Browsing by Subject "Early warning score"

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  • Hoikka, Marko; Silfvast, Tom; Ala-Kokko, Tero I. (2018)
    Objectives: The prehospital research field has focused on studying patient survival in cardiac arrest, as well as acute coronary syndrome, stroke, and trauma. There is little known about the overall short-term mortality and its predictability in unselected prehospital patients. This study examines whether a prehospital National Early Warning Score (NEWS) predicts 1-day and 30-day mortalities. Methods: Data from all emergency medical service (EMS) situations were coupled to the mortality data obtained from the Causes of Death Registry during a six-month period in Northern Finland. NEWS values were calculated from first clinical parameters obtained on the scene and patients were categorized to the low, medium and high-risk groups accordingly. Sensitivities, specificities, positive predictive values (PPVs), negative predictive values (NPVs), and likelihood ratios (PLRs and NLRs) were calculated for 1-day and 30-day mortalities at the cut-off risks. Results: A total of 12,426 EMS calls were included in the study. The overall 1-day and 30-day mortalities were 1.5 and 4.3%, respectively. The 1-day mortality rate for NEWS values = 13 higher than 20%. The high-risk NEWS group had sensitivities for 1-day and 30-day mortalities 0.801 (CI 0.74-0.86) and 0.42 (CI 0.38-0.47), respectively. Conclusion: In prehospital environment, the high risk NEWS category was associated with 1-day mortality well above that of the medium and low risk NEWS categories. This effect was not as noticeable for 30-day mortality. The prehospital NEWS may be useful tool for recognising patients at early risk of death, allowing earlier interventions and responds to these patients.
  • Hoikka, Marko; Länkimäki, Sami; Silfvast, Tom; Ala-Kokko, Tero I. (2016)
    Background: In Finland, calls for emergency medical services are prioritized by educated non-medical personnel into four categories-from A (highest risk) to D (lowest risk)-following a criteria-based national dispatch protocol. Discrepancies in triage may result in risk overestimation, leading to inappropriate use of emergency medical services units and to risk underestimation that can negatively impact patient outcome. To evaluate dispatch protocol accuracy, we assessed association between priority assigned at dispatch and the patient's condition assessed by emergency medical services on the scene using an early warning risk assessment tool. Methods: Using medical charts, clinical variables were prospectively recorded and evaluated for all emergency medical services missions in two hospital districts in Northern Finland during 1.1.2014-30.6.2014. Risk assessment was then re-categorized as low, medium, or high by calculating the National Early Warning Score (NEWS) based on the patients' clinical variables measured at the scene. Results: A total of 12,729 emergency medical services missions were evaluated, of which 616 (4.8%) were prioritized as A, 3193 (25.1%) as B, 5637 (44.3%) as C, and 3283 (25.8%) as D. Overall, 67.5% of the dispatch missions were correctly estimated according to NEWS. Of the highest dispatch priority missions A and B, 76.9 and 78.3%, respectively, were overestimated. Of the low urgency missions (C and D), 10.7% were underestimated; 32.0% of the patients who were assigned NEWS indicating high risk had initially been classified as low urgency C or D priorities at the dispatch. Discussion and conclusion: The present results show that the current Finnish medical dispatch protocol is suboptimal and needs to be further developed. A substantial proportion of EMS missions assessed as highest priority were categorized as lower risk according to the NEWS determined at the scene, indicating over-triage with the protocol. On the other hand, only a quarter of the high risk NEWS patients were classified as the highest priority at dispatch, indicating considerable under-triage with the protocol.
