scholarly journals Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study

BMJ ◽  
2017 ◽  
pp. j4208 ◽  
Author(s):  
Julia Hippisley-Cox ◽  
Carol Coupland
Keyword(s):  
Cohort Study ◽  
Risk Prediction ◽  
Prediction Algorithm ◽  
Short Term ◽  
Risk Of Death ◽  
Development And Validation

scholarly journals Which symptoms pose the highest risk in patients calling for an ambulance? A population-based cohort study from Denmark

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Stine Ibsen ◽  
Tim Alex Lindskou ◽  
Christian H. Nickel ◽  
Torben Kløjgård ◽  
Erika Frischknecht Christensen ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Cohort Study ◽  
Chest Pain ◽  
Emergency Medical Service ◽  
Medical Service ◽  
Population Based ◽  
Mechanism Of Injury ◽  
Short Term ◽  
Risk Of Death ◽  
Age And Sex

Abstract Background Emergency medical service patients are a vulnerable population and the risk of mortality is considerable. In Denmark, healthcare professionals receive 112-emergency calls and assess the main reason for calling. The main aim was to investigate which of these reasons, i.e. which symptoms or mechanism of injury, contributed to short-term risk of death. Secondary aim was to study 1–30 day-mortality for each symptom/ injury. Methods Historic population-based cohort study of emergency medical service patients calling 112 in the North Denmark Region between 01.01.2016–31.12.2018. We defined 1-day mortality as death on the same or the following day. The frequency of each symptom and cumulative number of deaths on day 1 and 30 together with 1- and 30-day mortality for each symptom/mechanism of injury is presented in proportions. Poisson regression with robust variance estimation was used to estimate incident rates (IR) of mortality with 95% confidence intervals (CI), crude and age and sex adjusted, mortality rates on day 1 per 100,000 person-year in the population. Results The five most frequent reasons for calling 112 were “chest pain” (15.9%), “unclear problem” (11.9%), “accidents” (11.2%), “possible stroke” (10.9%), and “breathing difficulties” (8.3%). Four of these contributed to the highest numbers of deaths: “breathing difficulties” (17.2%), “unclear problem” (13.2%), “possible stroke” (8.7%), and “chest pain” (4.7%), all exceeded by “unconscious adult – possible cardiac arrest” (25.3%). Age and sex adjusted IR of mortality per 100,000 person-year was 3.65 (CI 3.01–4.44) for “unconscious adult – possible cardiac arrest” followed by “breathing difficulties” (0.45, CI 0.37–0.54), “unclear problem”(0.30, CI 0.11–0.17), “possible stroke”(0.13, CI 0.11–0.17) and “chest pain”(0.07, CI 0.05–0.09). Conclusion In terms of risk of death on the same day and the day after the 112-call, “unconscious adult/possible cardiac arrest” was the most deadly symptom, about eight times more deadly than “breathing difficulties”, 12 times more deadly than “unclear problem”, 28 times more deadly than “possible stroke”, and 52 times more deadly than “chest pain”. “Breathing difficulties” and “unclear problem” as presented when calling 112 are among the top three contributing to short term deaths when calling 112, exceeding both stroke symptoms and chest pain.

DEVELOPMENT AND VALIDATION OF A RISK-PREDICTION ALGORITHM FOR THE RECURRENCE OF PANIC DISORDER

2015 ◽  
Vol 32 (5) ◽  
pp. 341-348 ◽  
Author(s):  
Yan Liu ◽  
Jitender Sareen ◽  
James Bolton ◽  
JianLi Wang
Keyword(s):  
Panic Disorder ◽  
Risk Prediction ◽  
Prediction Algorithm ◽  
Development And Validation
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