M Alchikh1, T Conrad2, C Hoppe3, X Ma4, E Broberg5, P Penttinen5, J Reiche6, B Biere6, B Schweiger6, B Rath7. 1. Department of Paediatrics, Charité University Berlin, Germany; Vienna Vaccine Safety Initiative, Berlin, Germany. 2. Department of Mathematics and Computer Sciences, Freie Universität Berlin, Germany. 3. Vienna Vaccine Safety Initiative, Berlin, Germany. 4. Department of Paediatrics, Charité University Berlin, Germany; Vienna Vaccine Safety Initiative, Berlin, Germany; National Reference Centre for Influenza, Robert Koch Institute, Berlin, Germany. 5. European Centre for Disease Prevention and Control, Stockholm, Sweden. 6. National Reference Centre for Influenza, Robert Koch Institute, Berlin, Germany. 7. Department of Paediatrics, Charité University Berlin, Germany; Vienna Vaccine Safety Initiative, Berlin, Germany; University of Nottingham School of Medicine, Nottingham, UK. Electronic address: Barbara.Rath@nottingham.ac.uk.
Abstract
OBJECTIVES: Hospital-based surveillance of influenza and acute respiratory infections relies on International Classification of Diseases (ICD) codes and hospital laboratory reports (Standard-of-Care). It is unclear how many cases are missed with either method, i.e. remain undiagnosed/coded as influenza and other respiratory virus infections. Various influenza-like illness (ILI) definitions co-exist with little guidance on how to use them. We compared the diagnostic accuracy of standard surveillance methods with a prospective quality management (QM) programme at a Berlin children's hospital with the Robert Koch Institute. METHODS: Independent from routine care, all patients fulfilling pre-defined ILI-criteria (QM-ILI) participated in the QM programme. A separate QM team conducted standardized clinical assessments and collected nasopharyngeal specimens for blinded real-time quantitative PCR for influenza A/B viruses, respiratory syncytial virus, adenovirus, rhinovirus and human metapneumovirus. RESULTS: Among 6073 individuals with ILI qualifying for the QM programme, only 8.7% (528/6073) would have undergone virus diagnostics during Standard-of-Care. Surveillance based on ICD codes would have missed 61% (359/587) of influenza diagnoses. Of baseline ICD codes, 53.2% (2811/5282) were non-specific, most commonly J06 ('acute upper respiratory infection'). Comparison of stakeholder case definitions revealed that QM-ILI and the WHO ILI case definition showed the highest overall sensitivities (84%-97% and 45%-68%, respectively) and the CDC ILI definition had the highest sensitivity for influenza infections (36%, 95% CI 31.4-40.8 for influenza A and 48%, 95% CI 40.5-54.7 for influenza B). CONCLUSIONS: Disease-burden estimates and surveillance should account for the underreporting of cases in routine care. Future studies should explore the effect of ILI screening and surveillance in various age groups and settings. Diagnostic algorithms should be based on the WHO ILI case definition combined with targeted testing.
OBJECTIVES: Hospital-based surveillance of influenza and acute respiratory infections relies on International Classification of Diseases (ICD) codes and hospital laboratory reports (Standard-of-Care). It is unclear how many cases are missed with either method, i.e. remain undiagnosed/coded as influenza and other respiratory virus infections. Various influenza-like illness (ILI) definitions co-exist with little guidance on how to use them. We compared the diagnostic accuracy of standard surveillance methods with a prospective quality management (QM) programme at a Berlin children's hospital with the Robert Koch Institute. METHODS: Independent from routine care, all patients fulfilling pre-defined ILI-criteria (QM-ILI) participated in the QM programme. A separate QM team conducted standardized clinical assessments and collected nasopharyngeal specimens for blinded real-time quantitative PCR for influenza A/B viruses, respiratory syncytial virus, adenovirus, rhinovirus and human metapneumovirus. RESULTS: Among 6073 individuals with ILI qualifying for the QM programme, only 8.7% (528/6073) would have undergone virus diagnostics during Standard-of-Care. Surveillance based on ICD codes would have missed 61% (359/587) of influenza diagnoses. Of baseline ICD codes, 53.2% (2811/5282) were non-specific, most commonly J06 ('acute upper respiratory infection'). Comparison of stakeholder case definitions revealed that QM-ILI and the WHO ILI case definition showed the highest overall sensitivities (84%-97% and 45%-68%, respectively) and the CDC ILI definition had the highest sensitivity for influenza infections (36%, 95% CI 31.4-40.8 for influenza A and 48%, 95% CI 40.5-54.7 for influenza B). CONCLUSIONS: Disease-burden estimates and surveillance should account for the underreporting of cases in routine care. Future studies should explore the effect of ILI screening and surveillance in various age groups and settings. Diagnostic algorithms should be based on the WHO ILI case definition combined with targeted testing.
Authors: Patrick E Obermeier; Albert Heim; Barbara Biere; Elias Hage; Maren Alchikh; Tim Conrad; Brunhilde Schweiger; Barbara A Rath Journal: iScience Date: 2022-04-21
Authors: Ioannis N Mammas; Simon B Drysdale; Barbara Rath; Maria Theodoridou; Georgia Papaioannou; Alexia Papatheodoropoulou; Eirini Koutsounaki; Chryssie Koutsaftiki; Eleftheria Kozanidou; Vassilis Achtsidis; Paraskevi Korovessi; George P Chrousos; Demetrios A Spandidos Journal: Int J Mol Med Date: 2020-06-15 Impact factor: 4.101