrence and Pseudoprogression in High-Grade Glioma: A Meta-analysis.

In glioma patients that have undergone surgical tumor resection, the ability to reliably distinguish between pseudoprogression (PsP) and a recurrent tumor (RT) is of key clinical importance. Accordingly, this meta-analysis evaluated the utility of dynamic susceptibility contrast-enhanced perfusion-weighted imaging as a means of distinguishing between PsP and RT when analyzing patients with high-grade glioma. The PubMed, Web of Science, and Wanfang databases were searched for relevant studies. Pooled analyses of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values were conducted, after which the area under the curve (AUC) for summary receiver operating characteristic curves was computed. This meta-analysis ultimately included 21 studies enrolling 879 patients with 888 lesions. Cerebral blood volume-associated diagnostic results were reported in 20 of the analyzed studies, and the respective pooled sensitivity, specificity, PLR, and NLR values were 86% (95% confidence interval [CI], 0.81-0.89), 83% (95% CI, 0.77-0.87), 4.94 (95% CI, 3.61-6.75), and 0.18 (95% CI, 0.13-0.23) for these 20 studies. The corresponding AUC value was 0.91 (95% CI, 0.88-0.93), and the publication bias risk was low ( P = 0.976). Cerebral blood flow-related diagnostic results were additionally reported in 6 of the analyzed studies, with respective pooled sensitivity, specificity, PLR, and NLR values of 85% (95% CI, 0.78-0.90), 85% (95% CI, 0.76-0.91), 5.54 (95% CI, 3.40-9.01), and 0.18 (95% CI, 0.12-0.26). The corresponding AUC value was 0.92 (95% CI, 0.89-0.94), and the publication bias risk was low ( P = 0.373). The present meta-analysis results suggest that dynamic susceptibility contrast-enhanced perfusion-weighted imaging represents an effective diagnostic approach to distinguishing between PsP and RT in high-grade glioma patients.

A prospective comparison of a modified miniaturised hand-held epifluorescence microscope and touch imprint cytology for evaluation of axillary sentinel lymph nodes intraoperatively in breast cancer patients.

The management of axillary lymph nodes in early-stage breast cancer patients has changed considerably, with the primary focus shifting from the examination of sentinel lymph nodes (SLNs) to toward the detection of all macro-metastases. However, current methods, such as touch imprint cytology (TIC) and frozen sections, are inadequate for clinical needs. To address this issue, we proposed a novel miniaturised epifluorescence widefield microscope (MEW-M) to assess SLN status intraoperatively for improved diagnostic efficiency. A prospective, side-by-side comparison of intraoperative SLN evaluation between MEW-M and TIC was performed. A total of 73 patients with 319 SLNs consecutive enrolled in this study. MEW-M showed significantly superior image quality compared to TIC (median score 3.1 vs 2.1, p < 0.0001) and had a shorter time to issue results (10.3 vs 19.4 min, p < 0.0001). Likelihood ratio analysis illustrated that the positive likelihood ratio value of MEW-M compared with TIC was infinitely great vs 52.37 (95% CI, 21.96-124.90) in model 1 (classifying results into negative/positive), infinitely great vs 52.37 (95% CI, 21.96-124.90) in model 2 (classifying results into macro-metastasis/others, and TIC results followed the same classification as model 1), respectively. Similarly, the negative likelihood ratio values of MEW-M compared with TIC were 0.055 (95% CI, 0.018-0.160) and 0.074 (95% CI, 0.029-0.190) in model 1; and 0.019 (95% CI, 0.003-0.130) vs 0.020 (95% CI, 0.003-0.140) in model 2, respectively. MEW-M is a promising technique that can be utilised to provide a rapid and accurate intraoperative assessment of SLN in a clinical setting to help improve decision-making in axillary surgery.

Computed Tomography-Based Predictive Model for the Probability of Lymph Node Metastasis in Gastric Cancer: A Meta-analysis.

