scholarly journals Diastolic stress test in the preoperative non-cardiac surgery examination

2020 ◽  
Vol 25 ◽  
pp. 3986
Author(s):  
O. N. Dzhioeva ◽  
O. M. Drapkina

Preoperative examination of patients undergoing high-risk elective non-cardiac surgery requires identifying factors associated with both the type of surgery and comorbidity profile of each patient. Determination of clinically significant echocardiographic changes, even without severe symptoms, can contribute to a change in management or revision of scheduled date and surgery tactics. The aspects of defining echocardiographic criteria for potential postoperative cardiovascular complications, especially in asymptomatic patients with preserved left ventricular ejection fraction, are an important clinical problem. The diastolic stress test, a relatively new type of exercise testing, is currently an additional diagnostic tool to detect heart failure in patients without reduced ejection fraction. The prospects of using this method before non-cardiac surgery in patients with preserved left ventricular ejection fraction is discussed in this article.

2021 ◽  
Author(s):  
Alexander Sandhu ◽  
Jimmy Zheng ◽  
Paul A Heidenreich

Introduction: Left ventricular ejection fraction (EF) is an important factor for treatment decisions for heart failure. The EF is unavailable in administrative claims. We sought to evaluate the predictive accuracy of claims diagnoses for classifying heart failure with reduced ejection fraction (HFrEF) versus heart failure with preserved ejection fraction (HFpEF) with International Classification of Disease-Tenth Revision codes. Methods: We identified HF diagnoses for VA patients between 2017-2019 and extracted the EF from clinical notes and imaging reports using a VA natural language processing algorithm. We classified sets of codes as HFrEF-related, HFpEF-related, or non-specific based on the closest EF within 180 days. We selected a random heart failure diagnosis for each patient and tested the predictive accuracy of various algorithms for identifying HFrEF using the last 1 year of heart failure diagnoses. We performed sensitivity analyses on the EF thresholds, the cohort, and the diagnoses used. Results: Between 2017-2019, we identified 358,172 patients and 1,671,084 diagnoses with an EF recording within 180 days. After dividing diagnoses into HFrEF-related, HFpEF-related, or non-specific, we found using the proportion of specific diagnoses classified as HFrEF-related had an AUC of 0.76 for predicting EF≤40% and 0.80 for predicting EF<50%. However, 23.3% of patients could not be classified due to only having non-specific codes. Predictive accuracy increased among patients with ≥4 HF diagnoses over the preceding year. Discussion: In a VA cohort, administrative claims with ICD-10 codes had moderate accuracy for identifying reduced ejection fraction. This level of specificity is likely inadequate for performance measures. Administrative claims need to better align terminology with relevant clinical definitions.


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