The Performance and Interrater Agreement of Vibration Perception for the Diagnosis of Loss of Protective Sensation in People With Diabetes Mellitus

2021 ◽  
pp. 153473462199405
Author(s):  
Anastasios Tentolouris ◽  
Nikolaos Tentolouris ◽  
Ioanna Eleftheriadou ◽  
Edward B. Jude
Keyword(s):  
Health Care ◽  
Receiver Operating Characteristic ◽  
Health Care Professionals ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Tuning Fork ◽  
Interrater Agreement ◽  
Protective Sensation ◽  
Loss Of Protective Sensation ◽  
Receiver Operating

This study examined the performance of VibraTip for the diagnosis of loss of protective sensation (LOPS) and the interrater agreement of different neurological modalities performed by 3 health care professionals, a consultant diabetologist, a diabetes specialist nurse, and a podiatrist. Diagnosis of LOPS was based on 10-g Semmes Weinstein monofilament testing performed by a consultant diabetologist (reference method), while examination with a 128-Hz tuning form was also performed. The performance of VibraTip for the diagnosis of LOPS was examined using the receiver operating characteristic curves analysis. Interrater agreement was determined by weighted kappa (κ) statistics. Diagnosis of LOPS (%) was 37.5%. Receiver operating characteristic curve analysis showed that VibraTip examination versus 10-g monofilament, both performed by a consultant, could diagnose LOPS ( P < .001). Sensitivity, specificity, positive predictive value, and negative predictive value of VibraTip versus 10-g monofilament, both performed by a consultant (value, 95% confidence interval), was 0.705 (0.591-0.803), 0.836 (0.758-0.897), 0.733 (0.642-0.808), and 0.816 (0.757-0.863), respectively. The interrater agreement among the health care professionals for 10-g monofilament, VibraTip, and 128-Hz tuning fork in neurological assessment was good with κ > 0.61. VibraTip can be used as a screening tool for the detection of LOPS. There was good overall agreement in the results of neurological examination using 10-g monofilament, 128-Hz tuning fork, and VibraTip among health care professionals.

scholarly journals Age-Adjusted Endothelial Activation and Stress Index for Coronavirus Disease 2019 at Admission Is a Reliable Predictor for 28-Day Mortality in Hospitalized Patients With Coronavirus Disease 2019

2021 ◽  
Vol 8 ◽  
Author(s):  
Felipe Pérez-García ◽  
Rebeca Bailén ◽  
Juan Torres-Macho ◽  
Amanda Fernández-Rodríguez ◽  
Maria Ángeles Jiménez-Sousa ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Receiver Operating Characteristic ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Predictive Performance ◽  
Endothelial Activation ◽  
Stress Index ◽  
Reliable Predictor ◽  
Receiver Operating

Background: Endothelial Activation and Stress Index (EASIX) predict death in patients undergoing allogeneic hematopoietic stem cell transplantation who develop endothelial complications. Because coronavirus disease 2019 (COVID-19) patients also have coagulopathy and endotheliitis, we aimed to assess whether EASIX predicts death within 28 days in hospitalized COVID-19 patients.Methods: We performed a retrospective study on COVID-19 patients from two different cohorts [derivation (n = 1,200 patients) and validation (n = 1,830 patients)]. The endpoint was death within 28 days. The main factors were EASIX [(lactate dehydrogenase * creatinine)/thrombocytes] and aEASIX-COVID (EASIX * age), which were log2-transformed for analysis.Results: Log2-EASIX and log2-aEASIX-COVID were independently associated with an increased risk of death in both cohorts (p &lt; 0.001). Log2-aEASIX-COVID showed a good predictive performance for 28-day mortality both in the derivation cohort (area under the receiver-operating characteristic = 0.827) and in the validation cohort (area under the receiver-operating characteristic = 0.820), with better predictive performance than log2-EASIX (p &lt; 0.001). For log2 aEASIX-COVID, patients with low/moderate risk (&lt;6) had a 28-day mortality probability of 5.3% [95% confidence interval (95% CI) = 4–6.5%], high (6–7) of 17.2% (95% CI = 14.7–19.6%), and very high (&gt;7) of 47.6% (95% CI = 44.2–50.9%). The cutoff of log2 aEASIX-COVID = 6 showed a positive predictive value of 31.7% and negative predictive value of 94.7%, and log2 aEASIX-COVID = 7 showed a positive predictive value of 47.6% and negative predictive value of 89.8%.Conclusion: Both EASIX and aEASIX-COVID were associated with death within 28 days in hospitalized COVID-19 patients. However, aEASIX-COVID had significantly better predictive performance than EASIX, particularly for discarding death. Thus, aEASIX-COVID could be a reliable predictor of death that could help to manage COVID-19 patients.

