Dae Hee Bae1, Hyoung Youn Lee1, Yong Hun Jung2, Kyung Woon Jeung3, Byung Kook Lee2, Chun Song Youn4, Byung Soo Kang5, Tag Heo2, Yong Il Min2. 1. Department of Emergency Medicine, Chonnam National University Hospital, 42 Jebong-ro, Donggu, Gwangju, Republic of Korea. 2. Department of Emergency Medicine, Chonnam National University Hospital, 42 Jebong-ro, Donggu, Gwangju, Republic of Korea; Department of Emergency Medicine, Chonnam National Univeristy Medical School, 160 Baekseo-ro, Donggu, Gwangju, Republic of Korea. 3. Department of Emergency Medicine, Chonnam National University Hospital, 42 Jebong-ro, Donggu, Gwangju, Republic of Korea; Department of Emergency Medicine, Chonnam National Univeristy Medical School, 160 Baekseo-ro, Donggu, Gwangju, Republic of Korea. Electronic address: neoneti@hanmail.net. 4. Department of Emergency Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, Republic of Korea. 5. Department of Medical Science, College of Medicine, Chosun University, 309 Pilmon-daero, Donggu, Gwangju, Republic of Korea.
Abstract
BACKGROUND: Early prognostication after cardiac arrest would be useful. We aimed to develop a scoring model for early prognostication in unselected adult cardiac arrest patients. METHODS: We retrospectively analysed data of adult non-traumatic cardiac arrest patients treated at a tertiary hospital between 2014 and 2018. The primary outcome was poor outcome at hospital discharge (cerebral performance category, 3-5). Using multivariable logistic regression analysis, independent predictors were identified among known outcome predictors, that were available at intensive care unit admission, in patients admitted in the first 3 years (derivation set, N = 671), and a scoring system was developed with the variables that were retained in the final model. The scoring model was validated in patients admitted in the last 2 years (validation set, N = 311). RESULTS: The poor outcome rates at hospital discharge were similar between the derivation (66.0%) and validation sets (64.3%). Age <59 years, witnessed collapse, shockable rhythm, adrenaline dose <2 mg, low-flow duration <18 min, reactive pupillary light reflex, Glasgow Coma Scale motor score ≥2, and levels of creatinine <1.21 mg dl-1, potassium <4.4 mEq l-1, phosphate <5.8 mg dl-1, haemoglobin ≥13.2 g dl-1, and lactate <8 mmol l-1 were retained in the final multivariable model and used to develop the scoring system. Our model demonstrated excellent discrimination in the validation set (area under the curve of 0.942, 95% confidence interval 0.917-0.968). CONCLUSIONS: We developed a scoring model for early prognostication in unselected adult cardiac arrest patients. Further validations in various cohorts are needed.
BACKGROUND: Early prognostication after cardiac arrest would be useful. We aimed to develop a scoring model for early prognostication in unselected adult cardiac arrestpatients. METHODS: We retrospectively analysed data of adult non-traumatic cardiac arrestpatients treated at a tertiary hospital between 2014 and 2018. The primary outcome was poor outcome at hospital discharge (cerebral performance category, 3-5). Using multivariable logistic regression analysis, independent predictors were identified among known outcome predictors, that were available at intensive care unit admission, in patients admitted in the first 3 years (derivation set, N = 671), and a scoring system was developed with the variables that were retained in the final model. The scoring model was validated in patients admitted in the last 2 years (validation set, N = 311). RESULTS: The poor outcome rates at hospital discharge were similar between the derivation (66.0%) and validation sets (64.3%). Age <59 years, witnessed collapse, shockable rhythm, adrenaline dose <2 mg, low-flow duration <18 min, reactive pupillary light reflex, Glasgow Coma Scale motor score ≥2, and levels of creatinine <1.21 mg dl-1, potassium <4.4 mEq l-1, phosphate <5.8 mg dl-1, haemoglobin ≥13.2 g dl-1, and lactate <8 mmol l-1 were retained in the final multivariable model and used to develop the scoring system. Our model demonstrated excellent discrimination in the validation set (area under the curve of 0.942, 95% confidence interval 0.917-0.968). CONCLUSIONS: We developed a scoring model for early prognostication in unselected adult cardiac arrestpatients. Further validations in various cohorts are needed.
Authors: Wan Young Heo; Yong Hun Jung; Hyoung Youn Lee; Kyung Woon Jeung; Byung Kook Lee; Chun Song Youn; Seung Pill Choi; Kyu Nam Park; Yong Il Min Journal: PLoS One Date: 2022-04-01 Impact factor: 3.240
Authors: Christoph Schriefl; Christian Schoergenhofer; Nina Buchtele; Matthias Mueller; Michael Poppe; Christian Clodi; Florian Ettl; Anne Merrelaar; Magdalena Sophie Boegl; Philipp Steininger; Michael Holzer; Harald Herkner; Michael Schwameis Journal: J Pers Med Date: 2022-05-26