scholarly journals Maximal kidney length predicts need for native nephrectomy in ADPCKD patients undergoing renal transplantation

2014 ◽  
Vol 8 (7-8) ◽  
pp. 278 ◽  
Author(s):  
Octav Cristea ◽  
Daniel Yanko ◽  
Sarah Felbel ◽  
Andrew House ◽  
Alp Sener ◽  
...  
Keyword(s):  
Renal Transplantation ◽  
Roc Curve ◽  
Test Performance ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Roc Curves ◽  
Clinical Tool ◽  
Roc Curve Analysis ◽  
Kidney Length ◽  
Autosomal Dominant Polycystic Kidney

Introduction: Native nephrectomy in patients with autosomal dominant polycystic kidney disease (ADPKD) is performed on a case-by-case basis. We determine if pre-transplant maximal kidney length (MKL) can be used to predict ultimate nephrectomy status.Methods: We performed a retrospective review of ADPKD patients who underwent renal transplantation at our centre between January2000 and December 2012. Pre-transplant measurements of MKL alone, MKL adjusted for height (HtMKL), weight (WtMKL) and body mass index (BMI-MKL) were each assessed for their predictive ability via a receiver operating characteristic (ROC) curve analysis.Results: In total, 84 patients met our inclusion criteria, of which17 (20.2%) underwent native nephrectomy. An MKL ROC curve analysis revealed an area under the curve (AUC) of 0.867 (95% confidence interval [CI] 0.775–0.931; p < 0.001). An optimal cut-off criterion of >21.5 cm revealed a sensitivity of 94.1% (95% CI 71.3–99.9) and specificity of 70.1% (95% CI 57.7–80.7) for eventual nephrectomy. The AUC of HtMKL, WtMKL and BMI-MKL ROC curves did not differ significantly from MKL alone. HtMKL improved specificity, but not overall test performance. The determination of the cut-off MKL may be influenced by the single-centre retrospective nature of this analysis, as well as the fact that renal size was determined by ultrasound and not computerized tomography or magnetic resonance imaging.Conclusion: MKL in patients with ADPKD is associated with the eventual need for nephrectomy and may be a useful clinical tool to risk stratify these patients and therefore guide patient conversations to a decision to leave the native kidneys in situ.

14-3-3η Autoantibodies: Diagnostic Use in Early Rheumatoid Arthritis

2015 ◽  
Vol 42 (9) ◽  
pp. 1587-1594 ◽  
Author(s):  
Walter P. Maksymowych ◽  
Gilles Boire ◽  
Dirkjan van Schaardenburg ◽  
Stephanie Wichuk ◽  
Samina Turk ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Early Rheumatoid Arthritis ◽  
Roc Curve ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Healthy Controls ◽  
Likelihood Ratios ◽  
Roc Curve Analysis ◽  
Diagnostic Use ◽  
Early Ra

Objective.To describe the expression and diagnostic use of 14-3-3η autoantibodies in early rheumatoid arthritis (RA).Methods.14-3-3η autoantibody levels were measured using an electrochemiluminescent multiplexed assay in 500 subjects (114 disease-modifying antirheumatic drug-naive patients with early RA, 135 with established RA, 55 healthy, 70 autoimmune, and 126 other non-RA arthropathy controls). 14-3-3η protein levels were determined in an earlier analysis. Two-tailed Student t tests and Mann-Whitney U tests compared differences among groups. Receiver-operator characteristic (ROC) curves were generated and diagnostic performance was estimated by area under the curve (AUC), as well as specificity, sensitivity, and likelihood ratios (LR) for optimal cutoffs.Results.Median serum 14-3-3η autoantibody concentrations were significantly higher (p < 0.0001) in patients with early RA (525 U/ml) when compared with healthy controls (235 U/ml), disease controls (274 U/ml), autoimmune disease controls (274 U/ml), patients with osteoarthritis (259 U/ml), and all controls (265 U/ml). ROC curve analysis comparing early RA with healthy controls demonstrated a significant (p < 0.0001) AUC of 0.90 (95% CI 0.85–0.95). At an optimal cutoff of ≥ 380 U/ml, the ROC curve yielded a sensitivity of 73%, a specificity of 91%, and a positive LR of 8.0. Adding 14-3-3η autoantibodies to 14-3-3η protein positivity enhanced the identification of patients with early RA from 59% to 90%; addition of 14-3-3η autoantibodies to anticitrullinated protein antibodies (ACPA) and/or rheumatoid factor (RF) increased identification from 72% to 92%. Seventy-two percent of RF- and ACPA-seronegative patients were positive for 14-3-3η autoantibodies.Conclusion.14-3-3η autoantibodies, alone and in combination with the 14-3-3η protein, RF, and/or ACPA identified most patients with early RA.

