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Erschienen in: Critical Care 1/2020

Open Access 01.12.2020 | Research Letter

Evaluation of the E-PRE-DELIRIC prediction model for ICU delirium: a retrospective validation in a UK general ICU

verfasst von: Sarah L. Cowan, Jacobus Preller, Robert J. B. Goudie

Erschienen in: Critical Care | Ausgabe 1/2020

Hinweise

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Abkürzungen
AUROC
Area under the ROC curve
AUPRC
Area under the PR curve
CAM-ICU
Confusion Assessment Method for the ICU
E-PRE-DELIRIC
Early prediction model for delirium in ICU patients
ICU
Intensive care unit
LoS
Length of stay
PPV
Positive predictive value
PR
Precision-recall
ROC
Receiver operator characteristic

Introduction

E-PRE-DELIRIC is a point-of-admission ICU delirium risk prediction tool [1], with reported good or moderate performance [24]. In this study, we assessed its performance in a large UK teaching hospital general ICU using routinely collected data, as approved by the local Research Data Governance Committee.

Methods

We retrospectively analysed data for 2445 consecutive ICU admissions (November 2014 to June 2017). Patients were routinely assessed for delirium, using twice daily Confusion Assessment Method for the ICU (CAM-ICU) assessment [5]. As in previous E-PRE-DELIRIC studies [14], delirium was defined as any positive CAM-ICU assessment or antipsychotic initiation while on ICU.
We adopted the original E-PRE-DELIRIC exclusion criteria [1], excluding 683 ICU admissions for ICU stay < 24 h (425 admissions), incomplete CAM-ICU data (152), delirium on admission (50), comatose throughout entire ICU stay (47), and age under 18 (9). Sixteen admissions were excluded due to missing E-PRE-DELIRIC components; 1746 admissions (1569 unique patients) remained for analysis; this 71.4% inclusion rate is consistent with previous studies (Table 1).
Table 1
Patient characteristics in this study, the E-PRE-DELIRIC development dataset [1] and other validation studies [24]
Factor
This study
Development dataset [1]
DECISION study [2, 3]
Green et al. [4]
Admissions during study period, n
2445
2802
803
Included in analysis, n (%)
1746 (71.4)
1962 (–)
2178 (77.7)
455 (56.7)
Delirium, n (%)
763 (43.7)
481 (24.5)
466 (21.4)
160 (35.2)
Age (years), mean (Q1–Q3, min/max)
58.6 (47.0–71.8, 18/94)
61.7 (53–74, 18/95)
62.1 (–)
66.7 (49.0–77.3, –/–)
Male, n (%)
1010 (57.8)
1166 (59.4)
1324 (60.8)
241 (53.0)
Admission category, n (%)
 Surgery
813 (46.6)
1019 (51.9)
1079 (49.5)
 Medicine
837 (47.9)
683 (34.8)
859 (39.3)
 Trauma
33 (1.9)
90 (4.6)
86 (4.0)
 Neurology/neurosurgery
63 (3.6)
170 (8.7)
157 (7.2)
Urgent admission, n (%)
1534 (87.9)
1163 (59.3)
1345 (61.8)
APACHE II
20.0 (mean)
17.4 (mean)
16 (median)
ICU LoS (days), median (Q1–Q3, min/max)
4.5 (2.4–10.0, 1.0/184.0)
2.0 (1–6, 1/133)
3.0 (2–6, 1/96)
2.6 (1.5–4.4, –/–)
ICU mortality, n (%)
210 (12.0)
17 (3.7)
– indicates the figure was not reported

Results and discussion

Seven hundred sixty-three delirium cases were identified (43.7% of ICU admissions), a higher incidence than reported previously (Table 1). This is likely due to differences in the study population compared to previous studies: more patients were classified as urgent, the mean APACHE II score was higher, and median length of stay (LoS) was longer (Table 1).
The mean E-PRE-DELIRIC score was 0.269 (Q1–Q3; 0.154–0.371). The histogram of E-PRE-DELIRIC scores shows extensive overlap between patients who did and did not develop delirium (Fig. 1a). The receiver operator characteristic (ROC) curve (Fig. 1b) and the precision-recall (PR) curve (Fig. 1c), showing precision (positive predictive value (PPV)) against recall (sensitivity), both indicate moderate-to-poor discriminative performance. The area under the ROC (AUROC) was 0.628 (95% CI 0.602–0.653). The area under the PR curve (AUPRC) was 0.534. For sensitivity > 0.1, PPV was between 0.437 and 0.585, indicating only around half of the patients predicted to develop delirium actually did, in a population with 43.7% incidence. Refitting the E-PRE-DELIRIC logistic regression model to our data hardly improved discrimination: AUROC was 0.648 (95% CI 0.622–0.673) and AUPRC was 0.566.
The calibration plot, of predicted risk against observed delirium rate, shows the risk of delirium is considerably underestimated, especially in patients with predicted risk of delirium less than 0.5 (Fig. 1d). Poor calibration is corroborated by the calibration slope model logit(probability of delirium) = alpha + beta ×logit(p), where p is the E-PRE-DELIRIC score [6]. The estimated slope beta = 0.58 (95% CI 0.46–0.71) is significantly below 1, indicating the predicted probabilities are overly variable; and the estimated intercept alpha = 0.84 (95% CI 0.74–0.95) is significantly above 0 when fixing beta = 1, indicating the predicted probabilities are predominantly too low. E-PRE-DELIRIC is particularly poorly calibrated for the surgical patients in the study, many of whom have major intraabdominal pathology: those with predicted risk < 10% had an observed incidence of 26%.
Of 763 delirium cases, 563 were CAM-ICU positive and 200 were included due to antipsychotic initiation. When including only CAM-ICU-positive delirium, calibration was improved (alpha = 0.29) but remained overly variable (beta = 0.52), while discrimination was similar (AUROC 0.615; AUPRC 0.396, with 32.2% observed incidence).
While E-PRE-DELIRIC is intended as a point-of-admission score, some of its exclusion criteria are retrospective (LoS; CAM-ICU completeness; comatose throughout). To assess real-world performance, we repeated our analysis without these criteria. The AUROC (0.615) and AUPRC (0.423, with 35.0% observed incidence) remained similar.

Conclusion

In this population, the E-PRE-DELIRIC score is not as discriminative or as well calibrated as previously reported. PPV was only slightly higher than delirium incidence, meaning the utility of E-PRE-DELIRIC for guiding clinical decision-making in this population is limited.

Acknowledgements

This study was supported by the UK National Institute for Health Research (NIHR) through the Cambridge Biomedical Research Centre (BRC), with data provided by Cambridge Clinical Informatics (Led by Drs. Afzal Chaudhry and Lydia Drumright). RJBG was supported by the UK Medical Research Council [programme code MC_UU_00002/2]. We are grateful to Vince Taylor for his careful work extracting data for this study.
The use of the anonymous data used in this study was approved by the Cambridge Clinical Informatics Research Data Governance Committee.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Metadaten
Titel
Evaluation of the E-PRE-DELIRIC prediction model for ICU delirium: a retrospective validation in a UK general ICU
verfasst von
Sarah L. Cowan
Jacobus Preller
Robert J. B. Goudie
Publikationsdatum
01.12.2020
Verlag
BioMed Central
Erschienen in
Critical Care / Ausgabe 1/2020
Elektronische ISSN: 1364-8535
DOI
https://doi.org/10.1186/s13054-020-2838-2

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