SROC Curve Research Articles

Cow's Milk-related Symptom Score for cow's milk allergy assessment: a meta-analysis for test accuracy.

We aimed to assess the ability of Cow's Milk-related Symptom Score (CoMiss) in screening cow's milk protein allergy (CMPA) and assess validation of its sensitivity and specificity. We searched the PubMed, WOS, Embase, and Ovid databases using broad terms and keywords for the concepts of the symptom-based score (CoMiss) and cow's milk allergy. We performed the meta-analyses using a meta-package of R software and Meta-DiSc software. Fourteen studies were included with a total of 1238 children. At cut-off value 12, CoMiss had a pooled sensitivity of 0.64 and a pooled specificity of 0.75. The PLR and NLR were 3.05 and 0.5, respectively. The AUC value of the sROC curve was 0.7866. CoMiss showed a significant difference in CMPA patients at baseline and after milk elimination for 2-4 weeks (MD, 7.18), as well as between the CMPA-positive group compared with the CMPA-negative group, however, the statistical significancy was obtained after leave study of Selbuz et al. out of the analysis (MD, 4.61). CoMiss may be a promising symptom score in the Awareness of the symptoms related to cow's milk allergy and a useful tool in monitoring the response to a cow's milk-free diet. Cow's milk protein allergy (CMPA) is the most frequent food allergy in children under the age of 3 years. Cow's Milk-related Symptom Score (CoMiss) is a clinical scoring system to assist primary healthcare providers in early detection of CMPA We performed a meta-analysis of CoMiss test accuracy. Our findings reflect that CoMiss may be a promising symptom score in CMPA awareness and a useful tool in monitoring the response to a cow's milk-free diet.

Exploring the Risk Factors of Conjunctival Squamous Cell Carcinoma and Establishing a Prognostic Model: Retrospective Study.

Objective Exploring the risk factors of conjunctival squamous cell carcinoma (CSCC) and establishing a prognostic model. Methods Information on patients with CSCC was extracted from the SEER database, conducting a retrospective study. 650 patients with CSCC were finally included in the model. Descriptive analysis was performed by Chi-square test and T-test. The risk factors of CSCC were explored by COX multivariate analysis, and the corresponding prognostic model was established as a result. Results The all-cause mortality rate of CSCC was 38.3%, and the risk factors were age (HR = 1.077), sex (HR = 0.691), grade (HR = 7.857), laterality (HR = 1.403), N (HR = 7.195), M (HR = 0.217), and surgery (HR = 1.618), all P < 0.05. The new model had C index and area under curve ROC (AUC) value greater than 0.7. Calibration curve, Net Reclassification Index (NRI), Integrated Discrimination Improvement (IDI), and Decision Curve Analysis (DCA) indicate the new model has better predictive performance than the American Joint Committee on Cancer (AJCC-TNM). Conclusions Compared with the clinical guidance of AJCC (TNM) for patients with CSCC, the established model exhibits good performance and can provide guidance for clinical decision-making.

Evaluating the Diagnostic Potentials of Circulating Tumor DNA against Melanoma: A Systematic Review and Meta-Analysis.

Background The accurate detection of circulating tumor (ct) DNA is affected by multiple factors, and several controversies still persists regarding clinical applications. In order to assess the consistency of ctDNA gene mutation detection findings in matched melanoma tissue samples and peripheral blood, a meta-analysis was performed and provided evidence-based analysis for its clinical applications. Method As of May 20, 2019, the database has been searched using the Embase, PubMed, and Cochrane Library search engines. The ctDNA investigations mentioned in this review may be used to directly or indirectly get the true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values of melanoma patients. To be excluded from the study are duplicate publications, research that do not offer a full text, inadequate material or an inability to extract data, and animal trials. Results Overall, the pooled specificity, sensitivity, NLR, PLR, and DOR were 0.94 (95% CI: 0.91-0.96), 0.73 (95% CI: 0.70-0.75), 0.32 (95% CI: 0.22-0.45), 8.21 (95% CI: 4.67-14.43), and 32.72 (95% CI: 14.81-72.30), respectively. Additionally, we calculated AUC by drawing the SROC curve, and the value of AUC is 0.9287, which indicates that the accuracy of ctDNA in diagnosing melanoma is 92.87% of the gold standard. Furthermore, we conducted a subgroup analysis for different countries, sample sources, and ctDNA detection methods. The pooled results showed that different countries, sample sources, and ctDNA detection methods showed significantly large differences in terms of sensitivity of ctDNA in diagnosing melanoma, while the specificity basically remained the same. Conclusion We discovered that the diagnostic outcomes between matched tumor samples and ctDNA remained more reliable in melanoma patients. ctDNA has the advantages of low trauma, convenient dynamic monitoring, and simple operation. ctDNA is expected to become an auxiliary method for the diagnosis of melanoma gene mutations.

