Positive Likelihood Ratio Research Articles

The performance of machine learning for predicting the recurrent stroke: a systematic review and meta-analysis on 24,350 patients.

Stroke is a leading cause of death and disability worldwide. Approximately one-third of patients with stroke experienced a second stroke. This study investigates the predictive value of machine learning (ML) algorithms for recurrent stroke. This study was prepared according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. PubMed, Scopus, Embase, and Web of Science (WOS) were searched until January 1, 2024. The quality assessment of studies was conducted using the QUADAS-2 tool. The diagnostic meta-analysis was conducted to calculate the pooled sensitivity, specificity, diagnostic accuracy, positive and negative diagnostic likelihood ratio (DLR), diagnostic accuracy, diagnostic odds ratio (DOR), and area under of the curve (AUC) by the MIDAS package in STATA V.17. Twelve studies, comprising 24,350 individuals, were included. The meta-analysis revealed a sensitivity of 71% (95% CI 0.64-0.78) and a specificity of 88% (95% confidence interval (CI) 0.76-0.95). Positive and negative DLR were 5.93 (95% CI 3.05-11.55) and 0.33 (95% CI 0.28-0.39), respectively. The diagnostic accuracy and DOR was 2.89 (95% CI 2.32-3.46) and 18.04 (95% CI 10.21-31.87), respectively. The summary ROC curve indicated an AUC of 0.82 (95% CI 0.78-0.85). ML demonstrates promise in predicting recurrent strokes, with moderate to high sensitivity and specificity. However, the high heterogeneity observed underscores the need for standardized approaches and further research to enhance the reliability and generalizability of these models. ML-based recurrent stroke prediction can potentially augment clinical decision-making and improve patient outcomes by identifying high-risk patients.

Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy.

To evaluate the diagnostic accuracy of machine learning models incorporating multimodal features for predicting radiation pneumonitis in lung cancer through a systematic review and meta-analysis. Relevant studies were identified through a systematic search of PubMed, Web of Science, Embase, and the Cochrane Library from October 2003 to December 2023. Additional studies were located by reviewing bibliographies and relevant websites. Two independent researchers screened titles, abstracts, and full-text articles according to predefined inclusion and exclusion criteria. Data extraction was performed using standardized forms, and study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The primary outcomes, including combined sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC), were calculated using STATA MP-64 software(Stata Corporation LLC, College Station, USA) with a random-effects model. Meta-analysis was conducted to synthesize diagnostic accuracy measures, and analyses of heterogeneity and publication bias were performed. A total of 1,406 patients with primary lung cancer were included in this systematic review, drawing data from 9 studies. The pooled analysis revealed a sensitivity of 0.74 [0.58-0.85] and a specificity of 0.91 [0.87-0.95] for machine learning models in diagnosing radiation pneumonitis. The positive likelihood ratio (PLR) was 8.69 [5.21-14.50], the negative likelihood ratio (NLR) was 0.28 [0.16-0.49], and the diagnostic odds ratio (DOR) was 30.73 [11.96-78.97]. The area under the curve (AUC) was 0.93 [0.90-0.95], indicating excellent diagnostic performance. Meta-regression analysis identified that the number of machine learning models, year of publication, and study design contributed to heterogeneity among studies. No evidence of publication bias was found. Overall, machine learning models incorporating multimodal characteristics demonstrated 75% accuracy in predicting moderate to severe radiation pneumonitis. In conclusion, by integrating the current machine learning (ML) algorithm's ability in big data mining, a predictive model can be constructed by combining multi-modal features such as genetics, imaging, and cell factors. By selecting multiple machine learning algorithm frameworks and competing for the best combination model based on research goals, the reliability and accuracy of the radiation pneumonitis prediction model can be greatly improved. PROSPERO (CRD42024497599).

Risk-stratification tools for emergency department patients with syncope: A systematic review and meta-analysis of direct evidence for SAEM GRACE.

Approximately 10% of patients with syncope have serious or life-threatening causes that may not be apparent during the initial emergency department (ED) assessment. Consequently, researchers have developed clinical decision rules (CDRs) to predict adverse outcomes and risk stratify ED syncope patients. This systematic review and meta-analysis (SRMA) aims to cohere and synthesize the best current evidence regarding the methodological quality and predictive accuracy of CDRs for developing an evidence-based ED syncope management guideline. We conducted a systematic literature search according to the patient-intervention-control-outcome question: In patients 16 years of age or older who present to the ED with syncope for whom no underlying serious/life-threatening condition was found during the index ED visit (population), are risk stratification tools (intervention), better than unstructured clinical judgment (i.e., usual care; comparison), for providing accurate prognosis and aiding disposition decision for outcomes within 30 days (outcome)? Two reviewers independently assessed articles for inclusion and methodological quality. We performed statistical analysis using Meta-DiSc. We used GRADEPro GDT software to determine the certainty of the evidence and create a summary of the findings (SoF) tables. Of 2047 publications obtained through the search strategy, 31 comprising 13 CDRs met the inclusion criteria. There were 13 derivation studies (17,578 participants) and 24 validation studies (14,845 participants). Only three CDRs were validated in more than two studies. The San Francisco Syncope Rule (SFSR) was validated in 12 studies: positive likelihood ratio (LR+) 1.15-4.70 and negative likelihood ratio (LR-) 0.03-0.64. The Canadian Syncope Risk Score (CSRS) was validated in five studies: LR+ 1.15-2.58 and LR- 0.05-0.50. The Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL) risk score was validated in five studies: LR+ 1.16-3.32 and LR- 0.14-0.46. Most CDRs for ED adult syncope management have low-quality evidence for routine clinical practice use. Only three CDRs (SFSR, CSRS, OESIL) are validated by more than two studies, with significant overlap in operating characteristics.

