What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Surgery
- Cancer
Tor D. Tosteson mainly focuses on Surgery, Randomized controlled trial, Physical therapy, Cohort and Internal medicine.
Within one scientific family, Tor D. Tosteson focuses on topics pertaining to Oswestry Disability Index under Surgery, and may sometimes address concerns connected to Cohort study.
His Randomized controlled trial research is multidisciplinary, incorporating perspectives in Clinical trial, Adenoma, Family caregivers, Palliative care and Depression.
The concepts of his Physical therapy study are interwoven with issues in Occupational safety and health and Outcomes research.
His work investigates the relationship between Cohort and topics such as Observational study that intersect with problems in Lumbar disc herniation, Nonoperative treatment and Confidence interval.
His Internal medicine research is multidisciplinary, incorporating elements of Oncology and Population study.
His most cited work include:
- Effects of a Palliative Care Intervention on Clinical Outcomes in Patients With Advanced Cancer: The Project ENABLE II Randomized Controlled Trial (1087 citations)
- Surgical vs Nonoperative Treatment for Lumbar Disk Herniation: The Spine Patient Outcomes Research Trial (SPORT): A Randomized Trial (780 citations)
- Surgical versus Nonsurgical Therapy for Lumbar Spinal Stenosis (766 citations)
What are the main themes of his work throughout his whole career to date?
Surgery, Physical therapy, Randomized controlled trial, Internal medicine and Outcomes research are his primary areas of study.
The study incorporates disciplines such as Subgroup analysis and Oswestry Disability Index in addition to Surgery.
His studies deal with areas such as Observational study, Physical medicine and rehabilitation, Intervention, Quality of life and Low back pain as well as Physical therapy.
His Randomized controlled trial study combines topics in areas such as Clinical trial, Cohort study, Mood, Sciatica and Palliative care.
Tor D. Tosteson combines subjects such as Gastroenterology and Oncology with his study of Internal medicine.
Tor D. Tosteson studied Outcomes research and Intervertebral disk that intersect with Diskectomy.
He most often published in these fields:
- Surgery (28.63%)
- Physical therapy (25.73%)
- Randomized controlled trial (21.99%)
What were the highlights of his more recent work (between 2014-2021)?
- Randomized controlled trial (21.99%)
- Physical therapy (25.73%)
- Internal medicine (20.75%)
In recent papers he was focusing on the following fields of study:
Tor D. Tosteson mostly deals with Randomized controlled trial, Physical therapy, Internal medicine, Family medicine and Surgery.
The Randomized controlled trial study combines topics in areas such as Multivariate adaptive regression splines, Mood, Outcomes research, Proportional hazards model and Palliative care.
Tor D. Tosteson has included themes like Massage, Reiki, Cohort study and Hospitalized patients in his Physical therapy study.
Many of his research projects under Internal medicine are closely connected to Fragility fracture and Fragility with Fragility fracture and Fragility, tying the diverse disciplines of science together.
As a member of one scientific family, Tor D. Tosteson mostly works in the field of Surgery, focusing on Cohort and, on occasion, Humerus fracture.
His Spinal stenosis research incorporates elements of Prospective cohort study, Spondylolisthesis and Lumbar spinal stenosis.
Between 2014 and 2021, his most popular works were:
- Early Versus Delayed Initiation of Concurrent Palliative Oncology Care: Patient Outcomes in the ENABLE III Randomized Controlled Trial (553 citations)
- Benefits of Early Versus Delayed Palliative Care to Informal Family Caregivers of Patients With Advanced Cancer: Outcomes From the ENABLE III Randomized Controlled Trial (222 citations)
- Long-term outcomes of lumbar spinal stenosis: eight-year results of the Spine Patient Outcomes Research Trial (SPORT). (113 citations)
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