  • Sartelli, Massimo; Abu-Zidan, Fikri M.; Labricciosa, Francesco M.; Kluger, Yoram; Coccolini, Federico; Ansaloni, Luca; Leppäniemi, Ari; Kirkpatrick, Andrew W.; Tolonen, Matti; Trana, Cristian; Regimbeau, Jean-Marc; Hardcastle, Timothy; Koshy, Renol M.; Abbas, Ashraf; Aday, Ulas; Adesunkanmi, A. R. K.; Ajibade, Adesina; Akhmeteli, Lali; Akin, Emrah; Akkapulu, Nezih; Alotaibi, Alhenouf; Altintoprak, Fatih; Anyfantakis, Dimitrios; Atanasov, Boyko; Augustin, Goran; Azevedo, Constanca; Bala, Miklosh; Balalis, Dimitrios; Baraket, Oussama; Baral, Suman; Barkai, Or; Beltran, Marcelo; Bini, Roberto; Bouliaris, Konstantinos; Caballero, Ana B.; Calu, Valentin; Catani, Marco; Ceresoli, Marco; Charalampakis, Vasileios; Jusoh, Asri Che; Chiarugi, Massimo; Cillara, Nicola; Cobos Cuesta, Raquel; Cobuccio, Luigi; Cocorullo, Gianfranco; Colak, Elif; Conti, Luigi; Cui, Yunfeng; De Simone, Belinda; Delibegovic, Samir; Demetrashvili, Zaza; Demetriades, Demetrios; Dimova, Ana; Dogjani, Agron; Enani, Mushira; Farina, Federica; Ferrara, Francesco; Foghetti, Domitilla; Fontana, Tommaso; Fraga, Gustavo P.; Gachabayov, Mahir; Gerard, Grelpois; Ghnnam, Wagih; Gimenez Maurel, Teresa; Gkiokas, Georgios; Gomes, Carlos A.; Guner, Ali; Gupta, Sanjay; Hecker, Andreas; Hirano, Elcio S.; Hodonou, Adrien; Hutan, Martin; Ilaschuk, Igor; Ioannidis, Orestis; Isik, Arda; Ivakhov, Georgy; Jain, Sumita; Jokubauskas, Mantas; Karamarkovic, Aleksandar; Kaushik, Robin; Kenig, Jakub; Khokha, Vladimir; Khokha, Denis; Kim, Jae Il; Kong, Victor; Korkolis, Dimitris; Kruger, Vitor F.; Kshirsagar, Ashok; Simoes, Romeo Lages; Lanaia, Andrea; Lasithiotakis, Konstantinos; Leao, Pedro; Leon Arellano, Miguel; Listle, Holger; Litvin, Andrey; Lizarazu Perez, Aintzane; Lopez-Tomassetti Fernandez, Eudaldo; Lostoridis, Eftychios; Luppi, Davide; Machain, Gustavo M.; Major, Piotr; Manatakis, Dimitrios; Reitz, Marianne Marchini; Marinis, Athanasios; Marrelli, Daniele; Martinez-Perez, Aleix; Marwah, Sanjay; McFarlane, Michael; Mesic, Mirza; Mesina, Cristian; Michalopoulos, Nickos; Misiakos, Evangelos; Moreira, Felipe Goncalves; Mouaqit, Ouadii; Muhtaroglu, Ali; Naidoo, Noel; Negoi, Ionut; Nikitina, Zane; Nikolopoulos, Ioannis; Nita, Gabriela-Elisa; Occhionorelli, Savino; Olaoye, Iyiade; Ordonez, Carlos A.; Ozkan, Zeynep; Pal, Ajay; Palini, Gian M.; Papageorgiou, Kyriaki; Papagoras, Dimitris; Pata, Francesco; Pedziwiatr, Michal; Pereira, Jorge; Pereira Junior, Gerson A.; Perrone, Gennaro; Pintar, Tadeja; Pisarska, Magdalena; Plehutsa, Oleksandr; Podda, Mauro; Poillucci, Gaetano; Quiodettis, Martha; Rahim, Tuba; Rios-Cruz, Daniel; Rodrigues, Gabriel; Rozov, Dmytry; Sakakushev, Boris; Sall, Ibrahima; Sazhin, Alexander; Semiao, Miguel; Sharda, Taanya; Shelat, Vishal; Sinibaldi, Giovanni; Skicko, Dmitrijs; Skrovina, Matej; Stamatiou, Dimitrios; Stella, Marco; Strzalka, Marcin; Sydorchuk, Ruslan; Gonsaga, Ricardo A. Teixeira; Tochie, Joel Noutakdie; Tomadze, Gia; Ugoletti, Lara; Ulrych, Jan; Umarik, Toomas; Uzunoglu, Mustafa Y.; Vasilescu, Alin; Vaz, Osborne; Vereczkei, Andras; Vlad, Nutu; Waledziak, Maciej; Yahya, Ali I.; Yalkin, Omer; Yilmaz, Tonguc U.; Unal, Ali Ekrem; Yuan, Kuo-Ching; Zachariah, Sanoop K.; Zilinskas, Justas; Zizzo, Maurizio; Pattonieri, Vittoria; Baiocchi, Gian Luca; Catena, Fausto (2019)
