scholarly journals Head injury outcome prediction in the emergency department: a role for protein S-100B?

2002 ◽  
Vol 73 (5) ◽  
pp. 542-546 ◽  
Author(s):  
W J Townend
Keyword(s):  
Emergency Department ◽  
Head Injury ◽  
Outcome Prediction ◽  
Protein S

Head injury outcome prediction: A role for protein S-100B?

Injury ◽  
2006 ◽  
Vol 37 (12) ◽  
pp. 1098-1108 ◽  
Author(s):  
Will Townend ◽  
Tor Ingebrigtsen
Keyword(s):  
Head Injury ◽  
Outcome Prediction ◽  
Protein S

scholarly journals Emergency Department Visits From 2014 to 2018 for Head Injuries in Youth Non-Tackle Football Compared With Other Sports

2021 ◽  
Vol 9 (1) ◽  
pp. 232596712097540
Author(s):  
Jessica M. Zendler ◽  
Ron Jadischke ◽  
Jared Frantz ◽  
Steve Hall ◽  
Grant C. Goulet
Keyword(s):  
United States ◽  
Emergency Department ◽  
Head Injury ◽  
Head Injuries ◽  
The United States ◽  
Emergency Department Visits ◽  
Head Region ◽  
Cerebral Contusion ◽  
Common Diagnosis ◽  
Tackle Football

Background: Non-tackle football (ie, flag, touch, 7v7) is purported to be a lower-risk alternative to tackle football, particularly in terms of head injuries. However, data on head injuries in non-tackle football are sparse, particularly among youth participants. Purpose: To describe the epidemiology of  emergency department visits for head injuries due to non-tackle football among youth players in the United States and compare the data with basketball, soccer, and tackle football. Study Design: Descriptive epidemiology study. Methods: Injury data from 2014 to 2018 were obtained from the National Electronic Injury Surveillance System database. Injury reports coded for patients aged 6 to 18 years and associated with basketball, football, or soccer were extracted. Data were filtered to include only injuries to the head region, specifically, the head, ear, eyeball, mouth, or face. Football injuries were manually assigned to “non-tackle” or “tackle” based on the injury narratives. Sports & Fitness Industry Association data were used to estimate annual sport participation and calculate annual injury rates per 100,000 participant-years. Results: A total of 26,770 incident reports from 2014 to 2018 were analyzed. For head region injuries in non-tackle football, the head was the most commonly injured body part, followed by the face; the most common diagnosis was a laceration, followed by concussion and internal injury (defined as an unspecified head injury or internal head injury [eg, subdural hematoma or cerebral contusion]). The most common contacting object was another player. The projected national rate of head region injuries was lowest for non-tackle football across the 4 sports. In particular, the projected rate of injuries to the head for non-tackle football (78.0 per 100,000 participant-years) was less than one-fourth the rates for basketball (323.5 per 100,000 participant-years) and soccer (318.2 per 100,000 participant-years) and less than one-tenth the rate for tackle football (1478.6 per 100,000 participant-years). Conclusion: Among youth in the United States aged 6 to 18 years who were treated in the emergency department for injuries related to playing non-tackle football, the most common diagnosis for injuries to the head region was a laceration, followed by a concussion. Head region injuries associated with non-tackle football occurred at a notably lower rate than basketball, soccer, or tackle football.

Use of an accident and emergency department observation ward in the management of head injury

1993 ◽  
Vol 80 (8) ◽  
pp. 1079-1079 ◽  
Author(s):  
A. F. T. Brown ◽  
G. J. Wilkes ◽  
C. T. Myers ◽  
R. E. Maclaren
Keyword(s):  
Emergency Department ◽  
Head Injury ◽  
Accident And Emergency ◽  
Accident And Emergency Department

scholarly journals Serum Concentration of Myelin Basic Protein as a Prognostic Marker in Mild-to-moderate Head Injury Patients: A Prospective Study in a Tertiary Care Center

