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Cerebrovascular disease
Research paper
Comparison of the diagnostic utility of physician-diagnosed with algorithm-defined stroke-associated pneumonia
  1. Lalit Kalra1,
  2. John Hodsoll2,
  3. Saddif Irshad1,
  4. David Smithard3,
  5. Dulka Manawadu4
  6. on behalf of the STROKE-INF Investigators
    1. 1Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
    2. 2Biostatistics Department, NIHR Biomedical Research Centre for Mental Health and Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
    3. 3University of Kent, Canterbury, UK
    4. 4King's College Hospital NHS Foundation Trust, London, UK
    1. Correspondence to Professor Lalit Kalra, Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neurosciences, King's College London, P.O. Box 41, London SE5 8AF, UK; lalit.kalra{at}kcl.ac.uk

    Abstract

    Objective Diagnosing stroke-associated pneumonia (SAP) is challenging and may result in inappropriate antibiotic use or confound research outcomes. This study evaluates the diagnostic accuracy of algorithm-defined versus physician-diagnosed SAP in 1088 patients who had dysphagic acute stroke from 37 UK stroke units between 21 April 2008 and 17 May 2014.

    Methods SAP in the first 14 days was diagnosed by a criteria-based algorithm applied to blinded patient data and independently by treating physicians. Patients in whom diagnoses differed were reassigned following blinded adjudication of individual patient records. The sensitivity, specificity, positive predictive value (PPV) and diagnostic OR of algorithmic and physician diagnosis of SAP were assessed using adjudicated SAP as the reference standard. Agreement was assessed using the κ statistic.

    Results Physicians diagnosed SAP in 176/1088 (16%) and the algorithm in 123/1088 (11.3%) patients. Diagnosis agreed in 885/1088 (81.3%) patients (κ 0.22 (95% CI 0.14 to 0.29)). On a blinded review, 129/1088 (11.8%) patients were adjudicated as patients with SAP. The algorithm and the physicians had high specificity (97% (95% CI 96% to 98%) and 90% (95% CI 88% to 92%), respectively) but only moderate sensitivity (72% (95% CI 64% to 80%) and 65% (95% CI 56% to 73%), respectively) in diagnosing SAP. The algorithm showed better PPV (76% (95% CI 67% to 83%) vs 48% (95% CI 40% to 55%)), diagnostic OR (80 (95% CI 42 to 136) vs 18 (95% CI 12 to 27)) and agreement (κ 0.70 (95% CI 0.63 to 0.78) vs 0.48 (95% CI 0.41 to 0.54)) than physician diagnosis with adjudicated SAP.

    Conclusions Algorithm-based approaches can standardise SAP diagnosis for clinical practice and research.

    Trial registration number ISRCTN37118456; Post-results.

    https://doi.org/10.1136/jnnp-2016-313508

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      Footnotes

      • Collaborators STROKE-INF Centres and Site Investigators: Barnsley Hospital, Barnsley Hospital NHS Foundation Trust (M Al-Bazzaz), Bishop Auckland Hospital, County Durham and Darlington NHS Foundation Trust (A Mehrzad), Calderdale Royal Hospital, Calderdale and Huddersfield NHS Trust (A Nair), Charing Cross Hospital, Imperial College Healthcare NHS Trust (A Kar), Colchester University Hospital NHS Foundation Trust (R Sivakumar), Dewsbury and District Hospital, The Mid Yorkshire Hospitals NHS Trust (P Datta), Doncaster Royal Infirmary, Doncaster and Bassetlaw Hospitals NHS Trust (D Chada), Eastbourne District General Hospital, East Sussex Healthcare NHS Trust (C Athulathmudali), Guy's and St Thomas' NHS Foundation Trust (J Birns), Ipswich Hospital, Ipswich Hospital NHS Trust (M Chowdhury), John Radcliffe Hospital, Oxford University Hospitals NHS Trust (J Kennedy), Kent and Canterbury Hospital, East Kent Hospitals University NHS Trust (I Burger), King's College Hospital. King's College Hospital NHS Foundation Trust (D Manawadu), Lewisham Hospital, Lewisham and Greenwich NHS Trust (M Patel), Lister Hospital, East and North Hertfordshire NHS Trust (A Pusalkar), Luton and Dunstable Hospital, Luton and Dunstable NHS Foundation Trust (L Sekaran), Morriston Hospital, ABM University Health Board (M Wani), Newham University Hospital, Barts Health NHS Trust (A Jackson), University Hospital of North Staffordshire, University Hospital of North Staffordshire NHS Trust (I Natarajan), North Tyneside General Hospital, Northumbria Healthcare NHS Foundation Trust (C Price), Pinderfields Hospital, The Mid Yorkshire Hospitals NHS Trust (P Datta), Princess of Wales Hospital, ABM University Health Board (H Bhat), Princes Royal University Hospital, South London NHS Foundation Trust (L Sztriha), Queen Elizabeth The Queen Mother Hospital, East Kent Hospitals University NHS Foundation Trust (G Gunathilagan), Queens Hospital, Barking, Havering and Redbridge University Hospitals NHS Trust (S Andole), The Royal Derby Hospital, Derby Hospitals NHS Trust (T England), Royal Gwent Hospital, Gwent Healthcare NHS Trust (Y Bhat), Royal London Hospital, Barts Health NHS Trust (P Gompertz), Royal Surrey County Hospital, Royal Surrey County NHS Foundation Trust (K Pasco), Royal Sussex County Hospital, Brighton and Sussex University Hospital (R RajKumar), Southend University Hospital, Southend University Hospital NHS Foundation Trust (P Guyler), St George's Hospital, St Georges Healthcare NHS Trust (B Moynihan), University College London Hospital, University College London Hospital NHS Foundation Trust (M Brown), University Hospital of North Durham, County Durham and Darlington NHS Foundation Trust (B Essi), University Hospital Of Wales, Cardiff and Vale University Health Board (H Shetty), Wansbeck General Hospital, Northumbria Healthcare NHS Foundation Trust (C Price), William Harvey Hospital, East Kent Hospitals University NHS Foundation Trust (D Hargroves), Yeovil District Hospital, Yeovil District Hospital NHS Foundation Trust (K Rashed).

      • Contributors LK, DS and DM contributed to generating the hypothesis for post hoc analyses, study design, data collation and interpretation, and drafting of the paper. SI contributed to trial coordination, data acquisition and interpretation, and drafting of the paper. JH contributed to the analysis plan prior to collection of data, data analysis and interpretation, and drafting of the report. The corresponding author (LK) has access to all the data and vouch for the completeness and accuracy of the analysis. LK had the final responsibility for the decision to submit for publication.

      • Funding The research was funded by the National Institute for Health Research (NIHR; Project number PB-PG-0906-11103). JH is supported by the NIHR Maudsley Biomedical Research Centre. The funders had no role in the study design; collection, analysis or interpretation of the data; or in writing of the report.

      • Disclaimer The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, NIHR or the Department of Health.

      • Competing interests None declared.

      • Ethics approval National Research Ethics Committee.

      • Provenance and peer review Not commissioned; externally peer reviewed.