Atherogenic indices in pediatric population in South-Southeast region of Mexico

Atherosclerosis is a cardiovascular disease, highly predictable, and associated with different atherogenic indices (AI) in adults. However, such indexes in the pediatric population are far less explored. The objective of this study was to evaluate the AI and the cardiovascular factors in the pediatric population in the South-Southeast of México. A total of 481 children between 2 and 17 years old were recruited. Anthropometric evaluation, blood pressure (BP), lipid profile, apolipoprotein A-I (ApoA-I) and apolipoprotein B (ApoB) were measured, and AI were calculated. The population was grouped by age, binary logistic regression analysis was performed to analysis for associations of AI and cardiovascular risk factors. Sensibility and specificity of AI to detect metabolic alteration were evaluated for curve ROC. The atherogenic risk presented a high prevalence in the pediatric population, such as LDL-c/ApoB (86.9%), AIP (78%) and AC (36.6%). Preschoolers showed a higher risk of ApoB/ApoA-I and ApoB/LDL-c, while adolescents have a high risk of AIP. CRI-I and AC were associated with elements of lipid profile and body mass index (BMI). ROC curves analysis shows that AIP is the best index evaluating metabolic syndrome (MS) (0.87) and dyslipidemia (0.91). Such pediatric population showed a high risk of AI, mainly by LDL-c/ApoB and AIP. The BMI was the cardiovascular risk factors most frequently related to AI, AIP is the best index for detecting cases of MS and dyslipidemia. This is the first study carried out in the pediatric population from the South-Southeast of Mexico that evaluated the AI.

Efficacy of computed tomography in diagnosing pulmonary hypertension: A systematic review and meta-analysis.

ObjectiveThis study seeks to evaluate the diagnostic value of computed tomography (CT) in pulmonary hypertension.MethodPubMed, Embase, Scopus, and Web of Science databases were searched to obtain the relevant English literature, and the retrieval time until June 2022. The quality of the included studies is evaluated using the QUADAS-2 tool. The quality of the included studies was assessed, followed by a meta-analysis, analyze heterogeneity, summarize sensitivity and specificity, draw the comprehensive subject working characteristics (sROC) curve, calculate the area under the curve and conduct subgroup analysis and sensitivity analysis to find the source of the heterogeneity.ResultsA total of 12 articles were included, all with pulmonary artery diameter/liter aortic diameter >1 or 1 as the diagnostic criteria for pulmonary hypertension, and a total of 1,959 patients were included. Deek’s funnel plot analysis suggests that there is no significant publication bias (P = 0.102). The combined sensitivity was 0.652 (95% CI: 0.579, 0.719), combined specificity was 0.830 (95% CI: 0.796, 0.880), positive likelihood ratio was 3.837 (95% CI: 3.215, 4.579), negative likelihood ratio was 0.419 (95% CI: 0.346, 0.507), diagnostic odds ratio was 9.157 (95% CI: 6.748, 12.427) and area under the summary receiver operating characteristic (SROC) curve was 0.84 (95% CI: 0.81, 0.87).ConclusionThe CT examination of pulmonary artery diameter/aortic artery hypertension is worthy of clinical application.

Performance of Serum Angiotensin-Converting Enzyme in Diagnosing Sarcoidosis and Predicting the Active Status of Sarcoidosis: A Meta-Analysis.

The usefulness of serum angiotensin-converting enzyme (sACE) for diagnosing sarcoidosis and determining the active status of sarcoidosis has been reported with varying outcomes. On the basis of the majority of published data, we conducted a meta-analysis to calculate the overall predictive accuracy of sACE in sarcoidosis disease and the active status of sarcoidosis. The inclusion of related research listed in Web of Science, PubMed, Scopus, and other literature databases was assessed. SROC curves were generated to characterize the overall test results after data on sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were combined. Publication bias was identified using Deeks’ funnel plot. Thirty-five publications with 8645 subjects met the inclusion criteria. The following are summary estimates of sACE diagnostic performance for sarcoidosis: sensitivity, 60% (95% confidence interval (CI), 52–68%); specificity, 93% (95% CI, 88–96%); PLR, 8.4 (95% CI, 5.3–13.3); NLR, 0.43 (95% CI, 0.36–0.52); and DOR, 19 (95% CI, 12–31). The area under the SROC curve (AUC) was 0.84 (95% CI, 0.80–0.87). Summary estimates for predicting the active status of sarcoidosis were as follows: sensitivity, 0.76 (95% CI, 0.61–0.87); specificity, 0.80 (95% CI, 0.64–0.90); PLR, 3.9 (95% CI, 2.1–7.3); NLR, 0.29 (95% CI, 0.17–0.49); and DOR, 13 (95% CI, 6–31). The AUC was 0.85 (95% CI, 0.82–0.88). There was no evidence of publication bias. Our meta-analysis suggests that measuring the sACE may assist in the diagnosis of sarcoidosis and predicting the active status of sarcoidosis, but the interpretation of the sACE results should be with caution. Future studies should validate our results.