Added value in low-risk pregnancies of longitudinal changes in uterine Doppler and circulating angiogenic factors during the third trimester in predicting term preeclampsia.

To assess the relationship between longitudinal changes in the uterine Doppler velocimetry and the maternal profile of angiogenic factors in the third trimester of pregnancy and to assess their ability to predict term preeclampsia. A cohort of low-risk pregnant women was constructed at second trimester routine scan and scheduled for a uterine Doppler evaluation and measurement of the circulating levels of angiogenic factors at ~30 and ~36 weeks. The performance of both parameters at both time-points and their change over time from the first to the second measurement in predicting term preeclampsia was evaluated by logistic regression and receiver operating characteristic curve (ROC) analyses. A total of 1172 women were analyzed, of which 28 (2.4%) women developed term preeclampsia. At ~30 weeks, a model including the ratio sFlt-1/PlGF (fms-like tyrosine kinase-1/placental growth factor) and the uterine Doppler explained 16.2% of the uncertainty of developing term preeclampsia, while at ~36 weeks the same variables explained 25.2% [p<0.001]. A model including the longitudinal changes of both predictors had an R2 of 26.8%, which was not significantly different from that of the ~36 weeks evaluation [p=0.45]. The area under the curve (AUC) of the ~36 weeks sFlt-1/PlGF ratio was significantly higher than at ~30 weeks (0.86 [0.77-0.94] vs. 0.81 [0.73-0.9]; p=0.043). The AUC of the 30-to-36 week change of the sFlt-1/PlGF ratio (0.85 [0.77-0.94]) did not significantly differ from that of at ~36 weeks (p=0.82). At ~36 weeks, for a 10% of false positives, the sFlt-1/PlGF ratio had a detection rate of 71.4%, with positive and negative likelihood ratios of 7.3 and 0.32, respectively. A cross-sectional measurement of the sFlt-1/PlGF ratio outperforms uterine Doppler in predicting term preeclampsia. The combination of both markers does not improve such prediction, nor the evaluation of the longitudinal changes between ~30 and ~36 weeks.

Clinical Performance of an N-Terminal Pro-B-Type Natriuretic Peptide Assay in Acute Heart Failure Diagnosis.

We evaluated the Vitros® Immunodiagnostic Products N-terminal pro B-type natriuretic peptide (NT-proBNP) II assay for aiding in diagnosis of heart failure (HF) in patients with acute dyspnea. Serum concentrations of NT-proBNP were measured in patient samples from 20 emergency departments across the United States. Study endpoints included sensitivity, specificity, likelihood ratios, and predictive values for diagnosis of acute HF according to age-stratified cutoffs (450, 900, and 1800 pg/mL), and a rule-out age-independent cutoff (300 pg/mL). Additional measures were area under the curve (AUC) for receiver operating characteristic (ROC) curves. Results were also interpreted in patient subgroups with relevant comorbidities, and gray zone/intermediate assay values. Of 2200 patients, 1095 (49.8%) were diagnosed with HF by clinical adjudication. Sensitivity and specificity for Vitros NT-proBNP II ranged from 84.0% to 92.1%, and 81.4% to 86.5%, respectively, within and across age groups, and positive predictive values were 80.4% to 85.7%. Using the rule-out cutoff, the negative predictive value was 97.9%, with a negative likelihood ratio of 0.02. In subgroups with comorbidities potentially affecting NT-proBNP concentrations, sensitivities ranged from 82.6% to 89.5%, and AUCs for ROC curves were 0.899 to 0.915. The Vitros NT-proBNP II assay demonstrated excellent clinical performance using age-stratified cutoffs along with other clinical information for supporting diagnosis of HF, and can rule out HF with a high negative predictive value using the age-independent cutoff. The assay retained utility in patient subgroups with conditions that influence NT-proBNP concentration, and for those with gray zone results. NCT03548909.

