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Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome.

Zimmerli L, Steurer J, Kofmehl R, Wertli MM, Held U - BMC Emerg Med (2014)

Bottom Line: The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables.The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes.If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution.

View Article: PubMed Central - PubMed

Affiliation: Horten Centre for Patient Oriented-Research and Knowledge Transfer, University of Zurich, Pestalozzistrasse 24, Zurich 8091, Switzerland. ulrike.held@usz.ch.

ABSTRACT

Background: We recently reported about the derivation of a diagnostic probability function for acute coronary syndrome (ACS). The present study aims to validate the probability function as a rule-out criterion in a new sample of patients.

Methods: 186 patients presenting with chest pain and/or dyspnea at one of the three participating hospitals' emergency rooms in Switzerland were included in the study. In these patients, information on a set of pre-specified variables was collected and a predicted probability of ACS was calculated for each patient. Approximately two weeks after the initial visit in the emergency room, patients were contacted by phone to assess whether a diagnosis of ACS was established.

Results: Of the 186 patients included in the study, 31 (17%) had an acute coronary syndrome. A risk probability for ACS below 2% was considered a rule-out criterion for ACS, leading to a sensitivity of 87% and a specificity of 17% of the rule. The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables.

Conclusions: The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes. If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution.

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Related in: MedlinePlus

Patient flow chart. (ACS = Acute Coronary Syndrome).
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Fig2: Patient flow chart. (ACS = Acute Coronary Syndrome).

Mentions: Of particular interest is the performance of the prediction rule when the calculated probabilities for ACS are below 2% (Figure 2). Two percent probability of presence of ACS seems to be the rule-out threshold for physicians without further testing[5]. In 31 (17%) patients the calculated probability was less than 2% and four of them actually had an ACS resulting in a sensitivity of 87%, with 95% confidence interval (CI) 70%-96% and a specificity of 17%, 95% CI 12%-24% (Table 2). The positive predictive value (PPV) is 0.17 (95% CI 0.15-0.19) and the negative predictive value (NPV) is 0.88 (95% CI 0.73-0.95). The positive likelihood ratio LR + = 1.04 and the negative likelihood ratio LR- = 0.76. Further investigation in the four patients with ACS but predicted probability below 2% of it led to the finding that three patients had extraordinary long times since onset of symptoms: the values were 24 hours, 48 hours and 96 hours, respectively. The range of time since onset of symptoms was 1-9 hours in the vignettes used to derive the probability function. The fourth patient had an extremely large number of pack years smoked, which was 180 and for that reason also far outside of the range of values in the original developmental set of vignettes.Figure 2


Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome.

Zimmerli L, Steurer J, Kofmehl R, Wertli MM, Held U - BMC Emerg Med (2014)

Patient flow chart. (ACS = Acute Coronary Syndrome).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4289321&req=5

Fig2: Patient flow chart. (ACS = Acute Coronary Syndrome).
Mentions: Of particular interest is the performance of the prediction rule when the calculated probabilities for ACS are below 2% (Figure 2). Two percent probability of presence of ACS seems to be the rule-out threshold for physicians without further testing[5]. In 31 (17%) patients the calculated probability was less than 2% and four of them actually had an ACS resulting in a sensitivity of 87%, with 95% confidence interval (CI) 70%-96% and a specificity of 17%, 95% CI 12%-24% (Table 2). The positive predictive value (PPV) is 0.17 (95% CI 0.15-0.19) and the negative predictive value (NPV) is 0.88 (95% CI 0.73-0.95). The positive likelihood ratio LR + = 1.04 and the negative likelihood ratio LR- = 0.76. Further investigation in the four patients with ACS but predicted probability below 2% of it led to the finding that three patients had extraordinary long times since onset of symptoms: the values were 24 hours, 48 hours and 96 hours, respectively. The range of time since onset of symptoms was 1-9 hours in the vignettes used to derive the probability function. The fourth patient had an extremely large number of pack years smoked, which was 180 and for that reason also far outside of the range of values in the original developmental set of vignettes.Figure 2

Bottom Line: The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables.The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes.If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution.

View Article: PubMed Central - PubMed

Affiliation: Horten Centre for Patient Oriented-Research and Knowledge Transfer, University of Zurich, Pestalozzistrasse 24, Zurich 8091, Switzerland. ulrike.held@usz.ch.

ABSTRACT

Background: We recently reported about the derivation of a diagnostic probability function for acute coronary syndrome (ACS). The present study aims to validate the probability function as a rule-out criterion in a new sample of patients.

Methods: 186 patients presenting with chest pain and/or dyspnea at one of the three participating hospitals' emergency rooms in Switzerland were included in the study. In these patients, information on a set of pre-specified variables was collected and a predicted probability of ACS was calculated for each patient. Approximately two weeks after the initial visit in the emergency room, patients were contacted by phone to assess whether a diagnosis of ACS was established.

Results: Of the 186 patients included in the study, 31 (17%) had an acute coronary syndrome. A risk probability for ACS below 2% was considered a rule-out criterion for ACS, leading to a sensitivity of 87% and a specificity of 17% of the rule. The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables.

Conclusions: The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes. If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution.

Show MeSH
Related in: MedlinePlus