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Physician's first clinical impression of emergency department patients with nonspecific complaints is associated with morbidity and mortality.

Beglinger B, Rohacek M, Ackermann S, Hertwig R, Karakoumis-Ilsemann J, Boutellier S, Geigy N, Nickel C, Bingisser R - Medicine (Baltimore) (2015)

Bottom Line: The variable "looking ill" was significantly associated with mortality and morbidity (per 10 point increase, odds ratio 1.23, 95% confidence interval [CI] 1.12-1.34, P < 0.001, and odds ratio 1.19, 95% CI 1.14-1.24, P < 0.001, respectively).The combination of the variables "looking ill," "age," "male sex," and "CCI" resulted in the best prediction of these outcomes (mortality: area under the curve [AUC] 0.77, 95% CI 0.72-0.82; morbidity: AUC 0.68, 95% CI 0.65-0.71).The physician's first impression, with or without additional variables such as age, male sex, and CCI, was associated with morbidity and mortality.

View Article: PubMed Central - PubMed

Affiliation: From the Department of Emergency Medicine, University Hospital Basel, Switzerland (BB, MR, SA, JI, SB, CN, RB); Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany (RH); and Department of Emergency Medicine, Hospital of Liestal, Switzerland (NG).

ABSTRACT
The association between the physician's first clinical impression of a patient with nonspecific complaints and morbidity and mortality is unknown. The aim was to evaluate the association of the physician's first clinical impression with acute morbidity and mortality. We conducted a prospective observational study with a 30-day follow-up. This study was performed at the emergency departments (EDs) of 1 secondary and 1 tertiary care hospital, from May 2007 to February 2011. The first clinical impression ("looking ill"), expressed on a numerical rating scale from 0 to 100, age, sex, and the Charlson Comorbidity Index (CCI) were evaluated. The association was determined between these variables and acute morbidity and mortality, together with receiver operating characteristics, and validity. Of 217,699 presentations to the ED, a total of 1278 adult nontrauma patients with nonspecific complaints were enrolled by a study team. No patient was lost to follow-up. A total of 84 (6.6%) patients died during follow-up, and 742 (58.0%) patients were classified as suffering from acute morbidity. The variable "looking ill" was significantly associated with mortality and morbidity (per 10 point increase, odds ratio 1.23, 95% confidence interval [CI] 1.12-1.34, P < 0.001, and odds ratio 1.19, 95% CI 1.14-1.24, P < 0.001, respectively). The combination of the variables "looking ill," "age," "male sex," and "CCI" resulted in the best prediction of these outcomes (mortality: area under the curve [AUC] 0.77, 95% CI 0.72-0.82; morbidity: AUC 0.68, 95% CI 0.65-0.71). The physician's first impression, with or without additional variables such as age, male sex, and CCI, was associated with morbidity and mortality. This might help in the decision to perform further diagnostic tests and to hospitalize ED patients.

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The performance of 2 single variables (looking ill and CCI) and 2 sets of predictors (looking ill, age and male sex, in combination with or without CCI) in the ROC space for the outcome variable mortality. CCI = Charlson Comorbidity Index, ROC = receiver operating characteristic.
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Figure 2: The performance of 2 single variables (looking ill and CCI) and 2 sets of predictors (looking ill, age and male sex, in combination with or without CCI) in the ROC space for the outcome variable mortality. CCI = Charlson Comorbidity Index, ROC = receiver operating characteristic.

Mentions: We calculated ROC curves and AUC values, both of which are based on the corresponding logistic regression models, for the 2 outcome measures. Figure 2 shows the ROC curves for mortality based on the variable “looking ill,” “looking ill” in combination with age and male sex, and “looking ill,” age and male sex, in combination with CCI. Figure 3 shows the ROC curves for acute morbidity. Table 3 lists the mean AUC values (with 95% CI) associated with the 3 sets of variables and with CCI alone. According to the AUC values, “looking ill,” age and male sex, in combination with CCI, yielded the best performance on both outcome variables. Using the Delong method to compare AUCs, we found that the performance levels of the 3 sets of variables were significantly different from one another at the 5% α level, with the “looking ill,” age and male sex, in combination with CCI, predicting the outcomes significantly better than the other 2 variable sets or CCI alone.


