scholarly journals Diagnosis of Asthma Based on Routine Blood Biomarkers Using Machine Learning

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jun Zhan ◽  
Wen Chen ◽  
Longsheng Cheng ◽  
Qiong Wang ◽  
Feifei Han ◽  
...  
Keyword(s):  
Roc Curve ◽  
Threshold Value ◽  
Healthy Individuals ◽  
Blood Biomarkers ◽  
Distribution Width ◽  
Mahalanobis Distances ◽  
Blood Biomarker ◽  
Routine Blood ◽  
Asthma Patients ◽  
Blood Data

Intelligent medical diagnosis has become common in the era of big data, although this technique has been applied to asthma only in limited contexts. Using routine blood biomarkers to identify asthma patients would make clinical diagnosis easier to implement and would enhance research of key asthma variables through data mining techniques. We used routine blood data from healthy individuals to construct a Mahalanobis space (MS). Then, we calculated Mahalanobis distances of the training routine blood data from 355 asthma patients and 1,480 healthy individuals to ensure the efficiency of MS. Orthogonal arrays and signal-to-noise ratios were used to optimize blood biomarker variables. Receiver operating characteristic (ROC) curve was used to determine the threshold value. Ultimately, we validated the system on 182 individuals based on the threshold value. Out of 35 patients with asthma, MTS correctly classified 94.15% of patients. In addition, 97.20% of 147 healthy individuals were correctly classified. The system isolated 7 routine blood biomarkers. Among these biomarkers, platelet distribution width, mean platelet volume, white blood cell count, eosinophil count, and lymphocyte ratio performed well in asthma diagnosis. In brief, MTS shows promise as an accurate method to identify asthma patients based on 7 vital blood biomarker variables and threshold determined by the ROC curve, thus offering the potential to simplify diagnostic complexity and optimize clinical efficiency.

scholarly journals A routine blood test-associated predictive model and application for tuberculosis diagnosis: a retrospective cohort study from northwest China

2019 ◽  
Vol 47 (7) ◽  
pp. 2993-3007 ◽  
Author(s):  
Kui Li ◽  
Sheng-Xi Liu ◽  
Cai-Yong Yang ◽  
Zi-Cheng Jiang ◽  
Jun Liu ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
High Sensitivity ◽  
Threshold Value ◽  
Northwest China ◽  
Optimal Threshold ◽  
Accuracy Rate ◽  
Distribution Width ◽  
Routine Blood ◽  
Resistant Tuberculosis ◽  
Diagnostic Values

Objectives This study aimed to use the results of routine blood tests and relevant parameters to construct models for the prediction of active tuberculosis (ATB) and drug-resistant tuberculosis (DRTB) and to assess the diagnostic values of these models. Methods We performed logistic regression analysis to generate models of plateletcrit-albumin scoring (PAS) and platelet distribution width-treatment-sputum scoring (PTS). Area under the curve (AUC) analysis was used to analyze the diagnostic values of these curves. Finally, we performed model validation and application assessment. Results In the training cohort, for the PAS model, the AUC for diagnosing ATB was 0.902, sensitivity was 82.75%, specificity was 82.20%, accuracy rate was 81.00%, and optimal threshold value was 0.199. For the PTS model, the AUC for diagnosing DRTB was 0.700, sensitivity was 63.64%, specificity was 73.53%, accuracy rate was 89.00%, and optimal threshold value was −2.202. These two models showed significant differences in the AUC analysis, compared with single-factor models. Results in the validation cohort were similar. Conclusions The PAS model had high sensitivity and specificity for the diagnosis of ATB, and the PTS model had strong predictive potential for the diagnosis of DRTB.

scholarly journals Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiajia Liu ◽  
Xiaoyi Tian ◽  
Yan Wang ◽  
Xixiong Kang ◽  
Wenqi Song
Keyword(s):  
T Lymphocyte ◽  
Roc Curve ◽  
Cytotoxic T Lymphocyte ◽  
Tumor Grade ◽  
Curve Analysis ◽  
Enzyme Linked Immunosorbent Assay ◽  
Low Grade ◽  
High Grade ◽  
Healthy Individuals ◽  
Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