2021 ◽  
Author(s):  
Ashvamedh Singh ◽  
Kulwant Singh ◽  
Anurag Sahu ◽  
R. S. Prasad ◽  
N. Pandey ◽  
...  
Keyword(s):  
Head Injury ◽  
Prospective Study ◽  
Myelin Basic Protein ◽  
Prognostic Marker ◽  
Outcome Prediction ◽  
Basic Protein ◽  
Care Center ◽  
Tertiary Care ◽  
Gcs Score ◽  
A Prospective Study

Abstract Objective To estimate the level of myelin basic protein (MBP) and look for its validity in outcome prediction among mild-to-moderate head injury patients. Materials and Methods It was a prospective study done at the Department of Neurosurgery, Institute of Medical Sciences, Banaras Hindu University from Jan 2018 to July 2019. All patients who presented to us within 48 hours of injury with mild-to-moderate head injury with apparently normal CT brain were include in the study. The serum sample were collected on the day of admission and 48 hours later, and patients were treated with standard protocols and observed 6 months postdischarge. Results Of the 32 patients enrolled, we observed mean MBP level was higher for severity of brain damage, but not associated with age, mode of injury, and radiological diagnosis. Mean MBP levels were not statistically associated with Glasgow coma scale (GCS) score at admission but was correlated to outcome with p < 0.05, with sensitivity of 50% and specificity 72%, that is, patients with good outcome have lower mean MBP levels. Conclusion MBP as per our analysis can be used as a prognostic marker in patients with head injury. It is not the absolute value rather a trend showing rise in serum MBP levels, which carries a significant value in outcome prediction.

scholarly journals Tablet-Based Patient-Centered Decision Support for Minor Head Injury in the Emergency Department: Pilot Study

2017 ◽  
Vol 5 (9) ◽  
pp. e144 ◽  
Author(s):  
Navdeep Singh ◽  
Erik Hess ◽  
George Guo ◽  
Adam Sharp ◽  
Brian Huang ◽  
...  
Keyword(s):  
Emergency Department ◽  
Decision Support ◽  
Pilot Study ◽  
Head Injury ◽  
Minor Head Injury ◽  
Patient Centered

scholarly journals COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e051468
Author(s):  
David van Klaveren ◽  
Alexandros Rekkas ◽  
Jelmer Alsma ◽  
Rob J C G Verdonschot ◽  
Dick T J J Koning ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Outcome Prediction ◽  
Characteristic Curve ◽  
Hospital Death ◽  
Hospital Data ◽  
Dutch Hospital ◽  
Icu Admission ◽  
Second Wave

ObjectivesDevelop simple and valid models for predicting mortality and need for intensive care unit (ICU) admission in patients who present at the emergency department (ED) with suspected COVID-19.DesignRetrospective.SettingSecondary care in four large Dutch hospitals.ParticipantsPatients who presented at the ED and were admitted to hospital with suspected COVID-19. We used 5831 first-wave patients who presented between March and August 2020 for model development and 3252 second-wave patients who presented between September and December 2020 for model validation.Outcome measuresWe developed separate logistic regression models for in-hospital death and for need for ICU admission, both within 28 days after hospital admission. Based on prior literature, we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. We assessed model performance by the area under the receiver operating characteristic curve (AUC) and by calibration plots.ResultsOf 5831 first-wave patients, 629 (10.8%) died within 28 days after admission. ICU admission was fully recorded for 2633 first-wave patients in 2 hospitals, with 214 (8.1%) ICU admissions within 28 days. A simple model—COVID outcome prediction in the emergency department (COPE)—with age, respiratory rate, C reactive protein, lactate dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well calibrated and showed good discrimination for mortality in second-wave patients (AUC in four hospitals: 0.82 (95% CI 0.78 to 0.86); 0.82 (95% CI 0.74 to 0.90); 0.79 (95% CI 0.70 to 0.88); 0.83 (95% CI 0.79 to 0.86)). COPE was also able to identify patients at high risk of needing ICU admission in second-wave patients (AUC in two hospitals: 0.84 (95% CI 0.78 to 0.90); 0.81 (95% CI 0.66 to 0.95)).ConclusionsCOPE is a simple tool that is well able to predict mortality and need for ICU admission in patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

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