Score to identify the severity of adult patients with influenza A (H1N1) 2009 virus infection at hospital admission

Effect of human H3N2 influenza virus reassortment on influenza incidence and severity during the 2017-18 influenza season in the USA: a retrospective observational genomic analysis

BACKGROUND

During the 2017-18 influenza season in the USA, there was a high incidence of influenza illness and mortality. However, no apparent antigenic change was identified in the dominant H3N2 viruses, and the severity of the season could not be solely attributed to a vaccine mismatch. We aimed to investigate whether the altered virus properties resulting from gene reassortment were underlying causes of the increased case number and disease severity associated with the 2017-18 influenza season.

METHODS

Samples included were collected from patients with influenza who were prospectively recruited during the 2016-17 and 2017-18 influenza seasons at the Johns Hopkins Hospital Emergency Departments in Baltimore, MD, USA, as well as from archived samples from Johns Hopkins Health System sites. Among 647 recruited patients with influenza A virus infection, 411 patients with whole-genome sequences were available in the Johns Hopkins Center of Excellence for Influenza Research and Surveillance network during the 2016-17 and 2017-18 seasons. Phylogenetic trees were constructed based on viral whole-genome sequences. Representative viral isolates of the two seasons were characterised in immortalised cell lines and human nasal epithelial cell cultures, and patients' demographic data and clinical outcomes were analysed.

FINDINGS

Unique H3N2 reassortment events were observed, resulting in two predominant strains in the 2017-18 season: HA clade 3C.2a2 and clade 3C.3a, which had novel gene segment constellations containing gene segments from HA clade 3C.2a1 viruses. The reassortant re3C.2a2 viruses replicated with faster kinetics and to a higher peak titre compared with the parental 3C.2a2 and 3C.2a1 viruses (48 h vs 72 h). Furthermore, patients infected with reassortant 3C.2a2 viruses had higher Influenza Severity Scores than patients infected with the parental 3C.2a2 viruses (median 3·00 [IQR 1·00-4·00] vs 1·50 [1·00-2·00]; p=0·018).

INTERPRETATION

Our findings suggest that the increased severity of the 2017-18 influenza season was due in part to two intrasubtypes, cocirculating H3N2 reassortant viruses with fitness advantages over the parental viruses. This information could help inform future vaccine development and public health policies.

FUNDING

The Center of Excellence for Influenza Research and Response in the US, National Science and Technology Council, and Chang Gung Memorial Hospital in Taiwan.

Differentiating severe and non-severe lower respiratory tract illness in patients hospitalized with influenza: Development of the Influenza Disease Evaluation and Assessment of Severity (IDEAS) scale

BACKGROUND

Experimental studies have shown that vaccination can reduce viral replication to attenuate progression of influenza-associated lower respiratory tract illness (LRTI). However, clinical studies are conflicting, possibly due to use of non-specific outcomes reflecting a mix of large and small airway LRTI lacking specificity for acute lung or organ injury.

METHODS

We developed a global ordinal scale to differentiate large and small airway LRTI in hospitalized adults with influenza using physiologic features and interventions (PFIs): vital signs, laboratory and radiographic findings, and clinical interventions. We reviewed the literature to identify common PFIs across 9 existing scales of pneumonia and sepsis severity. To characterize patients using this scale, we applied the scale to an antiviral clinical trial dataset where these PFIs were measured through routine clinical care in adults hospitalized with influenza-associated LRTI during the 2010-2013 seasons.

RESULTS

We evaluated 12 clinical parameters among 1020 adults; 210 (21%) had laboratory-confirmed influenza, with a median severity score of 4.5 (interquartile range, 2-8). Among influenza cases, median age was 63 years, 20% were hospitalized in the prior 90 days, 50% had chronic obstructive pulmonary disease, and 22% had congestive heart failure. Primary influencers of higher score included pulmonary infiltrates on imaging (48.1%), heart rate ≥110 beats/minute (41.4%), oxygen saturation <93% (47.6%) and respiratory rate >24 breaths/minute (21.0%). Key PFIs distinguishing patients with severity < or ≥8 (upper quartile) included infiltrates (27.1% vs 90.0%), temperature ≥ 39.1°C or <36.0°C (7.1% vs 27.1%), respiratory rate >24 breaths/minute (7.9% vs 47.1%), heart rate ≥110 beats/minute (29.3% vs 65.7%), oxygen saturation <90% (14.3% vs 31.4%), white blood cell count >15,000 (5.0% vs 27.2%), and need for invasive or non-invasive mechanical ventilation (2.1% vs 15.7%).

CONCLUSION

We developed a scale in adults hospitalized with influenza-associated LRTI demonstrating a broad distribution of physiologic severity which may be useful for future studies evaluating the disease attenuating effects of influenza vaccination or other therapeutics.

Validation of pneumonia prognostic scores in a statewide cohort of hospitalised patients with COVID-19

OBJECTIVE

We aimed to externally validate the predictive performance of two recently developed COVID-19-specific prognostic tools, the COVID-GRAM and CALL scores, and prior prognostic scores for community-acquired pneumonia (CURB-65), viral pneumonia (MuBLSTA) and H1N1 influenza pneumonia (Influenza risk score) in a contemporary US cohort.