scholarly journals Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Vincent J. Major ◽  
Yindalon Aphinyanaphongs
Keyword(s):  
Positive Predictive Value ◽  
Receiver Operating Characteristic ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Medical Center ◽  
Academic Medical Center ◽  
Model Performance ◽  
Risk Of Death ◽  
Temporal Validation ◽  
Receiver Operating

Abstract Background Automated systems that use machine learning to estimate a patient’s risk of death are being developed to influence care. There remains sparse transparent reporting of model generalizability in different subpopulations especially for implemented systems. Methods A prognostic study included adult admissions at a multi-site, academic medical center between 2015 and 2017. A predictive model for all-cause mortality (including initiation of hospice care) within 60 days of admission was developed. Model generalizability is assessed in temporal validation in the context of potential demographic bias. A subsequent prospective cohort study was conducted at the same sites between October 2018 and June 2019. Model performance during prospective validation was quantified with areas under the receiver operating characteristic and precision recall curves stratified by site. Prospective results include timeliness, positive predictive value, and the number of actionable predictions. Results Three years of development data included 128,941 inpatient admissions (94,733 unique patients) across sites where patients are mostly white (61%) and female (60%) and 4.2% led to death within 60 days. A random forest model incorporating 9614 predictors produced areas under the receiver operating characteristic and precision recall curves of 87.2 (95% CI, 86.1–88.2) and 28.0 (95% CI, 25.0–31.0) in temporal validation. Performance marginally diverges within sites as the patient mix shifts from development to validation (patients of one site increases from 10 to 38%). Applied prospectively for nine months, 41,728 predictions were generated in real-time (median [IQR], 1.3 [0.9, 32] minutes). An operating criterion of 75% positive predictive value identified 104 predictions at very high risk (0.25%) where 65% (50 from 77 well-timed predictions) led to death within 60 days. Conclusion Temporal validation demonstrates good model discrimination for 60-day mortality. Slight performance variations are observed across demographic subpopulations. The model was implemented prospectively and successfully produced meaningful estimates of risk within minutes of admission.

scholarly journals 215 Assessment of the Diagnostic Sensitivity and Specificity of Pain Biomarkers in Cattle Using Receiver Operating Characteristic Curves

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 7-8
Author(s):  
Miriam S Martin ◽  
Michael Kleinhenz ◽  
Karen Schwartzkopf-Genswein ◽  
Johann Coetzee
Keyword(s):  
Diagnostic Accuracy ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Predictive Value ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Diagnostic Sensitivity ◽  
Diagnostic Sensitivity And Specificity ◽  
Good Diagnostic Accuracy ◽  
Receiver Operating

Abstract Biomarkers are commonly used to assess pain and analgesic drug efficacy in livestock. However, the diagnostic sensitivity and specificity of these biomarkers for different pain conditions over time have not been described. Receiver operating characteristic (ROC) curves are graphical plots that illustrate the diagnostic ability of a test as its discrimination threshold is varied. The objective of this analysis was to use area under the curve (AUC) values derived from ROC analysis to assess the predictive value of pain biomarkers at specific timepoints. The biomarkers included in the analysis were blood cortisol, salivary cortisol, hair cortisol, infrared thermography (IRT), mechanical nociceptive threshold (MNT), substance P, and outcomes from a pressure/force measurement system and visual analog scale. A total sample size of 7,992 biomarker outcomes were collected from 6 pain studies involving pain associated with castration, dehorning, lameness, and surgery were included in the analysis. Each study consisted of three treatments; pain, no pain, and analgesia. All statistics were performed using statistical software (JMP Pro 14.0, SAS Institute, Inc., Cary, NC). Results comparing analgesia verses pain yielded good diagnostic accuracy (AUC &gt; 0.7; 95% CI: 0.40 to 0.99) for blood cortisol (timepoints 1.5, 2, and 6 hours); IRT (timepoints 6, 8, 12, and 72 hours); and MNT (timepoints 6, 25, and 49 hours). These results indicate that ROC analysis can be a useful indicator of the predictive value of pain biomarkers and certain timepoints seem to yield good diagnostic accuracy while many do not.