Predictive nomograms and an algorithm for managing patients with probable Meniere's disease

PurposeTo explore the efficacy of diagnostic tests in accurately reclassifying patients initially diagnosed with probable Meniere's disease (MD) into either definite or non-MD categories. Materials and methodsA retrospective cohort study was conducted at a neurotology clinic between 1/2016 and 5/2022. Patients underwent a battery of tests, from which sensitivity, specificity, positive and negative predictive values, as well as positive and negative likelihood ratios, were calculated. Additionally, prediction nomograms were developed. ResultsOf the 69 patients, 25 (36.2 %) were initially classified as definite MD, 21 (30.4 %), probable MD, and 23 (33.4 %) non-MD. The mean follow-up was 3.5 years. The sensitivity of electrocochleography (ECochG) was the highest (92 %), with a negative likelihood ratio of 15 %. Magnetic resonance imaging (MRI) with MD-protocol had the highest specificity (100 %), with a positive likelihood ratio of 100 %. Videonystagmography, video head impulse test, and cervical vestibular-evoked myogenic potentials, had lower sensitivity and specificity. We were able to reclassify 18 (86 %) patients with probable MD: 12 (57 %) were diagnosed with definite MD, and 6 (29 %) were diagnosed with non-MD, consistent with their clinical course. ConclusionsThe combination of ECochG and MRI with MD-protocol provides the most reliable approach to reclassify patients with Probable MD, ensuring a precise and accurate diagnosis. Vestibular tests express the functional status of the labyrinth and may not be reliable. Our findings provide valuable insights into clinical decision-making for patients with Probable MD and raise the consideration of additional diagnostic tests as supplementary to the existing clinical-only diagnosis criteria.

Accuracy of second and third molar maturity indices, Olze, Haavikko, and Demirjian methods for 14- and 16-year-old age thresholds assessment in Croatian children and adolescents.

This study explores the reliability of four established legal age threshold estimation approaches in a Croatian sample. We applied Haavikko stages, Demirjian stages, Olze's third molar eruption stages, and second and third molar maturity indices measurement in 593 orthopantomograms of Croatian children and adolescents aged 11.00-20.99years old. The left mandibular second and third molar were assessed. Logistic regression analysis was conducted to test the significance of predictive variables. Logistic Receiver operating characteristic (ROC) curves were performed to evaluate the classification ability of variables for estimating 14- and 16-year-old thresholds. The areas under the ROC curve (AUC), accuracy (Acc), sensitivity (Se), specificity (Sp), Positive Likelihood Ratio (LR +), Negative Likelihood Ratio (LR-), and Bayes post-test probability (Bayes PTP) were calculated to evaluate classification performance. Results suggest that the combination of I2M&I3M is the best classifier for the 14-year-old threshold (AUC = 0.879); for males alone, I2M is an even better classifier (AUC = 0.881). The highest Acc 80.1% (95%CI, 75.9%-83.9%), Bayes PTP 86.5% (95%CI, 82.8%-89.7%) and Sp 88.9% (95%CI, 83.0%-93.3%) were by I3M < 0.81 & I2M < 0.03 in total samples; the highest Acc 86.1% (80.6%- 90.6%), Bayes PTP 87.2% (95%CI, 81.7%- 91.4%) and Sp 87.8% (95%CI, 78.2%- 94.3%) were by I2M < 0.01 in males, Acc of Haavikko Ac and Demirjian H stage in second molar is very close with slightly lower Bayes PTP and Sp. I3M is a good classifier for 16-year-old threshold (AUC = 0.889). The cut-off value I3M < 0.34 can be used to classify the 16-year-old threshold with Acc of 80.6% (95%CI, 77.2%-83.7%), Sp of 83.4% (95%CI, 79.0%-87.3%), and 81.7% (95%CI, 78.4%-84.8%) Bayes PTP. In conclusion, to classify the 14-year-old threshold, a pair of cut-off values I3M < 0.81 & I2M < 0.03 can be used in Croatian females; I2M < 0.01, Demirjian H stage, Haavikko Ac stage in second molar, and the pair I3M < 0.81 & I2M < 0.03 can all be used in Croatian males. I3M < 0.34 can classify the 16-year-old threshold in Croatian populations.

Does the high-intensity zone of lumbar intervertebral disc at magnetic resonance imaging have diagnostic value for discogenic low back pain? A meta-analysis

