Imperial College London

Dr Jonathan Underwood

Faculty of MedicineDepartment of Infectious Disease

Honorary Clinical Research Fellow



+44 (0)20 3312 1466jonathan.underwood Website CV




Winston Churchill WingSt Mary's Campus






BibTex format

author = {Underwood, J and De, Francesco D and Leech, R and Sabin, CA and Winston, A},
doi = {10.1371/journal.pone.0194760},
journal = {PLoS ONE},
title = {Medicalising normality? Using a simulated dataset to assess the performance of different diagnostic criteria of HIV-associated cognitive impairment},
url = {},
volume = {13},
year = {2018}

RIS format (EndNote, RefMan)

AB - ObjectiveThe reported prevalence of cognitive impairment remains similar to that reported in the pre-antiretroviral therapy era. This may be partially artefactual due to the methods used to diagnose impairment. In this study, we evaluated the diagnostic performance of the HIV-associated neurocognitive disorder (Frascati criteria) and global deficit score (GDS) methods in comparison to a new, multivariate method of diagnosis.MethodsUsing a simulated ‘normative’ dataset informed by real-world cognitive data from the observational Pharmacokinetic and Clinical Observations in PeoPle Over fiftY (POPPY) cohort study, we evaluated the apparent prevalence of cognitive impairment using the Frascati and GDS definitions, as well as a novel multivariate method based on the Mahalanobis distance. We then quantified the diagnostic properties (including positive and negative predictive values and accuracy) of each method, using bootstrapping with 10,000 replicates, with a separate ‘test’ dataset to which a pre-defined proportion of ‘impaired’ individuals had been added.ResultsThe simulated normative dataset demonstrated that up to ~26% of a normative control population would be diagnosed with cognitive impairment with the Frascati criteria and ~20% with the GDS. In contrast, the multivariate Mahalanobis distance method identified impairment in ~5%. Using the test dataset, diagnostic accuracy [95% confidence intervals] and positive predictive value (PPV) was best for the multivariate method vs. Frascati and GDS (accuracy: 92.8% [90.3–95.2%] vs. 76.1% [72.1–80.0%] and 80.6% [76.6–84.5%] respectively; PPV: 61.2% [48.3–72.2%] vs. 29.4% [22.2–36.8%] and 33.9% [25.6–42.3%] respectively). Increasing the a priori false positive rate for the multivariate Mahalanobis distance method from 5% to 15% resulted in an increase in sensitivity from 77.4% (64.5–89.4%) to 92.2% (83.3–100%) at a cost of specificity from
AU - Underwood,J
AU - De,Francesco D
AU - Leech,R
AU - Sabin,CA
AU - Winston,A
DO - 10.1371/journal.pone.0194760
PY - 2018///
SN - 1932-6203
TI - Medicalising normality? Using a simulated dataset to assess the performance of different diagnostic criteria of HIV-associated cognitive impairment
UR -
UR -
UR -
VL - 13
ER -