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

2022 ◽  
Vol 8 ◽  
Author(s):  
Chu-Lin Tsai ◽  
Tsung-Chien Lu ◽  
Chih-Hung Wang ◽  
Cheng-Chung Fang ◽  
Wen-Jone Chen ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Oxygen Saturation ◽  
Vital Sign ◽  
Troponin I ◽  
Medical Center ◽  
Multivariable Analysis ◽  
Vital Signs ◽  
Reactive Protein ◽  
Laboratory Markers ◽  
Hospital Cardiac Arrest

Background: Little is known about the trajectories of vital signs prior to in-hospital cardiac arrest (IHCA), which could explain the heterogeneous processes preceding this event. We aimed to identify clinically relevant subphenotypes at high risk of IHCA in the emergency department (ED).Methods: This retrospective cohort study used electronic clinical warehouse data from a tertiary medical center. We retrieved data from 733,398 ED visits over a 7-year period. We selected one ED visit per person and retrieved patient demographics, triage data, vital signs (systolic blood pressure [SBP], heart rate [HR], body temperature, respiratory rate, oxygen saturation), selected laboratory markers, and IHCA status. Group-based trajectory modeling was performed.Results: There were 37,697 adult ED patients with a total of 1,507,121 data points across all vital-sign categories. Three to four trajectory groups per vital-sign category were identified, and the following five trajectory groups were associated with a higher rate of IHCA: low and fluctuating SBP, high and fluctuating HR, persistent hypothermia, recurring tachypnea, and low and fluctuating oxygen saturation. The IHCA-prone trajectory group was associated with a higher triage level and a higher mortality rate, compared to other trajectory groups. Except for the persistent hypothermia group, the other four trajectory groups were more likely to have higher levels of C-reactive protein, lactic acid, cardiac troponin I, and D-dimer. Multivariable analysis revealed that hypothermia (adjusted odds ratio [aOR], 2.20; 95% confidence interval [95%CI], 1.35–3.57) and recurring tachypnea (aOR 2.44; 95%CI, 1.24–4.79) were independently associated with IHCA.Conclusions: We identified five novel vital-sign sub-phenotypes associated with a higher likelihood of IHCA, with distinct patterns in clinical course and laboratory markers. A better understanding of the pre-IHCA vital-sign trajectories may help with the early identification of deteriorating patients.

Abstract 207: The Prevalence and Significance of Abnormal Vital Signs Prior to In-Hospital Cardiac Arrest

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Won Young Kim ◽  
Lars W Andersen ◽  
Sharri Mortensen ◽  
Maureen Chase ◽  
Katherine Berg ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Vital Sign ◽  
Multivariable Analysis ◽  
Vital Signs ◽  
National Registry ◽  
Patient Demographics ◽  
Get With The Guidelines ◽  
Hospital Wards ◽  
Hospital Cardiac Arrest ◽  
Overall Mortality

Background: The association between vital sign abnormalities prior to cardiac arrest and outcome has not been previously reported. In this study we investigated the prevalence of abnormal vital signs prior to in-hospital cardiac arrest and the association with mortality Methods: We utilized the Get With the Guidelines - Resuscitation national registry to identify adult patients with an in-hospital cardiac arrest between 2007-2010. We included index events and excluded patients with missing data on vital signs within 1-4 hours prior to arrest. We evaluated the prevalence of abnormal vital signs classified as mild, moderate or severe (Table 1). We determined the association between the number of abnormal vital signs per patient and in-hospital mortality using multivariate logistic regression with adjustment for multiple potential confounders including patient demographics and co-morbid conditions. Results: A total of 9,560 patients were included. Median age was 71 (60 - 81) years, 42% were female and overall mortality was 77%. The prevalence of vital sign abnormalities is shown in Table 1. As illustrated in Figure 1 we found a step-wise increase in mortality with increasing number of abnormal vital signs that remained in multivariable analysis across all categories (Mild: adjusted OR 1.37 [CI: 1.27 - 1.48], Moderate: adjusted OR 1.53 [CI: 1.35 - 1.73] and Severe: adjusted OR 1.43 [CI: 1.21 - 1.70], all p-values < 0.0001). Conclusion: Abnormal vital signs are common within four hours before cardiac arrest on in-hospital wards. Our study demonstrates incremental increases in mortality with both increasing number of pre-arrest abnormal vital signs as well as increased severity.