Evaluation of urinary γ-glutamyl transferase and serum creatinine in non-azotaemic hospitalised dogs

2019 ◽  
Vol 185 (2) ◽  
pp. 52-52 ◽  
Author(s):  
Francesca Perondi ◽  
Ilaria Lippi ◽  
Gianila Ceccherini ◽  
Veronica Marchetti ◽  
Grazia Guidi
Keyword(s):  
Serum Creatinine ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Intensive Care Unit Mortality ◽  
Kidney Injury ◽  
Blood Biomarkers ◽  
Urine Protein ◽  
Roc Curve Analysis ◽  
Significant Difference ◽  
Glutamyl Transferase

Urinary and blood biomarkers for diagnosis of acute kidney injury (AKI) in hospitalised dogs were evalueted. This prospective study included 97 dogs, classified according to the International Renal Interest Society classification into no AKI and AKI grade 1 (48-hour increase in serum creatinine≥0.3 mg/dl and/or urinary production <1 ml/kg/hour for at least six hours). A total of 62 of 97 dogs (64 per cent) were classified as AKI 1. A statistically significant difference was found between no AKI and AKI 1 in urine protein to creatinine ratio, urinary γ-glutamyl transferase (uGGT) and uGGT/cu (P<0.0001). Thirteen of 97 dogs (13.4 per cent) that developed increased creatinine and change in AKI grade showed high mortality (n=9/13; 69.2 per cent). The receiver operating characteristic (ROC) curve analysis of uGGT/cu index as a marker for AKI grade 1 had an area under the ROC curve of 0.78; optimal cut-off point was 57.50 u/g, with sensitivity and specificity of 75.4 per cent and 75.6 per cent, respectively. Overall intensive care unit mortality was 23.7 per cent (23/97), 13.4 per cent (13/97) of which died during hospitalisation and 10.3 per cent (10/97) within 28 days after discharge. uGGT is an acceptable marker for distinguishing between AKI 1 and no AKI.

Risk of Diabetes Mellitus in Patients with Juvenile Idiopathic Arthritis

2019 ◽  
Vol 47 (9) ◽  
pp. 1405-1408
Author(s):  
Hemin Lee ◽  
Yinzhu Jin ◽  
Jun Liu ◽  
Ezra M. Cohen ◽  
Sarah K. Chen ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Juvenile Idiopathic Arthritis ◽  
Index Date ◽  
Healthy Children ◽  
Healthy Individuals ◽  
Increased Risk ◽  
Asthma Patients

Objective.To examine the risk of type 1 diabetes (T1D) associated with juvenile idiopathic arthritis (JIA).Methods.Using the IBM MarketScan database, we compared JIA patients with asthma patients and healthy individuals for the risk of incident T1D.Results.We included patients with 15,210 JIA, 76,050 patients with asthma, and 76,050 healthy individuals matched 1:5 on age, sex, and index date. After adjustment for confounders, the multivariable HR of T1D associated with JIA was 1.48 (95% CI 0.86–2.56) versus asthma and 1.81 (95% CI 1.03–3.17) versus healthy individuals.Conclusion.JIA appears to be associated with an increased risk of T1D compared to patients with asthma and healthy children.