scholarly journals Saliva RNA biomarkers predict concussion duration and detect symptom recovery: a comparison with balance and cognitive testing

2021 ◽  
Author(s):  
Gregory Fedorchak ◽  
Aakanksha Rangnekar ◽  
Cayce Onks ◽  
Andrea C. Loeffert ◽  
Jayson Loeffert ◽  
...  
Keyword(s):  
Test Performance ◽  
Area Under The Curve ◽  
Prediction Rule ◽  
Cognitive Testing ◽  
Cognitive Test ◽  
Clinical Tool ◽  
Post Injury ◽  
Symptom Recovery ◽  
Cognitive Test Performance

Abstract Objective The goals of this study were to assess the ability of salivary non-coding RNA (ncRNA) levels to predict post-concussion symptoms lasting ≥ 21 days, and to examine the ability of ncRNAs to identify recovery compared to cognition and balance. Methods RNA sequencing was performed on 505 saliva samples obtained longitudinally from 112 individuals (8–24-years-old) with mild traumatic brain injury (mTBI). Initial samples were obtained ≤ 14 days post-injury, and follow-up samples were obtained ≥ 21 days post-injury. Computerized balance and cognitive test performance were assessed at initial and follow-up time-points. Machine learning was used to define: (1) a model employing initial ncRNA levels to predict persistent post-concussion symptoms (PPCS) ≥ 21 days post-injury; and (2) a model employing follow-up ncRNA levels to identify symptom recovery. Performance of the models was compared against a validated clinical prediction rule, and balance/cognitive test performance, respectively. Results An algorithm using age and 16 ncRNAs predicted PPCS with greater accuracy than the validated clinical tool and demonstrated additive combined utility (area under the curve (AUC) 0.86; 95% CI 0.84–0.88). Initial balance and cognitive test performance did not differ between PPCS and non-PPCS groups (p > 0.05). Follow-up balance and cognitive test performance identified symptom recovery with similar accuracy to a model using 11 ncRNAs and age. A combined model (ncRNAs, balance, cognition) most accurately identified recovery (AUC 0.86; 95% CI 0.83–0.89). Conclusions ncRNA biomarkers show promise for tracking recovery from mTBI, and for predicting who will have prolonged symptoms. They could provide accurate expectations for recovery, stratify need for intervention, and guide safe return-to-activities.

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 Evaluation of prediction score of contrast-induced nephropathy in inpatients undergone to digital or CT angiography

2020 ◽  
Vol 10 (3) ◽  
pp. 78-84
Author(s):  
Seleno Glauber de Jesus-Silva ◽  
Ana Elisa Chaves ◽  
Caio Augusto Alves Maciel ◽  
Edson Eziel Ferreira Scotini ◽  
Pablo Girardelli Mendonça Mesquita ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Roc Curve ◽  
Computed Tomography Angiography ◽  
Score Test ◽  
Area Under The Curve ◽  
Roc Curve Analysis ◽  
Contrast Induced Nephropathy ◽  
Mean Values ◽  
Iodinated Contrast ◽  
The Mean

