Reporting “specific abilities” after major stroke to better describe prognosis

Prognostication in post-stroke aphasia: speech pathologists' clinical insights on formulating and delivering information about recovery

PURPOSE

For people with post-stroke aphasia, "Will I get better?" is a question often asked, but one that is intellectually and emotionally demanding for speech pathologists to answer. Speech pathologists' formulation and delivery of aphasia prognoses is varied and there is limited evidence for optimising practice. We aimed to understand speech pathologists' clinical experiences, reasoning, and support needs in aphasia prognostication.

MATERIALS AND METHODS

Twenty-five Australian speech pathologists working with people with aphasia participated in individual, semi-structured interviews. Their age, level of experience, work setting, and location were maximally varied. Interview responses were analysed qualitatively using thematic analysis.

RESULTS

Five themes were drawn from the interviews: (1) prognostic challenges are shared but not voiced; (2) truth is there's no quick fix; (3) recovery is more than words; (4) the power of words; and, (5) prognostic competence is implicit.

CONCLUSIONS

Speech pathologists use implicit competencies to formulate and deliver aphasia prognoses. A patient-centred, holistic contextualisation of aphasia recovery may enable realistic, optimistic, and constructive conversations about prognosis. These conversations may have therapeutic potential if prognostic uncertainty, emotional adjustment, and conditional outcomes are carefully addressed. Future research should seek to understand the perceptions and preferences of people with aphasia and their significant others.Implications for RehabilitationAphasia prognostication in clinical practice is complex and nuanced, thus increased clinical and research focus is warranted to ensure key stakeholder needs are met.Conversations about prognosis may be more meaningful to people with aphasia if recovery is conceptualised as encompassing impairment, activity, and participation outcomes.Given the implicit competencies required for prognostication, a structured approach to reflective practice and experience-based training may be beneficial.Conversations about prognosis may have therapeutic value, but further research is needed to explore this potential.

Predicting specific abilities after disabling stroke: Development and validation of prognostic models

Background

Predicting specific abilities (e.g. walk and talk) to provide a functional profile six months after disabling stroke could help patients/families prepare for the consequences of stroke and facilitate involvement in treatment decision-making.

Aim

To develop new statistical models to predict specific abilities six months after stroke and test their performance in an independent cohort of patients with disabling stroke.

Methods

We developed models to predict six specific abilities (to be independent, walk, talk, eat normally, live without major anxiety/depression, and to live at home) using data from seven large multicenter stroke trials with multivariable logistic regression. We included 13,117 participants recruited within three days of hospital admission. We assessed model discrimination and derived optimal cut-off values using four statistical methods. We validated the models in an independent single-center cohort of patients (n = 403) with disabling stroke. We assessed model discrimination and calibration and reported the performance of our models at the statistically derived cut-off values.

Results

All six models had good discrimination in external validation (AUC 0.78–0.84). Four models (predicting to walk, eat normally, live without major anxiety/depression, live at home) calibrated well. Models had sensitivities between 45.0 and 97.9% and specificities between 21.6 and 96.5%.

Conclusions

We have developed statistical models to predict specific abilities and demonstrated that these models perform reasonably well in an independent cohort of disabling stroke patients. To aid decision-making regarding treatments, further evaluation of our models is required.