ObjectiveThe correlation between high-intensity zone (HIZ) of lumbar disc magnetic resonance imaging (MRI) and discogenic low back pain (DLBP) is currently controversial, this study aimed to systematically evaluate the correlation between HIZ of lumbar disc MRI and positive discography, as well as its diagnostic value for DLBP.MethodDatabases were searched to include research literature on high intensity zone (HIZ) related to discography and DLBP diagnosis. HIZ is a separate small, confined area of high signal located at the posterior border of the annulus fibrosus on MRI T2-weighted images of the lumbar spine, which is separated from the nucleus pulposus but has a higher signal than the nucleus pulposus. Studies on the correlation of HIZ with discography and DLBP diagnosis were searched in the Pubmed, EMBASE, Cochrane Central, Science Direct, China Knowledge Network, Wanfang Database, and China Biomedical Literature Databases, Scopus from January 1992 to June 2024. The outcomes were diagnostic values of HIZ for DLBP. The risk assessment was performed by Deeks’ funnel methods in the Stata 17.0 software after 2 investigators independently screened the literature, extracted information and evaluated the risk of bias of the included studies.ResultsA total of 25 studies including 5889 patients were included. meta-analysis showed that the sensitivity of HIZ for the diagnosis of DLBP was (0.49, 95% CI [0.37,0.61]) and specificity was (0.89, 95% CI [0.85,0.93]); the positive likelihood ratio was (4.52, 95% CI [3.28,6.25]) and the negative likelihood ratio was (0.58, 95% CI [0.46,0.71]). The diagnostic ratio was (7.87, 95% CI [5.05,12.26]).ConclusionThe available evidence suggests that HIZ has acceptable sensitivity and high specificity in the diagnosis of DLBP. Due to the limitation of the number and quality of included studies, the above conclusions need to be validated by more high-quality studies.

Prostate-Specific Antigen (PSA) as a Predictor of Prostate Cancer on Transrectal Biopsy: A Meta-Analysis

Prostate cancer is a leading cause of cancer-related death in men globally. Early detection is critical for improving patient outcomes. Prostate-specific antigen (PSA) testing is a widely used screening tool, but its accuracy in predicting prostate cancer on transrectal biopsy remains a topic of debate. This meta-analysis aims to evaluate the diagnostic accuracy of PSA in predicting prostate cancer on transrectal biopsy. A systematic search of electronic databases (PubMed, Scopus, Web of Science) was conducted to identify relevant studies published between 2013 and 2024. Studies reporting the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of PSA for predicting prostate cancer on transrectal biopsy were included. Data were extracted, and the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated using a random-effects model. Six studies met the inclusion criteria, comprising a total of 1,245 patients. The pooled sensitivity and specificity of PSA for predicting prostate cancer on transrectal biopsy were 0.77 (95% CI, 0.75 - 0.82) and 0.68 (95% CI, 0.62-0.73), respectively. The pooled PLR, NLR, and DOR were 3.27 (95% CI, 2.45-4.37), 0.20 (95% CI, 0.14-0.28), and 16.39 (95% CI, 10.27-26.21), respectively. The pooled AUC was 0.87 (95% CI, 0.84-0.90). In conclusion, PSA demonstrates good diagnostic accuracy in predicting prostate cancer on transrectal biopsy. However, it is essential to consider its limitations, including false positives and negatives. Further research is needed to identify strategies to improve the accuracy of PSA testing and reduce unnecessary biopsies.

The Evidence Base for Circulating Tumor DNA-Methylation in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Background: Non-Small Cell Lung Cancer (NSCLC) remains a challenging disease to manage with effectiveness. Early detection and precise monitoring are crucial for improving patient outcomes. Circulating tumor DNA (ctDNA) offers a non-invasive cancer detection and monitoring method. Emerging biomarkers, such as ctDNA methylation, have shown promise in enhancing diagnostic accuracy and prognostic assessment in NSCLC. In this review, we examined the current evidence regarding ctDNA methylation’s role in NSCLC detection through a systematic review of the existing literature and meta-analysis. Methods: We systematically searched PubMed, Medline, Embase, and Web of Science databases up to 26 June 2024 for studies on the role of ctDNA methylation analysis in NSCLC patients. We included studies from 2010 to 2024 on NSCLC patients. We excluded case reports, non-English articles, studies on cell lines or artificial samples, those without cfDNA detection, prognostic studies, and studies with non-extractable data or mixed cancer types. Funnel plots were visually examined for potential publication bias, with a p value &lt; 0.05 indicating bias. Meta-analysis was conducted using R packages (meta, forestplot, and mada). Combined sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), positive and negative predictive values, diagnostic odds ratio (DOR), and 95% confidence intervals (95% CI) were calculated. A summary receiver operating characteristic curve (SROC) and area under the curve (AUC) with related Standard Error (SE) were used to evaluate the overall diagnostic performance. Additionally, RASSF1A, APC, SOX17, SEPT9, and RARβ2 were analyzed, since their methylation was assessed in two or more studies. Results: From 38 candidate papers, we finally identified 12 studies, including 472 NSCLC patients. The pooled sensitivity was 0.62 (0.47–0.77) and the specificity was 0.90 (0.85–0.94). The diagnostic odds ratio was 15.6 (95% CI 9.36–26.09) and the area under the curve was 0.249 (SE = 0.138). The positive and negative predictive values were 5.38 (95% CI 3.89–7.44) and 0.34 (95% CI 0.22–0.54), respectively. For single genes, the specificity reached 0.83~0.96, except for RARβ2, but the sensitivity was relatively low for each gene. Significant heterogeneity across the included studies, the potential publication bias for specificity (p = 0.0231), and the need to validate the clinical utility of ctDNA methylation for monitoring treatment response and predicting outcomes in NSCLC patients represent the main limitations of this study. Conclusions: These results provide evidence of the significant potential of ctDNA methylation as a valuable biomarker for improving the diagnosis of NSCLC, advocating for its integration into clinical practice to enhance patient management.