scholarly journals Predictive value of a novel lncRNA LINC02518 in evaluating the prognosis of patients with hepatocellular carcinoma

2021 ◽  
Author(s):  
Wei Cui ◽  
Jingzhi Huang ◽  
Ruiqi Wang ◽  
Yu Wang ◽  
Xiaoming Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Predictive Value ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Aim: The potential of long noncoding RNA in hepatocellular carcinoma (HCC) has led to promising insights into therapeutic intervention. The clinical significance of LINC02518 in HCC is unclear. This study aimed to evaluate the predictive value of a novel long noncoding RNA, LINC02518, for the prognosis of patients with HCC. Methods: Between December 2005 and November 2011, 125 and 75 HCC patients in the training and validation groups, respectively, who underwent liver surgery were included in our study. The LINC02518 expression of HCC and corresponding nontumor liver tissues was detected using microarray and reverse transcription quantitative polymerase chain reaction (RT-qPCR). These HCC patients were assigned into high and low LINC02518 expression groups based on the threshold of the receiver operating characteristic curve. Kaplan-Meier analysis was performed to determine the prognosis of HCC patients. Results: LINC02518 expression was upregulated in paired tumor samples compared with corresponding nontumor samples in the two groups. The area under the receiver operating characteristic curve for the levels of LINC02518 in the diagnosis of HCC was 0.66, 95% CI: 0.59–0.73. HCC patients with high LINC02518 expression had significantly worse tumor recurrence-free, metastasis-free, disease-free and overall survival than those with low LINC02518 expression. Conclusion: LINC02518 is negatively correlated with the prognosis of HCC and provides a promising strategy for the treatment and prognosis of HCC.

scholarly journals “Emergency Room Evaluation and Recommendations” (ER2) Tool for the Screening of Older Emergency Department Visitors With Major Neurocognitive Disorders: Results From the ER2 Database

2022 ◽  
Vol 12 ◽  
Author(s):  
Olivier Beauchet ◽  
Liam A. Cooper-Brown ◽  
Joshua Lubov ◽  
Gilles Allali ◽  
Marc Afilalo ◽  
...  
Keyword(s):  
Emergency Department ◽  
High Risk ◽  
Emergency Room ◽  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Neurocognitive Disorders ◽  
Risk Level ◽  
Receiver Operating

Purpose: The Emergency Room Evaluation and Recommendation (ER2) is an application in the electronic medical file of patients visiting the Emergency Department (ED) of the Jewish General Hospital (JGH; Montreal, Quebec, Canada). It screens for older ED visitors at high risk of undesirable events. The aim of this study is to examine the performance criteria (i.e., sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], positive likelihood ratio [LR+], negative likelihood ratio [LR-] and area under the receiver operating characteristic curve [AUROC]) of the ER2 high-risk level and its “temporal disorientation” item alone to screen for major neurocognitive disorders in older ED visitors at the JGH.Methods: Based on a cross-sectional design, 999 older adults (age 84.9 ± 5.6, 65.1% female) visiting the ED of the JGH were selected from the ER2 database. ER2 was completed upon the patients' arrival at the ED. The outcomes were ER2's high-risk level, the answer to ER2's temporal disorientation item (present vs. absent), and the diagnosis of major neurocognitive disorders (yes vs. no) which was confirmed when it was present in a letter or other files signed by a physician.Results: The sensitivities of both ER2's high-risk level and temporal disorientation item were high (≥0.91). Specificity, the PPV, LR+, and AROC were higher for the temporal disorientation item compared to ER2's high-risk level, whereas a highest sensitivity, LR-, and NPV were obtained with the ER2 high-risk level. Both area under the receiver operating characteristic curves were high (0.71 for ER2's high-risk level and 0.82 for ER2 temporal disorientation item). The odds ratios (OR) of ER2's high-risk level and of temporal disorientation item for the diagnosis of major neurocognitive disorders were positive and significant with all OR above 18, the highest OR being reported for the temporal disorientation item in the unadjusted model [OR = 26.4 with 95% confidence interval (CI) = 17.7–39.3].Conclusion: Our results suggest that ER2 and especially its temporal disorientation item may be used to screen for major neurocognitive disorders in older ED users.