Helmet: A device to reduce mortality and severity of trauma

Introduction: Objective of the present study was to evaluate the nosocomial outcomes and severity of trauma among motorcyclist trauma patients with and without using helmet. Materials and Methods: A prospective descriptive study was performed on 1000 motorcyclist trauma patients between December 2019 and May 2021. After collecting data and recording patients’ outcomes, patients were divided into two groups of users and non-users of helmets, and patients’ outcomes and severity of trauma were evaluated. Results: The median age of patients was 27 years and only 36.2% of patients had worn helmet when they were traumatised. Of the patients, 41 died during hospitalization, out of which 36 individuals did not have helmet during trauma. In the group without a helmet, the most common sites of injury were head and neck. There was a significant difference in the severity of trauma based on GAP, RTS, and NTS in the two groups of patients (P &lt;0.05). In reviewing the GAP, RTS, and NTS models, in determining the prognosis of survival rate of patients, the cut-off point values were obtained as 18.5, 7, and 16.5, respectively, with the area under the curve ROC of about 0.95. Conclusion: Helmet plays an important role in reducing the hospital mortality rate of motorcycle trauma patients. Additively, wearing a helmet is very effective in reducing the severity of trauma. It is recommended to take necessary measures to increase the use of helmet among motorcyclists by training and also using the force of law.

Panels of circulating microRNAs as potential diagnostic biomarkers for breast cancer: a systematic review and meta-analysis.

Circulating microRNAs (miRNAs) are potential diagnostic biomarkers for breast cancer (BC). The application of miRNA panels could improve the performance of screening tests. Here, we integrated bioinformatic tools and meta-analyses to select circulating miRNAs with high diagnostic accuracy and combined these markers to develop diagnostic panels for BC. Analyses across databases were performed to identify potential BC-related circulating miRNAs. Next, a comprehensive meta-analysis was conducted for each miRNA following the PRISMA guidelines. An electronic and manual search for relevant literature was carried out by two reviewers through PubMed, ScienceDirect, Biomed Central, and Google Scholar. The quality of the included studies was assessed using the QUADAS-2, and the statistical analyses were performed using R software 4.1.1. Finally, the accurate biomarkers confirmed through meta-analyses were combined into diagnostic models for BC. Twenty-seven circulating miRNAs were identified as BC-related by bioinformatic tools. After screening, only 10 miRNAs presented in 45 studies were eligible for meta-analyses. By assessing pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio, 8 miRNAs (miR-21, miR-30b, miR-125b, miR-145, miR221 miR-222, and miR-335) were revealed as promising BC diagnostic biomarkers. Two panels constructed from these miRNAs showed excellent diagnostic accuracy for BC, with areas under the SROC curve of 0.917 and 0.944. We identified 8 potential circulating miRNAs and 2 diagnostic models that are useful for diagnosing BC. However, the established miRNA panels have not been tested in any experimental studies and thus should be validated in large case-control studies for clinical use.

Diagnostic performance of the six-item cognitive impairment test as first-step screening for dementia: a meta-analysis.

Dementia, a slowly progressive disease, is poorly diagnosed. One reason is that it is difficult to use the screening tools. The six-item cognitive impairment test (6-CIT) is brief, with six items, and has a confirmed scoring system that can easily be used by an average individual. This review aimed to analyze the predictive validity of the 6-CIT including comparisons with other tools such as the Mini-Mental State Examination (MMSE). Literature searches were performed on the MEDLINE, EMBASE, CINAHL, and PsycArticles using the dementia and 6-CITas keywords. The Quality Assessment of Diagnostic Accuracy Studies-2 was applied to assess the risk of bias. Seven studies with 6,831 participants that met the selection criteria were included. The pooled sensitivity of the 6-CIT analyzed in seven studies was 0.82 (95% CI 0.73-0.89), the pooled specificity was 0.87, and the summary receiver operating characteristic (sROC) curve was 0.90 (SE = 0.04). The diagnostic performance of the 6-CIT and MMSE was compared in three studies. The pooled sensitivity of the 6-CIT was 0.85, the pooled specificity was 0.91, and the sROC curve was 0.91, whereas the MMSE values were 0.70, 0.93, and 0.68, respectively. This review presents evidence that the 6-CIT has excellent dementia screening performance and could be used as a potential alternative to the MMSE. The 6-CIT may provide an opportunity for early detection of dementia.

Elevated Surgical Pleth Index at the End of Surgery Is Associated with Postoperative Moderate-to-Severe Pain: A Systematic Review and Meta-Analysis.