Clinical and spirometric variables are better predictors of COPD exacerbations than routine blood biomarkers

2020 ◽  
Vol 171 ◽  
pp. 106091
Author(s):  
Alexa Nuñez ◽  
Viviana Marras ◽  
Matevz Harlander ◽  
Evgeni Mekov ◽  
Matjaz Turel ◽  
...  
Keyword(s):  
Blood Biomarkers ◽  
Copd Exacerbations ◽  
Routine Blood

scholarly journals Platelet and Red Blood Cell Indices in Patients with Panic Disorder: A Receiver Operating Characteristic Analysis

2020 ◽  
Vol 11 (02) ◽  
pp. 261-266 ◽  
Author(s):  
Ramdas S. Ransing ◽  
Neha Gupta ◽  
Girish Agrawal ◽  
Nilima Mahapatro
Keyword(s):  
Panic Disorder ◽  
Blood Cell ◽  
Receiver Operating Characteristic ◽  
Red Blood Cell ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Healthy Controls ◽  
Distribution Width ◽  
Rbc Indices ◽  
Receiver Operating

Abstract Objective Panic disorder (PD) is associated with changes in platelet and red blood cell (RBC) indices. However, the diagnostic or predictive value of these indices is unknown. This study assessed the diagnostic and discriminating value of platelet and RBC indices in patients with PD. Materials and Methods In this cross-sectional study including patients with PD (n = 98) and healthy controls (n = 102), we compared the following blood indices: mean platelet volume (MPV), platelet distribution width (PDW), and RBC distribution width (RDW). The receiver operating characteristic (ROC) curve was used to calculate the area under the ROC curve (AUC), sensitivity, specificity, and likelihood ratio for the platelet and RBC indices. Results Statistically significant increase in PDW (17.01 ± 0.91 vs. 14.8 ± 2.06; p < 0.0001) and RDW (16.56 ± 2.32 vs. 15.12 ± 2.43; p < 0.0001) levels were observed in patients with PD. PDW and mean corpuscular hemoglobin concentration had larger AUC (0.89 and 0.74, respectively) and Youden’s index (0.65 and 0.39, respectively), indicating their higher predictive capacity as well as higher sensitivity in discriminating patients with PD from healthy controls. Conclusion PDW can be considered a “good” diagnostic or predictive marker in patients with PD.

Individualized Prediction of Follicular Lymphoma Risk Using a Combination of Blood t(14;18) Frequency Years before Diagnosis and a Polygenic Risk Score (PRS) of 9 SNPs Associated with Follicular Lymphoma Susceptibility

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2775-2775
Author(s):  
Herve Ghesquieres ◽  
Youenn Drouet ◽  
Manon Zala ◽  
Paolo Vineis ◽  
Gilles A. Salles ◽  
...  
Keyword(s):  
High Risk ◽  
Follicular Lymphoma ◽  
Board Of Directors ◽  
Roc Curve ◽  
Genetic Variants ◽  
Epidemiological Studies ◽  
Polygenic Risk Score ◽  
Healthy Individuals ◽  
Advisory Committees ◽  
Polygenic Risk

