scholarly journals Procollagen I and III as Prognostic Markers in Patients Treated with Extracorporeal Membrane Oxygenation: A Prospective Observational Study

2021 ◽  
Vol 10 (16) ◽  
pp. 3686
Author(s):  
Christoph Boesing ◽  
Peter T. Graf ◽  
Manfred Thiel ◽  
Thomas Luecke ◽  
Joerg Krebs
Keyword(s):  
Extracorporeal Membrane Oxygenation ◽  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Roc Curve Analysis ◽  
Membrane Oxygenation ◽  
Icu Discharge ◽  
Procollagen Iii Peptide ◽  
Poor Outcomes ◽  
Receiver Operating

Background: Procollagen peptides have been associated with lung fibroproliferation and poor outcomes in patients with acute respiratory distress syndrome (ARDS). Therefore, serum procollagen concentrations might have prognostic value in ARDS patients treated with extracorporeal membrane oxygenation (ECMO). Methods: In a prospective cohort study, serum N-terminal procollagen I-peptide (PINP) and N-terminal procollagen III-peptide (PIIINP) concentrations in twenty-three consecutive patients with severe ARDS treated with ECMO were measured at the time of ECMO initiation and during the course of treatment. The predictive value of PINP and PIIINP at the time of ECMO initiation was tested with a univariable logistic regression and a receiver operating characteristic (ROC) curve analysis. Results: Thirteen patients survived to intensive care unit (ICU) discharge. Non-survivors had higher serum PINP and PIIINP concentrations at all points in time during the course of treatment. Serum PIIINP at the day of ECMO initiation showed an odds ratio of 1.37 (95% CI 1.10–1.89, p = 0.017) with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.87 (95% CI 0.69–1.00, p = 0.0029) for death during the course of treatment. Conclusions: PINP and PIIINP concentrations differ between survivors and non-survivors in ARDS treated with ECMO. This exploratory hypothesis generating study suggests an association between PIIINP serum concentrations at ECMO initiation and an unfavorable clinical outcome.

scholarly journals On the Binormal Predictive Receiver Operating Characteristic Curve for the Joint Assessment of Positive and Negative Predictive Values

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 593 ◽  
Author(s):  
Gareth Hughes
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Statistical Evaluation ◽  
Characteristic Curve ◽  
Disease Status ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Predictive Values ◽  
Receiver Operating

The predictive receiver operating characteristic (PROC) curve is a diagrammatic format with application in the statistical evaluation of probabilistic disease forecasts. The PROC curve differs from the more well-known receiver operating characteristic (ROC) curve in that it provides a basis for evaluation using metrics defined conditionally on the outcome of the forecast rather than metrics defined conditionally on the actual disease status. Starting from the binormal ROC curve formulation, an overview of some previously published binormal PROC curves is presented in order to place the PROC curve in the context of other methods used in statistical evaluation of probabilistic disease forecasts based on the analysis of predictive values; in particular, the index of separation (PSEP) and the leaf plot. An information theoretic perspective on evaluation is also outlined. Five straightforward recommendations are made with a view to aiding understanding and interpretation of the sometimes-complex patterns generated by PROC curve analysis. The PROC curve and related analyses augment the perspective provided by traditional ROC curve analysis. Here, the binormal ROC model provides the exemplar for investigation of the PROC curve, but potential application extends to analysis based on other distributional models as well as to empirical analysis.

Understanding receiver operating characteristic (ROC) curves

CJEM ◽  
2006 ◽  
Vol 8 (01) ◽  
pp. 19-20 ◽  
Author(s):  
Jerome Fan ◽  
Suneel Upadhye ◽  
Andrew Worster
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Neuron Specific Enolase ◽  
Roc Curves ◽  
Serum Levels ◽  
Spontaneous Circulation ◽  
Roc Curve Analysis ◽  
Prediction Of Survival ◽  
Receiver Operating

In this issue of the Journal, Auer and colleagues conclude that serum levels of neuron-specific enolase (NSE), a biochemical marker of ischemic brain injury, may have clinical utility for the prediction of survival to hospital discharge in patients experiencing the return of spontaneous circulation following at least 5 minutes of cardiopulmonary resuscitation. The authors used a receiver operating characteristic (ROC) curve to illustrate and evaluate the diagnostic (prognostic) performance of NSE. We explain ROC curve analysis in the following paragraphs.

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