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John D. Ward

Researcher at Virginia Commonwealth University

Publications -  85
Citations -  12058

John D. Ward is an academic researcher from Virginia Commonwealth University. The author has contributed to research in topics: Intracranial pressure & Diabetes mellitus. The author has an hindex of 39, co-authored 79 publications receiving 11563 citations. Previous affiliations of John D. Ward include Royal Hallamshire Hospital & VCU Medical Center.

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Vascular risk factors and diabetic neuropathy

TL;DR: It is indicated that, apart from glycemic control, the incidence of neuropathy is associated with potentially modifiable cardiovascular risk factors, including a raised triglyceride level, body-mass index, smoking, and hypertension.
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Adverse effects of prolonged hyperventilation in patients with severe head injury: a randomized clinical trial

TL;DR: It is concluded that prophylactic hyperventilation is deleterious in head-injured patients with motor scores of 4-5 and that the course of ICP was most stable in the HV + THAM group, although mean ICP could be kept well below 25 mm Hg in all three groups.
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The outcome from severe head injury with early diagnosis and intensive management

TL;DR: It is proposed that vigorous surgical and medical therapy, by preventing or reversing secondary cerebral insults, enables some patients who would have died to make a good recovery without increasing the proportion of severely disabled patients.
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Traumatic acute subdural hematoma: major mortality reduction in comatose patients treated within four hours.

TL;DR: The delay from injury to operation was the factor of greatest therapeutic importance, and patients who underwent surgery within the first four hours had a 30 per cent mortality rate, as compared with 90 percent in those who had surgery after four hours.
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Impact of ICP instability and hypotension on outcome in patients with severe head trauma

TL;DR: The relationship between raised intracranial pressure (ICP), hypotension, and outcome from severe head injury is described and a stepwise ordinal logistic regression was used to determine outcome.