Head-to-head comparison of 19 prediction models for short-term outcome in medical patients in the emergency department: a retrospective study

van Dam, Paul M. E. L.; Lievens, Sien; Zelis, Noortje; van Doorn, William P. T. M.; Meex, Steven J. R.; Cals, Jochen W. L.; Stassen, Patricia M.

doi:10.1080/07853890.2023.2290211

Cited by 2 publications

(1 citation statement)

References 49 publications

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“…Second, there is a risk of bias since we used a convenience sample. To address selection bias, we compared the age, MTS triage categories and hospital admission rate of our study sample with all medical (non-trauma) ED patients during an entire year and in a previous study in our ED, and found no differences (S2 Table) [35]. Therefore, the study sample appears to be a representative sample of the ED population at the MUMC+.…”

Section: Study Limitationsmentioning

confidence: 88%

Acute internal medicine physicians’ clinical intuition based on acute care telephone referral: A prospective study

van Dam,

Lasso Peña,

Mommertz

et al. 2024

PLoS ONE

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Introduction In the Netherlands, most emergency department (ED) patients are referred by a general practitioner (GP) or a hospital specialist. Early risk stratification during telephone referral could allow the physician to assess the severity of the patients’ illness in the prehospital setting. We aim to assess the discriminatory value of the acute internal medicine (AIM) physicians’ clinical intuition based on telephone referral of ED patients to predict short-term adverse outcomes, and to investigate on which information their predictions are based. Methods In this prospective study, we included adult ED patients who were referred for internal medicine by a GP or a hospital specialist. Primary outcomes were hospital admission and triage category according to the Manchester Triage System (MTS). Secondary outcome was 31-day mortality. The discriminatory performance of the clinical intuition was assessed using an area under the receiver operating characteristics curve (AUC). To identify which information is important to predict adverse outcomes, we performed univariate regression analysis. Agreement between predicted and observed MTS triage category was assessed using intraclass and Spearman’s correlation. Results We included 333 patients, of whom 172 (51.7%) were referred by a GP, 146 (43.8%) by a hospital specialist, and 12 (3.6%) by another health professional. The AIM physician’s clinical intuition showed good discriminatory performance regarding hospital admission (AUC 0.72, 95% CI: 0.66–0.78) and 31-day mortality (AUC 0.73, 95% CI: 0.64–0.81). Univariate regression analysis showed that age ≥65 years and a sense of alarm were significant predictors. The predicted and observed triage category were similar in 45.2%, but in 92.5% the prediction did not deviate by more than one category. Intraclass and Spearman’s correlation showed fair agreement between predicted and observed triage category (ICC 0.48, Spearman’s 0.29). Conclusion Clinical intuition based on relevant information during a telephone referral can be used to accurately predict short-term outcomes, allowing for early risk stratification in the prehospital setting and managing ED patient flow more effectively.

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Section: Study Limitationsmentioning

confidence: 88%

Acute internal medicine physicians’ clinical intuition based on acute care telephone referral: A prospective study

van Dam,

Lasso Peña,

Mommertz

et al. 2024

PLoS ONE

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At-home validation of remote breathing monitoring: A proof-of-concept for long-term care of respiratory patients using a non-contact, radar-based biomotion sensor

Fischer,

Eggert,

Wildenauer

et al. 2024

Preprint

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Purpose Long-term monitoring of respiratory rate (RR) is promising for the management of chronic conditions. Research interest is particularly high in chronic respiratory diseases (CRDs), especially for predicting acute exacerbations of COPD (AECOPD). The aim of the present study was to evaluate the long-term validity of a recent non-contact biomotion sensor in the home environment of CRD patients with domiciliary ventilator support, focusing on patient acceptance and usability of this device, as well as RR fluctuations related to AECOPD. Patients and methods In this prospective proof-of-concept study, 19 patients requiring non-invasive ventilation (NIV) and seven patients requiring invasive mechanical ventilation (IMV) were provided with the non-contact device for six and one month, respectively. Main indication for NIV therapy was COPD. Real-world validation of the device was performed by comparing nocturnal RR values between the non-contact system and both types of ventilators. The acceptance and operability of the biomotion sensor were evaluated using a questionnaire. COPD exacerbations that occurred during the study period were assessed for possible RR fluctuations preceding these events. Results Mean absolute error (MAE) of median RR between the NIV device and the non-contact system, based on 2326 nights, was 0.78 (SD: 1.96) breaths per minute (brpm). MAE between the IMV device and the non-contact system was 0.12 brpm (SD: 0.52) for 215 nights. The non-contact device was accepted by the patients and proved to be easy to use. In some of the overall 13 cases of AECOPD, RR time courses showed variations of increased nocturnal respiratory activity a few days before the occurrence of such events. Conclusion The present non-contact system is suitable and well accepted for valid long-term monitoring of nocturnal RR in the patient's home environment. This finding may serve as a starting point for larger studies, e.g., to develop robust AECOPD prediction rules.

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Head-to-head comparison of 19 prediction models for short-term outcome in medical patients in the emergency department: a retrospective study

Cited by 2 publications

References 49 publications

Acute internal medicine physicians’ clinical intuition based on acute care telephone referral: A prospective study

Acute internal medicine physicians’ clinical intuition based on acute care telephone referral: A prospective study

At-home validation of remote breathing monitoring: A proof-of-concept for long-term care of respiratory patients using a non-contact, radar-based biomotion sensor

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