Predictive performance of cerebrospinal fluid parameters for diagnosis of meningitis in infants: a cohort study

BackgroundThe gold standard for diagnosis of meningitis is the isolation of a pathogen from cerebrospinal fluid (CSF) by culture or PCR. However, treatment is routinely commenced based on CSF findings prior to microbiological results. This study determined the predictive value of CSF parameters for diagnosing bacterial and viral meningitis in young infants.MethodsMulticentre retrospective (2010–2020) cohort study of 1088 CSF results from infants aged 0–90 days. The predictive value of CSF parameters (white blood cell count (WCC), neutrophil, protein, glucose) was evaluated in 538 meningitis cases (39 bacterial, 499 viral) compared with controls with negative CSF microbiological testing and no prior antibiotics.ResultsFor bacterial meningitis, the sensitivity of the commonly used CSF WCC cut-off of 20×106/L for neonates, 15×106/L for infants 1–2 months old and 5×106/L for infants 2–3 months old was 89%, 91% and 86% and the specificity was 78%, 77% and 61%, respectively. CSF protein levels ≥1 g/L in neonates and ≥0.8 g/L in infants aged 1–3 month, or CSF neutrophils ≥2×106/L, independently increased the likelihood of bacterial meningitis (positive likelihood ratios ≥5 and ≥3, respectively). 3 of 39 cases of bacterial meningitis would have been missed using the commonly used WCC cut-offs alone. However, two would have been identified using CSF protein and neutrophil thresholds. All CSF parameters were poor at identifying viral meningitis.ConclusionA single CSF parameter cannot reliably diagnose bacterial meningitis. For identification of bacterial meningitis, elevation of CSF WCC, neutrophil count or protein levels above threshold values improves accuracy of diagnosis.

Validating Simple Modifications to the Rome IV Criteria for the Diagnosis of Irritable Bowel Syndrome in Secondary Care.

The Rome IV criteria for irritable bowel syndrome (IBS) may be too restrictive for clinical practice and research. To validate the Rome IV criteria and study the diagnostic performance of simple modifications to them. We collected symptom data from consecutive adults with suspected IBS seen in a single clinic. We used a reference standard to confirm IBS (presence of lower abdominal pain associated with altered stool form or frequency; no evidence of organic gastrointestinal disease after limited investigation). We applied Rome IV criteria, but also two modifications. First, we re-incorporated abdominal discomfort but kept symptom frequency required for both abdominal pain and discomfort to at least 1 day per week. Second, we included only abdominal pain but relaxed symptom frequency back to 3 days per month. We calculated sensitivity, specificity and positive and negative likelihood ratios (LRs), with 95% confidence intervals (CIs), for each diagnostic criterion. We recruited 170 patients (76.5% female, mean age 37.9 years). Sensitivity and specificity of the Rome IV criteria were 82.1% and 85.1%, respectively; positive and negative LRs were 5.51 (95% CI 2.95-11.3) and 0.21 (95% CI 0.14-0.31), respectively. Modifying the criteria by relaxing the frequency of abdominal pain to 3 days per month led to the best performance [sensitivity 90.2%, specificity 85.1%, positive LR 6.06 (95% CI 3.25-12.2), and negative LR 0.11 (95% CI 0.07-0.19)]. The Rome IV criteria performed well in diagnosing IBS. A simple modification relaxing the required frequency of abdominal pain improved their performance.

Exploring the Discriminant Validity of the Modified Arm Care Screen (MACS), Designed for Overhead Athletes, in Detecting Musculoskeletal Risk Factors in the General Population

Background: Shoulder pain is the third most common musculoskeletal issue in primary care, affecting up to 50% of patients six months post-consultation, leading to significant functional impairments and societal costs, especially due to sick leave. Shoulder injuries are particularly prevalent among ‘overhead athletes’ in sports like swimming, volleyball, and handball, with high injury rates reported annually. Screening tools like the Arm Care Screen (ACS) have been used to effectively identify athletes at risk of shoulder injuries. However, their applicability to the general population is less understood. This study aimed to assess the discriminant validity of a modified ACS (MACS) in detecting musculoskeletal risk factors among non-athletes. Methods: A prospective cross-sectional study was conducted with 30 asymptomatic subjects over 18, excluding those with a history of shoulder injuries or surgeries. The MACS, comprising four tests, was administered, and its diagnostic performance was evaluated through sensitivity, specificity, predictive values, and likelihood ratios. Results: The results indicated low sensitivity (0–47.62%) and variable specificity (55.56–100%), suggesting that the MACS may not effectively identify risk factors in the general population. Positive and negative predictive values were inconsistent (ranging from 0 to 100), as well as positive and negative likelihood ratios (ranging from 0 to 3.47), highlighting the need for non-athlete-specific screening tools. Conclusion: While the MACS shows promise in athletes, its application in the general population requires further refinement. This study underscores the necessity for tailored screening methods to enhance the early detection and prevention of musculoskeletal issues in diverse populations.

