Harmonising knee pain patient-reported outcomes: a systematic literature review and meta-analysis of Patient Acceptable Symptom State (PASS) and individual participant data (IPD).

OBJECTIVE: In order to facilitate data pooling between studies, we explored harmonisation of patient-reported outcome measures (PROMs) in people with knee pain due to osteoarthritis or knee trauma, using the Patient Acceptable Symptom State scores (PASS) as a criterion. METHODS: We undertook a systematic literature review (SLR) of PASS scores, and performed individual participant data (IPD) analysis of score distributions from concurrently completed PROM pairs. Numerical rating scales (NRS), visual analogue scales, KOOS and WOMAC pain questionnaires were standardised to 0 to 100 (worst) scales. Meta-regression explored associations of PASS. Bland Altman plots compared PROM scores within individuals using IPD from WebEx, KICK, MenTOR and NEKO studies. RESULTS: SLR identified 18 studies reporting PASS in people with knee pain. Pooled standardised PASS was 27 (95% CI: 21 to 35; n = 6,339). PASS was statistically similar for each standardised PROM. Lower PASS was associated with lower baseline pain (ß = 0.49, P = 0.01) and longer time from treatment initiation (Q = 6.35, P = 0.04). PASS scores were lowest in ligament rupture (12, 95% CI: 11 to 13), but similar between knee osteoarthritis (31, 95% CI: 26 to 36) and meniscal tear (27, 95% CI: 20 to 35). In IPD, standardised PROMs each revealed similar group mean scores, but scores within individuals diverged between PROMs (LoA between -7 to -38 and +25 to 52). CONCLUSION: Different standardised PROMs give similar PASS thresholds in group data. PASS thresholds may be affected more by patient and treatment characteristics than between PROMs. However, different PROMs give divergent scores within individuals, possibly reflecting different experiences of pain.

A fuzzy cognitive map hierarchical model for differential diagnosis of dysarthrias and apraxia of speech.

This paper presents a novel soft computing system for differential diagnosis of the dysarthrias and apraxia of speech based on well accepted dysarthrias' classification system used by speech and language pathologists. The dysarthrias and apraxia are complex disorders of speech because they represent a variety of neurological disturbances that can potentially affect every component of speech production. Since an accurate diagnosis is a very challenging task for the clinician, the under development system based on hierarchical Fuzzy Cognitive Maps (FCMs) will be used as a "second opinion" or training system. The hierarchical FCM differential diagnosis system is capable of differentiating between the six types of dysarthria as well as apraxia. The system was tested using published case studies and real patients and examples are presented here.

Online collaboration environments in telemedicine applications of speech therapy.

The use of telemedicine in speech and language pathology provides patients in rural and remote areas with access to quality rehabilitation services that are sufficient, accessible, and user-friendly leading to new possibilities in comprehensive and long-term, cost-effective diagnosis and therapy. This paper discusses the use of online collaboration environments for various telemedicine applications of speech therapy which include online group speech therapy scenarios, multidisciplinary clinical consulting team, and online mentoring and continuing education.