Potilaan ennusteen arviointi ensihoidossa

Väittelijä Jussi Pirneskoski : Helsingin yliopisto, 2021

Ensihoitojärjestelmä Suomessa

Teema : ensihoit

Ability of prehospital NEWS to predict 1-day and 7-day mortality is reduced in older adult patients

Background National Early Warning Score (NEWS) does not include age as a parameter despite age is a significant independent risk factor of death. The aim of this study was to examine whether age has an effect on predictive performance of short-term mortality of NEWS in a prehospital setting. We also evaluated whether adding age as an additional parameter to NEWS improved its short-term mortality prediction. Methods We calculated NEWS scores from retrospective prehospital electronic patient record data for patients 18 years or older with sufficient prehospital data to calculate NEWS. We used area under receiver operating characteristic (AUROC) to analyse the predictive performance of NEWS for 1 and 7 day mortalities with increasing age in three different age groups: = 80 years. We also explored the ORs for mortality of different NEWS parameters in these age groups. We added age to NEWS as an additional parameter and evaluated its effect on predictive performance. Results We analysed data from 35 800 ambulance calls. Predictive performance for 7-day mortality of NEWS decreased with increasing age: AUROC (95% CI) for 1-day mortality was 0.876 (0.848 to 0.904), 0.824 (0.794 to 0.854) and 0.820 (0.788 to 0.852) for first, second and third age groups, respectively. AUROC for 7-day mortality had a similar trend. Addition of age as an additional parameter to NEWS improved its ability to predict short-term mortality when assessed with continuous Net Reclassification Improvement. Conclusions Age should be considered as an additional parameter to NEWS, as it improved its performance in predicting short-term mortality in this prehospital cohort.Peer reviewe

Urgent EMS managed out-of-hospital delivery dispatches in Helsinki

Background: The aim of this study was to examine Helsinki Emergency Medical Services (EMS) and hospital records to determine the incidence and possible complications of out-of-hospital deliveries managed by EMS in Helsinki. Methods: We retrospectively analysed all urgent ambulance dispatches relating to childbirth in Helsinki from January 1, 2010 to December 31, 2014 with further analysis of hospital records for the out-of-hospital deliveries. Patients were divided in to two groups: those who delivered before reaching hospital and those who did not deliver before reaching hospital and differences between groups were analysed. Deliveries with gestational age of at least 22 + 0 weeks were considered as births in statistical analysis as this is the current national practice. Results: There were 799 urgent dispatches during the study period. In 102 (12.8 %) of these delivery took place before reaching the hospital. The incidence of EMS managed out-of-hospital delivery was found to be 3.0/1000 births. The annual number of out-of-hospital deliveries attended by EMS increased from 15 in 2010 to 28 in 2014. No stillbirths were reported. Neither maternal or perinatal deaths nor major maternal complications were noted in the study population. Discussion: Out-of-hospital deliveries represent a small minority of EMS calls and remain a challenge to maintaining professional capabilities. Small sample size might have limited the ability of the study to pick up rare complications. Conclusions: The amount of out-of-hospital deliveries in Helsinki increased during the five-year study period. There were no maternal or perinatal mortality or major complications resulting in long-term sequelae associated with the EMS-managed out-of-hospital births.Peer reviewe

Intubation first-pass success in a high performing pre-hospital critical care system is not associated with 30-day mortality : a registry study of 4496 intubation attempts

Peer reviewe

Intubation first-pass success in a high performing pre-hospital critical care system is not associated with 30-day mortality: a registry study of 4496 intubation attempts

BackgroundLower intubation first-pass success (FPS) rate is associated with physiological deterioration, and FPS is widely used as a quality indicator of the airway management of a critically ill patient. However, data on FPS's association with survival is limited. We aimed to investigate if the FPS rate is associated with 30-day mortality or physiological complications in a pre-hospital setting. Furthermore, we wanted to describe the FPS rate in Finnish helicopter emergency medical services. MethodsThis was a retrospective observational study. Data on drug-facilitated intubation attempts by helicopter emergency medical services were gathered from a national database and analysed. Multivariate logistic regression, including known prognostic factors, was performed to assess the association between FPS and 30-day mortality, collected from population registry data. ResultsOf 4496 intubation attempts, 4082 (91%) succeeded on the first attempt. The mortality rates in FPS and non-FPS patients were 34% and 38% (P = 0.21), respectively. The adjusted odds ratio of FPS for 30-day mortality was 0.88 (95% CI 0.66-1.16). Hypoxia after intubation and at the time of handover was more frequent in the non-FPS group (12% vs. 5%, P ConclusionFPS is not associated with 30-day mortality in pre-hospital critical care delivered by advanced providers. It should therefore be seen more as a process quality indicator instead of a risk factor of poor outcome, at least considering the current limitations of the parameter.</p

Random forest machine learning method outperforms prehospital National Early Warning Score for predicting one-day mortality : A retrospective study

Aim of the study: The National Early Warning Score (NEWS) is a validated method for predicting clinical deterioration in hospital wards, but its performance in prehospital settings remains controversial. Modern machine learning models may outperform traditional statistical analyses for predicting short-term mortality. Thus, we aimed to compare the mortality prediction accuracy of NEWS and random forest machine learning using prehospital vital signs. Methods: In this retrospective study, all electronic ambulance mission reports between 2008 and 2015 in a single EMS system were collected. Adult patients (>= 18 years) were included in the analysis. Random forest models with and without blood glucose were compared to the traditional NEWS for predicting one-day mortality. A ten-fold cross-validation method was applied to train and validate the random forest models. Results: A total of 26,458 patients were included in the study of whom 278 (1.0%) died within one day of ambulance mission. The area under the receiver operating characteristic curve for one-day mortality was 0.836 (95% CI, 0.810-0.860) for NEWS, 0.858 (95% CI, 0.832-0.883) for a random forest trained with NEWS variables only and 0.868 (0.843-0.892) for a random forest trained with NEWS variables and blood glucose. Conclusion: A random forest algorithm trained with NEWS variables was superior to traditional NEWS for predicting one-day mortality in adult prehospital patients, although the risk of selection bias must be acknowledged. The inclusion of blood glucose in the model further improved its predictive performance.Peer reviewe

Suositus peruselintoimintojen arvioinnista ja seurannasta

NEWS-pisteytys yhtenäistää ja systematisoi peruselintoimintojen arviointia. Se kannattaa ottaa kattavasti käyttöön ensihoidon alkuarviosta aina kotiutuspäätökseen saakka

Critically ill patients in emergency department may be characterized by low amplitude and high variability of amplitude of pulse photoplethysmography

Peer reviewe