Podium 20
Tracks
Breakout 3
| Sunday, September 8, 2024 |
| 11:15 AM - 11:45 AM |
| Dobson 3 |
Speaker
Mr Rohil Chauhan
Orthopaedic Physiotherapy Clinician
Auckland Spine Surgery Centre
Diagnostic Criteria and Surgical Thresholds for Degenerative Cervical Myelopathy: Survey of New Zealand Spine Surgeons
Presentation Abstract
Background
The recognition of diagnostic features of degenerative cervical myelopathy (DCM) amongst New Zealand (NZ) primary care clinicians is highly varied. Early recognition is key for DCM, as delayed diagnosis leads to poor outcomes. Thus, understanding NZ spine surgeons' diagnostic criteria would be a useful step toward the development of consensus-based criteria.
Purpose
To explore DCM diagnostic criteria and key signs warranting expeditious surgical management, utilised by NZ spine surgeons.
Methods
A cross-sectional survey was conducted to gather anonymized responses from NZ-based spine surgeons. The questionnaire was piloted, and ethical approval granted by AUTEC (23/351) before dissemination via the NZ spine society.
Results
Thirty-seven respondents, constituting a 56% response rate, participated in the survey. The mean post-fellowship experience was 14.2 years (SD: 8.52), with an average monthly caseload of 1.83 DCM patients (SD: 1.22). Approximately 50% of patients (SD: 35.1) are surgical candidates upon initial consultation, indicating a notable clinical severity.
Key symptoms diagnostic of DCM included gait clumsiness (reported by 84% of respondents), hand dexterity decline (78%), hand clumsiness (65%), and hand numbness/paraesthesia (46%). The most diagnostic signs included clonus (62%), Hoffmann (62%), inability to tandem gait (60%), and hyperreflexia (60%).
Symptoms with the most influence on surgical urgency were hand dexterity decline (reported by 70%), hand clumsiness (49%), history of falls (41%), and autonomic dysfunction (32%). Key signs contributing to surgical urgency included inability to tandem gait (62%), hyperreflexia (51%), clonus (41%), and positive Romberg's (24%).
Conclusion
The survey reveals key clinical features aiding DCM diagnosis and surgical decision-making. Further consensus-based processes will be undertaken to create clinical criteria to improve DCM recognition and referral in primary care.
Implications
Gait clumsiness and hand dexterity decline were identified as key DCM symptoms, although clinical signs for diagnostic and surgical workup received more varied responses, yet to be agreed upon.
The recognition of diagnostic features of degenerative cervical myelopathy (DCM) amongst New Zealand (NZ) primary care clinicians is highly varied. Early recognition is key for DCM, as delayed diagnosis leads to poor outcomes. Thus, understanding NZ spine surgeons' diagnostic criteria would be a useful step toward the development of consensus-based criteria.
Purpose
To explore DCM diagnostic criteria and key signs warranting expeditious surgical management, utilised by NZ spine surgeons.
Methods
A cross-sectional survey was conducted to gather anonymized responses from NZ-based spine surgeons. The questionnaire was piloted, and ethical approval granted by AUTEC (23/351) before dissemination via the NZ spine society.
Results
Thirty-seven respondents, constituting a 56% response rate, participated in the survey. The mean post-fellowship experience was 14.2 years (SD: 8.52), with an average monthly caseload of 1.83 DCM patients (SD: 1.22). Approximately 50% of patients (SD: 35.1) are surgical candidates upon initial consultation, indicating a notable clinical severity.
Key symptoms diagnostic of DCM included gait clumsiness (reported by 84% of respondents), hand dexterity decline (78%), hand clumsiness (65%), and hand numbness/paraesthesia (46%). The most diagnostic signs included clonus (62%), Hoffmann (62%), inability to tandem gait (60%), and hyperreflexia (60%).
Symptoms with the most influence on surgical urgency were hand dexterity decline (reported by 70%), hand clumsiness (49%), history of falls (41%), and autonomic dysfunction (32%). Key signs contributing to surgical urgency included inability to tandem gait (62%), hyperreflexia (51%), clonus (41%), and positive Romberg's (24%).
Conclusion
The survey reveals key clinical features aiding DCM diagnosis and surgical decision-making. Further consensus-based processes will be undertaken to create clinical criteria to improve DCM recognition and referral in primary care.
Implications
Gait clumsiness and hand dexterity decline were identified as key DCM symptoms, although clinical signs for diagnostic and surgical workup received more varied responses, yet to be agreed upon.