Introduction: The risk of developing a follicular lymphoma (FL) begins to be better understood with the identification in large epidemiological studies of familial predisposition, some occupational exposures and genetic factors. Genome wide-association studies (GWAS) identified constitutional single nucleotide polymorphisms (SNPs) at risk of FL in HLA region (rs12195582), in 11q23.3 (near CXCR5), in 11q24.3 (near ETS1), in 3q28 (near LPP), in 18q21.33 (near BCL2), and 8q24 (near PVT1); three suggestive loci are localized at 17q25.3 (near CYBC1), 3q13.33 (CD86), 18q12.3 (SLC14A2) (Skibola, Am J Hum Genet. 2014). High t(14;18) frequency in blood years before diagnosis from healthy individuals was also defined as a predictive biomarker for FL (Roulland, J Clin Oncol 2014). It is currently unknown whether any relationship exists between inherited genetic variants associated with FL susceptibility and t(14;18) frequency and if the combination of the two biomarkers could be useful for a better stratification of risk of FL development in healthy individuals. Methods: We used quantitative PCR assays to estimate t(14;18) frequency in prediagnostic blood samples from 105 individuals that were obtained on average 6.4 years before FL diagnosis (pre-FL group) together with 236 age and gender-matched individuals (control group) that were issued from the participants in the EPIC cohort ( European Prospective Investigation Into Cancer and Nutrition). Constitutional DNA was analyzed for the genotyping of the nine SNPs associated with FL risk (HLA, rs12195582; CXCR5, rs4938573; ETS1, rs4937362; LPP, rs6444305; BCL2, rs17749561; PVT1, rs13254990; CYBC1, rs3751913; CD86, rs2681416; SLC14A2, rs11082438). Genotyping were performed in duplicate using TaqMan® assays on Fluidigm platform. The nine SNPs were analyzed individually and combined in a polygenic risk score (PRS). PRS is a weighted average of the number of risk alleles with the weights being the log of the odds-ratio (OR) reported in the FL GWAS (Skibola, Am J Hum Genet. 2014). A model for FL risk was developed using multivariable logistic regression. Predictive ability was assessed by area under Receiver Operating Characteristic (ROC) curve, with 10-fold cross-validation. This work is supported by the French NCI (INCA, PRT-K16-167). Results: t(14;18) frequency as a log-transformed continuous variable is predictive of FL risk (OR: 1.50; 95%CI: 1.29-1.78, P<0.001); PRS is also strongly associated with FL risk (OR: 3.31; 95%CI: 2.01-5.62, P<0.001). Age at screening (OR: 0.98; 95%CI: 0.95-1.01, P=0.24) did not influence FL risk. A weak but statistically significant correlation between t(14; 18) frequency and PRS was observed (Pearson correlation=0.18, P=0.002). In multivariable analysis, both PRS (OR: 2.84, 95%CI: 1.66-4.99, P<0.001) and t(14;18) frequency (OR: 1.45, 95%CI: 1.18-1.84, P<0.001) remained statistically significant. No departure from log-linear effect was observed in the modeling nor statistical interaction between PRS and log-transformed t(14;18), confirming that t(14; 18) frequency and genetic markers (PRS) were two independent factors of FL risk. Sensitivity analyses showed that these results were not influenced by the delay between the date of the screening and the FL diagnosis. Combining t(14;18) frequency and the PRS in a prediction model allowed the identification of some individuals at very high risk of developing FL and a shiny web application was developed to provide an easy-to-use tool to obtain individualized risk predictions for new patients (Figure). Area under ROC curve (AUC) showed that the model that integrated t(14;18) frequency and PRS (AUC: 0.69, 95%CI: 0.62-0.76) had a better prediction of FL risk than t(14;18) frequency (AUC: 0.62, 95%CI: 0.55-0.70) and PRS alone (AUC: 0.68, 95%CI: 0.61-0.75). Conclusions: Genetic variants combined in PRS and t(14;18) frequency allowed the identification of individuals at high-risk of FL development and provided a better way, when these two biomarkers were combined, to discriminate healthy individuals from pre-FL cases many years before malignant transformation. These findings could be used for screening test of populations with some environmental exposures positively associated with FL development in epidemiological studies and may contribute in the future to monitoring or early intervention. Figure Disclosures Salles: Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy, Honoraria.

Measurement of Whole Blood Platelet Aggregation by Multiplate® Aggregometry Before and during Aspirin Treatment.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3895-3895
Author(s):  
Susanne B. Pedersen ◽  
Steen D. Kristensen ◽  
Anne-Mette Hvas
Keyword(s):  
Platelet Aggregation ◽  
Roc Curve ◽  
Area Under The Curve ◽  
Reference Method ◽  
Adenosine Diphosphate ◽  
Blood Platelet ◽  
Impedance Method ◽  
Healthy Individuals ◽  
Operating Characteristics ◽  
Normal Platelet