Objectives: To assess the incidence of contrast-induced nephropathy (CIN) and determine the Mehran Score's (MS) ability to predict CIN in patients undergoing digital angiography or computed tomography angiography. Methods: 252 medical records of inpatients who underwent DA or CTA over 28 months in a quaternary hospital were reviewed. CIN was defined as serum creatinine> 0.5 mg / dL or > 25% increase in baseline creatinine, 48 h after administration of iodinated contrast. The ROC curve and the area under the curve (AUC) were used as a score test. Results: The majority (159; 63.1%) were male, and the average age was 60.4 years. Anemia, diabetes mellitus, and age > 75 years were the most prevalent factors. The incidence of CIN was 17.8% (n = 45). There was a decrease in the mean values ​​of creatinine pre and post among patients who did not suffer CIN (1.38 ± 1.22 vs 1.19 ± 0.89; t = 3.433; p = 0.0007), while among patients who suffering CIN, the mean increase was 1.03 mg / dL (1.43 ± 1.48 vs 2.46 ± 2.35 mg / dL; t = 5.44; p = 0.117). The ROC curve analysis identified a low correlation between MS and the occurrence of CIN (AUC = 0.506). Conclusion: The incidence of CIN in hospitalized patients undergoing angiography or computed tomography angiography was high. The EM did not allow the prediction of NIC.

scholarly journals Using Circ-ANAPC7 as a Novel Type of Biomarker in the Monitoring of Acute Myeloid Leukemia

2021 ◽  
pp. 1-7
Author(s):  
Ying Shen ◽  
Yachun Jia ◽  
Ru Zhang ◽  
Hongli Chen ◽  
Yuandong Feng ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Roc Curve ◽  
Myeloid Leukemia ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Circular Rnas ◽  
Transcriptional Level ◽  
Roc Curve Analysis ◽  
Cell Counts ◽  
Acute Myeloid

<b><i>Introduction:</i></b> Circular RNAs (circRNAs) are a novel class of RNAs which occupy gene expression at the transcriptional or post-transcriptional level, involve in many physiological processes, and participate in many diseases, especially in cancer. Our previous study showed 1 altered circRNA named circ-anaphase promoting complex subunit 7 (ANAPC7) that was upregulated in acute myeloid leukemia (AML). To further clear the expression and clinical significance of circ-ANAPC7, we enlarged the sample size and illuminated the diagnostic and monitoring value of circ-ANAPC7 in AML. <b><i>Methods:</i></b> Real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was supposed to confirm the expression of circ-ANAPC7 of AML patients. We assessed the correlation of circ-ANAPC7 and clinical variables using the Spearman correlation test. The receiver operating characteristic (ROC) curve was carried out to evaluate the diagnostic value. <b><i>Results:</i></b> Circ-ANAPC7 was first found to be upregulated in AML, and its expression was correlated to white blood cell counts in peripheral blood and blast percentage in bone marrow. ROC curve analysis revealed that circ-ANAPC7 has a significant value of auxiliary AML diagnosis (area under the curve = 0.915, <i>p</i> &#x3c; 0.001). Furthermore, the expression level of circ-ANAPC7 was changed accompanied with disease condition transformation. <b><i>Conclusion:</i></b> Circ-ANAPC7 was upregulated in newly diagnosed and relapsed AML. It may serve as potential biomarkers for AML patient’s diagnosis and monitoring.

scholarly journals What are the optimal cut-off points of anthropometric indices for prediction of overweight and obesity? Predictive validity of waist circumference, waist-to-hip and waist-to-height ratios

2020 ◽  
Vol 10 (2) ◽  
pp. 142-147 ◽  
Author(s):  
Helda Tutunchi ◽  
Mehrangiz Ebrahimi-Mameghani ◽  
Alireza Ostadrahimi ◽  
Mohammad Asghari-Jafarabadi
Keyword(s):  
Waist Circumference ◽  
Roc Curve ◽  
Predictive Ability ◽  
Diagnostic Value ◽  
Cross Sectional Study ◽  
Overweight And Obesity ◽  
Roc Curve Analysis ◽  
Anthropometric Indices ◽  
Cross Sectional ◽  
Anthropometric Indicators

