Use of Patient-Reported Symptom Data in Clinical Decision Rules for Predicting Influenza in a Telemedicine Setting.

INTRODUCTION: Increased use of telemedicine could potentially streamline influenza diagnosis and reduce transmission. However, telemedicine diagnoses are dependent on accurate symptom reporting by patients. If patients disagree with clinicians on symptoms, previously derived diagnostic rules may be inaccurate. METHODS: We performed a secondary data analysis of a prospective, nonrandomized cohort study at a university student health center. Patients who reported an upper respiratory complaint were required to report symptoms, and their clinician was required to report the same list of symptoms. We examined the performance of 5 previously developed clinical decision rules (CDRs) for influenza on both symptom reports. These predictions were compared against PCR diagnoses. We analyzed the agreement between symptom reports, and we built new predictive models using both sets of data. RESULTS: CDR performance was always lower for the patient-reported symptom data, compared with clinician-reported symptom data. CDRs often resulted in different predictions for the same individual, driven by disagreement in symptom reporting. We were able to fit new models to the patient-reported data, which performed slightly worse than previously derived CDRs. These models and models built on clinician-reported data both suffered from calibration issues. DISCUSSION: Patients and clinicians frequently disagree about symptom presence, which leads to reduced accuracy when CDRs built with clinician data are applied to patient-reported symptoms. Predictive models using patient-reported symptom data performed worse than models using clinician-reported data and prior results in the literature. However, the differences are minor, and developing new models with more data may be possible.

Associations Between Relative Viral Load at Diagnosis and Influenza A Symptoms and Recovery.

BACKGROUND: Rapid point-of-care polymerase chain reaction (PCR) diagnostic tests generally provide a qualitative result of positive or negative only. Additional information about the relative viral load could be calculated. Such quantitative information might be useful for making treatment decisions. METHODS: We enrolled students at a university health center who presented with cough and 1 additional flu-like symptom from December 2016 to February 2017. Data were collected before, during, and 5 days after the clinic visit. All those enrolled in the study received a point-of-care PCR test (cobas Liat). For those patients that tested positive for influenza A, we investigated correlations between the relative viral load and measures of disease severity and recovery. RESULTS: One hundred thirty-five students tested positive for influenza A. We found a positive correlation between viral load and body temperature. Time since symptom onset seemed to have a negative correlation but was not statistically significant. We did not find any correlations between viral load and overall symptom severity or outcomes related to recovery. CONCLUSIONS: Although we found a correlation between relative viral load and body temperature, for our study population of young, overall healthy adults, we did not find that relative viral load provided additional information that could help in determining treatment and disease outcomes. It could be that viral load does provide useful additional information for other groups of patients, such as young children or older adults. Further studies on those populations are warranted.

Virulence-mediated infectiousness and activity trade-offs and their impact on transmission potential of influenza patients.

Communicable diseases are often virulent, i.e. they cause morbidity symptoms in those infected. While some symptoms may be transmission-enhancing, other symptoms are likely to reduce transmission potential. For human diseases, the reduction in transmission opportunities is commonly caused by reduced activity. There is limited data regarding the potential impact of virulence on transmission potential. We performed an exploratory data analysis of 324 influenza patients at a university health centre during the 2016/2017 influenza season. We classified symptoms as infectiousness-related or morbidity-related and calculated two scores. The scores were used to explore the relationship between infectiousness, morbidity (virulence), and activity level. We found a decrease in the activity level with increasing morbidity scores. There was no consistent pattern between an activity level and an infectiousness score. We also found a positive correlation between morbidity and infectiousness scores. Overall, we find that increasing virulence leads to increased infectiousness and reduced activity, suggesting a trade-off that can impact overall transmission potential. Our findings indicate that a reduction of systemic symptoms may increase host activity without reducing infectiousness. Therefore, interventions should target both systemic- and infectiousness-related symptoms to reduce overall transmission potential. Our findings can also inform simulation models that investigate the impact of different interventions on transmission.

Impact of a Rapid Point of Care Test for Influenza on Guideline Consistent Care and Antibiotic Use.

