Understanding Non response in Spine Fusion Surgery
Understanding Non response in Spine Fusion Surgery
批准号:
9102903
负责人:
David R Flum
金额:
$14.27万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-01 至 2018-06-30
关键词:
AddressAmericanAnxietyAreaBenchmarkingBlindedCaringCase SeriesCharacteristicsCicatrixClinicalClinical DataCohort StudiesControl LocusData CollectionDecision MakingDiseaseEffectivenessEvaluationFailureFutureGrantHealthHealth StatusHealthcareHeterogeneityHospitalsImageInpatientsInterventionLinkLordosisMagnetic Resonance ImagingMeasuresMedical RecordsMental HealthMinorityNerve compression syndromeOperative Surgical ProceduresOpioidOutcomeOutcome AssessmentOutcome MeasurePainPatient Outcomes AssessmentsPatientsPerceived quality of lifePersonality CharacterPersonality TraitsPharmaceutical PreparationsPopulationPrevalenceProceduresProcessRandomized Controlled TrialsReportingResearchRisk FactorsRoentgen RaysScanningSelection CriteriaSelf PerceptionSleepSocial supportSpine surgeryState HospitalsSurveysSymptomsTranslationsVertebral columnWashingtonWorkX-Ray Computed Tomographybasecase controlcigarette smokingclinical carecomparative effectivenesscostdesigndisabilityeffectiveness researchevidence baseexpectationfollow-uphigh riskimprovedimproved functioningimproved outcomeintervertebral disk degenerationmodifiable risknoveloperationprediction algorithmpredictive modelingprogramsprospectiveresponsesatisfactionstandardize measuresymptomatic improvementtraittreatment effect
中文摘要
英文摘要
DESCRIPTION (provided by applicant): Each year more than 800,000 Americans undergo spine surgery. There is considerable debate about the effectiveness of one of the more commonly performed procedures-spine fusion for pain and functional limitations related to degenerative disc disease (DDD). Randomized controlled trials (RCTs) and case series from centers of excellence highlight the potential benefits, but other RCTs and assessments of patient reported outcomes (PROs) after spine fusion from broader populations, indicate heterogeneity of treatment effect. Failure to improve on PRO measures (i.e., non-response) after spine fusion may occur in as many as 1 in 3 patients, but has not been systematically evaluated. While many clinicians have opinions about which patients are likely to have a good outcome based on personality traits or other characteristics, there are no evidence- based selection criteria. In fact, only a handful of modifiable characteristics (e.g., cigarette smoking)
and non- modifiable factors (e.g., work-related disability) have been identified as predictors of non-response. Similarly, radiographic features at baseline that may be associated with non-response have not been systematically evaluated, but these too have been suspected. Addressing these gaps in evidence should help inform decision making about spine surgery. Identifying and addressing modifiable factors may improve outcomes. To accomplish this, we propose leveraging ongoing medical record-based clinical data collection and survey- based PRO data collection being performed at Washington (WA) State hospitals participating in the Spine Surgical Care and Outcomes Assessment Program (Spine SCOAP). The proposed aims include the addition of surveys related to personality traits, mental health and relationships and adding standardized evaluations of preoperative radiographic images used in the course of clinical care. Specifically, among patients with DDD undergoing fusion we aim to: (1) Determine patient characteristics associated with non-response; and (2) Determine radiographic features at baseline that are associated with non-response. Addressing these evidence gaps should help inform decision makers about the likely impact of spine operations on the outcomes that matter most to patients. The findings of this study will also be used to create predictive models that support patient and clinician decision making. Spine SCOAP is linked to the Comparative Effectiveness Research Translation Network (CERTAIN) which performs implementation activities related to evidence that emerges from the statewide network. Once validated, these predictive models can be widely disseminated and used to support decision makers.
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会议论文
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