Abstract The inhibition of platelet aggregation by aspirin (ASA) is fundamental in treatment of ischemic heart disease (IHD). Several studies report findings of normal platelet aggregation despite ASA treatment in some individuals, referred to as ASA resistance (AR). It has been hypothesized that AR increases the risk of a future ischemic event. We evaluated a new impedance method for measurement of platelet aggregation, Multiplate® aggregometry (MA), and compared this method to light aggregometry ad modum Born (OPA), with reference to repeatability and detection of AR. Blood samples from 43 IHD patients and 21 healthy individuals treated with ASA 75 mg daily were analyzed in duplicate by MA and OPA on 4 consecutive days. An additional blood sample was obtained prior to ASA treatment in the group of healthy individuals. Compliance was confirmed by measurements of thromboxane B2 in serum. MA was performed with arachidonic acid (AA) in concentrations of 0.25 mM, 0.50 mM and 0.75 mM, and with adenosine diphosphate (ADP) in concentrations of 7.5 μM and 15 μM. OPA was performed with AA-concentrations of 0.5 mM, 1.0 mM and 1.5 mM, and with ADP-concentrations of 5 μM and 10 μM. Table 1. Area under the curve (AUC) measured by MA in patients and in healthy individuals before and during ASA treatment. Agonist AUC, aggregation units · min Healthy Before ASA HealthyDuring ASA PatientsDuring ASA Median Range Median Range Median Range AA, mM 0.25 520 402–999 38 12–83 41 8–110 0.50 574 461–976 51 20–112 56 17–187 0.75 551 434–889 68 21–333 98 18–418 ADP, μM 7.5 474 272–859 422 195–816 472 126–720 15 503 328–922 479 262–995 525 172–834 In healthy individuals, the AA-induced AUC was reduced significantly by ASA at all concentrations (88–93%, p=0.0001). The reduction of AUC was small and insignificant when using ADP (5–11%, p≥0.06). There was a trend towards a higher median AUC measured in patients than in healthy individuals during ASA (p=0.07). Table 2. Coefficients of variation (CV) of double measurements determined by MA and OPA in healthy individuals prior to ASA treatment and during ASA treatment. AA, mM MA AA, mM OPA CVBefore ASA, % CVDuring ASA, % CVBefore ASA, % CVDuring ASA, % 0.25 8 46 0.5 48 25 0.50 10 40 1.0 5 20 0.75 12 41 1.5 5 21 The CV of OPA was generally lower. The reference method was OPA with AA 1.0 mM and AR was defined as a residual platelet aggregation ≥ 20%. According to this definition 7 participants (16%) had AR. A receiver operating characteristics (ROC) analysis showed a sensitivity of MA using AA 0.75 mM of 100% at an AUC cut-point of 94 aggregation units (AU) · min, 71% at 135 AU · min and 29% at 212 AU · min. The specificity was 60, 81 and 93%, respectively. The area under the ROC-curve was 0.79 (95% CI 0.66–0.92). In conclusion, the large ASA-induced reduction in AUC of healthy individuals indicated that MA measures the effect of ASA efficiently when using AA. ADP seems less suitable, as the AUC was only slightly reduced by ASA. The CV of MA was high during ASA treatment, indicating that platelet aggregation during ASA was low and difficult to measure precisely with MA. The area under the ROC-curve was moderately satisfying, but of uncertain correctness due to the rather small number of observations.

scholarly journals A new “ASAP Scoring System and Risk Table” in patients with Atypical Small Acinar Proliferation (ASAP) to predict the second prostate biopsy outcomes

2021 ◽  
Author(s):  
Caner Ediz ◽  
Serkan Akan ◽  
Neslihan Kaya Terzi ◽  
Aysenur Ihvan
Keyword(s):  
Prostate Biopsy ◽  
Roc Curve ◽  
Scoring System ◽  
Risk Group ◽  
Area Under The Curve ◽  
Threshold Value ◽  
Roc Curve Analysis ◽  
Atypical Small Acinar Proliferation ◽  
The Mean ◽  
Density Assessment