Despite acceptance of the surgical pleth index (SPI) for monitoring the intraoperative balance between noxious stimulation and anti-nociception under general anesthesia, its efficacy for predicting postoperative moderate-to-severe pain remains unclear. We searched electronic databases (e.g., Google Scholar, MEDLINE, Cochrane Library, and EMBASE) to identify articles focusing on associations of SPI at the end of surgery with immediate moderate-to-severe pain in the postanesthesia care unit from inception to 7 July 2022. A total of six observational studies involving 756 adults published between 2016 and 2020 were eligible for quantitative syntheses. Pooled results revealed higher values of SPI in patients with moderate-to-severe pain than those without (mean difference: 7.82, 95% CI: 3.69 to 11.95, p = 0.002, I2 = 46%). In addition, an elevated SPI at the end of surgery was able to predict moderate-to-severe pain with a sensitivity of 0.71 (95% confidence interval (CI): 0.65–0.77; I2 = 29.01%) and a specificity of 0.58 (95% CI: 0.39–0.74; I2 = 79.31%). The overall accuracy based on the summary receiver operating characteristic (sROC) curve was 0.72. In conclusion, this meta-analysis highlighted the feasibility of the surgical pleth index to predict postoperative moderate-to-severe pain immediately after surgery. Our results from a limited number of studies warrant further investigations for verification.

The accuracy of triglyceride-glucose (TyG) index for the screening of metabolic syndrome in adults: A systematic review and meta-analysis

AimsTo investigate the relationship between the triglyceride-glucose (TyG) index, a novel surrogate index of insulin resistance (IR), and metabolic syndrome (MetS) in a systematic review and meta-analysis. Data synthesisStudies that report the TyG index in adult subjects with and without MetS were included. Thirteen observational articles were included in this study, with a total of 49,325 participants. Two different categories of meta-analyses were performed. First, the means of the TyG index were compared in participants with and without MetS. The pooled mean difference (MD) of the TyG index between groups was 0.83 units (CI 95: 0.74–0.92, I2 = 98, P-value < 0.001), and the subgroup analyses showed MD significantly differed based on the MetS diagnostic criteria. The pooled MD were 0.80 units (CI 95: 0.70–0.91, I2 = %88, P-value < 0.001) and 0.82 units (CI 95: 0.79–0.86, I2 = %0, P-value > 0.767) for studies reported data for males and females individual, respectively. Second bivariate diagnostic test accuracy (DTA) meta-analysis was performed and determined that the TyG index's pooled sensitivity and specificity for screening of MetS were 80% (CI95: 75%–84%, I2 = 87%, P-value < 0.001) and 81% (CI95: 77%–84%, I2 = 90.45%, P-value < 0.001), respectively. Summary receiver-operating characteristics (sROC) curves were also plotted with the area under the sROC curve of 0.87 (CI 95: 0.84–0.90). ConclusionsThe TyG index is a sensitive and specific index for MetS and may be valuable for MetS screening. ProsperoCRD42022316209.

Deep Learning Algorithms for Diagnosis of Lung Cancer: A Systematic Review and Meta-Analysis.

Simple SummaryLung cancer screening has been shown to help reduce mortality in selected populations of smokers; however, performing screening programs at a larger scale with high accuracy is still a challenge. The use of artificial intelligence (AI) has been investigated to improve large scale screening. We have performed a meta-analysis of the diagnostic accuracy of deep learning (DL) algorithms to diagnose lung cancer. Combining six eligible studies, the pooled sensitivity and specificity of DL algorithms were 0.93 (95% CI 0.85–0.98) and 0.68 (95% CI 0.49–0.84), respectively. Despite remaining challenges in the field, AI is likely to play an important role in disease screening in the future.We conducted a systematic review and meta-analysis of the diagnostic performance of current deep learning algorithms for the diagnosis of lung cancer. We searched major databases up to June 2022 to include studies that used artificial intelligence to diagnose lung cancer, using the histopathological analysis of true positive cases as a reference. The quality of the included studies was assessed independently by two authors based on the revised Quality Assessment of Diagnostic Accuracy Studies. Six studies were included in the analysis. The pooled sensitivity and specificity were 0.93 (95% CI 0.85–0.98) and 0.68 (95% CI 0.49–0.84), respectively. Despite the significantly high heterogeneity for sensitivity (I2 = 94%, p < 0.01) and specificity (I2 = 99%, p < 0.01), most of it was attributed to the threshold effect. The pooled SROC curve with a bivariate approach yielded an area under the curve (AUC) of 0.90 (95% CI 0.86 to 0.92). The DOR for the studies was 26.7 (95% CI 19.7–36.2) and heterogeneity was 3% (p = 0.40). In this systematic review and meta-analysis, we found that when using the summary point from the SROC, the pooled sensitivity and specificity of DL algorithms for the diagnosis of lung cancer were 93% and 68%, respectively.

