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Prediction scores do not correlate with clinically adjudicated categories of pulmonary embolism in critically ill patients.

ABSTRACT: Prediction scores for pretest probability of pulmonary embolism (PE) validated in outpatient settings are occasionally used in the intensive care unit (ICU).To evaluate the correlation of Geneva and Wells scores with adjudicated categories of PE in ICU patients.In a randomized trial of thromboprophylaxis, patients with suspected PE were adjudicated as possible, probable or definite PE. Data were then retrospectively abstracted for the Geneva Diagnostic PE score, Wells, Modified Wells and Simplified Wells Diagnostic scores. The chance-corrected agreement between adjudicated categories and each score was calculated. ANOVA was used to compare values across the three adjudicated PE categories.Among 70 patients with suspected PE, agreement was poor between adjudicated categories and Geneva pretest probabilities (kappa=0.01 [95% CI -0.0643 to 0.0941]) or Wells pretest probabilities (kappa=-0.03 [95% CI -0.1462 to 0.0914]). Among four possible, 16 probable and 50 definite PEs, there were no significant differences in Geneva scores (possible = 4.0, probable = 4.7, definite = 4.5; P=0.90), Wells scores (possible = 2.8, probable = 4.9, definite = 4.1; P=0.37), Modified Wells (possible = 2.0, probable = 3.4, definite = 2.9; P=0.34) or Simplified Wells (possible = 1.8, probable = 2.8, definite = 2.4; P=0.30).Pretest probability scores developed outside the ICU do not correlate with adjudicated PE categories in critically ill patients. Research is needed to develop prediction scores for this population.

SUBMITTER: Katsios C

PROVIDER: S-EPMC3938238 | biostudies-literature | 2014 Jan-Feb

REPOSITORIES: biostudies-literature

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Prediction scores do not correlate with clinically adjudicated categories of pulmonary embolism in critically ill patients.

Katsios Christina C Donadini Marco M Meade Maureen M Mehta Sangeeta S Hall Richard R Granton John J Kutsogiannis Jim J Dodek Peter P Heels-Ansdell Diane D McIntyre Lauralynn L Vlahakis Nikolas N Muscedere John J Friedrich Jan J Fowler Robert R Skrobik Yoanna Y Albert Martin M Cox Michael M Klinger James J Nates Joseph J Bersten Andrew A Doig Chip C Zytaruk Nicole N Crowther Mark M Cook Deborah J DJ

Canadian respiratory journal 20130930 1

<h4>Background</h4>Prediction scores for pretest probability of pulmonary embolism (PE) validated in outpatient settings are occasionally used in the intensive care unit (ICU).<h4>Objective</h4>To evaluate the correlation of Geneva and Wells scores with adjudicated categories of PE in ICU patients.<h4>Methods</h4>In a randomized trial of thromboprophylaxis, patients with suspected PE were adjudicated as possible, probable or definite PE. Data were then retrospectively abstracted for the Geneva D ...[more]

PMID: 24083302

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Project description:ObjectivesTo assess the role of thromboprophylaxis regimens on the occurrence of pulmonary embolism in coronavirus disease 2019 patients.DesignRetrospective analysis of prospectively collected data on coronavirus disease 2019 patients, included between March 10, and April 30, 2020.SettingICU of an University Hospital in Belgium.Patients and interventionsCritically ill adult mechanically ventilated coronavirus disease 2019 patients were eligible if they underwent a CT pulmonary angiography, as part of the routine management in case of persistent hypoxemia or respiratory deterioration. The primary endpoint of this study was the occurrence of pulmonary embolism according to the use of standard thromboprophylaxis (i.e. subcutaneous enoxaparin 4,000 international units once daily) or high regimen thromboprophylaxis (i.e. subcutaneous enoxaparin 4,000 international units bid or therapeutic unfractioned heparin).Measurements and main resultsOf 49 mechanically ventilated coronavirus disease 2019, 40 underwent CT pulmonary angiography after a median of 7 days (4-8 d) since ICU admission and 12 days (9-16 d) days since the onset of symptoms. Thirteen patients (33%) were diagnosed of pulmonary embolism, which was bilateral in six patients and localized in the right lung in seven patients. D-dimers on the day of CT pulmonary angiography had a predictive accuracy of 0.90 (95% CIs: 0.78-1.00) for pulmonary embolism. The use of high-regimen thromboprophylaxis was associated with a lower occurrence of pulmonary embolism (2/18; 11%) than standard regimen (11/22, 50%-odds ratio 0.13 [0.02-0.69]; p = 0.02); this difference remained significant even after adjustment for confounders. Six patients with pulmonary embolism (46%) and 14 patients without pulmonary embolism (52%) died at ICU discharge (odds ratio 0.79 [0.24-3.26]; p = 0.99).ConclusionsIn this study, one third of coronavirus disease 2019 mechanically ventilated patients have a pulmonary embolism visible on CT pulmonary angiography. High regimen thromboprophylaxis may decrease the occurrence of such complication.

Project description:Sepsis is defined by life-threatening organ dysfunction during infection and is the leading cause of death in hospitals. During sepsis, there is a high risk that new onset of atrial fibrillation (AF) can occur, which is associated with significant morbidity and mortality. Consequently, early prediction of AF during sepsis would allow testing of interventions in the intensive care unit (ICU) to prevent AF and its severe complications. In this paper, we present a novel automated AF prediction algorithm for critically ill sepsis patients using electrocardiogram (ECG) signals. From the heart rate signal collected from 5-min ECG, feature extraction is performed using the traditional time, frequency, and nonlinear domain methods. Moreover, variable frequency complex demodulation and tunable Q-factor wavelet-transform-based time-frequency methods are applied to extract novel features from the heart rate signal. Using a selected feature subset, several machine learning classifiers, including support vector machine (SVM) and random forest (RF), were trained using only the 2001 Computers in Cardiology data set. For testing the proposed method, 50 critically ill ICU subjects from the Medical Information Mart for Intensive Care (MIMIC) III database were used in this study. Using distinct and independent testing data from MIMIC III, the SVM achieved 80% sensitivity, 100% specificity, 90% accuracy, 100% positive predictive value, and 83.33% negative predictive value for predicting AF immediately prior to the onset of AF, while the RF achieved 88% AF prediction accuracy. When we analyzed how much in advance we can predict AF events in critically ill sepsis patients, the algorithm achieved 80% accuracy for predicting AF events 10 min early. Our algorithm outperformed a state-of-the-art method for predicting AF in ICU patients, further demonstrating the efficacy of our proposed method. The annotations of patients' AF transition information will be made publicly available for other investigators. Our algorithm to predict AF onset is applicable for any ECG modality including patch electrodes and wearables, including Holter, loop recorder, and implantable devices.

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Prediction scores do not correlate with clinically adjudicated categories of pulmonary embolism in critically ill patients.

Publications

Prediction scores do not correlate with clinically adjudicated categories of pulmonary embolism in critically ill patients.

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