Background: Planning for obesity prevention is an important global health priority. Our aim in this study was to find the optimal cut-off points of waist circumference (WC), waist- to- hipratio (WHR) and waist- to- height ratio (WHtR), as three anthropometric indices, for prediction of overweight and obesity. We also aimed to compare the predictive ability of these indices to introduce the best choice. Methods: In this cross-sectional study, a total of 500 subjects were investigated. Anthropometric indicators were measured using a standard protocol. We considered body mass index (BMI) as the simple and most commonly used index for measuring general obesity as the comparison indicator in the present study to assess the diagnostic value for other reported obesity indices.We also performed receiver operating characteristic (ROC) curve analysis to define the optimal cut-off points of the anthropometric indicators and the best indices for overweight and obesity. Results: The proposed optimal cut-offs for WC, WHtR, and WHR were 84 cm, 0.48 and 0.78for women and 98 cm, 0.56 and 0.87 for men, respectively. The area under the ROC curve ofWHtR (women: AUC=0.97, 95% CI: 0.96-0.99 vs. men: AUC=0.97, 95%CI: 0.96-0.99) and WC(women: AUC=0.97, 95% CI, 0.95-0.99 vs. men: AUC=0.98, 95% CI: 0.97-0.99) were greater than WHR (women: AUC=0.79, 95% CI =0.74-0.85 vs. men: AUC=0.84, 95% CI=0.79-0.88). Conclusion: This study demonstrated that the WC and WHtR indicators are stronger indicators compared to the others. However, further studies using desirable and also local cutoffs against more accurate techniques for body fat measurement such as computerized tumor (CT) scans and dual-energy x-ray absorptiometry (DEXA) are required.

ROC Curve Analysis: An Example Showing the Relationships Among Serum Lipid and Apolipoprotein Concentrations in Identifying Patients with Coronary Artery Disease

1992 ◽  
Vol 38 (8) ◽  
pp. 1425-1428 ◽  
Author(s):  
M H Zweig ◽  
S K Broste ◽  
R A Reinhart
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Roc Curve ◽  
Serum Lipid ◽  
Fundamental Property ◽  
Roc Curves ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Clinical Sensitivity ◽  
Artery Disease

Abstract Clinical accuracy, defined as the ability to discriminate between states of health, is the fundamental property of any diagnostic test or system. It is readily expressed as clinical sensitivity and specificity, and elegantly represented by the receiver operating characteristic (ROC) curve. To demonstrate the use of ROC curves, we reexamine a study of the ability of serum lipid and apolipoprotein measures to discriminate among degrees of coronary artery disease in patients undergoing coronary angiography. ROC curve analysis reveals that none of these indexes is highly accurate, but demonstrates a modest increase in the accuracy of apolipoprotein over lipid indexes.

scholarly journals Simultaneous external validation of various cardiac arrest prognostic scores: a single-center retrospective study

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Takumi Tsuchida ◽  
Kota Ono ◽  
Kunihiko Maekawa ◽  
Takeshi Wada ◽  
Kenichi Katabami ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Roc Curve ◽  
External Validation ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Prognostic Scores ◽  
Low Flow ◽  
Neurological Outcomes ◽  
Shockable Rhythm ◽  
End Stage

Abstract Background This study aimed to compare and validate the out-of-hospital cardiac arrest (OHCA); cardiac arrest hospital prognosis (CAHP); non-shockable rhythm, unwitnessed arrest, long no-flow or long low-flow period, blood pH < 7.2, lactate > 7.0 mmol/L, end-stage chronic kidney disease, age ≥ 85 years, still resuscitation, and extracardiac cause (NULL-PLEASE) clinical; post-cardiac arrest syndrome for therapeutic hypothermia (CAST); and revised CAST (rCAST) scores in OHCA patients treated with recent cardiopulmonary resuscitation strategies. Methods We retrospectively collected data on adult OHCA patients admitted to our emergency department between February 2015 and July 2018. OHCA, CAHP, NULL-PLEASE clinical, CAST, and rCAST scores were calculated based on the data collected. The predictive abilities of each score were tested using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Results We identified 236 OHCA patients from computer-based medical records and analyzed 189 without missing data. In OHCA patients without bystander witnesses, CAHP and OHCA scores were not calculated. Although the predictive abilities of the scores were not significantly different, the NULL-PLEASE score had a large AUC of ROC curve in various OHCA patients. Furthermore, in patients with bystander-witnessed OHCA, the NULL-PLEASE score had large partial AUCs of ROC from sensitivity 0.8–1.0 and specificity 0.8–1.0. Conclusions The NULL-PLEASE score had a high, comprehensive predictive ability in various OHCA patients. Furthermore, the NULL-PLEASE score had a high predictive ability for good and poor neurological outcomes in patients with bystander-witnessed OHCA.