Xpert MTB/RIF Assay for the Diagnosis of Lymph Node Tuberculosis in Children: A Systematic Review and Meta-Analysis.

Background: Lymph node tuberculosis (LNTB) is the leading type of extrapulmonary tuberculosis (EPTB) causing death in children. The Xpert MTB/RIF assay is a novel rapid test for the diagnosis of LNTB. Although previous evidence suggests that Xpert is reliably accurate in diagnosing EPTB in children, information is lacking for the specific type of LNTB in children. The aim of this study was to systematically assess the accuracy and reliability of Xpert for the diagnosis of LNTB in children. Methods: We systematically searched four databases, Embase, Cochrane Library, PubMed, and Web of Science, which extracted relevant data according to predefined inclusion and exclusion criteria. The data were analyzed by meta-Disc 1.4 and Stata 12.0 software to determine sensitivity, specificity, diagnostic odds ratio (DOR), etc. Results: A total of 646 samples from 8 studies were included in the analysis. The pooled sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR,) and combined diagnostic odds ratio (DOR) of Xpert for all samples were 0.79 (95% CI 0.70, 0.87), 0.90 (95% CI 0.86, 0.92), 0.29 (95% CI 0.19, 0.43), 7.20 (95% CI 3.32, 15.60), and 37.56 (95% CI 13.04, 108.15), respectively. The area under the curve (AUC) of the summary receiver operating characteristic (sROC) curve was 0.9050. Conclusion: Overall, Xpert showed moderate sensitivity and high specificity compared with culture in the diagnosis of LNTB in children. In addition, after analyzing the combined diagnostic odds ratio and positive LR, our study showed that Xpert has excellent diagnostic accuracy.

Diagnostic accuracy of S-Detect in distinguishing benign and malignant thyroid nodules: A meta-analysis.

In this meta-analysis study, the main objective was to determine the accuracy of S-detect in effectively distinguishing malignant thyroid nodules from benign thyroid nodules. We searched the PubMed, Cochrane Library, and CBM databases from inception to August 1, 2021. Meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 softwares. We calculated summary statistics for sensitivity (Sen), specificity (Spe), positive and negative likelihood ratio (LR+/LR-), diagnostic odds ratio(DOR), and receiver operating characteristic (SROC) curves. Cochran's Q-statistic and I2 test were used to evaluate potential heterogeneity between studies. A sensitivity analysis was performed to evaluate the influence of single studies on the overall estimate. We also performed meta-regression analyses to investigate the potential sources of heterogeneity. In this study, a total of 17 studies meeting the requirements of the standard were used. The number of benign and malignant nodules analyzed and evaluated in this paper was 1595 and 1118 respectively. This paper mainly completes the required histological confirmation through s-detect. The pooled Sen and pooled Spe were 0.87 and 0.74, respectively, (95%CI = 0.84-0.89) and (95%CI = 0.66-0.81). Furthermore, the pooled LR+ and negative LR- were determined to be 3.37 (95%CI = 2.53-4.50) and 0.18 (95%CI = 0.15-0.21), respectively. The experimental results showed that the pooled DOR of thyroid nodules was 18.83 (95% CI = 13.21-26.84). In addition, area under SROC curve was determined to be 0.89 (SE = 0.0124). It should be pointed out that there is no evidence of bias (i.e. t = 0.25, P = 0.80). Through this meta-analysis, it can be seen that the accuracy of s-detect is relatively high for the effective distinction between malignant thyroid nodules and benign thyroid nodules.

Predictive value of the combination between the intracranial arterial culprit plaque characteristics and the Essen Stroke Risk Score for short-term stroke recurrence

