30 Chapter 2 as ‘cognitive impairment’. Notes of emergency physicians and geriatricians were evaluated on terms as ‘unreliable anamnesis’, ‘confusion’ and ‘possible delirium’ and when found, were scored ‘probable cognitive impairment’. In the absence of a pre-existing diagnosis of dementia and no notes of suspected cognitive impairment, ‘no cognitive impairment’ was noted. The number of (how many) other specialisms that were consulted within one presentation at the ED were counted. Diagnostic interventions consisted of blood examinations, electrocardiogram, ultrasound, X-rays, CT-scan, MRI-scan, lumbar puncture, puncture of a swollen joint, thoracocentesis, ankle brachial pressure index, and flexible endoscopy by an ENT-physician. Radiological imaging with the same type of diagnostics, but on multiple body parts, was counted as one (e.g. X-rays of neck, pelvis and hip made at one ED visit). Therapeutic interventions comprised: (re)placing a urinary catheter, suprapubic catheter or nasogastric tube, reposition of a fracture or dislocation, sedation (including intubation), thrombolysis, placing a chest tube, or placing a halo-frame. Statistical analyses We used frequencies and percentages to describe discrete variables and the mean and standard deviation (SD) to describe continuous variables. We used a dataset consisting of patients with complete medical charts without any missing values of our study variables. We performed bivariate analysis to identify factors to be included in our multivariable analysis. The two-sample t-test was used to identify associations between continuous variables and prolonged ED LOS. The association between discrete variables and ED LOS was assessed by using the Pearson’s Chi-square test. We decided to use a p-value of < 0.05 in bivariate analysis as an entry criterion for the multivariable model. We checked the correlation of the factors and when factors were mutually strongly related, a variable was selected for exclusion from the multivariable logistic regression analysis model. Multivariable logistic regression analysis was used to calculate the odds ratio (OR) with 95% confidence intervals (CI) to identify independent risk factors for a prolonged ED LOS. p-values < 0.05 were considered statistically significant, based on two sided tests. The Nagelkerke‘s R2 is calculated for testing the performance of the model.
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