Meta-analysis of the diagnostic value of exosomal microRNAs in renal cell carcinoma

AimThis meta-analysis aims to evaluate the potential of exosomal microRNAs(Exo-miRs) as diagnostic biomarkers for renal cell carcinoma(RCC).MethodsClinical studies reporting the use of Exo-miRs in the diagnosis of RCC were retrieved from PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Chinese Biomedical Literature Database (SinoMed). After relevant data were screened and extracted, the quality of the included studies was assessed using the QUADAS-2 tool. The Meta-disc (version 1.4) software was used to analyze the heterogeneity of threshold/non-threshold effects in the included studies. The Stata MP (version 16.0) software was used to calculate sensitivity(Sen), specificity(Spe), positive likelihood ratio(+LR), negative likelihood ratio(-LR), area under the curve(AUC), diagnostic odds ratio(DOR), and publication bias.ResultsA total of 11 studies were included in this meta-analysis. Spearman correlation coefficient was 0.319 (P = 0.075; &amp;gt;0.05), indicating no threshold effects. The pooled Sen, Spe, +LR, -LR, DOR, and AUC were 0.73 (95% CI, 0.68–0.78), 0.81 (95% CI, 0.76–0.85), 3.80 (95% CI, 3.02–4.77), 0.33 (95% CI, 0.28–0.40), 11.48 (95% CI, 8.27–15.95), and 0.84 (95% CI, 0.80–0.87), respectively. No publication bias was detected among the included studies.ConclusionThe expression of Exo-miRs plays an important role in the diagnosis of RCC. However, owing to the limited number of included studies and heterogeneity among them, further clinical research is necessary to verify the findings of this meta-analysis.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42023445956.

Excluding significant coronary artery disease in patients planned for TAVR using CT: Diagnostic accuracy of newest generation dual source photon counting scanner compared to coronary angiography

Abstract Introduction Patients with significant aortic stenosis routinely undergo CT for evaluation of the aortic root prior to interventional aortic valve replacement (TAVR). Assessment of CAD is usually performed by invasive coronary angiography. We assessed the diagnostic accuracy of the latest generation dual source photon counting scanner for exclusion of relevant CAD in a contemporary TAVR cohort. Methods Patients referred for cardiac CT prior to transcatheter aortic valve implantation were screened for inclusion this analysis. All cardiac CT exams were performed by dual source photon counting scanner (NAEOTOM alpha, Siemens healthineers, Germany). CT acquisitions were performed using retrospectively triggered spiral acquisition (30-70% of the cardiac cycle) without ultra-high resolution. For each patient, several reconstructions were rendered (thin slice reconstruction with 0.4 mm slice thickness: best diastolic phase, best systolic phase, 200-350 ms folllowing R-wave in 50 ms intervals as well as 0.6 mm slice thickness multiphase reconstruction 0-90% of the cardiac cycle in 10 % increments). Assessment of significant CAD was performed in CT and invasive angiography on a per-vessel analysis and a per-patient analysis using 2 thresholds: ≥ 50% stenosis and ≥ 70% stenosis. Assessment of stenoses in CT was performed using multiplanar reconstructions (MPR) and curved MPR and only in vessels &amp;gt; 1.5mm diameter. Assessment of stenosis in invasive angiography was performed using the projection with the most relevant lumen reduction. Image quality in CT was assessed on a likert scale from 1 to 4 (1=excellent, 2=minor artifacts, 3=major artifacts still assessable, 4=non-assessable). Results In this analysis 31 consecutive patients were included (mean age 79.5y, 64.5% males, 35.5% females). Mean heart rate was 66.5 bpm and 19% were in atrial fibrillation during CT acquisition. Mean image quality was 1.4. 13 Patients had no relevant CAD (stenosis ≥50%) in invasive angiography and in 18 patients at least 1 vessel was deemed to have ≥ 50% stenosis in invasive angiography. On a per vessel analysis, sensitivity, specificity and accuracy of cardiac CT to exclude stenoses using 50% and 70% thresholds were 98%, 93% and 94% vs. 97%, 93% and 94%, respectively. Negative likelihood ratio was 0.02 vs. 0.03 respectively. On a per-patient level, sensitivity and specificity were 100%. Out of 31 patients, only 2 vessels in 2 patients were deemed non-assessable. 3 patients with previous PCI as well as 3 patients with previous CABG were included in this analysis. Only 1 false negative vessel was reported in a very distal LAD segment. Conclusion Using newest generation dual source CT with photon counting, CT allowed highly reliable diagnostic workup regarding the presence of CAD in this TAVR cohort. The use of CT to assess CAD in TAVR patients seems clinically feasible especially in patients without previous percutaneous revascularisation.