AimIn the current study we aim the identification of the culprit plaque characteristics of intracranial arteries using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI). Moreover, we target the evaluation of the predictive value of culprit plaque characteristics for short-term stroke recurrence combined with ESRS. Materials and methodsWe conducted a prospective cohort study on 342 patients diagnosed with symptomatic intracranial atherosclerotic stenosis (sICAS), out of which 243 were men and 99 were women with an average age of 64 ± 12 years. 184 cases of anterior circulation ischemia (ACIS) and 158 cases of posterior circulation ischemia (PCIS) were included in the study. All of them underwent HR-MR-VWI during the period between February 2020 and June 2021 in the Second Affiliated Hospital of Nantong University, Nantong, China. The culprit vessel and culprit plaque characteristics were assessed based on HR-MR-VWI images, and the patients' ESRS were obtained from the electronic medical records of the hospital. Concerning the obtained results from the 6-month follow-up, the patients were divided into the non-recurrence group and the recurrence group, and the differences in the above-mentioned features between the two groups were compared. The univariate Cox regression analysis combined with ESRS was performed to screen out the independent risk factors associated with recurrent stroke with P < 0.1. Receiver operating characteristic curves (ROC curves) were plotted to analyze the predictive performance of the culprit plaque characteristics, ESRS and combined variables for stroke recurrence. We used the area under the curve (AUC) ROC, while the sensitivity and specificity were calculated at the optimal threshold. The Delong test was employed to compare the quality of the AUC of the predictors. ResultsA total of 15.5% (53/342) of patients had a stroke recurrence within six months, with statistically significant differences (P < 0.05) between the two groups regarding the ESRS, medical history of diabetes mellitus, myocardial infarction, data for previous acute ischemic stroke (AIS) or transient ischemic attack(TIA), history of peripheral vascular disease, and serum brain natriuretic peptide level. In the patients with ACIS, the incidence of hyperintensity on the T1-weighted imaging (T1WI) was significantly different between the recurrence and the non-recurrence groups (P < 0.05). In the patients with PCIS, statistically significant differences between the recurrence and the non-recurrence group were detected in the culprit plaque burden, degree of enhancement, and incidence of hyperintensity on T1WI (P < 0.05). The ESRS (hazard ratios [HR], 1.598, 95% confidence interval [CI], 1.193–2.141, P = 0.002) ,degree of enhancement (HR = 1.764, 95% CI 0.985–3.087, P = 0.047) and hyperintensity on T1WI (HR = 2.745, 95% CI 1.373–5.488, P = 0.004) proved to be independent risk factors for stroke recurrence. The ESRS predicted stroke recurrence with AUC = 0.618 (95% CI 0.564–0.670), while the best cut-off value was 2 points. Furthermore, the registered sensitivity and specificity were 60.4% and 58.5%, respectively. Regarding the degree of enhancement in the culprit plaque, the prediction of stroke recurrence was with AUC = 0.628 (95% CI 0.574–0.679) as well as with sensitivities and specificities of 58.5% and 64.4%, respectively. Regarding the hyperintensity on T1WI in culprit plaque, the prediction of stroke recurrence was with AUC = 0.678 (95% CI 0.626–0.727) as well as with sensitivities and specificities of 66.0% and 70.0%, respectively. The ESRS combined with the degree of enhancement predicted stroke recurrence with an AUC = 0.685 (95CI% 0.633–0.734), while the recorded sensitivity and specificity were 56.6% and 73.4%, respectively. The ESRS combined with hyperintensity on the T1WI predicted stroke recurrence with an AUC = 0.745 (95CI% 0.696–0.791). The recorded sensitivity and specificity were 64.2% and 76.8%, respectively. The AUC quality of the ESRS combined with hyperintensity on T1WI was higher than that of other indices (P < 0.05). ConclusionsThe hyperintensity on T1WI of the culprit plaque in intracranial arteries combined with ESRS demonstrated better predictive ability for short-term stroke recurrence. We consider this of high importance for clinical application since it provides an easier way of obtaining data for precise diagnosis.

The Neutrophil-to-Lymphocyte Ratio and the Platelet-to-Lymphocyte Ratio as Predictors of Mortality in Older Adults Hospitalized with COVID-19 in Peru.

Background The prognostic value of the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in patients with COVID-19 is rarely described in older adults. We aimed to estimate the prognostic value of NLR and PLR, determining the mortality of adults over 60 years of age hospitalized for COVID-19 in three hospitals in Peru from March to May 2020. Methods We performed a secondary analysis of data from a retrospective cohort carried out in Lambayeque, Peru, from March 18 to May 13, 2020. Older adults hospitalized for COVID-19 were included. The outcome variable was in-hospital mortality by all causes, while the exposure variable was the NLR and PLR (categorized in tertiles and numerically, performing a logarithmic transformation). We included sociodemographic variables, comorbidities, vital functions, laboratory markers, and treatment received during hospital stay. We evaluated the association between NLR and PLR using the hazard ratio (HR) in a Cox regression model. We estimated HR with their respective 95% confidence intervals (95% CI). We estimated cumulative/dynamic time-dependent ROC curves and reported area under the curve ROC (AUC-ROC) for 15-, 30-, and 60-day mortality with their respective simultaneous confidence intervals (confidence bands (CB)). Also, we estimated an optimal cut-off point based on the maximally selected rank statistics. Results A total of 262 hospitalized older adults were analyzed, 71.8% (n = 188) of whom were male with a median age of 70 years (interquartile range: 65-78). The mean NLR and PLR were 16.8 (95% CI: 14.9-18.7; SD: 15.5) and 50.3 (95% CI: 44.6-55.9; SD: 46.3), respectively. The mortality rate was 68.7% (95% CI: 62.7-74.3). The adjusted Cox regression analysis showed that the high NLR (adjusted HR (aHR) = 2.12; 95% CI: 1.43-3.14) and PLR (aHR = 1.90; 95% CI: 1.30-2.79) tertiles were associated with a higher risk of mortality. The maximum AUC-ROC values at 60 days of follow-up for NLR and PLR were 0.713 (95%CB: 0.627-0.800) and 0.697 (95%CB: 0.583-0.754), respectively. Conclusions The NLR and PLR are predictors of higher risk of mortality, and these results suggest that both could be reliable and practical markers for the identification of older adults at high risk of mortality by COVID-19. NLR and PLR have prognostic value, with an AUC greater than 0.5; however, by themselves, they are weak prognostic markers. It is important to carry out future studies incorporating these two markers into preexisting models or designing new ones considering them.