Whether or not a gastric cancer (GC) patient exhibits lymph node metastasis (LNM) is critical to accurately guiding their treatment and prognostic evaluation, necessitating the ability to reliably predict preoperative LNM status. The present meta-analysis sought to examine the diagnostic value of computed tomography (CT)-based predictive models as a tool to gauge the preoperative LNM status of patients with GC. Relevant articles were identified in the PubMed, Web of Science, and Wanfang databases. These studies were used to conduct pooled analyses examining sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values, and area under the curve values were computed for summary receiver operating characteristic curves. The final meta-analysis incorporated data from 15 studies, all of which were conducted in China, enrolling 3,817 patients with GC (LNM+: 1790; LNM-: 2027). The developed CT-based predictive model exhibited respective pooled sensitivity, specificity, PLR, and NLR values of 84% (95% confidence interval [CI], 0.79-0.87), 81% (95% CI, 0.76-0.85), 4.39 (95% CI, 3.40-5.67), and 0.20 (95% CI, 0.16-0.26). The identified results were not associated with significant potential for publication bias ( P = 0.071). Similarly, CT-based analyses of LN status exhibited respective pooled sensitivity, specificity, PLR, and NLR values of 62% (95% CI, 0.53-0.70), 77% (95% CI, 0.72-0.81), 2.71 (95% CI, 2.20-3.33), and 0.49 (95% CI, 0.40-0.61), with no significant risk of publication bias ( P = 0.984). Overall, the present meta-analysis revealed that a CT-based predictive model may outperform CT-based analyses alone when assessing the preoperative LNM status of patients with GC, offering superior diagnostic utility.

Development of clinical criteria for the evaluation of indirect restorations.

To propose the development and validation of criteria for evaluating the clinical performance of indirect restorations, considering the variables related to the operator, material, and/or patient. The experimental design of this study was divided into three stages. Stage 1: development of the new criteria items by specialists in Prosthodontics. Step 2: creation of the criteria, named UERJ criteria, with the description of the parameters that indicate the quality of the restoration, the possible associated complications, and a detailed description of each classification. As well as the development of a form of variables. Step 3: validation of the UERJ criteria. Cohen's Kappa statistic registered for both intra- and inter-examiner agreements a coefficient >0.91 with a p-value <0.0001. The validity of the UERJ criteria was evaluated by tests of sensitivity (0.96) and specificity (0.91) and had a satisfactory accuracy (92.7%), a positive (10.99), and negative (0.05) likelihood ratio and high values predictive variables, with positive (PPV) 0.84 (high specificity) and negative (VPN) 0.98 (high sensitivity), with a confidence interval of 95%. The UERJ criteria is a valid instrument for evaluating the clinical performance of indirect restorations. The UERJ criteria, developed exclusively for the analysis of indirect restorations, elucidates the details necessary to identify the causes of failures and complications of these restorations.

The Application of a New, Modified Algorithm for the Differentiation of Regular Ventricular and Pre-excited Tachycardias.

The three-step Brugada group algorithm is the only published electrocardiographical (ECG) algorithm for differentiating ventricular tachycardia (VT) from pre-excited tachycardia (PXT) as a cause of regular wide QRS complex tachycardia (WCT). This study aimed to improve the diagnostic accuracy of the Brugada group algorithm. This study modified the Brugada group algorithm by adding a new aVR lead criterion (initial positive deflection in lead aVR and the QRS complex area above the baseline is greater than the area below the baseline). The Brugada group algorithm and the new, modified four-step algorithm in 300 WCT ECGs (241 VTs, 59 PXTs) was applied. If any of the criteria were fulfilled, VT was diagnosed; if none were fulfilled, a diagnosis of PXT was established. The test accuracy, VT diagnosis sensitivity, and negative predictive value (NPV) of the new, modified algorithm were significantly greater than that of the Brugada group algorithm: test accuracy 220 of 300 (73%) vs 182 of 300 (61%); sensitivity 73% vs 55% (p<0.001 for both); NPV 40% vs 31% (p=0.0205). The VT diagnosis specificity of the Brugada group algorithm was greater than that of the new, modified algorithm (83% vs 75%; p=0.019). There was no significant difference between the new, modified and Brugada group algorithms in the positive predictive values (92% vs 93%, respectively) for a VT diagnosis, and positive and negative likelihood ratio values (2.87 vs 3.26; 0.36 vs 0.54, respectively). The new, modified algorithm proved to be more sensitive for the differentiation of VT from PXT than the Brugada group algorithm.

Prediction models for chronic postsurgical pain in patients with breast cancer based on machine learning approaches.

This study aimed to develop prediction models for chronic postsurgical pain (CPSP) after breast cancer surgery using machine learning approaches and evaluate their performance. The study was a secondary analysis based on a high-quality dataset from a randomized controlled trial (NCT00418457), including patients with primary breast cancer undergoing mastectomy. The primary outcome was CPSP at 12 months after surgery, defined as modified Brief Pain Inventory > 0. The dataset was randomly split into a training dataset (90%) and a testing dataset (10%). Variables were selected using recursive feature elimination combined with clinical experience, and potential predictors were then incorporated into three machine learning models, including random forest, gradient boosting decision tree and extreme gradient boosting models for outcome prediction, as well as logistic regression. The performances of these four models were tested and compared. 1152 patients were finally included, of which 22.1% developed CPSP at 12 months after breast cancer surgery. The 6 leading predictors were higher numerical rating scale within 2 days after surgery, post-menopausal status, urban medical insurance, history of at least one operation, under fentanyl with sevoflurane general anesthesia, and received axillary lymph node dissection. Compared with the multivariable logistic regression model, machine learning models showed better specificity, positive likelihood ratio and positive predictive value, helping to identify high-risk patients more accurately and create opportunities for early clinical intervention. Our study developed prediction models for CPSP after breast cancer surgery based on machine learning approaches, which may help to identify high-risk patients and improve patients' management after breast cancer.