Sex-specific syncope characteristics in the early diagnosis of cardiac syncope

Abstract Background The Lancet women and cardiovascular disease commission requested evaluating sex-specific approaches in the diagnosis and management of acute cardiovascular disease. Purpose We aimed to explore 1) the utility of sex-specific syncope characteristics in the early diagnosis of cardiac syncope 2) sex-related differences in the management and outcomes of patients with a cardiac syncope. Methods Thirty-one syncope characteristics were prospectively assessed in women and men presenting with syncope to the emergency department (ED) in an international multicenter study. The final diagnosis of cardiac syncope was centrally adjudicated by two independent cardiologists. Sex-specific differences in the prevalence of syncope characteristics and their positive likelihood ratio (pLR) for cardiac syncope were the primary diagnostic endpoints. Sex-specific differences in hospital admission, diagnostic procedures performed in patients with a cardiac syncope and adverse events in patients directly discharged from the ED during one-year follow-up were secondary endpoints. Results Among 2661 patients (median age 71 years, 1099 women and 1562 men), 14.6% of women and 18.2% of men (p=0.02) were adjudicated to have a cardiac syncope. Eleven syncope characteristics showed diagnostic utility (statistically significant pLRs) in assessing cardiac syncope in the overall population. However, none of the syncope characteristics demonstrated significant sex interaction. Women adjudicated as having a cardiac syncope were as likely to be hospitalized as men (OR 1.12; 95% CI: 0.61-2.08, p=0.7) and to receive telemetry (40% vs 41%, p=0.9), ergometry (3.1% vs 6.3%, p=0.4), a holter (21% vs 17%, p=0.3), a loop recorder (0.6% vs 3.9%, p=0.06) and an echocardiogram (69% vs 65%, p=0.4). Among the 591 women and 796 men directly discharged from the ED, 18 women (3%) and 36 men (5%) were finally adjudicated as cardiac syncope. Noteworthy, within this cardiac syncope subgroup, 28% of women experienced major adverse cardiac events (MACE) during the 365-day follow-up period, in comparison to 67% men (OR 0.20; 95% CI: 0.06-0.68, p=0.011, Figure). Conclusion Syncope characteristics contributed to the early diagnosis of cardiac syncope, however, none had a significant sex interaction. Women with a cardiac syncope had a similar likelihood of being hospitalized and receiving diagnostic testing. Compard to men, women had a significantly decreased risk of MACE when not hospitalized after a cardiac syncope.Kaplan-Meier curves for 1 year MACE

SMART-2D: a novel scoring system to predict non diagnostic exercise stress echocardiography in renal transplant candidates

Abstract Background Exercise stress echocardiography (ESE) is often used for pre-renal transplant risk stratification. Nearly 20% of ESE may be non-diagnostic, resulting in delays to transplant and increased healthcare cost. A simple, reliable tool for predicting non-diagnostic ESE may streamline assessment. Methods Retrospective analysis of 898 kidney transplant candidates between 2013-2020 who underwent exercise stress echocardiography for pre-transplant cardiovascular assessment was performed. The cohort was separated into a derivation and validation set. Multivariable logistic regression identified predictors of non-diagnostic ESE. Covariates associated with non-diagnostic ESE (p&amp;lt;0.10) on univariate analysis were included in the multivariable model. From this model, only variables with p&amp;lt;0.05 were included for score development. Model discrimination was assessed by area under the receiver operating curve (AUROC). Results Non-diagnostic ESE occurred in 17% (151/898). Predictors of non-diagnostic study formed the scoring system: 1 point for female sex, 2 points for BMI &amp;gt;40, 1 point for age &amp;gt;55, Heart Rate&amp;lt;55 4 points, &amp;lt;65 3 points and &amp;lt;75 2 points. LV Hypertrophy was assigned 2 points, Type 1 Diabetes 3 points and Type 2 diabetes 1 point, LV Dysfunction was assigned 2 points. This scoring system had excellent discriminative ability (derivation AUROC 0.80, validation AUROC 0.81). A score of 8 or more had a specificity of 97% and a positive likelihood ratio of 9.4 for non-diagnostic ESE. A score of &amp;lt;8 had a negative predictive value of 86%. Patients with Non-Diagnostic ESE had longer time to transplantation (695 vs 636 days), and more investigations performed (43.05% vs 17.94%, p&amp;lt;0.001) and less likely to receive a renal transplant (OR 0.47, p&amp;lt;0.001). Conclusion Non diagnostic ESE in pre-transplant assessment causes significant delays to patient care. A simple clinical scoring system may identify patients likely to have non-diagnostic ESE and can be utilised to identify patients who may benefit from alternative risk-stratification investigations.

External Validation of the fullPIERS Risk Prediction Model in a U.S. Cohort of Individuals with Preeclampsia.

