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Background Influenza and respiratory syncytial virus (RSV) contribute significantly to the burden of acute lower respiratory infection (ALRI) inpatient care, but heterogeneous coding practices and availability of inpatient data make it difficult to estimate global hospital utilization for either disease based on coded diagnoses alone. Methods This study estimates rates of influenza and RSV hospitalization by calculating the proportion of ALRI due to influenza and RSV and applying this proportion to inpatient admissions with ALRI coded as primary diagnosis. Proportions of ALRI attributed to influenza and RSV were extracted from a meta-analysis of 360 total sources describing inpatient hospital admissions which were input to a Bayesian mixed effects model over age with random effects over location. Results of this model were applied to inpatient admission datasets for 44 countries to produce rates of hospital utilization for influenza and RSV respectively, and rates were compared to raw coded admissions for each disease. Results For most age groups, these methods estimated a higher national admission rate than the rate of directly coded influenza or RSV admissions in the same inpatient sources. In many inpatient sources, International Classification of Disease (ICD) coding detail was insufficient to estimate RSV burden directly. The influenza inpatient burden estimates in older adults appear to be substantially underestimated using this method on primary diagnoses alone. Application of the mixed effects model reduced heterogeneity between countries in influenza and RSV which was biased by coding practices and between-country variation. Conclusions This new method presents the opportunity of estimating hospital utilization rates for influenza and RSV using a wide range of clinical databases. Estimates generally seem promising for influenza and RSV associated hospitalization, but influenza estimates from primary diagnosis seem highly underestimated among older adults. Considerable heterogeneity remains between countries in ALRI coding (i.e., primary vs non-primary cause), and in the age profile of proportion positive for influenza and RSV across studies. While this analysis is interesting because of its wide data utilization and applicability in locations without laboratory-confirmed admission data, understanding the sources of variability and data quality will be essential in future applications of these methods.
Background Influenza and respiratory syncytial virus (RSV) contribute significantly to the burden of acute lower respiratory infection (ALRI) inpatient care, but heterogeneous coding practices and availability of inpatient data make it difficult to estimate global hospital utilization for either disease based on coded diagnoses alone. Methods This study estimates rates of influenza and RSV hospitalization by calculating the proportion of ALRI due to influenza and RSV and applying this proportion to inpatient admissions with ALRI coded as primary diagnosis. Proportions of ALRI attributed to influenza and RSV were extracted from a meta-analysis of 360 total sources describing inpatient hospital admissions which were input to a Bayesian mixed effects model over age with random effects over location. Results of this model were applied to inpatient admission datasets for 44 countries to produce rates of hospital utilization for influenza and RSV respectively, and rates were compared to raw coded admissions for each disease. Results For most age groups, these methods estimated a higher national admission rate than the rate of directly coded influenza or RSV admissions in the same inpatient sources. In many inpatient sources, International Classification of Disease (ICD) coding detail was insufficient to estimate RSV burden directly. The influenza inpatient burden estimates in older adults appear to be substantially underestimated using this method on primary diagnoses alone. Application of the mixed effects model reduced heterogeneity between countries in influenza and RSV which was biased by coding practices and between-country variation. Conclusions This new method presents the opportunity of estimating hospital utilization rates for influenza and RSV using a wide range of clinical databases. Estimates generally seem promising for influenza and RSV associated hospitalization, but influenza estimates from primary diagnosis seem highly underestimated among older adults. Considerable heterogeneity remains between countries in ALRI coding (i.e., primary vs non-primary cause), and in the age profile of proportion positive for influenza and RSV across studies. While this analysis is interesting because of its wide data utilization and applicability in locations without laboratory-confirmed admission data, understanding the sources of variability and data quality will be essential in future applications of these methods.
Amaç Solunum yolu enfeksiyonları, tüm yaş gruplarında en sık karşılaşılan hastalıklardan olup etkenlerin görülme sıklığı ve mevsimsel dağılımı coğrafi bölgeler arasında farklılıklar gösterebilmektedir. Bu çalışmada, Süleyman Demirel Üniversitesi Araştırma ve Uygulama Hastanesi’ne başvuran hastalarda solunum yolu etkenlerinin prevalansı ve mevsimsel dağılımının belirlenmesi amaçlanmıştır. Gereç ve Yöntem Tıbbi Mikrobiyoloji Laboratuvarı’na 1 Ocak 2019-31 Aralık 2019 tarihleri arasında akut solunum yolu enfeksiyonu ön tanısı alan hastalardan gönderilen solunum yolu örnekleri, multipleks gerçek zamanlı polimeraz zincir reaksiyonu (MRT-PCR) yöntemi (FTD Respiratory Pathogens 21 plus, Fast Track Diagnostics, Luxembourg) ile viral ve bakteriyel etkenlerin varlığı açısından araştırıldı. Yirmisi çocuk, 100’ü erişkin toplam 120 hastanın sonuçları retrospektif olarak incelendi. Bulgular Örneklerin 71 (%59.2)’inde bir veya birden fazla etken pozitifliği saptanırken, 49 (%40.8)’unda etken saptanmadı. Çocuk hastaların 9’unda (%45), erişkinlerin 62’sinde (%62) pozitiflik saptandı. Enfeksiyona en sık yol açan viral ve bakteriyel etkenler sırasıyla rinovirüs ve Streptococcus pneumoniae olarak belirlendi. Rinovirüs (n=20) ve S.pneumoniae (n=16) yıl boyunca saptanırken, koronavirüslerin (n=15) kış ve ilkbahar aylarında, influenza virüsleri (n=9) ve solunum sinsityal virüs (RSV) A/B’nin (n=8) kış aylarında daha sıklıkla enfeksiyona neden oldukları gözlendi. Sonuç Solunum yolu patojenlerinin moleküler yöntemlerle tanımlanmasına yönelik ilimizde yapılan ilk araştırma özelliğini taşıyan bu çalışmada, çocuklarda ve erişkinlerde en sık saptanan etkenlerin sırasıyla RSV A/B ve rinovirüs olduğu görülmüştür. Solunum yolu enfeksiyonlarından sorumlu viral ve bakteriyel etkenlerin MRT-PCR yöntemiyle eş zamanlı, hızlı ve duyarlı bir şekilde tespiti, gereksiz antibiyotik kullanımının önlen- multipmesi ve enfeksiyon kontrolü açısından klinisyenlere yol gösterici olacaktır.
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