scholarly journals Sensitivity and Specificity of Spectral Oct in Patients with Early Glaucoma

2019 ◽  
Vol 75 (5) ◽  
pp. 260-264
Author(s):  
Magdaléna Bočková ◽  
Petr Veselý ◽  
Svatopluk Synek ◽  
Lubomír Hanák ◽  
Pavel Beneš
Keyword(s):  
Retrospective Study ◽  
Visual Field ◽  
Sensitivity And Specificity ◽  
Area Under Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Test Statistics ◽  
Early Glaucoma ◽  
Spectral Oct ◽  
Operating Characteristic Curve

The study examines the sensitivity and specificity of spectral OCT in detecting early glaucoma. The aim was to evaluate data obtained by RNFL analysis in 4 observed quadrants and to compare it with the resulting diagnosis of glaucoma neuropathy determined subsequently on the basis of changes in the visual field. This concerns a retrospective study numbering 31 probands who underwent OCT examination at our centre in the period from 2008 to 2017. Test statistics demonstrated sensitivity of OCT examination (specific RNFL analysis) of 63.64% and specificity of 90%. The used ROC (receiver operating characteristic curve) test showed an AUC (area under curve) value of 0.734 on a statistically significant level of p = 0.0097. We therefore found that the instrument Spectral OCT SLO, with the aid of RNFL analysis, was effective in determining probands in whom development of glaucoma pathology was subsequently confirmed.

scholarly journals Evaluation on the Diagnostic Efficiency of Different Methods in Detecting COVID-19.

2020 ◽  
Author(s):  
Haitao Yang ◽  
Yuzhu Lan ◽  
Xiujuan Yao ◽  
Sheng Lin ◽  
Baosong Xie
Keyword(s):  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Web Of Science ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Efficiency ◽  
Summary Receiver Operating Characteristic ◽  
Operating Characteristic Curve ◽  
Higher Sensitivity

Abstract Objective: To evaluate the diagnostic efficiency of different methods in detecting COVID-19.Methods: PubMed, Web of Science and Embase databases were searched for identifing eligible articles. All data were calculated utilizing Meta Disc 1.4, Revman 5.3.2 and Stata 12. The diagnostic efficiency was assessed via these indicators including summary sensitivity and specificity, positive likelihood ratio (PLR), negative LR (NLR), diagnostic odds ratio (DOR), summary receiver operating characteristic curve (sROC) and calculate the AUC. Results: 18 articles (3648 cases) were included. EPlex: pooled sensitivity was 0.94; specificity 1.0; PLR 90.91; NLR 0.07; DOR 1409.49; AUC=0.9979, Q*=0.9840. Panther Fusion: pooled sensitivity was 0.99; specificity 0.98; PLR 42.46; NLR 0.02; DOR 2300.38; AUC=0.9970, Q*=0.9799. Simplexa: pooled sensitivity was 1.0; specificity 0.97; PLR 26.67; NLR 0.01; DOR 3100.93; AUC=0.9970, Q*=0.9800. Cobas®: pooled sensitivity was 0.99; specificity 0.96; PLR 37.82; NLR 0.02; DOR 3754.05; AUC=0.9973, Q*=0.9810. RT-LAMP: pooled sensitivity was 0.98; specificity 0.99; PLR 36.22; NLR 0.04; DOR 751.24; AUC=0.9905, Q*=0.9596. Xpert Xpress: pooled sensitivity was 0.99; specificity 0.97; PLR 27.44; NLR 0.01; DOR 3488.15; AUC=0.9977, Q*=0.9829.Conclusions: These methods (ePlex, Panther Fusion, Simplexa, Cobas®, RT-LAMP and Xpert Xpress) bear higher sensitivity and specificity, and might be efficient methods complement to the gold standard.

scholarly journals Is obstructive sleep apnoea associated with hypoxaemia and prolonged ICU stay after type A aortic dissection repair? A retrospective study in Chinese population

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xin Xi ◽  
Yu Chen ◽  
Wei-Guo Ma ◽  
Jiang Xie ◽  
Yong-Min Liu ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Aortic Dissection ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Sleep Apnoea ◽  
Type A Aortic Dissection ◽  
Icu Stay ◽  
Obstructive Sleep ◽  
Operating Characteristic Curve ◽  
Prolonged Icu Stay

