Objective: to develop and test an algorithm for conversion of the Northwick Park Dependency Scale (NPDS) to a Barthel Index.
Design And Setting: conversion criteria were developed to derive a Barthel Index from NPDS data. The criteria were then applied in two community-based datasets of NPDS and Barthel scores, gathered from carers/patients via postal questionnaires. A retrospective exploratory analysis (dataset A) was followed by prospective confirmatory analysis (dataset B).
Subjects: patients with neurological disabilities, mainly following acquired brain injury: dataset A (n = 225) and dataset B (n = 96).
Main Measures: comparison of NPDS-derived Barthel scores with parallel directly rated Barthel scores.
Results: the exploratory analysis identified that one Barthel item ('Stairs') could not be derived from the NPDS items alone, and required minor adaptation of one of the five additional questions that are included to translate the NPDS into an assessment of community care needs (Northwick Park Care Needs Assessment, NPCNA). For the prospective confirmatory analysis, the NPCNA 'Stairs' question was adjusted to support full conversion. Very strong intraclass correlations were observed between the total 'direct' and 'derived' Barthel scores (0.97 (dataset A), 0.95 (dataset B), P<0.001); 95% limits of agreement ranged from -2.52 to 2.56 (dataset A) and -3.29-3.91 (dataset B). Item-by-item agreement (linear-weighted Cohen's kappa coefficients) ranged from 0.68 to 0.85 (dataset A) and 0.59-0.83 (dataset B), which represents 'substantial' to 'almost perfect' agreement.
Conclusions: this study demonstrates that a Barthel Index can be reliably derived from NPDS and NPCNA data through a conversion algorithm which has now been built into the supporting software package.
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http://dx.doi.org/10.1177/0269215510371432 | DOI Listing |
Sci Data
January 2025
The Griffin Institute, Northwick Park and St Mark's Hospital, Watford Road, London, HA13UJ, UK.
Minimally invasive surgery is complex and prone to variation not routinely objectively measured. We established an association between skills and patient outcomes. The evolving application of artificial intelligence techniques could assist intraoperative analysis.
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Stellenbosch University, Faculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Desmond Tutu TB Centre, Tygerberg, South Africa.
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