Summary
Background
Management of increased referrals for transthoracic echocardiography (TTE) examinations is a challenge. Patients with normal TTE examinations take less time to explore than those with heart abnormalities. A reliable method for assessing pretest probability of a normal TTE may optimize management of requests.
Aim
To establish and validate, based on requests for examinations, a simple algorithm for defining pretest probability of a normal TTE.
Methods
In a retrospective phase, factors associated with normality were investigated and an algorithm was designed. In a prospective phase, patients were classified in accordance with the algorithm as being at high or low probability of having a normal TTE.
Results
In the retrospective phase, 42% of 618 examinations were normal. In multivariable analysis, age and absence of cardiac history were associated to normality. Low pretest probability of normal TTE was defined by known cardiac history or, in case of doubt about cardiac history, by age > 70 years. In the prospective phase, the prevalences of normality were 72% and 25% in high ( n = 167) and low ( n = 241) pretest probability of normality groups, respectively. The mean duration of normal examinations was significantly shorter than abnormal examinations (13.8 ± 9.2 min vs 17.6 ± 11.1 min; P = 0.0003).
Conclusion
A simple algorithm can classify patients referred for TTE as being at high or low pretest probability of having a normal examination. This algorithm might help to optimize management of requests in routine practice.
Résumé
Contexte
La gestion de la demande croissante d’échocardiographies trans-thoraciques (ETT) est une problématique majeure des laboratoires spécialisés. Comparé à un examen complexe, le temps d’exploration d’un cœur normal est plus court.
Objectif
À partir des demandes d’explorations, élaborer et valider un algorithme simple d’évaluation de la probabilité pré-test de normalité d’une ETT.
Méthodes
À partir de l’analyse rétrospective des comptes rendus d’ETT un algorithme, basé sur les éléments associés à un examen normal, a été proposé. Dans un second temps, les demandes d’explorations ont été évaluées et classées prospectivement selon l’algorithme comme étant à forte ou à faible probabilité de normalité.
Résultats
Dans la première phase ( n = 618), le taux d’examens normaux était de 42 %, les facteurs associés en analyse multivariée à la normalité étaient : l’âge et l’absence de cardiopathie connue. La faible probabilité pré-test d’ETT normale a été définie par l’existence d’une cardiopathie connue ou en cas de doute sur une cardiopathie préexistante par un âge > 70 ans. Toutes les autres demandes étaient considérées à forte probabilité de normalité. La phase prospective a confirmé la validité de l’algorithme, il y avait 72 % d’ETT normales dans le groupe à forte probabilité ( n = 167) et 25 % d’ETT normales dans celui à faible probabilité ( n = 241). La durée d’un examen normal était plus courte qu’un examen anormal (13,8 ± 9,2 contre 17,6 ± 11,1 minutes ; p = 0,0003).
Conclusion
Un algorithme simple permet de classer les patients adressés pour ETT comme étant à forte ou à faible probabilité d’examen normal. Cet outil pourrait aider à l’optimisation du tri des demandes en routine clinique.
Introduction
The clinical value of transthoracic echocardiography (TTE) has been widely proven and there are currently a high number of indications for this technique . Over the past two decades, there has been a sustained increase in the diagnostic use of TTE . Good management of the large number of TTE requests daily is an important issue for echocardiography laboratories. The echocardiography laboratories are often overloaded, with negative consequences for the patients and their caregivers: lengthening of the period of appointment, long waiting time on the day of the examination, stress and risk of delaying an urgent review. Given this workload, and in order to optimize laboratory workflow, some teams have reported changes in their practice .
To the best of our knowledge, no specific work has been done to rationalize and pre-sort the examination requests. Discriminating between a long and complex examination requiring an expert operator (e.g. for the evaluation of valvular disease) and a routine, relatively more simple and potentially faster examination feasible by a less experienced operator (e.g. evaluation of left ventricular ejection fraction [LVEF]) before a cardiotoxic chemotherapeutic agent) may help to improve the efficiency of the laboratory.
The objective of this work was to develop and validate a simple and reproducible algorithm to assess the pretest probability of a normal TTE by analyzing the request data.
Methods
The study was conducted at the echocardiography laboratory of the “Groupe Hospitalier Pitié-Salpêtrière”, which is a tertiary centre of expertise. Approximately 11,000 tests/year are performed by expert physicians. All examinations are stored on a dedicated server (Image Arena™ Version 4.6, TomTec Imaging Systems, Munich, Germany).
The study only involved TTE and was divided in two periods: a retrospective period for the design of the algorithm and a prospective period for algorithm validation. The study was approved by the institutional committee on human research.