Abstract Background Although obstructive sleep apnoea (OSA) is prevalent among patients with aortic dissection, its prognostic impact is not yet determined in patients undergoing major vascular surgery. We aimed to investigate the association of OSA with hypoxaemia and with prolonged intensive care unit (ICU) stay after type A aortic dissection (TAAD) repair. Methods This retrospective study continuously enrolled 83 patients who underwent TAAD repair from January 1 to December 31, 2018. OSA was diagnosed by sleep test and defined as an apnoea hypopnea index (AHI) of ≥ 15/h, while an AHI of > 30/h was defined severe OSA. Hypoxaemia was defined as an oxygenation index (OI) of < 200 mmHg. Prolonged ICU stay referred to an ICU stay of > 72 h. Receiver operating characteristic curve analysis was performed to evaluate the predictive value of postoperative OI for prolonged ICU stay. Multivariate logistic regression was performed to assess the association of OSA with hypoxaemia and prolonged ICU stay. Results A total of 41 (49.4%) patients were diagnosed with OSA using the sleep test. Hypoxaemia occurred postoperatively in 56 patients (67.5%). Postoperatively hypoxaemia developed mostly in patients with OSA (52.4% vs. 83.0%, p = 0.003), and particularly in those with severe OSA (52.4% vs. 90.5%, p = 0.003). The postoperative OI could fairly predict a prolonged ICU stay (area under the receiver-operating characteristic curve, 0.72; 95% confidence intervals [CI] 0.60–0.84; p = 0.002). Severe OSA was associated with both postoperative hypoxaemia (odds ratio [OR] 6.65; 95% CI 1.56–46.26, p = 0.008) and prolonged ICU stay (OR 5.58; 95% CI 1.54–20.24, p = 0.009). Conclusions OSA was common in patients with TAAD. Severe OSA was associated with postoperative hypoxaemia and prolonged ICU stay following TAAD repair.

A simple method to estimate the time-dependent receiver operating characteristic curve and the area under the curve with right censored data

2016 ◽  
Vol 27 (8) ◽  
pp. 2264-2278 ◽  
Author(s):  
Liang Li ◽  
Tom Greene ◽  
Bo Hu
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Disease Onset ◽  
Area Under The Curve ◽  
Time Dependent ◽  
Operating Characteristic Curve ◽  
Receiver Operating

The time-dependent receiver operating characteristic curve is often used to study the diagnostic accuracy of a single continuous biomarker, measured at baseline, on the onset of a disease condition when the disease onset may occur at different times during the follow-up and hence may be right censored. Due to right censoring, the true disease onset status prior to the pre-specified time horizon may be unknown for some patients, which causes difficulty in calculating the time-dependent sensitivity and specificity. We propose to estimate the time-dependent sensitivity and specificity by weighting the censored data by the conditional probability of disease onset prior to the time horizon given the biomarker, the observed time to event, and the censoring indicator, with the weights calculated nonparametrically through a kernel regression on time to event. With this nonparametric weighting adjustment, we derive a novel, closed-form formula to calculate the area under the time-dependent receiver operating characteristic curve. We demonstrate through numerical study and theoretical arguments that the proposed method is insensitive to misspecification of the kernel bandwidth, produces unbiased and efficient estimators of time-dependent sensitivity and specificity, the area under the curve, and other estimands from the receiver operating characteristic curve, and outperforms several other published methods currently implemented in R packages.

scholarly journals Gastrin-17 Combined With CEA, CA12-5 and CA19-9 Improves the Sensitivity For the Diagnosis of Gastric Cancer

2021 ◽  
Author(s):  
Zhen Wang ◽  
Tang-ming Mo ◽  
Lei Tian ◽  
Jun-qiang Chen
Keyword(s):  
Gastric Cancer ◽  
Area Under Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Diagnostic Value ◽  
Serum Markers ◽  
Control Group ◽  
Positive Rate ◽  
Healthy Control ◽  
Operating Characteristic Curve

Abstract Background: Previous studies reported the utility of serum tumor markers (such as CEA, CA12-5 and CA19-9) and gastrin-17 in the diagnosis of gastric cancer (GC). However, the value of these serum markers for diagnosing GC is still under debate.Methods: The level of CEA, CA12-5, CA19-9 and gastrin-17 was tested in 230 GC patients and 99 healthy people. The value of the four markers for diagnosing GC was analyzed.Results: The positive rate of Gastrin-17, CEA, CA199 and CA125 were much higher in GC group (22.61%, 22.61%, 20.00% and 8.26%, respectively) than that of healthy control group (5.05%, 2.02%, 1.01% and 2.02%, respectively). The sensitivity of Gastrin-17, CEA, CA125 and CA199 in the diagnosis of GC were 22.61%, 22.61%, 6.96% and 20.00%, respectively, and the corresponding specificity were 94.95%, 97.98%, 98.99% and 98.99%, respectively. By using the optimal cut-off value derived from the area under curve (AUC) of receiver operating characteristic curve, the AUC of gastin-17, CEA, CA125, CA199 increased to 0.72, 0.64, 0.61 and 0.65, respectively. After combining the four markers, the AUC increased to 0.79 (95% CI: 0.75-0.84), and the corresponding sensitivity and specificity were 65.22% (95% CI: 58.70% - 71.40%) and 84.85% (95% CI: 76.20% - 91.30%), respectively.Conclusion: CEA, CA12-5, CA19-9 and gastrin-17 were all valuable in the diagnosis of GC, and gastrin-17 had the best diagnostic value among the four markers. Gastrin-17 combined with CEA, CA12-5 and CA19-9 could improve the diagnostic value of GC significantly. Prospective, multi-center studies are needed to validate our findings.