    BackgroundTiming and adequacy of peritoneal source control are the most important pillars in the management of patients with acute peritonitis. Therefore, early prognostic evaluation of acute peritonitis is paramount to assess the severity and establish a prompt and appropriate treatment. The objectives of this study were to identify clinical and laboratory predictors for in-hospital mortality in patients with acute peritonitis and to develop a warning score system, based on easily recognizable and assessable variables, globally accepted.MethodsThis worldwide multicentre observational study included 153 surgical departments across 56 countries over a 4-month study period between February 1, 2018, and May 31, 2018.ResultsA total of 3137 patients were included, with 1815 (57.9%) men and 1322 (42.1%) women, with a median age of 47years (interquartile range [IQR] 28-66). The overall in-hospital mortality rate was 8.9%, with a median length of stay of 6days (IQR 4-10). Using multivariable logistic regression, independent variables associated with in-hospital mortality were identified: age > 80years, malignancy, severe cardiovascular disease, severe chronic kidney disease, respiratory rate >= 22 breaths/min, systolic blood pressure <100mmHg, AVPU responsiveness scale (voice and unresponsive), blood oxygen saturation level (SpO(2)) <90% in air, platelet count <50,000 cells/mm3, and lactate > 4mmol/l. These variables were used to create the PIPAS Severity Score, a bedside early warning score for patients with acute peritonitis. The overall mortality was 2.9% for patients who had scores of 0-1, 22.7% for those who had scores of 2-3, 46.8% for those who had scores of 4-5, and 86.7% for those who have scores of 7-8.ConclusionsThe simple PIPAS Severity Score can be used on a global level and can help clinicians to identify patients at high risk for treatment failure and mortality.
  • Sartelli, Massimo; Abu-Zidan, Fikri M; Labricciosa, Francesco M; Kluger, Yoram; Coccolini, Federico; Ansaloni, Luca; Leppäniemi, Ari; Kirkpatrick, Andrew W; Tolonen, Matti; Tranà, Cristian; Regimbeau, Jean-Marc; Hardcastle, Timothy; Koshy, Renol M; Abbas, Ashraf; Aday, Ulaş; Adesunkanmi, A. R K; Ajibade, Adesina; Akhmeteli, Lali; Akın, Emrah; Akkapulu, Nezih; Alotaibi, Alhenouf; Altintoprak, Fatih; Anyfantakis, Dimitrios; Atanasov, Boyko; Augustin, Goran; Azevedo, Constança; Bala, Miklosh; Balalis, Dimitrios; Baraket, Oussama; Baral, Suman; Barkai, Or; Beltran, Marcelo; Bini, Roberto; Bouliaris, Konstantinos; Caballero, Ana B; Calu, Valentin; Catani, Marco; Ceresoli, Marco; Charalampakis, Vasileios; Jusoh, Asri C; Chiarugi, Massimo; Cillara, Nicola; Cuesta, Raquel C; Cobuccio, Luigi; Cocorullo, Gianfranco; Colak, Elif; Conti, Luigi; Cui, Yunfeng; De Simone, Belinda; Delibegovic, Samir; Demetrashvili, Zaza; Demetriades, Demetrios; Dimova, Ana; Dogjani, Agron; Enani, Mushira; Farina, Federica; Ferrara, Francesco; Foghetti, Domitilla; Fontana, Tommaso; Fraga, Gustavo P; Gachabayov, Mahir; Gérard, Grelpois; Ghnnam, Wagih; Maurel, Teresa G; Gkiokas, Georgios; Gomes, Carlos A; Guner, Ali; Gupta, Sanjay; Hecker, Andreas; Hirano, Elcio S; Hodonou, Adrien; Hutan, Martin; Ilaschuk, Igor; Ioannidis, Orestis; Isik, Arda; Ivakhov, Georgy; Jain, Sumita; Jokubauskas, Mantas; Karamarkovic, Aleksandar; Kaushik, Robin; Kenig, Jakub; Khokha, Vladimir; Khokha, Denis; Kim, Jae I; Kong, Victor; Korkolis, Dimitris; Kruger, Vitor F; Kshirsagar, Ashok; Simões, Romeo L; Lanaia, Andrea; Lasithiotakis, Konstantinos; Leão, Pedro; Arellano, Miguel L; Listle, Holger; Litvin, Andrey; Lizarazu Pérez, Aintzane; Lopez-Tomassetti Fernandez, Eudaldo; Lostoridis, Eftychios; Luppi, Davide; Machain V, Gustavo M; Major, Piotr; Manatakis, Dimitrios; Reitz, Marianne