RESUMEN
OBJECTIVES: To describe the symptoms, duration, severity, and microbiology of lower respiratory tract infection (LRTI) in outpatients. METHODS: Prospective cohort study of adults in US primary or urgent care with a chief complaint of cough and symptoms consistent with LRTI. Baseline data included demographics, signs, symptoms and PCR for 46 viruses and bacteria. Severity of symptoms reported for up to 28 days follow-up via diary and text message. The Bronchitis Severity Score (BSS) assessed severity at baseline; overall severity was defined as the area under the symptom severity curve. RESULTS: Of 718 patients with complete baseline data, 618 had valid PCR results, and 443 were followed until symptoms resolved. Of those with valid PCR, 100 (16.2%) had 1+ viruses detected, 211 (34.1%) had 1+ bacteria, and 168 (27.2%) had both. Symptoms more likely with viral or mixed infection included feverishness (36.7% to 38.4% vs 18.5%), chills or sweats (36.0% to 38.1% vs 17.9%), being generally unwell (78.2% to 81.3% vs 64.9%), and myalgias (42.7% to 48.2% vs 28.6%). Colored sputum (42.9% vs 23.2% to 29.5%) was more common with bacterial infection. Mean duration of cough was 14.7 days with viruses (95% CI 13.2-16.2), 17.3 with bacteria (95% CI 15.9-18.6), 16.9 with mixed infection (95% CI 15.2-18.6), and 18.4 with no detection (95% CI 16.1-20.8). Overall severity of cough was lower for viral infections (20.9 points, 95% CI 18.6-23.3) than for other groups (range 24.2-26.3). The most common potential bacterial pathogens were Haemophilus influenza (28.0%), Moraxella catarrhalis (16.2%), and Streptococcus pneumoniae (10.2%), while the most common viral pathogens were rhinovirus (17.3%), influenza (12.8%), SARS-CoV-2 (11.5%), and seasonal coronaviruses (8.1%). CONCLUSION: The mean duration of cough was 16.4 days. Consistent with European studies, the type of infection or potential pathogen was not an important predictor of the duration or severity of LRTI.
RESUMEN
School-based outbreaks often precede increased incidence of acute respiratory infections in the greater community. We conducted acute respiratory infection surveillance among children to elucidate commonly detected pathogens in school settings and their unique characteristics and epidemiological patterns. The ORegon CHild Absenteeism due to Respiratory Disease Study (ORCHARDS) is a longitudinal, laboratory-supported, school-based, acute respiratory illness (ARI) surveillance study designed to evaluate the utility of cause-specific student absenteeism monitoring for early detection of increased activity of influenza and other respiratory viruses in schools from kindergarten through 12th grade. Eligible participants with ARIs provided demographic, epidemiologic, and symptom data, along with a nasal swab or oropharyngeal specimen. Multipathogen testing using reverse-transcription polymerase chain reaction (RT-PCR) was performed on all specimens for 18 respiratory viruses and 2 atypical bacterial pathogens (Chlamydia pneumoniae and Mycoplasma pneumoniae). Between 5 January 2015 and 9 June 2023, 3498 children participated. Pathogens were detected in 2455 of 3498 (70%) specimens. Rhinovirus/enteroviruses (36%) and influenza viruses A/B (35%) were most commonly identified in positive specimens. Rhinovirus/enteroviruses and parainfluenza viruses occurred early in the academic year, followed by seasonal coronaviruses, RSV, influenza viruses A/B, and human metapneumovirus. Since its emergence in 2020, SARS-CoV-2 was detected year-round and had a higher median age than the other pathogens. A better understanding of the etiologies, presentations, and patterns of pediatric acute respiratory infections can help inform medical and public health system responses.
RESUMEN
BACKGROUND: Testing for influenza in patients with acute lower respiratory tract infection (LRTI) is common and in some cases is performed for all patients with LRTI. A more selective approach to testing could be more efficient. METHODS: We used data from two prospective studies in the US primary and urgent care settings that enrolled patients with acute LRTI or influenza-like illness. Data were collected in the 2016, 2019, 2021, and 2022 flu seasons. All patients underwent polymerase chain reaction (PCR) testing for influenza and the FluScore was calculated based on patient-reported symptoms at their initial visit. The probability of influenza in each risk group was reported, as well as stratum-specific likelihood ratios (SSLRs) for each risk level. RESULTS: The prevalence of influenza within risk groups varied based on overall differences in flu seasons and populations. However, the FluScore exhibited consistent performance across various seasons and populations based on the SSLRs. The FluScore had a consistent SSLR range of 0.20 to 0.23 for the low-risk group, 0.63 to 0.99 for the moderate-risk group, and 1.46 to 1.67 for the high-risk group. The diagnostic odds ratio based on the midpoints of these ranges was 7.25. CONCLUSIONS: The FluScore could streamline patient categorization, identifying patients who could be exempted from testing, while identifying candidates for rapid influenza tests. This has the potential to be more efficient than a "one size fits all" test strategy, as it strategically targets the use of tests on patients most likely to benefit. It is potentially usable in a telehealth setting.