Predictive value of immature granulocyte in the diagnosis of acute complicated appendicitis.

The goal in appendicitis is early diagnosis and early treatment. Complications develop as treatment is delayed. Therefore, there is a need for fast, low-cost markers that can be diagnosed earlier. The aim of this study is to show the effectiveness of immature granulocyte (IG) level in determining the complication of acute appendicitis. In this retrospective cross-sectional study, 99 patients with acute appendicitis and 41 control groups were included in the study. Acute appendicitis patients were divided into two groups as acute simple appendicitis(n = 65) and acute complicated appendicitis(n = 34). In all groups, demographic data, immature granulocyte (IG) count(x103/μL), IG ratio (IG%), white blood cell (WBC), polymorphonuclear leukocytes (PNL), lymphocyte, monocyte, platelet, mean platelet volume (MPV), ferritin levels were recorded. The blood analyses were performed the Mindray BC6800 automated hematology analyzer using standard laboratory protocols. All statistical testing was undertaken using IBM SPSS Statistics for Mac. Compared to the acute simple appendicitis, acute complicated appendicitis patients had significantly higher levels WBC, PNL, monocyte, IG count, and IG% (p = 0.009, p = 0047, p = 0.001, p = 0.018; respectively) while there was no significant difference in ferritin between groups (p = 0.49). In the ROC analysis, AUC value was found for IG count and IG% (0.893 and 0.725, cut-off 0.005 and 0.05; respectively) for acute appendicitis. The negative predictive value of IG for Acute Appendicitis was 85% and was the same as that of WBC. In acute complicated appendicitis, the AUC for IG and IG% was 0.796 (cut-off 0.02) and 0.693 (cut-off 0.2), respectively. Positive Likelihood Ratio (+LR; 2.1) value of IG was found higher than other complete blood count (CBC) tests. The IG count is test with fast, more predictive value than another CBC tests, and without cost in the early diagnosis of acute complicated appendicitis. It is strong negative predictive test for Acute Appendicitis disease.

Diagnostic value of magnetic resonance imaging features of microvascular invasion in hepatocellular carcinoma: a meta-analysis.

PURPOSE This systematic review and meta-analysis of conventional enhanced magnetic resonance imaging (MRI) were conducted to evaluate the diagnostic performance of imaging features of microvascular invasion (MVI) prediction in hepatocellular carcinoma (HCC). METHODS Relevant studies on diagnosing MVI in HCC by MRI were searched in the MEDLINE, PUBMED, EMBASE, Cochrane library, and Web of Science databases. The pooled mean sensitivity and specificity were calculated using a random effects model. The corresponding positive likelihood ratio (PLR), negative likelihood ratio (NLR), and pooled diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic (SROC) curve was used to summarize the overall diagnostic accuracy. Diagnostic performance was evaluated by determining the area under the curve (AUC). Regression analysis by subgroup and sensitivity analysis were used to explore potential sources of heterogeneity. RESULTS A total of 19 studies comprising 1920 HCC patients with 2033 tumors were ultimately enrolled. For the signs of the presence of peritumoral enhancement in the arterial phase, peritumoral hypointensity in the hepatobiliary phase, irregular non-smooth margin, and rim-like enhancement in the arterial phase, the pooled sensitivity values, the pooled specificity values, the pooled PLR values, the pooled NLR values, the pooled DOR values, and the values of the AUC of SROC curves were determined. CONCLUSION The conventional MRI features for predicting MVI showed poor diagnostic performance in HCC. Only signs of the presence of peritumoral enhancement in the arterial phase showed a moderate diagnostic accuracy.

Prediction of the Presence of Targetable Molecular Alteration(s) with Clinico-Metabolic 18 F-FDG PET Radiomics in Non-Asian Lung Adenocarcinoma Patients.