Protocol for a systematic review and meta-analysis of the diagnostic accuracy of artificial intelligence for grading of ophthalmology imaging modalities

BackgroundWith the rise of artificial intelligence (AI) in ophthalmology, the need to define its diagnostic accuracy is increasingly important. The review aims to elucidate the diagnostic accuracy of AI algorithms in screening for all ophthalmic conditions in patient care settings that involve digital imaging modalities, using the reference standard of human graders.MethodsThis is a systematic review and meta-analysis. A literature search will be conducted on Ovid MEDLINE, Ovid EMBASE, and Wiley Cochrane CENTRAL from January 1, 2000, to December 20, 2021. Studies will be selected via screening the titles and abstracts, followed by full-text screening. Articles that compare the results of AI-graded ophthalmic images with results from human graders as a reference standard will be included; articles that do not will be excluded. The systematic review software DistillerSR will be used to automate part of the screening process as an adjunct to human reviewers. After the full-text screening, data will be extracted from each study via the categories of study characteristics, patient information, AI methods, intervention, and outcomes. Risk of bias will be scored using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) by two trained independent reviewers. Disagreements at any step will be addressed by a third adjudicator. The study results will include summary receiver operating characteristic (sROC) curve plots as well as pooled sensitivity and specificity of artificial intelligence for detection of any ophthalmic conditions based on imaging modalities compared to the reference standard. Statistics will be calculated in the R statistical software.DiscussionThis study will provide novel insights into the diagnostic accuracy of AI in new domains of ophthalmology that have not been previously studied. The protocol also outlines the use of an AI-based software to assist in article screening, which may serve as a reference for improving the efficiency and accuracy of future large systematic reviews.Trial registrationPROSPERO, CRD42021274441

The Effectiveness of Metagenomic Next-Generation Sequencing in the Diagnosis of Prosthetic Joint Infection: A Systematic Review and Meta-Analysis.

BackgroundA prosthetic joint infection (PJI) is a devastating complication following total joint arthroplasties with poor prognosis. Identifying an accurate and prompt diagnostic method is particularly important for PJI. Recently, the diagnostic value of metagenomic next-generation sequencing (mNGS) in detecting PJI has attracted much attention, while the evidence of its accuracy is quite limited. Thus, this study aimed to evaluate the accuracy of mNGS for the diagnosis of PJI.MethodsWe summarized published studies to identify the potential diagnostic value of mNGS for PJI patients by searching online databases using keywords such as “prosthetic joint infection”, “PJI”, and “metagenomic sequencing”. Ten of 380 studies with 955 patients in total were included. The included studies provided sufficient data for the completion of 2-by-2 tables. We calculated the sensitivity, specificity, and area under the SROC curve (AUC) to evaluate mNGS for PJI diagnosis.ResultsWe found that the pooled diagnostic sensitivity and specificity of mNGS for PJI were 0.93 (95% CI, 0.83 to 0.97) and 0.95 (95% CI, 0.92 to 0.97), respectively. Positive and negative likelihood ratios were 18.3 (95% CI, 10.9 to 30.6) and 0.07 (95% CI, 0.03 to 0.18), respectively. The area under the curve was 0.96 (95% CI, 0.93 to 0.97).ConclusionMetagenomic next-generation sequencing displays high accuracy in the diagnosis of PJI, especially for culture-negative cases.

FLOT neoadjuvant therapy turns the expression patterns of cancer cells similar to those of non-cancer cells in gastric cancer patients.