scholarly journals An Early Predictive Scoring Model for In-Hospital Cardiac Arrest of Emergent Hemodialysis Patients

2021 ◽  
Vol 10 (15) ◽  
pp. 3241
Author(s):  
Shih-Hao Chen ◽  
Ya-Yun Cheng ◽  
Chih-Hao Lin
Keyword(s):  
Cardiac Arrest ◽  
Risk Group ◽  
Vital Signs ◽  
Area Under The Curve ◽  
Hemodialysis Patients ◽  
High Risk Group ◽  
Predictive Score ◽  
Primary Group ◽  
Sum Scores ◽  
Hospital Cardiac Arrest

Background: Patients undergoing hemodialysis are prone to cardiac arrests. Methods: This study aimed to develop a risk score to predict in-hospital cardiac arrest (IHCA) in emergency department (ED) patients undergoing emergency hemodialysis. Patients were included if they received urgent hemodialysis within 24 h after ED arrival. The primary outcome was IHCA within three days. Predictors included three domains: comorbidity, triage information (vital signs), and initial biochemical results. The final model was generated from data collected between 2015 and 2018 and validated using data from 2019. Results: A total of 257 patients, including 52 with IHCA, were analyzed. Statistical analysis selected significant variables with higher sensitivity cutoff, and scores were assigned based on relative beta coefficient ratio: K > 5.5 mmol/L (score 1), pH < 7.35 (score 1), oxygen saturation < 85% (score 1), and mean arterial pressure < 80 mmHg (score 2). The final scoring system had an area under the curve of 0.78 (p < 0.001) in the primary group and 0.75 (p = 0.023) in the validation group. The high-risk group (defined as sum scores ≥ 3) had an IHCA risk of 47.2% and 41.7%, while the low-risk group (sum scores < 3) had 18.3% and 7%, in the primary and validation databases, respectively. Conclusions: This predictive score model for IHCA in emergent hemodialysis patients could help healthcare providers to take necessary precautions and allocate resources.

scholarly journals 156 Prehospital determinants of successful resuscitation after traumatic and non-traumatic out-of-hospital cardiac arrest

2020 ◽  
Vol 37 (12) ◽  
pp. 825.1-825
Author(s):  
Ed Barnard ◽  
Daniel Sandbach ◽  
Tracy Nicholls ◽  
Alastair Wilson ◽  
Ari Ercole
Keyword(s):  
Overall Survival ◽  
Cardiac Arrest ◽  
Hospital Admission ◽  
Hospital Discharge ◽  
Multivariable Analysis ◽  
Discharge Data ◽  
Successful Resuscitation ◽  
Bystander Cpr ◽  
Number Percentage ◽  
Hospital Cardiac Arrest

Aims/Objectives/BackgroundOut-of-hospital cardiac arrest (OHCA) is prevalent in the UK. Reported survival is lower than in countries with comparable healthcare systems; a better understanding of outcome determinants may identify areas for improvement. Aim: to compare differential determinants of survival to hospital admission and survival to hospital discharge for traumatic (TCA) and non-traumatic cardiac arrest (NCTA).Methods/DesignAn analysis of 9109 OHCA in East of England between 1 January 2015 and 31 July 2017. Univariate descriptives and multivariable analysis were used to understand the determinants of survival for NTCA and TCA. Two Utstein outcome variables were used: survival to hospital admission and hospital discharge. Data reported as number (percentage), number (percentage (95% CI)) and median (IQR) as appropriate. Continuous data have been analysed with a Mann-Whitney U test, and categorical data have been analysed with a χ2 test. Analyses were performed using the R statistical programming language.Results/ConclusionsThe incidence of OHCA was 55.1 per 100 000 population/year. The overall survival to hospital admission was 27.6% (95%CI 26.7% to 28.6%) and the overall survival to discharge was 7.9% (95%CI 7.3% to 8.5%). Survival to hospital admission and survival to hospital discharge were both greater in the NTCA group compared with the TCA group: 27.9% vs 19.3% p=0.001, and 8.0% vs 3.8% p=0.012 respectively.Determinants of NTCA and TCA survival were different, and varied according to the outcome examined. In NTCA, bystander cardiopulmonary resuscitation (CPR) was associated with survival at discharge but not at admission, and the likelihood of bystander-CPR was dependent on geographical socioeconomic status.NTCA and TCA are clinically distinct entities with different predictors for outcome and should be reported separately. Determinants of survival to hospital admission and discharge differ in a way that likely reflects the determinants of neurological injury. Bystander CPR public engagement may be best focused in more deprived areas.

