A new classification for emergency critically ill patients and analysis of their adverse events during intrahospital transport: A cluster analysis.

BACKGROUND: Critical patients may experience various adverse events during transportation within hospitals. Therefore, quickly evaluating and classifying patients before transporting them from the emergency department and focusing on managing high-risk patients are critical. At present, no unified classification method exists; all the current approaches are subjective. AIMS: To ensure transportation safety, we conducted a cluster analysis of critically ill patients transferred from the emergency department to the intensive care unit. STUDY DESIGN: Single-centre cohort study. This study was conducted at a comprehensive first-class teaching hospital in Beijing. Convenience sampling and continuous enrolment were employed. We collected data from 1 January 2019, to 31 December 2021. All patients were transferred from the emergency department to the intensive care unit, and cluster analysis was conducted using five variables. RESULTS: A total of 584 patients were grouped into three clusters. Cluster 1 (high systolic blood pressure group) included 208 (35.6%) patients. Cluster 2 (high heart rate and low blood oxygen group) included 55 (9.4%) patients. Cluster 3 (normal group) included the remaining 321 (55%) patients. The oxygen saturation levels of all the patients were lower after transport, and the proportion of adverse events (61.8%) was the highest in Cluster 2 (p < .05). CONCLUSIONS: This study utilized data on five important vital signs from a cluster analysis to explore possible patient classifications and provide a reference for ensuring transportation safety. RELEVANCE TO CLINICAL PRACTICE: Before transferring patients, we should classify them and implement targeted care. Changes in blood oxygen levels in all patients should be considered, with a focus on the occurrence of adverse events during transportation among patients with high heart rates and low blood oxygen levels.

Establishment of a simplified score for predicting risk during intrahospital transport of critical patients: A prospective cohort study.

AIMS AND OBJECTIVES: To establish a simple score that enables nurses to quickly, conveniently and accurately identify patients whose condition may change during intrahospital transport. BACKGROUND: Critically ill patients may experience various complications during intrahospital transport; therefore, it is important to predict their risk before they leave the emergency department. The existing scoring systems were not developed for this population. DESIGN: A prospective cohort study. METHODS: This study used convenience sampling and continuous enrolment from 1 January, 2019, to 30 June, 2021, and 584 critically ill patients were included. The collected data included vital signs and any condition change during transfer. The STROBE checklist was used. RESULTS: The median age of the modelling group was 74 (62, 83) years; 93 (19.7%) patients were included in the changed group, and 379 (80.3%) were included in the stable group. The five independent model variables (respiration, pulse, oxygen saturation, systolic pressure and consciousness) were statistically significant (p < .05). The above model was simplified based on beta coefficient values, and each variable was assigned 1 point, for a total score of 0-5 points. The AUC of the simplified score in the modelling group was 0.724 (95% CI: 0.682-0.764); the AUC of the simplified score in the validation group (112 patients) was 0.657 (95% CI: 0.566-0.741). CONCLUSIONS: This study preliminarily established a simplified scoring system for the prediction of risk during intrahospital transport from the emergency department to the intensive care unit. It provides emergency nursing staff with a simple assessment tool to quickly, conveniently and accurately identify a patient's transport risk. RELEVANCE TO CLINICAL PRACTICE: This study suggested the importance of strengthening the evaluation of the status of critical patients before intrahospital transport, and a simple score was formed to guide emergency department nurses in evaluating patients.

Risk prediction using the National Early Warning Score and the Worthing Physiological Scoring System in patients who were transported to the Intensive Care Unit from the Emergency Department: A cohort study.

OBJECTIVES: The aim of this study was to assess the value of the National Early Warning Score and Worthing Physiological Scoring System for predicting changes in the condition of critical cases during transfer from the emergency department to the intensive care unit. METHODS: This prospective single-centre study was conducted at a 1759-bed hospital in Beijing. We recorded the vital signs in the cases before leaving the emergency department and their changes in condition during transit. RESULTS: A total of 258 critically ill cases were included. Forty-four cases (17.05%) exhibited changes in their condition during transit. Compared with cases with NEWS ≤ 5, cases with NEWS > 5 were more likely to experience changes with an OR of 5.744 (95% CI 2.888-11.426). Compared with cases with WPS ≤ 2, cases with WPS > 2 were more likely to experience changes with an OR of 7.217 (95% CI 3.575-14.569). The difference between the areas under the curve of the NEWS (0.751 ± 0.045) and the WPS (0.736 ± 0.045) was not statistically significant (P = 0.4518). CONCLUSION: In our study, the Worthing Physiological Scoring System and National Early Warning Score both exhibited good discriminatory power, but the Worthing Physiological Scoring System is simpler to use and more suitable for use in a busy emergency department.