Biography
Rohil is an Auckland-based physiotherapist, working in an orthopaedic-triage role at the Auckland Spine Surgery Centre and in musculoskeletal private practice. He has a research interest in Degenerative Cervical Myelopathy (DCM), and is an invited member of 2 international DCM working groups: Perioperative Management and Professional Education for DCM. The latter aims to bridge knowledge gaps in DCM awareness and screening confidence amongst primary healthcare clinicians worldwide. Further, he is actively researching the current 'state of play' of DCM Assessment practices in Australasia and the validity of a novel MRI screening technique as part of his Masters thesis.
Mr Ben Scrivener
Research Physiotherapist
University Of Auckland
Can physiotherapists predict walking recovery after stroke?
Presentation Abstract
Background:
Regaining independent walking after a stroke is significant for patients and their families, as it affects both rehabilitation and discharge planning. Patients and families report wanting information about walking recovery. However, the degree to which physiotherapists can accurately provide predictions on walking recovery is unknown.
Purpose:
The aim was to explore whether physiotherapists can accurately predict, at 1-week post-stroke, whether and when their patient will achieve independent walking after stroke.
Methods:
Adults with lower-limb weakness and unable to walk independently were recruited within 5 days of stroke from two Aotearoa hospitals. Clinical assessments were completed at 1 week. At 1-week post-stroke, the treating physiotherapist was asked to predict whether their patient would walk independently by 4, 6, 9, 12, 16, or 26 weeks post-stroke. Physiotherapists rated their confidence in their predictions on a 6-point Likert scale. Functional Ambulation Category (FAC) assessment was completed at each timepoint to determine time by which independent walking was achieved, defined as FAC ≥ 4. Binary logistic regressions were conducted with physiotherapist accuracy as the dependent variable and confidence, years of stroke-specific experience, stroke severity, patient age, lower limb strength and 1-week FAC as independent variables.
Results:
We included 91 patients (median age 71y) and 37 physiotherapists (median 2y stroke-specific experience, range 0 – 14y). Physiotherapists correctly predicted whether independent walking was achieved by 26 weeks for 80/91 (88%) participants. Predictions of time taken to achieve independent walking were accurate for 39/91 (43%), optimistic for 28/91 (31%) and pessimistic for 24/91 (26%). Prediction accuracy was not related to physiotherapist confidence in their predictions or years of experience (both p > 0.4).
Conclusion:
Physiotherapists can accurately predict whether a patient will walk independently after stroke but not when they will achieve this.
Implications:
Validated walking prediction tools may assist physiotherapists in rehabilitation and discharge planning.
Regaining independent walking after a stroke is significant for patients and their families, as it affects both rehabilitation and discharge planning. Patients and families report wanting information about walking recovery. However, the degree to which physiotherapists can accurately provide predictions on walking recovery is unknown.
Purpose:
The aim was to explore whether physiotherapists can accurately predict, at 1-week post-stroke, whether and when their patient will achieve independent walking after stroke.
Methods:
Adults with lower-limb weakness and unable to walk independently were recruited within 5 days of stroke from two Aotearoa hospitals. Clinical assessments were completed at 1 week. At 1-week post-stroke, the treating physiotherapist was asked to predict whether their patient would walk independently by 4, 6, 9, 12, 16, or 26 weeks post-stroke. Physiotherapists rated their confidence in their predictions on a 6-point Likert scale. Functional Ambulation Category (FAC) assessment was completed at each timepoint to determine time by which independent walking was achieved, defined as FAC ≥ 4. Binary logistic regressions were conducted with physiotherapist accuracy as the dependent variable and confidence, years of stroke-specific experience, stroke severity, patient age, lower limb strength and 1-week FAC as independent variables.
Results:
We included 91 patients (median age 71y) and 37 physiotherapists (median 2y stroke-specific experience, range 0 – 14y). Physiotherapists correctly predicted whether independent walking was achieved by 26 weeks for 80/91 (88%) participants. Predictions of time taken to achieve independent walking were accurate for 39/91 (43%), optimistic for 28/91 (31%) and pessimistic for 24/91 (26%). Prediction accuracy was not related to physiotherapist confidence in their predictions or years of experience (both p > 0.4).
Conclusion:
Physiotherapists can accurately predict whether a patient will walk independently after stroke but not when they will achieve this.
Implications:
Validated walking prediction tools may assist physiotherapists in rehabilitation and discharge planning.
Biography
Ben is a Research Physiotherapist and Professional Teaching Fellow in the Department of Medicine, at the University of Auckland. His clinical and research interests include: stroke patient and family experiences of care, predicting recovery after stroke, and neurophysiological assessment for stroke and functional neurological disorders.
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