Abstract 246: The Relationship Between Favorable Neurological Outcome in Patients With Out-of-Hospital Cardiac Arrest Due to Cardiac Etiology and Regional Disparity of the Number of Physicians

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
Tsukasa Yagi ◽  
Ken Nagao ◽  
Shigemasa Tani ◽  
Eizo Tachibana ◽  
Nobutaka Chiba ◽  
...  
Keyword(s):  
Public Health ◽  
Cardiac Arrest ◽  
Neurological Outcome ◽  
Multivariable Analysis ◽  
Public Health Problem ◽  
Regional Disparity ◽  
Major Public Health Problem ◽  
Favorable Neurological Outcome ◽  
The Relationship ◽  
Hospital Cardiac Arrest

Background: Cardiac arrest is a major public health issue worldwide. In Japan, the regional disparity of the number of physicians per 100000 population is also a major public health problem. However, it is unknown whether there is the relationship between favorable neurological outcome in patients with out-of-hospital cardiac arrest (OHCA) due to cardiac etiology and this regional disparity. The aim of the present study was to clarify this relationship using the data of the All-Japan Utstein Registry, a prospective, nationwide, population-based registry of OHCA. Methods: From the data of the All-Japan Utstein Registry between 2011 and 2015, we included adult patients who had OHCA due to cardiac etiology. 47 prefectures of Japan were divided into quartiles on the basis of the number of physicians in each prefecture, reported by Ministry of Health, Labor and Welfare in Japan. In addition, study patients were divided into four groups based on these quartiles. We compared favorable neurological outcome at 30 days after OHCA in each group, using the multivariable logistic-regression analysis. Results: Four quartile ranges of the number of physicians were set for this study (Figure). Moreover, of the 629,471 OHCA victims between 2011 and 2015, 358,993 met the inclusion criteria. Figure represented favorable neurological outcome at 30 days after OHCA in each quartile. In the multivariable analysis, the adjusted odds ratios for Quartile 2, Quartile 3 and Quartile 4 compared with Quartile 1 for favorable neurological outcome at 30 days after OHCA was 0.971 (95%CI 0.918- 1.027; P=0.307), 1.011 (95%CI 0.956- 1.069; P=0.703) and 0.850 (95%CI 0.809- 0.893; P<0.001), respectively. Conclusion: The regions in which the number of physicians per 100000 population was larger were inferior to the regions in which the number of these was smaller, in terms of neurological benefits in patients with OHCA due to cardiac etiology.

scholarly journals Design and Improving Vital Sign with Parameter Body Temperature (axilla) and Oxymetry for Patient Monitoring

2020 ◽  
Vol 2 (2) ◽  
pp. 58-64
Author(s):  
Mohamad Adam Firdaus ◽  
Andjar Pudji ◽  
Muhammad Ridha Mak'ruf
Keyword(s):  
Body Temperature ◽  
Oxygen Saturation ◽  
Vital Sign ◽  
Medical Service ◽  
Vital Signs ◽  
Measuring Instruments ◽  
Dressing Tool ◽  
Number Of Patients ◽  
Quality Of Patient Care

In most hospitals, nurses routinely calculate and document primary vital signs for all patients 2-3 times per day to get information on the patient's condition. Vital Sign Monitor is made for medical devices that can diagnose patients who need intensive care to determine patient needs. Some parameters used in patient renewal: Oxygen saturation (SPO2), and body temperature. This makes additional tasks very important to be evaluated for medical staff and equipment manufacturers. This evaluation is needed to get the real condition of the patient. With the large number of patients who need evaluation, it is not possible to see the condition of some medical workers who work. This medical service is expected to reduce the workload of nurses with doctors and improve the quality of patient care. The large demand for these devices, mostly in hospital intensive rooms, is the basis for researching the output of data from multiple vital sensor monitor monitors to obtain accurate and precise outputs. The output of the two sensors is processed by Arduino Mega2560 and requested on a 5 inch TFT LCD in the form of body temperature and oxygen saturation. Comparison of module results with standard measuring instruments calibrated to reference this module is used for accurate and precise results. According to the assessment and reversing tool data with the dressing tool, the highest error value is 1%. With a maximum permitted permission of 5%.

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