scholarly journals Clinical Significance of Serum HE4, CA125, CA724, and CA19-9 in Patients With Endometrial Cancer

2016 ◽  
Vol 16 (4) ◽  
pp. 435-439 ◽  
Author(s):  
Jing Bian ◽  
Xiaoxu Sun ◽  
Bo Li ◽  
Liang Ming
Keyword(s):  
Endometrial Cancer ◽  
Receiver Operating Characteristic ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
International Federation ◽  
Characteristic Analysis ◽  
Predictive Values ◽  
Gynecology And Obstetrics ◽  
Receiver Operating

Purpose: Serum markers with increased sensitivity and specificity for endometrial cancer are required. To date, no good marker has met this standard. The aims of our study were to evaluate the utility of tumor markers HE4, CA125, CA724, and CA19-9 as potential markers in patients diagnosed with endometrial cancer. Methods: Blood samples from 105 patients with endometrial cancer and 87 healthy women were analyzed by Roche electrochemiluminescent immunoassay, and serum values were measured for the following biomarkers: HE4, CA125, CA724, and CA19-9. Results: Serum HE4, CA125, CA724, and CA19-9 concentrations were significantly higher in patients with endometrial cancer, compared with controls ( P < .001). In the receiver operating characteristic analysis, the area under the curve value for combination of HE4, CA125, CA724, and CA19-9 was 82.1% (95% confidence interval: 75.3%-86.2%), the maximum area of the test groups. For all stages of patients with endometrial cancer, HE4 had higher sensitivity (58%), positive predictive value (60%), and negative predictive value (67%) than any other single tumor marker, and in the combination of HE4, CA125, CA724, and CA19-9, the sensitivity and positive predictive values reached 59.1% and 88%, respectively. Meanwhile, the receiver operating characteristic area under the curve of the combination of the 4 markers was significantly increased than any other group, either in stage I or in stage II to IV cases. HE4 and CA125 both correlate with advanced age; in addition, HE4 was related to pathology subtypes and positive adnexal involvement, CA125 was related to International Federation of Gynecology and Obstetrics stage, CA19-9 was related to International Federation of Gynecology and Obstetrics stage, and CA724 was correlated with positive lymph node. Conclusion: Combination of HE4, CA125, CA724, and CA19-9 has the highest value in diagnosing endometrial cancer, and they can be a useful tissue immune marker for patients with endometrial cancer.

scholarly journals Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients

2020 ◽  
pp. 1-8
Author(s):  
Hai Hu ◽  
Ni Yao ◽  
Yanru Qiu
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Early Warning ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Early Warning Score ◽  
Early Warning Scores ◽  
Operating Characteristic Curve ◽  
Receiver Operating

ABSTRACT Objectives: A simple evaluation tool for patients with novel coronavirus disease 2019 (COVID-19) could assist the physicians to triage COVID-19 patients effectively and rapidly. This study aimed to evaluate the predictive value of 5 early warning scores based on the admission data of critical COVID-19 patients. Methods: Overall, medical records of 319 COVID-19 patients were included in the study. Demographic and clinical characteristics on admission were used for calculating the Standardized Early Warning Score (SEWS), National Early Warning Score (NEWS), National Early Warning Score2 (NEWS2), Hamilton Early Warning Score (HEWS), and Modified Early Warning Score (MEWS). Data on the outcomes (survival or death) were collected for each case and extracted for overall and subgroup analysis. Receiver operating characteristic curve analyses were performed. Results: The area under the receiver operating characteristic curve for the SEWS, NEWS, NEWS2, HEWS, and MEWS in predicting mortality were 0.841 (95% CI: 0.765-0.916), 0.809 (95% CI: 0.727-0.891), 0.809 (95% CI: 0.727-0.891), 0.821 (95% CI: 0.748-0.895), and 0.670 (95% CI: 0.573-0.767), respectively. Conclusions: SEWS, NEWS, NEWS2, and HEWS demonstrated moderate discriminatory power and, therefore, offer potential utility as prognostic tools for screening severely ill COVID-19 patients. However, MEWS is not a good prognostic predictor for COVID-19.