scholarly journals Serum miR-214 Serves as a Biomarker for Prodromal Parkinson’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Lanting Li ◽  
Jingru Ren ◽  
Chenxi Pan ◽  
Yuqian Li ◽  
Jianxia Xu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Area Under Curve ◽  
Operating Characteristic ◽  
De Novo ◽  
Characteristic Curve ◽  
The Other ◽  
Circulating Micrornas ◽  
Potential Biomarker ◽  
Operating Characteristic Curve

Circulating microRNAs (miRNAs) have been proposed to be accessible biomarkers for Parkinson’s disease (PD). However, there is a lack of known miRNAs that can serve as biomarkers for prodromal PD (pPD). We previously identified that miR-31 and miR-214 were dysregulated in PD. The aim of this study was to explore the roles of miR-31 and miR-214 in pPD. We recruited 25 pPD patients, 20 patients with de novo PD (dnPD), 24 advanced PD (aPD) patients and 21 controls. Next, we investigated the expression of miR-31 and miR-214. Compared to controls, miR-214 was found to be significantly upregulated in pPD patients while miR-31 was significantly upregulated in aPD patients. In addition, the expression of miR-214 was lower in aPD patients compared to both dnPD or pPD patients, while the expression of miR-31 was higher in aPD patients compared to dnPD patients. In order to predict pPD via miRNA expression, the receiver operating characteristic curve was constructed and the area under curve (AUC) was calculated. For pPD prediction by miR-214, the AUC was 0.756. The optimal cut-off value of miR-214 was 0.1962, and the sensitivity and specificity were 72.0% and 76.2%, respectively. On the other hand, the AUC for aPD detection by miR-31 was 0.744. The optimal cut-off value for miR-31 was 0.0148, with a sensitivity of 87.5% and a specificity of 71.4%. In conclusion, miR-214 can distinguish pPD patients from controls and may be used as a potential biomarker for pPD diagnosis.

scholarly journals Decision Threshold for Kryptor sFlt‐1/PlGF Ratio in Women With Suspected Preeclampsia: Retrospective Study in a Routine Clinical Setting

2021 ◽  
Author(s):  
Lise Lotte Torvin Andersen ◽  
Annemarie Helt ◽  
Lene Sperling ◽  
Martin Overgaard
Keyword(s):  
Retrospective Study ◽  
Early Onset ◽  
Operating Characteristic ◽  
Late Onset ◽  
Characteristic Curve ◽  
Predictive Performance ◽  
Decision Threshold ◽  
Operating Characteristic Curve ◽  
Early Onset Preeclampsia ◽  
Plgf Ratio

Background The objective was to evaluate predictive performance and optimal decision threshold of the Kryptor soluble fms‐like tyrosine kinase‐1 (sFlt‐1)/placental growth factor (PlGF) ratio when implemented for routine management of women presenting with symptoms of preeclampsia. Methods and Results Observational retrospective study of a cohort of 501 women with suspected preeclampsia after 20 weeks of gestation. Women referred to maternity ward for observation of preeclampsia had an sFlt‐1/PlGF ratio test included in routine diagnostic workup. Maternal and offspring characteristic data included maternal risk factors, outcomes, delivery mode, and indication for suspected preeclampsia. Biochemical measurements to determine sFlt‐1/PlGF ratio were performed using the BRAHMS/Kryptor sFlt‐1/PlGF ratio immunoassays. Results were analyzed by area under receiver‐operating characteristic curve. Preeclampsia occurred in 150 of 501 (30%) of symptomatic women with an sFlt‐1/PlGF ratio determined before the time of diagnosis. Area under receiver‐operating characteristic curve for diagnosis of early‐onset preeclampsia within 1 and 4 weeks was 0.98 (95% CI, 0.96–1.00) and 0.95 (95% CI, 0.92–0.98), respectively. For late‐onset preeclampsia, predictive performance within 1 and 4 weeks was lower: 0.90 (95% CI, 0.85–0.94) and 0.85 (95% CI, 0.80–0.90), respectively. The optimal single sFlt‐1/PlGF ratio threshold for all preeclampsia and late‐onset preeclampsia within 1 and 4 weeks was 66. The negative and positive predictive values for ruling out and ruling in developing preeclampsia within 1 week were 96% and 70%, respectively. Conclusions The Kryptor sFlt‐1/PlGF ratio is a useful clinical tool ruling out and in preeclampsia within 1 week. Prediction within 4 weeks is superior for early‐onset preeclampsia. A single decision threshold of 66 is indicated for use in clinical routine.

