| review article | Q7318358 |
| scholarly article | Q13442814 |
| systematic review | Q1504425 |
| P8978 | DBLP publication ID | journals/midm/PerelEWR06 |
| P6179 | Dimensions Publication ID | 1019156164 |
| P356 | DOI | 10.1186/1472-6947-6-38 |
| P932 | PMC publication ID | 1657003 |
| P698 | PubMed publication ID | 17105661 |
| P5875 | ResearchGate publication ID | 6691400 |
| P50 | author | Phil Edwards | Q85666275 |
| Pablo Perel | Q87095883 | ||
| P2093 | author name string | Ian Roberts | |
| Reinhard Wentz | |||
| P2860 | cites work | Prediction of non-survival after trauma: Innsbruck Coma Scale | Q51704337 |
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| P275 | copyright license | Creative Commons Attribution 2.0 Generic | Q19125117 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P921 | main subject | systematic review | Q1504425 |
| Glasgow Outcome Scale | Q1529519 | ||
| brain injury | Q3280669 | ||
| statistical model | Q3284399 | ||
| P5008 | on focus list of Wikimedia project | ScienceSource | Q55439927 |
| P304 | page(s) | 38 | |
| P577 | publication date | 2006-11-14 | |
| P1433 | published in | BMC Medical Informatics and Decision Making | Q15757608 |
| P1476 | title | Systematic review of prognostic models in traumatic brain injury | |
| P478 | volume | 6 |
| Q33992305 | A clinical decision rule to predict adult patients with traumatic intracranial haemorrhage who do not require intensive care unit admission |
| Q48820053 | A comparison of the Full Outline of UnResponsiveness (FOUR) score and Glasgow Coma Score (GCS) in predictive modelling in traumatic brain injury. |
| Q33844484 | A simple method to adjust clinical prediction models to local circumstances |
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| Q38836447 | Developing a Cognition Endpoint for Traumatic Brain Injury Clinical Trials |
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| Q37594475 | Head injury--a neglected public health problem: a four-month prospective study at Jimma University Specialized Hospital, Ethiopia |
| Q82037808 | Hospital mortality of patients with severe traumatic brain injury is associated with serum PTX3 levels |
| Q81446137 | Hypoxia and hypotension, the "lethal duo" in traumatic brain injury: implications for prehospital care |
| Q37686776 | IMPACT recommendations for improving the design and analysis of clinical trials in moderate to severe traumatic brain injury |
| Q47659690 | Impact of grouping complications on mortality in traumatic brain injury: A nationwide population-based study. |
| Q31004653 | Individual participant data (IPD) meta-analyses of diagnostic and prognostic modeling studies: guidance on their use. |
| Q48286942 | Limited predictive power of hospitalization variables for long-term cognitive prognosis in adult patients with severe traumatic brain injury |
| Q64080372 | Longitudinal Changes in Disability Rating Scale Scores: A Secondary Analysis Among Patients With Severe TBI Enrolled in the Epo Clinical Trial |
| Q51740389 | Meta-analysis and aggregation of multiple published prediction models. |
| Q92969828 | Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature |
| Q35801974 | Modeling community integration in workers with delayed recovery from mild traumatic brain injury |
| Q34797375 | Moderate and severe traumatic brain injury in adults. |
| Q37383633 | Molecular mechanisms of traumatic brain injury: the missing link in management |
| Q36353011 | Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted. |
| Q35183733 | Neurological outcomes of neurosurgical operations for multiple trauma elderly patients in Hong Kong |
| Q24243612 | Non-pharmacological interventions for perceptual disorders following stroke and other adult, acquired, non-progressive brain injury |
| Q24235073 | Non-pharmacological interventions for perceptual disorders following stroke and other adult-acquired, non-progressive brain injury |
| Q26775003 | Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: a systematic review with statistical and cost-effectiveness modelling |
| Q37579302 | Outcome Prediction after Traumatic Brain Injury: Comparison of the Performance of Routinely Used Severity Scores and Multivariable Prognostic Models |
| Q41363400 | Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory |
| Q46216439 | Outcome prediction in moderate and severe traumatic brain injury: a focus on computed tomography variables |
| Q33368354 | Patient outcome after traumatic brain injury in high-, middle- and low-income countries: analysis of data on 8927 patients in 46 countries |
| Q34709768 | Performance of IMPACT, CRASH and Nijmegen models in predicting six month outcome of patients with severe or moderate TBI: an external validation study |
| Q47433039 | Predicted Unfavorable Neurologic Outcome Is Overestimated by the Marshall Computed Tomography Score, Corticosteroid Randomization After Significant Head Injury (CRASH), and International Mission for Prognosis and Analysis of Clinical Trials in Traum |
| Q35908959 | Predicting 14-day mortality after severe traumatic brain injury: application of the IMPACT models in the brain trauma foundation TBI-trac® New York State database. |
| Q34479802 | Predicting intracranial hemorrhage after traumatic brain injury in low and middle-income countries: a prognostic model based on a large, multi-center, international cohort |
| Q37236902 | Predicting mortality in patients treated differently: updating and external validation of a prediction model for nursing home residents with dementia and lower respiratory infections |
| Q33358264 | Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. |
| Q36473793 | Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients |
| Q40039193 | Predicting outcomes of decompressive craniectomy: use of Rotterdam Computed Tomography Classification and Marshall Classification |
| Q51705772 | Predicting the risks of pregnancy in congenital heart disease: the importance of external validation. |
| Q89620602 | Prediction of Early TBI Mortality Using a Machine Learning Approach in a LMIC Population |
| Q35910757 | Prediction of outcome after moderate and severe traumatic brain injury: external validation of the International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognost |
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