BACKGROUND: Rapid influenza diagnostic tests that detect the presence of viral antigens are currently used throughout the United States but have poor sensitivity. The objective of this study was to identify if the use of a new highly accurate rapid point of care test would significantly increase the likelihood of guideline consistent care. METHODS: We prospectively recruited 300 students at a university health clinic who presented with cough and 1 influenza-like illness symptom between December 2016 and February 2017 to receive care guided by a rapid polymerase chain reaction (PCR) test. Of the 300 patients receiving the PCR test, 264 had complete medical records and were compared to 771 who received usual care. We used a logistic regression model to identify whether PCR guided care was associated with guideline consistent care, based on the appropriate use of oseltamivir and antibiotics. We also assessed whether PCR guided care decreased the likelihood of return visits within 2 weeks by patients. RESULTS: Logistic regression revealed that the odds of receiving guideline supported care did not significantly increase for patients who received PCR guided care (adjusted odds ratio [aOR], 1.24; 95% CI, 0.83-1.88). It significantly decreased the likelihood of an antibiotic prescription (aOR, 0.61; 95% CI, 0.40-0.94), increased the likelihood of receiving oseltamivir (aOR, 1.57; 95% CI, 1.09-2.28), and decreased the likelihood of return visit within 2 weeks (aOR, 0.19; 95% CI, 0.04-0.81). CONCLUSIONS: The use of a rapid PCR test did not significantly improve the likelihood of guideline consistent care. However, independent of test outcome, patients who received the test were more likely to receive an antiviral and less likely to receive an antibiotic or have a return visit within 2 weeks.

Seroprevalence of Dengue and Zika Virus in Blood Donations: A Systematic Review.

The presence of antibodies to Zika virus (ZIKV) and dengue virus (DENV) can be detected in blood donations. Donation-based surveillance provides an alternative strategy to estimate population prevalence by detecting antibodies that are circulating. To estimate population prevalence, we conducted a systematic review of literature on the seroprevalence of ZIKV and DENV antibodies in blood donations. We searched PubMed and Web of Science for studies that reported the seroprevalence of ZIKV and DENV in blood donations. The title and abstract of each study were screened by 2 reviewers simultaneously for possible inclusion, and the full text of selected studies was reviewed to ensure that they met inclusion criteria (used primary data collection, reported evidence of immunoglobulin M (IgM) or immunoglobulin G (IgG) antibodies in the blood supply, and included a representative sample of the total population). Immunoglobin test measuring levels of antibodies to IgM and IgG and number of positive cases were extracted from each study. No exclusions were made based on language or country. Our initial search identified 1890 studies after excluding duplicates, of which 76 were assessed for full text eligibility to ensure that they met our final inclusion criteria. There were 14 studies included in our review; 11 examined the seroprevalence of DENV, and 3 examined ZIKV. The highest seroprevalence by IgM was 2.82% for DENV and 0.53% for ZIKV. Our results indicate that the seroprevalence of ZIKV and DENV antibody presence in countries with active transmission is higher than reports by traditional surveillance in some countries. This finding is expected due to the large percentage of asymptomatic cases. The highest seroprevalence was observed for IgG, which can persist over long periods of time compared to IgM. Screening of blood donations may help supplement traditional surveillance measures, especially during outbreak settings.

Prevalence of Atypical Pathogens in Patients With Cough and Community-Acquired Pneumonia: A Meta-Analysis.

PURPOSE: Community-acquired pneumonia (CAP), acute cough, bronchitis, and lower respiratory tract infections (LRTI) are often caused by infections with viruses or Streptococcus pneumoniae. The prevalence of atypical pathogens Mycoplasma pneumoniae, Chlamydophila pneumoniae, Legionella pneumophila, and Bordetella pertussis among patients with these illnesses in the ambulatory setting has not been previously summarized. We set out to derive prevalence information from the existing literature. METHODS: We performed a systematic review of MEDLINE for prospective, consecutive-series studies reporting the prevalence of M pneumoniae, C pneumoniae, L pneumophila and/or B pertussis in outpatients with cough, acute bronchitis, LRTI, or CAP. Articles were independently reviewed by 2 authors for inclusion and abstraction of data; discrepancies were resolved by consensus discussion. A meta-analysis was performed on each pathogen to calculate the pooled prevalence estimates using a random effects model of raw proportions. RESULTS: Fifty studies met our inclusion criteria. While calculated heterogeneity was high, most studies reported prevalence for each pathogen within a fairly narrow range. In patients with CAP, the overall prevalences of M pneumoniae and C pneumoniae were 10.1% (95% CI, 7.1%-13.1%) and 3.5% (95% CI, 2.2%-4.9%), respectively. Consistent with previous reports, M pneumoniae prevalence peaked in roughly 6-year intervals. Overall prevalence of L pneumophila was 2.7% (95% CI, 2.0%-3.4%), but the organism was rare in children, with only 1 case in 1,765. In patients with prolonged cough in primary care, the prevalence of B pertussis was 12.4% (95% CI, 4.9%-19.8%), although it was higher in studies that included only children (17.6%; 95% CI, 3.4%-31.8%). CONCLUSIONS: Atypical bacterial pathogens are relatively common causes of lower respiratory diseases, including cough, bronchitis, and CAP. Where surveillance data were available, we found higher prevalences in studies where all patients are tested for these pathogens. It is likely that these conditions are underreported, underdiagnosed, and undertreated in current clinical practice.