e16056 Background: FLOT perioperative have emerged as a new standard for locally advanced gastric cancer (LAGC). Nevertheless, the molecular consequences of such therapy remain obscure. Aiming to investigate changes in the tumor transcriptional landscape in LAGC patients treated with FLOT, a comprehensive analysis of messenger RNA (mRNAs) and long noncoding RNA (lncRNAs) expression was developed using next-generation sequencing (NGS). Methods: Paired tumor and non-tumor fresh samples, including 17 patients with intestinal-type LAGC submitted to neoadjuvant FLOT treatment (treated group) and 13 who did not receive neoadjuvant therapy (untreated group), were sequenced and compared. Differential expression analyses were performed using the DESeq2 package. Criteria for differentially expressed (DE) lncRNAs and mRNAs were|Log2(Fold-Change)| &gt; 2; and adjusted p-value &lt; 0.05. In silico analyses were adopted to identify DE lncRNAs with transcription factors (TFs) and RNA-binding proteins (RPBs). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene ontology (GO) was also performed to elucidate these target proteins’ and mRNAs biological’s roles. Results: In tumor samples from the untreated group, 4443 mRNAs and 961 lncRNAs DE were found, in which 293 mRNAs and 148 lncRNAs accurately discriminated (the area under the curve ROC &gt; 0.9) tumor and non-tumor tissues. Only 265 mRNAs and 29 lncRNAs DE were detected in treated patients, indicating that neoadjuvant therapy led to changes in expression patterns, making tumor tissues similar to non-tumor tissues. Subsequent analyzes identified that non-tumor tissues (treated vs. untreated) showed similar expression profiles. Among tumor samples, 34 mRNAs and 54 lncRNAs DE were found, in which 7 mRNAs and 16 lncRNAs can discriminate between treated and untreated tumors, indicating the effect of neoadjuvant treatment is predominant in the tumor. GO evaluation of genes was significant for 83 terms for biological process. The most annotated terms were the regulation of catalytic activity. We also observed that DE lncRNAs interact with TFs and RBPs were enriched in related cancer development and progression pathways, including transcriptional dysregulation and cellular senescence. Conclusions: Despite the need for further validation to better understand the transcriptional landscape related to neoadjuvant treatment, the present study highlights the functional relevance of lncRNAs in tumor biology and, mainly, shed light on the molecular effects of FLOT neoadjuvant treatment, that might help to guide future investigations aiming to establish personalized management of GC.

The interferon-gamma (IFN-y) signature from baseline tumor material predicts pathologic response after neoadjuvant ipilimumab (IPI) + nivolumab (NIVO) in stage III melanoma.

9539 Background: Neoadjuvant IPI + NIVO induces high pathologic response rates (pRR) of 74-78% in macroscopic stage III melanoma. Pathologic response ( &lt; 50% viable tumor) is strongly associated with improved relapse-free survival (RFS); the previous OpACIN-neo study demonstrated a 2-year RFS of 96.9% in patients (pts) with pathologic response, whereas the 2-year RFS in non-responders was 35.5%. These data highlight the need for baseline biomarkers predictive for response and survival. Here, we present the predictive value of the 10-gene IFN-y expression signature algorithm (based on Ayers et al.) for pathologic response and relapse in a cohort of melanoma pts treated with neoadjuvant IPI + NIVO. Methods: Baseline tumor biopsies from lymph node metastases of stage III melanoma pts were used for IFN-y signature assessment. Pts were treated with a maximum of two cycles of neoadjuvant IPI 1mg/kg + NIVO 3mg/kg in the OpACIN-neo (arm B) and PRADO studies. RNA expression analysis was conducted using the nCounter® PanCancer Immune Profiling panel on the NanoString Flex machine (NanoString Technologies), which is clinically applicable due to its fast turn-around-time (two days). An IFN-y signature gene expression score (IFN-y score) was calculated using a NKI-developed algorithm. Association between IFN-y score and pathologic response or event-free survival (EFS) was examined by logistic regression and Cox analyses. The optimal cutoff between a high and low IFN-y score was defined based on a summary receiver operating characteristic (sROC) curve. Results: In total, 103 pts treated in the OpACIN-neo and PRADO studies had baseline tumor material available. Median age was 56 years, 62% was male, and 52% had a high baseline IFN-y score. The pRR of the total cohort was 70% (72/103 pts), including 56% (58/103) major pathologic response (MPR, 0-≤10% viable tumor) and 14% (14/103) partial responses (pPR, 10-≤50% viable tumor). 30% (31/103 pts) had no pathologic response. After a median follow-up of 25.2 months, 26 pts (25.2%) developed a melanoma relapse. The IFN-y score was significantly associated with response (OR 1.061, p &lt; 0.001) and relapse (OR 0. 974, p = 0.029). The pRR was 89% (48/54) in pts with a high IFN-y score versus 49% (24/49) in those with a low IFN-y score (p &lt; 0.001). Pts with a high IFN-y score were also less likely to develop a relapse (11% [6/54] versus 41% [20/49], p = 0.001). Conclusions: Pts with a high IFN-y score in pre-treatment biopsies are more likely to respond to neoadjuvant IPI + NIVO with favorable EFS. A rapid gene expression analysis enables the IFN-y score to be used in daily clinical practice to identify pts who might qualify for treatment escalation or de-escalation. The DONIMI study [NCT04133948] currently investigates different neoadjuvant treatment combinations in stage III melanoma pts based on their intratumoral IFN-y score.