M; Marinis, Athanasios; Marrelli, Daniele; Martínez-Pérez, Aleix; Marwah, Sanjay; McFarlane, Michael; Mesic, Mirza; Mesina, Cristian; Michalopoulos, Nickos; Misiakos, Evangelos; Moreira, Felipe G; Mouaqit, Ouadii; Muhtaroglu, Ali; Naidoo, Noel; Negoi, Ionut; Nikitina, Zane; Nikolopoulos, Ioannis; Nita, Gabriela-Elisa; Occhionorelli, Savino; Olaoye, Iyiade; Ordoñez, Carlos A; Ozkan, Zeynep; Pal, Ajay; Palini, Gian M; Papageorgiou, Kyriaki; Papagoras, Dimitris; Pata, Francesco; Pędziwiatr, Michał; Pereira, Jorge; Pereira Junior, Gerson A; Perrone, Gennaro; Pintar, Tadeja; Pisarska, Magdalena; Plehutsa, Oleksandr; Podda, Mauro; Poillucci, Gaetano; Quiodettis, Martha; Rahim, Tuba; Rios-Cruz, Daniel; Rodrigues, Gabriel; Rozov, Dmytry; Sakakushev, Boris; Sall, Ibrahima; Sazhin, Alexander; Semião, Miguel; Sharda, Taanya; Shelat, Vishal; Sinibaldi, Giovanni; Skicko, Dmitrijs; Skrovina, Matej; Stamatiou, Dimitrios; Stella, Marco; Strzałka, Marcin; Sydorchuk, Ruslan; Teixeira Gonsaga, Ricardo A; Tochie, Joel N; Tomadze, Gia; Ugoletti, Lara; Ulrych, Jan; Ümarik, Toomas; Uzunoglu, Mustafa Y; Vasilescu, Alin; Vaz, Osborne; Vereczkei, Andras; Vlad, Nutu; Walędziak, Maciej; Yahya, Ali I; Yalkin, Omer; Yilmaz, Tonguç U; Ünal, Ali E; Yuan, Kuo-Ching; Zachariah, Sanoop K; Žilinskas, Justas; Zizzo, Maurizio; Pattonieri, Vittoria; Baiocchi, Gian L; Catena, Fausto (BioMed Central, 2019)
    Abstract Background Timing and adequacy of peritoneal source control are the most important pillars in the management of patients with acute peritonitis. Therefore, early prognostic evaluation of acute peritonitis is paramount to assess the severity and establish a prompt and appropriate treatment. The objectives of this study were to identify clinical and laboratory predictors for in-hospital mortality in patients with acute peritonitis and to develop a warning score system, based on easily recognizable and assessable variables, globally accepted. Methods This worldwide multicentre observational study included 153 surgical departments across 56 countries over a 4-month study period between February 1, 2018, and May 31, 2018. Results A total of 3137 patients were included, with 1815 (57.9%) men and 1322 (42.1%) women, with a median age of 47 years (interquartile range [IQR] 28–66). The overall in-hospital mortality rate was 8.9%, with a median length of stay of 6 days (IQR 4–10). Using multivariable logistic regression, independent variables associated with in-hospital mortality were identified: age > 80 years, malignancy, severe cardiovascular disease, severe chronic kidney disease, respiratory rate ≥ 22 breaths/min, systolic blood pressure < 100 mmHg, AVPU responsiveness scale (voice and unresponsive), blood oxygen saturation level (SpO2) < 90% in air, platelet count < 50,000 cells/mm3, and lactate > 4 mmol/l. These variables were used to create the PIPAS Severity Score, a bedside early warning score for patients with acute peritonitis. The overall mortality was 2.9% for patients who had scores of 0–1, 22.7% for those who had scores of 2–3, 46.8% for those who had scores of 4–5, and 86.7% for those who have scores of 7–8. Conclusions The simple PIPAS Severity Score can be used on a global level and can help clinicians to identify patients at high risk for treatment failure and mortality.
  • Pirneskoski, Jussi; Tamminen, Joonas; Kallonen, Antti; Nurmi, Jouni; Kuisma, Markku; Olkkola, Klaus T.; Hoppu, Sanna (2020)
    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.