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Record W6995638600

Patients’ expectations of spine surgery for degenerative conditions: results from the Canadian Spine Outcomes and Research Network (CSORN)

2020· article· en· W6995638600 on OpenAlexaffabout

Bibliographic record

VenueScholarship@Western (Western University) · 2020
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsSaint John Regional HospitalLondon Health Sciences CentreUniversity of TorontoWestern UniversityUniversity of CalgaryUniversité LavalUniversity of AlbertaUniversity Health NetworkOttawa HospitalUniversity of ManitobaDalhousie UniversityUniversity of British Columbia
Fundersnot available
KeywordsObservational studyBayesian multivariate linear regressionMultivariate analysisSpinal surgeryOutcomes researchIntervention (counseling)Outcome (game theory)Multivariate statistics
DOInot available

Abstract

fetched live from OpenAlex

© 2019 Elsevier Inc. BACKGROUND: Understanding patient expectations is a critical component of patient-centered care; however, little is known about which expectation(s) are most important to patients as they relate to their sense of postoperative success. PURPOSE: To investigate patient's preoperative expectations of change in symptoms, function, and well-being resulting from surgical intervention and to examine the associations between sociodemographic, lifestyle, health status, and clinical characteristics with patient outcome expectations STUDY DESIGN: Observational cross-sectional study. SAMPLE: Preoperative data from the Canadian Spine Outcomes and Research Network national registry of patients of patients (n=4,333) undergoing surgery for degenerative spinal conditions between 2012 and 2017. OUTCOME MEASURES: Patients reported their expectations as a result of the surgery (0 [no change], 1 [somewhat better], 2 [better] or 3 [much better]) for seven items: leg/arm pain, back/neck pain, independence in everyday activities, sporting activities/recreation, general physical capacity, frequency and quality of social contacts, and mental well-being. Patients also reported the single most important change expected. METHODS: Data on demographic, lifestyles, health status, clinical factors, and reasons for having surgery were also collected. Factor analysis was used to examine the multidimensionality of expectations. Multivariate linear regression was used to examine factors associated with expectations. RESULTS: Over 80% of patients reported expectation for improvements (at least somewhat better) in all items with the exception of social contacts (75.8%). Expectations are multidimensional; a two factor structure emerged indicating two expectation dimensions (pain relief and overall functional well-being). Two expectation scores were calculated corresponding to the two dimensions (0–100), with higher scores reflecting higher expectations. The mean±standard deviation pain relief expectation score was 78.5±24.7 and the mean overall functional well-being expectation score was 69.7±24.4. In multivariate analysis, the variables associated with these dimensions either differed or differed in degree of influence. For example, higher pain and disability scores, thoracolumbar location and diagnosis of spondylolisthesis were associated with higher expectations in both dimensions, while longer disease duration was only associated with lower overall functional well-being expectations. The top three most important expected change items were pain (improvement of leg or arm pain (29.1%)/improvement in back/neck pain (26.0%)), improvement in general capacity/function (21.0%), and improvement of independence in everyday activities (15.9%). Rankings of the most important expected change were similar across sociodemographic, lifestyle, health status, and clinical variables examined. CONCLUSIONS: Our findings highlight the need to identify and address specific individual expectations as part of the shared decision-making and presurgery education process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.240
GPT teacher head0.386
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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