71: Does the Pulmonary Embolism Severity Index Identify Patients at Risk for Short Term Clinical Deterioration?

100 post-operative subjects were observed following total hip replacement using 125I-fibrinogen (125I-Fg) and impedance plethysmography (IPG) with thigh cuff. Phlebo-grams were obtained if these tests indicated venous thrombosis. Also, lung scan was obtained if clinical evidence of pulmonary embolism developed. Sustained significant isotope localization occurred in 40. 32 of these had abnormal IPG. Four patients had minor pulmonary embolism, which was associated with abnormality of either 125I-Fg or IPG. All major obstructive venous thrombosis and all moderately extensive thrombosis was associated with abnormal IPG. Only minute thrombi were not correctly classified by IPG. The following conclusions are supported by this experience. 1) If prospectively applied in patients at risk, the combination of both techniques (125I-Fg, IPG) is capable of detecting all silent venous thrombosis even minute thrombi of negligible significance. 2) IPG is capable of detecting all major obstructive and all moderately extensive thrombi, that is, all thrombosis of clinical significance arising in the leg. 3) Minute thrombi will not be detected by IPG alone and small emboli resulting from detachment of such minute thrombi would be unheralded unless monitoring includes 125I-Fg.

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MEWS++: Enhancing the Prediction of Clinical Deterioration in Admitted Patients through a Machine Learning Model

Journal of Clinical Medicine ◽

10.3390/jcm9020343 ◽

2020 ◽

Vol 9 (2) ◽

pp. 343 ◽

Cited By ~ 4

Author(s):

Arash Kia ◽

Prem Timsina ◽

Himanshu N. Joshi ◽

Eyal Klang ◽

Rohit R. Gupta ◽

...

Keyword(s):

Machine Learning ◽

At Risk ◽

Area Under The Curve ◽

Learning Model ◽

Clinical Deterioration ◽

Early Warning Score ◽

Support Vector ◽

Adult Age ◽

Machine Learning Model ◽

Patients At Risk

Early detection of patients at risk for clinical deterioration is crucial for timely intervention. Traditional detection systems rely on a limited set of variables and are unable to predict the time of decline. We describe a machine learning model called MEWS++ that enables the identification of patients at risk of escalation of care or death six hours prior to the event. A retrospective single-center cohort study was conducted from July 2011 to July 2017 of adult (age > 18) inpatients excluding psychiatric, parturient, and hospice patients. Three machine learning models were trained and tested: random forest (RF), linear support vector machine, and logistic regression. We compared the models’ performance to the traditional Modified Early Warning Score (MEWS) using sensitivity, specificity, and Area Under the Curve for Receiver Operating Characteristic (AUC-ROC) and Precision-Recall curves (AUC-PR). The primary outcome was escalation of care from a floor bed to an intensive care or step-down unit, or death, within 6 h. A total of 96,645 patients with 157,984 hospital encounters and 244,343 bed movements were included. Overall rate of escalation or death was 3.4%. The RF model had the best performance with sensitivity 81.6%, specificity 75.5%, AUC-ROC of 0.85, and AUC-PR of 0.37. Compared to traditional MEWS, sensitivity increased 37%, specificity increased 11%, and AUC-ROC increased 14%. This study found that using machine learning and readily available clinical data, clinical deterioration or death can be predicted 6 h prior to the event. The model we developed can warn of patient deterioration hours before the event, thus helping make timely clinical decisions.

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Pulmonary embolism in old age: usefulness of risk stratification in clinical decision-making

Geriatric Care ◽

10.4081/gc.2016.6080 ◽

2016 ◽

Vol 2 (2) ◽

Author(s):

Carlo Bova ◽

Vitaliano Spagnuolo ◽

Alfonso Noto

Keyword(s):

Decision Making ◽

Pulmonary Embolism ◽

High Risk ◽

Clinical Decision Making ◽

Clinical Status ◽

Severity Index ◽

Common Disease ◽

Early Complications ◽

Short Term ◽

Risk Of Death

Pulmonary embolism (PE) is a common disease with a not negligible short-term risk of death, in particular in the elderly. An adequate evaluation of the prognosis in patients with PE may guide decision-making in terms of the intensity of the initial treatment during the acute phase. Patients with shock or persistent hypotension are at high risk of early mortality and may benefit from immediate reperfusion. Several tools are available to define the short-term prognosis of hemodynamically stable patients. The pulmonary embolism severity index (PESI) score, and the simplified PESI score are particularly useful for identifying patients at low risk of early complications who might be safely treated at home. The identification of patients who are hemodynamically stable at diagnosis but are at a high risk of early complications is more challenging. Current guidelines recommend a multi-parametric prognostic algorithm based on the clinical status, biomarkers and imaging tests. However an aggressive treatment in hemodynamically stable patients is still controversial.