Retrospective period: design of the algorithm
All examinations performed between 2nd and 30th November 2011 were reviewed for inclusion in the study. From reports, the following information was collected: age and gender, the origin of the request (cardiology department or other) and the pattern of the examination. The reason for examination was classified as being an exploration of a known cardiac disease (cardiology pattern) if it fitted with one of the predefined definitions shown in Table 1 . Items included in the table were assembled from collective experience of the participating investigators. Exclusion criteria were limited to non-exhaustive reporting.
| Known left ventricular disease/cardiomyopathies |
| Acute or history of coronary syndrome |
| Dilated cardiomyopathy |
| Hypertrophic cardiomyopathy |
| Restrictive cardiomyopathy |
| Arrhythmogenic right ventricular dysplasia |
| History of acute myocarditis |
| Heart transplantation |
| Known valvular dysfunction |
| Any valvulopathy |
| Valvular prostheses |
| Known congenital heart disease |
| Known pericardial disease |
| Known aortic dilatation |
| Known heart mass |
| Known rhythm or conduction dysfunction |
| Permanent atrial fibrillation |
| Pacemaker |
| Complete left bundle branch block |
| Sustained ventricular tachycardia |
An abnormal echocardiogram was defined by an LVEF < 50%, a left ventricular (LV) dilation with LV telediastolic diameter > 32 mm/m 2 or LV end-diastolic volume > 75 mL/m 2 , LV hypertrophy (LV mass > 95 g/m 2 or > 115 g/m 2 for women or men, respectively) , the presence of regional wall motion abnormalities (at least two segments of the same territory), mitral or tricuspid regurgitation > 2/4, aortic regurgitation > 1/4, the presence of an aortic stenosis (maximal velocity > 2.5 m/s and/or valve area ≤ 1.5 cm 2 ) , right ventricular dilatation defined as recommended by ASE , the presence of pulmonary hypertension (defined as a systolic pulmonary pressure > 40 mmHg) , the presence of more than a minimal pericardial effusion and an aortic dilatation (> 40 mm).
Prospective period: validation of the algorithm
Between 2nd and 30th April 2012, we asked all the physicians working in the laboratory to collect the requests of TTE examinations. These requests were reviewed through a blinded method according to the results of the exploration. Depending on the algorithm, they were classified into two categories: high or low pretest probability of normal TTE. In a second step, the results of this screening were compared with the results of TTE using the same criteria of abnormality as in the retrospective period. During this period, the duration of the examinations was also collected.
Statistical analysis
Quantitative data are expressed as mean ± standard deviation (SD); qualitative data are expressed as number and percentage. Univariate analysis of continuous variables was performed using the parametric t test. The chi-squared test was used to compare categorical data. The evaluation of determinants of normal TTE was carried out by performing a multivariable analysis. The variables included in the analysis were those associated with normality of the TTE in univariate analysis with P ≤ 0.20.
The population of the retrospective period was divided into tertiles according to age. The tertile with the lowest prevalence of normal TTE helped to establish the threshold for the algorithm.
The intra- and inter-observer concordance of the algorithm was tested on 50 randomly selected requests by calculating the correlation coefficient, Kappa. Statview software version 5.0 (SAS institute, Inc) was used for statistical analysis. A value of P < 0.05 was considered significant.
Results
Retrospective analysis
Among 762 TTEs performed during the study period, 144 were excluded due to non-exhaustive reporting. Thus, 618 examinations (81%) were included. The rate of normal examinations was 42% ( n = 259). The number of TTEs requested by the cardiology department was 458 (74%). The mean patient age was 59 ± 18 years and there were 359 men (58%).
Table 2 describes the univariate analysis. Patients with normal TTE were significantly younger, less likely to have had a request from the cardiology department, and less likely to have a cardiology pattern of request. In multivariable analysis, age and cardiology pattern were both independently associated with a normal TTE ( Table 3 ).
| Normal TTE ( n = 259) | Abnormal TTE ( n = 359) | P | |
|---|---|---|---|
| Age (years) | 54.1 ± 18.4 | 62.5 ± 16.5 | < 0.0001 |
| Male | 137 (53) | 222 (62) | 0.026 |
| Request from cardiology department | 145 (56) | 313 (87) | < 0.0001 |
| Pattern of the request | |||
| Cardiology pattern | 51 (20) | 274 (76) | < 0.0001 |
| Symptoms, clinical signs or ECG abnormalities potentially related to cardiac disease | 72 (28) | 37 (10) | < 0.0001 |
| Suspected pulmonary hypertension or suspected cardiac complications of systemic diseases | 64 (25) | 18 (5) | < 0.0001 |
| Evaluation of cardiac function before cardiotoxic drug or before non-cardiac surgery | 30 (12) | 8 (2) | < 0.0001 |
| Suspected infective endocarditis | 16 (6) | 9 (3) | 0.02 |
| Suspected cardiac source of embolus | 5 (2) | 6 (2) | 0.81 |
| Other pattern | 21(8) | 7 (2) | 0.0003 |
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