Physician's first clinical impression of emergency department patients with nonspecific complaints is associated with morbidity and mortality.

Beglinger B, Rohacek M, Ackermann S, Hertwig R, Karakoumis-Ilsemann J, Boutellier S, Geigy N, Nickel C, Bingisser R - Medicine (Baltimore) (2015)

The performance of 2 single variables (looking ill and CCI) and 2 sets of predictors (looking ill, age and male sex, in combination with or without CCI) in the ROC space for the outcome variable mortality. CCI = Charlson Comorbidity Index, ROC = receiver operating characteristic.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4554174&req=5

Figure 2: The performance of 2 single variables (looking ill and CCI) and 2 sets of predictors (looking ill, age and male sex, in combination with or without CCI) in the ROC space for the outcome variable mortality. CCI = Charlson Comorbidity Index, ROC = receiver operating characteristic.
Mentions: We calculated ROC curves and AUC values, both of which are based on the corresponding logistic regression models, for the 2 outcome measures. Figure 2 shows the ROC curves for mortality based on the variable “looking ill,” “looking ill” in combination with age and male sex, and “looking ill,” age and male sex, in combination with CCI. Figure 3 shows the ROC curves for acute morbidity. Table 3 lists the mean AUC values (with 95% CI) associated with the 3 sets of variables and with CCI alone. According to the AUC values, “looking ill,” age and male sex, in combination with CCI, yielded the best performance on both outcome variables. Using the Delong method to compare AUCs, we found that the performance levels of the 3 sets of variables were significantly different from one another at the 5% α level, with the “looking ill,” age and male sex, in combination with CCI, predicting the outcomes significantly better than the other 2 variable sets or CCI alone.

Bottom Line: The variable "looking ill" was significantly associated with mortality and morbidity (per 10 point increase, odds ratio 1.23, 95% confidence interval [CI] 1.12-1.34, P < 0.001, and odds ratio 1.19, 95% CI 1.14-1.24, P < 0.001, respectively).The combination of the variables "looking ill," "age," "male sex," and "CCI" resulted in the best prediction of these outcomes (mortality: area under the curve [AUC] 0.77, 95% CI 0.72-0.82; morbidity: AUC 0.68, 95% CI 0.65-0.71).The physician's first impression, with or without additional variables such as age, male sex, and CCI, was associated with morbidity and mortality.

View Article: PubMed Central - PubMed

Affiliation: From the Department of Emergency Medicine, University Hospital Basel, Switzerland (BB, MR, SA, JI, SB, CN, RB); Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany (RH); and Department of Emergency Medicine, Hospital of Liestal, Switzerland (NG).

ABSTRACT
The association between the physician's first clinical impression of a patient with nonspecific complaints and morbidity and mortality is unknown. The aim was to evaluate the association of the physician's first clinical impression with acute morbidity and mortality. We conducted a prospective observational study with a 30-day follow-up. This study was performed at the emergency departments (EDs) of 1 secondary and 1 tertiary care hospital, from May 2007 to February 2011. The first clinical impression ("looking ill"), expressed on a numerical rating scale from 0 to 100, age, sex, and the Charlson Comorbidity Index (CCI) were evaluated. The association was determined between these variables and acute morbidity and mortality, together with receiver operating characteristics, and validity. Of 217,699 presentations to the ED, a total of 1278 adult nontrauma patients with nonspecific complaints were enrolled by a study team. No patient was lost to follow-up. A total of 84 (6.6%) patients died during follow-up, and 742 (58.0%) patients were classified as suffering from acute morbidity. The variable "looking ill" was significantly associated with mortality and morbidity (per 10 point increase, odds ratio 1.23, 95% confidence interval [CI] 1.12-1.34, P < 0.001, and odds ratio 1.19, 95% CI 1.14-1.24, P < 0.001, respectively). The combination of the variables "looking ill," "age," "male sex," and "CCI" resulted in the best prediction of these outcomes (mortality: area under the curve [AUC] 0.77, 95% CI 0.72-0.82; morbidity: AUC 0.68, 95% CI 0.65-0.71). The physician's first impression, with or without additional variables such as age, male sex, and CCI, was associated with morbidity and mortality. This might help in the decision to perform further diagnostic tests and to hospitalize ED patients.

Show MeSH
Related in: MedlinePlus