Trajectories of Vital Signs and Risk of In-Hospital Cardiac Arrest

Tsai, Chu‐Lin; Lu, Tsung-Chien; Wang, Chih‐Hung; Chen, Wen-Jone

doi:10.3389/fmed.2021.800943

Cited by 5 publications

(2 citation statements)

References 26 publications

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“…Previous research has already shown that accounting for differences in vital signs values between day and night may reduce alarm rate in various models at the general ward [ 24 ]. The next step in predictive modeling with continuous data is trend analysis, since changes of vital signs might be better predictors than single values [ 43 , 44 ]. Both model builders and hospital professionals should be aware however that a rise in heart rate and respiratory rate in the morning, or a rise of skin temperature in the evening, might not be a deteriorating trend at all, but rather a part of a physiological rhythm.…”

Section: Discussionmentioning

confidence: 99%

Circadian patterns of heart rate, respiratory rate and skin temperature in hospitalized COVID-19 patients

et al. 2022

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Rationale Vital signs follow circadian patterns in both healthy volunteers and critically ill patients, which seem to be influenced by disease severity in the latter. In this study we explored the existence of circadian patterns in heart rate, respiratory rate and skin temperature of hospitalized COVID-19 patients, and aimed to explore differences in circadian rhythm amplitude during patient deterioration. Methods We performed a retrospective study of COVID-19 patients admitted to the general ward of a tertiary hospital between April 2020 and March 2021. Patients were continuously monitored using a wireless sensor and fingertip pulse oximeter. Data was divided into three cohorts: patients who recovered, patients who developed respiratory insufficiency and patients who died. For each cohort, a population mean cosinor model was fitted to detect rhythmicity. To assess changes in amplitude, a mixed-effect cosinor model was fitted. Results A total of 429 patients were monitored. Rhythmicity was observed in heartrate for the recovery cohort (p<0.001), respiratory insufficiency cohort (p<0.001 and mortality cohort (p = 0.002). Respiratory rate showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.18 and p = 0.51). Skin temperature also showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.22 and p = 0.12). For respiratory insufficiency, only the amplitude of heart rate circadian pattern increased slightly the day before (1.2 (99%CI 0.16–2.2, p = 0.002)). In the mortality cohort, the amplitude of heart rate decreased (-1.5 (99%CI -2.6- -0.42, p<0.001)) and respiratory rate amplitude increased (0.72 (99%CI 0.27–1.3, p = 0.002) the days before death. Conclusion A circadian rhythm is present in heart rate of COVID-19 patients admitted to the general ward. For respiratory rate and skin temperature, rhythmicity was only found in patients who recover, but not in patients developing respiratory insufficiency or death. We found no consistent changes in circadian rhythm amplitude accompanying patient deterioration.

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Section: Discussionmentioning

confidence: 99%

Circadian patterns of heart rate, respiratory rate and skin temperature in hospitalized COVID-19 patients

et al. 2022

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“…Key considerations include aggregating vital signs [40], integrating contextual factors like signs/symptoms, patient circadian rhythm, and activity levels. Establishing baseline values preoperatively and assessing relative deviations from established trends in vital signs over time intervals [78], along with incorporating laboratory values, can bolster prediction models for clinical deterioration [79].…”

Section: Software Platforms For Trend Analysismentioning

confidence: 99%

Wearable wireless continuous vital signs monitoring on the general ward

Leenen,

Schoonhoven,

Patijn

2024

Current Opinion in Critical Care

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Purpose of review Wearable wireless sensors for continuous vital signs monitoring (CVSM) offer the potential for early identification of patient deterioration, especially in low-intensity care settings like general wards. This study aims to review advances in wearable CVSM – with a focus on the general ward – highlighting the technological characteristics of CVSM systems, user perspectives and impact on patient outcomes by exploring recent evidence. Recent findings The accuracy of wearable sensors measuring vital signs exhibits variability, especially notable in ambulatory patients within hospital settings, and standard validation protocols are lacking. Usability of CMVS systems is critical for nurses and patients, highlighting the need for easy-to-use wearable sensors, and expansion of the number of measured vital signs. Current software systems lack integration with hospital IT infrastructures and workflow automation. Imperative enhancements involve nurse-friendly, less intrusive alarm strategies, and advanced decision support systems. Despite observed reductions in ICU admissions and Rapid Response Team calls, the impact on patient outcomes lacks robust statistical significance. Summary Widespread implementation of CVSM systems on the general ward and potentially outside the hospital seems inevitable. Despite the theoretical benefits of CVSM systems in improving clinical outcomes, and supporting nursing care by optimizing clinical workflow efficiency, the demonstrated effects in clinical practice are mixed. This review highlights the existing challenges related to data quality, usability, implementation, integration, interpretation, and user perspectives, as well as the need for robust evidence to support their impact on patient outcomes, workflow and cost-effectiveness.

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Prediction of clinical deterioration risk at 8 hours after arrival in emergency department in non‐traumatic patients using trends in modified early warning score level

Lin,

Chang,

Lin

et al. 2024

Hong Kong j. emerg. med.

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BackgroundImproving the quality of medical care in hospitals is a major priority for all departments. The early warning score (EWS) trend is an effective early risk stratification tool that reflects the changes in patient condition and allows better assessment of deterioration risk.ObjectiveThe aim of this study was to investigate whether utilizing the trend of the modified early warning score (MEWS) level within 4 h of a patient's arrival in the emergency department (ED) could identify patients at risk of clinical deterioration at 8 h after arrival in the ED.MethodsWe conducted a retrospective observational study of non‐trauma patients who had at least two vital sign measurements (Glasgow Coma Scale score, heart rate, blood pressure, respiratory rate, and body temperature) within 8 h of arriving in the ED. The primary outcome was patients who had MEWS ≥ 4 at 8 h after arrival in the ED. We performed multivariate logistic regression analysis using age, sex, MEWS level at arrival in the ED, MEWS level within 4 h after arrival in the ED, and MEWS level trend over time.ResultsAmong the 5825 patients, 680 (11.7%) were at risk of deterioration at 8 h after arrival in the ED. To predict the risk of deteriorating conditions (MEWS ≥ 4), utilizing the MEWS level trend within 4 h of arrival in the ED was more effective in identifying patients at risk of deterioration after 8 h of arrival in the ED compared to using a single MEWS value during the ED stay. The corresponding areas under the receiver operating characteristic curve were 0.756 (95% confidence interval (CI) 0.734–0.778) and 0.846 (95% CI 0.827–0.865), respectively (p < 0.01).ConclusionsThe proposed trend‐based predictive model for MEWS levels can alert healthcare personnel regarding patients at increased risk of deterioration (MEWS ≥ 4), potentially reducing mortality rates during ED stays.

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Trajectories of Vital Signs and Risk of In-Hospital Cardiac Arrest

Cited by 5 publications

References 26 publications

Circadian patterns of heart rate, respiratory rate and skin temperature in hospitalized COVID-19 patients

Circadian patterns of heart rate, respiratory rate and skin temperature in hospitalized COVID-19 patients

Wearable wireless continuous vital signs monitoring on the general ward

Prediction of clinical deterioration risk at 8 hours after arrival in emergency department in non‐traumatic patients using trends in modified early warning score level

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