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Using scores to identify patients at risk of short term mortality at arrival to the acute medical unit: A validation study of six existing scores

European Journal of Internal Medicine ◽

10.1016/j.ejim.2017.09.042 ◽

2017 ◽

Vol 45 ◽

pp. 32-36 ◽

Cited By ~ 5

Author(s):

Mikkel Brabrand ◽

Peter Hallas ◽

Søren Nygaard Hansen ◽

Kristian Møller Jensen ◽

Janni Lynggård Bo Madsen ◽

...

Keyword(s):

At Risk ◽

Validation Study ◽

Short Term ◽

Medical Unit ◽

Acute Medical Unit ◽

Short Term Mortality ◽

Patients At Risk

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Using an Automated Risk Assessment Report to Identify Patients at Risk for Clinical Deterioration

The Joint Commission Journal on Quality and Patient Safety ◽

10.1016/s1553-7250(07)33061-4 ◽

2007 ◽

Vol 33 (9) ◽

pp. 569-574 ◽

Cited By ~ 14

Author(s):

John Whittington ◽

Robert White ◽

Kathleen M. Haig ◽

Marla Slock

Keyword(s):

Risk Assessment ◽

At Risk ◽

Clinical Deterioration ◽

Assessment Report ◽

Patients At Risk

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Lethal Trauma Pulmonary Embolism is a Black Swan Event in Patients at Risk for Deep Vein Thrombosis: An Evidence-Based Review

The American Surgeon ◽

10.1177/000313481708300431 ◽

2017 ◽

Vol 83 (4) ◽

pp. 403-413 ◽

Cited By ~ 2

Author(s):

C. Michael Dunham ◽

Gregory S. Huang

Keyword(s):

At Risk ◽

Pulmonary Embolism ◽

Deep Vein Thrombosis ◽

Confidence Interval ◽

Hospital Stay ◽

Trauma Patients ◽

Black Swan ◽

Vein Thrombosis ◽

Patients At Risk ◽

Deep Vein

We delineated the incidence of trauma patient pulmonary embolism (PE) and risk conditions by performing a systematic literature review of those at risk for deep vein thrombosis (DVT). The PE proportion was 1.4 per cent (95% confidence interval = 1.2–1.6) in at-risk patients. Of 10 conditions, PE was only associated with increased age (P < 0.01) or leg injury (P < 0.01; risk ratio = 1.6). As lower extremity DVT (LEDVT) proportions increased, mortality proportions (P = 0.02) and hospital stay (P = 0.0002) increased, but PE proportions did not (P = 0.13). LEDVT was lower with chemoprophylaxis (CP) (4.9%) than without CP (19.1%; P < 0.01). PEwas lower withCP (1.0%) than without CP (2.2%; P = 0.0004). Mortality was lower with CP (6.6%) than without CP (11.6%; P = 0.002). PE was similar with (1.2%) and without (1.9%; P = 0.19) mechanical prophylaxis (MP). LEDVT was lower with MP (8.5%) than without MP (12.2%; P = 0.0005). PE proportions were similar with (1.3%) and without (1.5%; P = 0.24) LEDVTsurveillance. Mortality was higher with LEDVTsurveillance (7.9%) than without (4.8%; P < 0.01). A PE mortality of 19.7 per cent (95% confidence interval = 18–22) 3 a 1.4 per cent PE proportion yielded a 0.28 per cent lethal PE proportion. As PE proportions increased, mortality (P = 0.52) and hospital stay (P = 0.13) did not. Of 176 patients with PE, 76 per cent had no LEDVT. In trauma patients at risk for DVT, PE is infrequent, has a minimal impact on outcomes, and death is a black swan event. LEDVTsurveillance did not improve outcomes. Because PE was not associated with LEDVT and most patients with PE had no LEDVT, preventing, diagnosing, and treating LEDVT may be ineffective PE prophylaxis.

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