Complications and risk factors for severe outcome in children with measles

2019 ◽  
Vol 105 (9) ◽  
pp. 896-899 ◽  
Author(s):  
Andrea Lo Vecchio ◽  
Andrzej Krzysztofiak ◽  
Carlotta Montagnani ◽  
Piero Valentini ◽  
Nadia Rossi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Retrospective Study ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Operating Characteristic Curve ◽  
Organ Complications

Objective and designRisk factors for severe measles are poorly investigated in high-income countries. The Italian Society for Paediatric Infectious Diseases conducted a retrospective study in children hospitalised for measles from January 2016 to August 2017 to investigate the risk factors for severe outcome defined by the presence of long-lasting sequelae, need of intensive care or death.ResultsNineteen hospitals enrolled 249 children (median age 14.5 months): 207 (83%) children developed a complication and 3 (1%) died. Neutropaenia was more commonly reported in children with B3-genotype compared with other genotypes (29.5% vs 7.7%, p=0.01). Pancreatitis (adjusted OR [aOR] 9.19, p=0.01) and encephalitis (aOR 7.02, p=0.04) were related to severe outcome in multivariable analysis, as well as C reactive protein (CRP) (aOR 1.1, p=0.028), the increase of which predicted severe outcome (area under the receiver operating characteristic curve 0.67, 95% CI 0.52 to 0.82). CRP values >2 mg/dL were related to higher risk of complications (OR 2.0, 95% CI 1.15 to 3.7, p=0.01) or severe outcome (OR 4.13, 95% CI 1.43 to 11.8, p<0.01).ConclusionThe risk of severe outcome in measles is independent of age and underlying conditions, but is related to the development of organ complications and may be predicted by CRP value.

scholarly journals Artificial Intelligence-Enabled ECG Algorithm to Identify Patients With Left Ventricular Systolic Dysfunction Presenting to the Emergency Department With Dyspnea

2020 ◽  
Vol 13 (8) ◽  
Author(s):  
Demilade Adedinsewo ◽  
Rickey E. Carter ◽  
Zachi Attia ◽  
Patrick Johnson ◽  
Anthony H. Kashou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Left Ventricular Systolic Dysfunction ◽  
Characteristic Curve ◽  
Left Ventricular ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Background: Identification of systolic heart failure among patients presenting to the emergency department (ED) with acute dyspnea is challenging. The reasons for dyspnea are often multifactorial. A focused physical evaluation and diagnostic testing can lack sensitivity and specificity. The objective of this study was to assess the accuracy of an artificial intelligence-enabled ECG to identify patients presenting with dyspnea who have left ventricular systolic dysfunction (LVSD). Methods: We retrospectively applied a validated artificial intelligence-enabled ECG algorithm for the identification of LVSD (defined as LV ejection fraction ≤35%) to a cohort of patients aged ≥18 years who were evaluated in the ED at a Mayo Clinic site with dyspnea. Patients were included if they had at least one standard 12-lead ECG acquired on the date of the ED visit and an echocardiogram performed within 30 days of presentation. Patients with prior LVSD were excluded. We assessed the model performance using area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results: A total of 1606 patients were included. Median time from ECG to echocardiogram was 1 day (Q1: 1, Q3: 2). The artificial intelligence-enabled ECG algorithm identified LVSD with an area under the receiver operating characteristic curve of 0.89 (95% CI, 0.86–0.91) and accuracy of 85.9%. Sensitivity, specificity, negative predictive value, and positive predictive value were 74%, 87%, 97%, and 40%, respectively. To identify an ejection fraction <50%, the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were 0.85 (95% CI, 0.83–0.88), 86%, 63%, and 91%, respectively. NT-proBNP (N-terminal pro-B-type natriuretic peptide) alone at a cutoff of >800 identified LVSD with an area under the receiver operating characteristic curve of 0.80 (95% CI, 0.76–0.84). Conclusions: The ECG is an inexpensive, ubiquitous, painless test which can be quickly obtained in the ED. It effectively identifies LVSD in selected patients presenting to the ED with dyspnea when analyzed with artificial intelligence and outperforms NT-proBNP. Graphic Abstract: A graphic abstract is available for this article.

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