scholarly journals Serum Globulin and Albumin to Globulin Ratio as Potential Diagnostic Biomarkers for Periprosthetic Joint Infection: A Retrospective Review

2020 ◽  
Author(s):  
Yongyu Ye ◽  
Weishen Chen ◽  
Minghui Gu ◽  
Guoyan Xian ◽  
Baiqi Pan ◽  
...  
Keyword(s):  
Roc Curve ◽  
Periprosthetic Joint Infection ◽  
Diagnostic Performance ◽  
Serum Proteins ◽  
Joint Infection ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Roc Curve Analysis ◽  
Serum Globulin ◽  
G Ratio

Abstract Background: Periprosthetic joint infection (PJI) has been increasingly documented; however, its preoperative accurate diagnosis remains challenging. Furthermore, there is a dire need to identify appropriate and effective biomarkers. We aimed to evaluate the relationship between globulin, albumin to globulin (A/G) ratio, and development of PJI in patients undergoing revision total joint arthroplasty (TJA).Methods: A retrospective study was conducted on patients who had undergone revision TJA between 2011 and 2018 (89 with aseptic mechanic failure and 38 with PJI). The serum proteins were explored using univariate analysis followed by multivariate logistic regression. The diagnostic performance of these proteins was assessed by the receiver operating characteristic (ROC) curve.Results: Higher globulin levels (odds ratio [OR], 1.239; P<0.001) and lower A/G ratio (OR, 0.007; P<0.001) were strongly associated with the risk of PJI. ROC curve analysis demonstrated reasonable diagnostic performance for globulin (area under the curve [AUC], 0.77; sensitivity, 78.95%; and specificity, 69.66%) and A/G ratio (AUC, 0.779; sensitivity, 65.79%; and specificity, 78.65%).Conclusions: Both globulin and A/G ratio were associated with PJI and may serve as potential adjuvant biomarkers in the diagnosis of PJI.

scholarly journals Serum Proteomic Fingerprints of Adult Patients with Severe Acute Respiratory Syndrome

2006 ◽  
Vol 52 (3) ◽  
pp. 421-429 ◽  
Author(s):  
Ronald TK Pang ◽  
Terence CW Poon ◽  
KC Allen Chan ◽  
Nelson LS Lee ◽  
Rossa WK Chiu ◽  
...  
Keyword(s):  
Viral Load ◽  
Severe Acute Respiratory Syndrome ◽  
Roc Curve ◽  
Serum Proteins ◽  
Early Stage ◽  
High Specificity ◽  
Roc Curves ◽  
Roc Curve Analysis ◽  
Outbreak Period ◽  
Specificity And Sensitivity

Abstract Background: Severe acute respiratory syndrome (SARS) is an emerging infectious disease caused by a new coronavirus strain, SARS-CoV. Specific proteomic patterns might be present in serum in response to the infection and could be useful for early detection of the disease. Methods: Using surface-enhanced laser desorption/ionization (SELDI) ProteinChip technology, we profiled and compared serum proteins of 39 patients with early-stage SARS infection and 39 non-SARS patients who were suspected cases during the SARS outbreak period. Proteomic patterns associated with SARS were identified by bioinformatic and biostatistical analyses. Features of interest were then purified and identified by tandem mass spectrometry. Results: Twenty proteomic features were significantly different between the 2 groups. Fifteen were increased in the SARS group, and 5 were decreased. Their concentrations were correlated with 2 or more clinical and/or biochemical variables. Two were correlated with the SARS-CoV viral load. Hierarchical clustering analysis showed that a majority of the SARS patients (95%) had similar serum proteomic profiles and identified 2 subgroups with poor prognosis. ROC curve analysis identified individual features as potential biomarkers for SARS diagnosis (areas under ROC curves, 0.733–0.995). ROC curve areas were largest for an N-terminal fragment of complement C3c α chain (m/z 28 119) and an internal fragment of fibrinogen α-E chain (m/z 5908). Immunoglobulin κ light chain (m/z 24 505) positively correlated with viral load. Conclusions: Specific proteomic fingerprints in the sera of adult SARS patients could be used to identify SARS cases early during onset with high specificity and sensitivity.

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