Search

BackgroundIndividuals with deafblindness experience a combination of hearing and vision impairments. The World Health Organization has developed a global framework referred to as the International Classification of Functioning, Disability and Health (ICF) to describe health and functioning. From the full ICF classification, a selection of categories, referred to as ICF Core Sets, provide users with a tool to describe functioning and disability in specific health conditions. There has been no ICF Core Set created for deafblindness. Given that core sets are instrumental in improving clinical practice, research, and service delivery, the aim of this study is to develop an ICF Core Set for deafblindness.MethodsAs part of the preparatory phase in the ICF Core Set development, there are four studies that will be conducted. This includes the [1] systematic literature review that examines the researcher's perspective, [2] qualitative study focusing on the individuals with deafblindness experience, [3] experts survey that looks at health professional's perspective, and [4] empirical study that examines the clinical perspective. The studies will be conducted using the principles outlined by the ICF Research Branch for the development of ICF Core Sets. The systematic literature review protocol was submitted for registration on PROSPERO CRD42021247952.DiscussionAn ICF Core Set created for deafblindness will benefit individuals living with deafblindness who are often excluded from social participation, policies, and services. An ICF Core Set for deafblindness will have a significant impact on healthcare professionals, policymakers, researchers, service providers and individuals with deafblindness by facilitating communication among all stakeholder to support the functioning of those with deafblindness.

Manual ELISA assays are the most commonly used methods for quantification of biomarkers; however, they often show inter- and intra-laboratory variability that limits their wide use. Here, we compared the Innotest ELISA method with two fully automated platforms (Lumipulse and Elecsys) to determine whether these new methods can provide effective substitutes for ELISA assays. We included 149 patients with AD (n = 34), MCI (n = 94) and non-AD dementias (n = 21). Aβ42, T-tau, and P-tau were quantified using the ELISA method (Innotest, Fujirebio Europe), CLEIA method on a Lumipulse G600II (Fujirebio Diagnostics), and ECLIA method on a Cobas e 601 (Roche Diagnostics) instrument. We found a high correlation between the three methods, although there were systematic differences between biomarker values measured by each method. Both Lumipulse and Elecsys methods were highly concordant with clinical diagnoses, and the combination of Lumipulse Aβ42 and P-tau had the highest discriminating power (AUC 0.915, 95% CI 0.822–1.000). We also assessed the agreement of AT(N) classification for each method with AD diagnosis. Although differences were not significant, the use of Aβ42/Aβ40 ratio instead of Aβ42 alone in AT(N) classification enhanced the diagnostic accuracy (AUC 0.798, 95% CI 0.649–0.947 vs. AUC 0.778, 95% CI 0.617–0.939). We determined the cut-offs for the Lumipulse and Elecsys assays based on the Aβ42/Aβ40 ratio ± status as a marker of amyloid pathology, and these cut-offs were consistent with those recommended by manufacturers, which had been determined based on visual amyloid PET imaging or diagnostic accuracy. Finally, the biomarker ratios (P-tau/Aβ42 and T-tau/Aβ42) were more consistent with the Aβ42/Aβ40 ratio for both Lumipulse and Elecsys methods, and Elecsys P-tau/Aβ42 had the highest consistency with amyloid pathology (AUC 0.994, 95% CI 0.986–1.000 and OPA 96.4%) at the ≥0.024 cut-off. The Lumipulse and Elecsys cerebrospinal fluid (CSF) AD assays showed high analytical and clinical performances. As both automated platforms were standardized for reference samples, their use is recommended for the measurement of CSF AD biomarkers compared with unstandardized manual methods, such as Innotest ELISA, that have demonstrated a high inter and intra-laboratory variability.