JMIR Publications

ABSTRACT

Background:

Hemodynamic assessment of critically ill patients is a challenging endeavor, and advanced monitoring techniques are often required to guide treatment choices. Given the technical complexity and occasional unavailability of these techniques, being able to estimate cardiac function based on clinical examination is a valuable tool for critical care physicians to diagnose circulatory shock. Yet, the lack of knowledge on how to best conduct and teach clinical examination has reduced its accuracy to almost that of “flipping a coin”.

Objective:

The aim of this study was to investigate the decision-making process underlying estimates of cardiac function of patients acutely admitted to the ICU, based on current standardized clinical examination using Bayesian methods.

Methods:

Patient data was collected as part of the SICS-I prospective cohort study (ClinicalTrials.gov Identifier: NCT02912624). All adult patients consecutively admitted to the ICU with an expected stay longer than 24 hours were included, for whom clinical examination was conducted and cardiac function was estimated. Using these data, first, the probabilistic dependencies between the examiners’ estimates and the set of clinically measured variables upon which these rely were analyzed by means of a Bayesian network. Second, the accuracy of cardiac function estimates was assessed by comparison to the cardiac index values measured by critical care ultrasonography.

Results:

1075 patients were included, of which 783 patients had validated cardiac index measurements. Bayesian network analysis identified two clinical variables upon which cardiac function estimate is conditionally dependent, namely noradrenaline administration and presence of delayed capillary refill time and/or mottling. When the patient received noradrenaline, the probability of cardiac function being estimated as reasonable P(ER,G) was lower irrespective of whether the patient was or was not mechanically ventilated ((P(ER,G|Ventilation, Noradrenaline) = 0.63, P(ER,G|Ventilation, No Noradrenaline) = 0.91, P(ER,G|No Ventilation, Noradrenaline) = 0.67, P(ER,G|No Ventilation, No Noradrenaline) = 0.93)). The same trend was found for capillary refill time and/or mottling. Sensitivity of estimating a low cardiac index was 26% and 39%, and specificity was 83% and 74%, for students and physicians. Positive and negative likelihood ratios were 1.53 (1.19 - 1.97) and 0.87 (0.80 – 0.95), respectively, for all groups.

Conclusions:

The conditional dependencies between clinical variables and the cardiac function estimates resulted in a network consistent with known physiological relations. Conditional probability queries allow for multiple clinical scenarios to be recreated which provide insight into the possible thought process underlying the examiners’ cardiac function estimates. This information can help develop interactive digital training tools for students and physicians, and contribute towards the goal of further improving the diagnostic accuracy of clinical examination in ICU patients. Clinical Trial: ClinicalTrials.gov Identifier: NCT02912624 URL: https://clinicaltrials.gov/ct2/show/NCT02912624