This study aimed to investigate if combining clinical characteristics with pre-therapeutic 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET) radiomics could predict the presence of molecular alteration(s) in key molecular targets in lung adenocarcinoma. This non-interventional monocentric study included patients with newly diagnosed lung adenocarcinoma referred for baseline PET who had tumour molecular analyses. The data were randomly split into training and test datasets. LASSO regression with 100-fold cross-validation was performed, including sex, age, smoking history, AJCC cancer stage and 31 PET variables. In total, 109 patients were analysed, and it was found that 63 (57.8%) patients had at least one molecular alteration. Using the training dataset (n = 87), the model included 10 variables, namely age, sex, smoking history, AJCC stage, excessKustosis_HISTO, sphericity_SHAPE, variance_GLCM, correlation_GLCM, LZE_GLZLM, and GLNU_GLZLM. The ROC analysis for molecular alteration prediction using this model found an AUC equal to 0.866 (p < 0.0001). A cut-off value set to 0.48 led to a sensitivity of 90.6% and a positive likelihood ratio (LR+) value equal to 2.4. After application of this cut-off value in the unseen test dataset of patients (n = 22), the test presented a sensitivity equal to 90.0% and an LR+ value of 1.35. A clinico-metabolic 18 F-FDG PET phenotype allows the detection of key molecular target alterations with high sensitivity and negative predictive value. Hence, it opens the way to the selection of patients for molecular analysis.

Screening chronic myeloid leukemia neutrophils using a novel 3-Dimensional Spectral Gradient Mapping algorithm on hyperspectral images

Background and objective Early diagnosis of chronic myeloid leukemia (CML) is important for effective treatment. The high spectral and spatial resolution of hyperspectral cellular or tissue images coupled with image analysis algorithms may provide avenues to detect and diagnose diseases early. Many algorithms have been used to analyze medical hyperspectral image data, each having their own strengths and short-comings. We present a novel 3-Dimensional Spectral Gradient Mapping (3-D SGM) method to analyze hyperspectral image cubes of CML versus healthy blood smears.Methods In the present study, we analyzed 13 hyperspectral image cubes of CML and healthy neutrophils. The 3-D SGM algorithm was compared to the conventional Windowed Spectral Angle Mapping (Windowed SAM) method. The 3-D SGM exploited the spectral information of the image cube together with the inter-band and inter-pixel data by extracting the 3-D gradient vector from each pixel. The Windowed SAM determined the similarity between the averaged window of a 2×2 training pixel group and the test pixel, in the multidimensional spectral angle.Results The specificity measure of 3-D SGM (97.7%) was superior to Windowed SAM (72.7%) at ruling out the presence of the disease, making it potentially ideal for screening patients. The positive likelihood ratio value of 3-D SGM (16.70) was superior in diagnosing the presence of the disease (i.e., positive test for CML) versus Windowed SAM (2.26). An accuracy value of 84.2% was achieved with 3-D SGM versus only 70.2% for Windowed SAM.Conclusion The new method is efficient and robust for analyzing hyperspectral images of CML versus healthy neutrophils. It has the potential to be developed into an inexpensive, minimally invasive method for screening CML, and could directly facilitate early diagnosis and treatment of the disease.

Accuracy of 18F-FDG PET/CT in patients with the suspicion of cardiac implantable electronic device infections

BackgroundUtility of 18F-FDG PET/CT in diagnosing infective endocarditis (IE) associated with cardiac implantable electronic devices (CIEDs) is not well established. Current ESC guidelines recommend the use of FDG-PET imaging in patients with CIEDs and positive blood cultures, but the number of studies evaluating the diagnostic performance of FDG-PET imaging in these patients remain limited. Our objective was to assess the diagnostic yield of 18F-FDG PET/CT in patients with suspected CIED infections, differentiating between pocket infection (PI) and lead infection (CIED-IE). Methods and ResultsFrom 2013 to 2018, all patients (n = 63) admitted to a hospital with suspected CIED infection were prospectively recruited, undergoing a diagnostic work-up including a PET/CT. Explanted devices and material from the pocket were cultured. 14 cases corresponded to isolated PI and 13 were categorized as CIED-IE. Considering radionuclide uptake in the intracardiac portion of the lead, sensitivity and specificity of PET/CT for CIED-IE were 38.5% and 98.0%, respectively. Positive (19.2) and negative (0.6) likelihood ratio values, suggest that a positive PET/CT is much more probable to correspond to a patient with CIED-IE, whereas it is not possible to exclude this diagnosis when negative. For PI, sensitivity and specificity were 72.2% and 95.6%, respectively. ConclusionsThe yield of 18F-FDG PET/CT for suspected CIED infections differs depending on the site of infection. Due to very high specificity but poor sensitivity, negative studies must be interpreted with caution if the suspicion of CIED-IE is high.