scholarly journals Predictive Value of A Novel lncRNA LINC02518 in Evaluating the Prognosis of Patients With Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Wei Cui ◽  
Jingzhi Huang ◽  
Ruiqi Wang ◽  
Yu Wang ◽  
Xiaoming Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Training Group ◽  
Kaplan Meier ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract BACKGROUND: The potential of lncRNA in hepatocellular carcinoma (HCC) has led to promising insights in therapeutic intervention. The clinical significance of LINC02518 in HCC is unclear. This study aimed to evaluate the predictive value of a novel long non-coding RNA LINC02518 for the prognosis of patients with HCC. METHODS: Between December 2005 and November 2011, 125 HCC patients in training group and 75 HCC patients in validation group who underwent liver surgery were involved in our study. The LINC02518 expression of HCC and corresponding non-tumor liver tissues was detected by microarray and qRT-PCR. These HCC patients were divided into high and low LINC02518 expression groups based on the threshold of the receiver operating characteristic curve. Kaplan-Meier analysis was performed to determine the prognosis of HCC patients.RESULTS: LINC02518 expression was upregulated in paired tumor samples compared to that in corresponding non-tumor samples in two groups. The areas under the receiver operating characteristic curve for the levels of LINC02518 in the diagnosis of HCC was 0.66, 95% CI: 0.59–0.73. HCC patients with high LINC02518 expression had significantly worse tumor recurrence-free, metastasis-free, disease-free, and overall survival than those with low LINC02518 expression.CONCLUSIONS: LINC02518 is negatively correlated with the prognosis of HCC and provides a promising strategy for the treatment and prognosis of HCC.

scholarly journals Machine Learning to Predict Tamoxifen Nonadherence Among US Commercially Insured Patients With Metastatic Breast Cancer

2021 ◽  
pp. 814-825 ◽  
Author(s):  
Gayathri Yerrapragada ◽  
Athanasios Siadimas ◽  
Amir Babaeian ◽  
Vishakha Sharma ◽  
Tyler J. O'Neill
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Logistic Regression ◽  
Metastatic Breast Cancer ◽  
Receiver Operating Characteristic ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Treatment Initiation ◽  
Metastatic Breast ◽  
Receiver Operating

PURPOSE Adherence to tamoxifen citrate among women diagnosed with metastatic breast cancer can improve survival and minimize recurrence. This study aimed to use real-world data and machine learning (ML) methods to classify tamoxifen nonadherence. METHODS A cohort of women diagnosed with metastatic breast cancer from 2012 to 2017 were identified from IBM MarketScan Commercial Claims and Encounters and Medicare claims databases. Patients with < 80% proportion of days coverage in the year following treatment initiation were classified as nonadherent. Training and internal validation cohorts were randomly generated (4:1 ratio). Clinical procedures, comorbidity, treatment, and health care encounter features in the year before tamoxifen initiation were used to train logistic regression, boosted logistic regression, random forest, and feedforward neural network models and were internally validated on the basis of area under receiver operating characteristic curve. The most predictive ML approach was evaluated to assess feature importance. RESULTS A total of 3,022 patients were included with 40% classified as nonadherent. All models had moderate predictive accuracy. Logistic regression (area under receiver operating characteristic 0.64) was interpreted with 94% sensitivity (95% CI, 89 to 92) and 0.31 specificity (95% CI, 29 to 33). The model accurately classified adherence (negative predictive value 89%) but was nondiscriminate for nonadherence (positive predictive value 48%). Variable importance identified top predictive factors, including age ≥ 55 years and pretreatment procedures (lymphatic nuclear medicine, radiation oncology, and arterial surgery). CONCLUSION ML using baseline administrative data predicts tamoxifen nonadherence. Screening at treatment initiation may support personalized care, improve health outcomes, and minimize cost. Baseline claims may not be sufficient to discriminate adherence. Further validation with enriched longitudinal data may improve model performance.

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