To externally validate the fullPIERS risk prediction model in a cohort of pregnant individuals with preeclampsia in the United States. This was a retrospective study of individuals with preeclampsia who delivered at 22 weeks or greater from January 1, 2010, to December 31, 2020. The primary outcome was a composite of maternal mortality or other serious complications of preeclampsia occurring within 48 hours of admission. We calculated the probability of the composite outcome using the fullPIERS prediction model based on data available within 12 hours of admission including, gestational age, chest pain or dyspnea, serum creatinine levels, platelet count, aspartate transaminase levels, and oxygen saturation. We assessed the model performance using the area under the curve (AUC) of the receiver operating characteristic curve. The optimal cutoff point was determined using Liu's method. A calibration plot was used to evaluate the model's goodness-of-fit. Among 1,510 individuals with preeclampsia, 82 (5.4%) experienced the composite outcome within 48 hours. The fullPIERS model achieved an AUC of 0.80 (95% confidence interval: 0.75-0.86). The predicted probability for individuals with the composite outcome (median: 18.8%; interquartile range: 2.9-59.1) was significantly higher than those without the outcome (median: 0.9%; interquartile range: 0.4-2.7). The optimal cutoff point of 5.5% yielded a sensitivity of 70.7% (95% CI: 59.6-80.3), a specificity of 85% (95% CI: 82.7-86.5), a positive likelihood ratio of 4.6 (95% CI: 3.8-5.5), and an odds ratio of 13.3 (95% CI: 8.1-21.8). The calibration plot indicated that the model underestimated risk when the predicted probability was below 1% and overestimated risk when the predicted probability exceeded 5%. The fullPIERS model demonstrated good discrimination in this U.S. cohort of individuals with preeclampsia, suggesting it may be a useful tool for healthcare providers to identify individuals at risk for severe complications.

Clinical Performance of the LiquidArray® Gastrointestinal VER 1.0 Assay in Patients with Suspected Gastroenteritis

Background/Objectives: Rapid and accurate pathogen identification is essential for the proper management of patients with infectious gastroenteritis, as well as for a better control of disease outbreaks. This observational, non-interventional, single-site study evaluated the diagnostic accuracy of LiquidArray® Gastrointestinal VER 1.0, a multiplex PCR syndromic panel capable of detecting up to 26 clinically relevant enteropathogens. Methods: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratio (LR) were evaluated using stool samples from 1512 patients with suspected gastroenteritis and were compared to seven competitor assays. Results: LiquidArray® Gastrointestinal VER 1.0 showed a very low invalid rate (0.5% at initial testing, down to 0% after repeat) and high sensitivity (&gt;90% for most detected targets) and specificity (&gt;99% for all detected targets). Accordingly, the PPV and NPV were high (&gt;90% for most targets and &gt;99% for all targets, respectively). The analytical performance of LiquidArray® Gastrointestinal VER 1.0 was also excellent as to co-amplification capability, cross-reactivity and assay precision. Conclusions: This study demonstrates the excellent clinical performance of LiquidArray® Gastrointestinal VER 1.0 and its suitability for implementation in clinical routine for the rapid and accurate diagnosis of infectious gastroenteritis.

Diagnostic accuracy of NT-proBNP to predict the incidence of CSA-AKI: A systematic review and meta-analysis.

Cardiac surgery-associated acute kidney injury (CSA-AKI) is a severe complication following cardiac surgery. Early identification and diagnosis are critical. In this study, we aim to systematically assess the diagnostic value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) for CSA-AKI. The PubMed, Embase, Web of Science, and Cochrane Library databases were searched from January 1971 to October 2023 to identify prospective observational and retrospective observational studies. Data extraction and study screening were carried out independently by 2 authors. The methodological quality of the included studies was evaluated by the Quality Assessment of Diagnostic Accuracy Studies 2 standards, and all statistical analyses were conducted by Stata 15.0. Seven studies including 37,200 patients were identified. The pooled sensitivity of 0.67 (95% credible interval [CI] = 0.56-0.77), specificity of 0.55 (95% CI = 0.45-0.64), area under the summary receiver operating characteristic curve of 0.65 (95% CI = 0.60-0.69), positive likelihood ratio of 1.5 (95% CI = 1.2-1.8), negative likelihood ratio of 0.60 (95% CI = 0.46-0.79), and diagnostic odds ratio of 2 (95% CI = 2-4) suggested that patients with higher preoperative NT-proBNP levels (pg/mL) are at higher risk of developing acute kidney injury after cardiac surgery. However, NT-proBNP lacks sufficient sensitivity and specificity to reliably predict CSA-AKI. Our findings suggest that the diagnostic accuracy of NT-proBNP to predict the incidence of CSA-AKI is limited. However, we provide novel perspectives on the early detection of CSA-AKI biomarkers, and it is urgent to identify more precise and practical biomarkers for the early diagnosis of CSA-AKI.