Background: To discuss the necessity of the second prostate biopsy in the patients with atypical small acinar proliferation (ASAP) and to develop a scoring system and risk table as a new re-biopsy criteria. Methods: 2845 patients who were performed transrectal ultrasonography-guided prostate biopsy between January 2008 and May 2019 were evaluated. 128 patients, whose data were reached, were enrolled into the study. Before the first and the second biopsy, tPSA, fPSA, f/tPSA rate and PSA-Density assessment and changes in these parameters between the two biopsies were recorded. “ASAP Scoring System and risk table” (ASS-RT) was evaluated before the second biopsy. Results: The mean age of 128 patients with ASAP was 62.9±7.8 years. The ASS-RT scores of the patients with PCa were statistically significantly higher than the patients with non-PCa (p: 0.001). In the ROC curve analysis of ASS-RT, area under the curve was 0.804 and the standard error was 0.04. The area under the ROC curve was significantly higher than 0.5 (p:0.001). The cut-off point of ASS-RT score in diagnosis of malignancy was ≥ 7. The sensitivity of this value was found to be 60.8% and its specificity as 80.5%. Conclusions: The threshold value for the ASS-RT score may be used as 7 and the second biopsy may be performed immediately to patients over this value. We think that there may be no need for a second biopsy if the ASS-RT score under the 7 (especially low-risk group) before the second biopsy.

scholarly journals The Prognostic Value of the Results of 123I-metaiodobenzylguanidine Myocardial Scintigraphy in the Examination of Patients with Atrial Fibrillation Referred for Its Interventional Treatment

2019 ◽  
Vol 100 (5) ◽  
pp. 247-253
Author(s):  
Yu. V. Varlamova ◽  
Yu. B. Lishmanov ◽  
I. V. Kisteneva
Keyword(s):  
Atrial Fibrillation ◽  
Roc Curve ◽  
Sympathetic Innervation ◽  
Threshold Value ◽  
Myocardial Scintigraphy ◽  
Washout Rate ◽  
Interventional Treatment ◽  
Area Under Roc Curve ◽  
One Year ◽  
Radionuclide Scanning

Objective. To identify the scintigraphic predictors of the efficiency of interventional treatment for atrial fibrillation (AF) by cardiac 123I-metaiodobenzylguanidine (123I-MIBG) radionuclide scanning.Material and methods. The investigation enrolled 35 patients with AF concurrent with hypertensive disease (HD): 17 persons with persistent AF (PAF) and 18 patients with long-standing PAF (LPAF). In addition, 10 patients with HD without arrhythmia signs were examined as a comparison group. All the patients with AF before radiofrequency ablation (RFA) and those with sinus rhythm underwent 123I-MIBG myocardial scintigraphy to assess the sympathetic innervation of the heart. The efficiency of RFA was evaluated after 12 months by 24-hour ECG monitoring.Results. The patients of both groups were divided into subgroups according to the presence of recurrent arrhythmia one year after interventional treatment. ROC analysis could determine the main scintigraphic predictors of the efficiency of RFA. The preoperative indicators, in which the subgroups with and without recurrent AF showed significant differences, were studied. In the patients with PAF, the delayed Heart/ Mediastinum (H/M) ratio cutoff was ≥1.55 (the area under the ROC curve was 0.929; 100% sensitivity and 57% specificity), and the threshold value of 123I-MIBG washout rate was ≤22.3% (the area under ROC curve was 0.957; 100% sensitivity and 43% specificity) may suggest that RFA is effective. In the patients with LPAF, the threshold values of early H/M ratio were ≥1.69 (the area under the ROC curve was 0.849; 100% sensitivity and 62% specificity) and those of delayed H/M ratio were ≥1.66 (the area under the ROC curve was 0.938; 94% sensitivity and 23% specificity) allow the prediction of a risk for postoperative recurrent AF.Conclusion. The findings suggest that 123I-MIBG scintigraphy can be used to predict a high risk for recurrent AF after RFA of the pathological pathways of a pulse in the myocardium.

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