METHODS

We included 257 hospitalised patients with laboratory-confirmed COVID-19 pneumonia from three teaching hospitals in Rhode Island. We extracted data from within the first 24 hours of admission. Variables were excluded if values were missing in >20% of cases, otherwise, missing values were imputed. One hundred and fifteen patients with complete data after imputation were used for the primary analysis. Sensitivity analysis was performed after the exclusion of one variable (LDH) in the complete dataset (n = 257). Primary and secondary outcomes were in-hospital mortality and critical illness (mechanical ventilation or death), respectively.

RESULTS

Only the areas under the receiver-operating characteristic curves (RO-AUC) of COVID-GRAM (RO-AUC = 0.775, 95% CI 0.525-0.915) for in-hospital death, and CURB65 for in-hospital death (RO-AUC = 0.842, 95% CI 0.674-0.932) or critical illness (RO-AUC = 0.766, 95% CI 0.584-0.884) were significantly better than random. Sensitivity analysis yielded similar trends. Calibration plots showed better agreement between the estimated and observed probability of in-hospital death for CURB65, compared with COVID-GRAM. The negative predictive value (NPV) of CURB65 ≥2 was 97.2% for in-hospital death and 88.1% for critical illness.

CONCLUSIONS

The COVID-GRAM score demonstrated acceptable predictive performance for in-hospital death. The CURB65 score had better prognostic utility for in-hospital death and critical illness. The high NPV of CURB65 values ≥2 may be useful in triaging and allocation of resources.

SARIMA-modelled greater severity and mortality during the 2010/11 post-pandemic influenza season compared to the 2009 H1N1 pandemic in English hospitals

OBJECTIVE

The COVID-19 pandemic demonstrates the need for understanding pathways to healthcare demand, morbidity, and mortality of pandemic patients. We estimate H1N1 (1) hospitalization rates, (2) severity rates (length of stay, ventilation, pneumonia, and death) of those hospitalized, (3) mortality rates, and (4) time lags between infections and hospitalizations during the pandemic (June 2009 to March 2010) and post-pandemic influenza season (November 2010 to February 2011) in England.

METHODS

Estimates of H1N1 infections from a dynamic transmission model are combined with hospitalizations and severity using time series econometric analyses of administrative patient-level hospital data.

RESULTS

Hospitalization rates were 34% higher and severity rates of those hospitalized were 20%-90% higher in the post-pandemic period than the pandemic. Adults (45-64-years-old) had the highest ventilation and pneumonia hospitalization rates. Hospitalizations did not lag infection during the pandemic for the young (<24-years-old) but lagged by one or more weeks for all ages in the post-pandemic period.

DISCUSSION

The post-pandemic flu season exhibited heightened H1N1 severity, long after the pandemic was declared over. Policymakers should remain vigilant even after pandemics seem to have subsided. Analysis of administrative hospital data and epidemiological modelling estimates can provide valuable insights to inform responses to COVID-19 and future influenza and other disease pandemics.

Inter- Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes

The diversity of RNA viruses dictates their evolution in a particular host, community or environment. Here, we reported within- and between-host pH1N1virus diversity at consensus and sub-consensus levels over a three-year period (2015-2017) and its implications on disease severity. A total of 90 nasal samples positive for the pH1N1 virus were deep-sequenced and analyzed to detect low-frequency variants (LFVs) and haplotypes. Parallel evolution of LFVs was seen in the hemagglutinin (HA) gene across three scales: among patients (33%), across years (22%), and at global scale. Remarkably, investigating the emergence of LFVs at the consensus level demonstrated that within-host virus evolution recapitulates evolutionary dynamics seen at the global scale. Analysis of virus diversity at the HA haplotype level revealed the clustering of low-frequency haplotypes from early 2015 with dominant strains of 2016, indicating rapid haplotype evolution. Haplotype sharing was also noticed in all years, strongly suggesting haplotype transmission among patients infected during a specific influenza season. Finally, more than half of patients with severe symptoms harbored a larger number of haplotypes, mostly in patients under the age of five. Therefore, patient age, haplotype diversity, and the presence of certain LFVs should be considered when interpreting illness severity. In addition to its importance in understanding virus evolution, sub-consensus virus diversity together with whole genome sequencing is essential to explain variabilities in clinical outcomes that cannot be explained by either analysis alone.

External validation and update of a prognostic model to predict mortality in hospitalized adults with RSV: A retrospective Dutch cohort study

Respiratory syncytial virus (RSV) causes significant mortality in hospitalized adults. Prediction of poor outcomes improves targeted management and clinical outcomes. We externally validated and updated existing models to predict poor outcome in hospitalized RSV-infected adults. In this single center, retrospective, observational cohort study, we included hospitalized adults with respiratory tract infections (RTIs) and a positive polymerase chain reaction for RSV (A/B) on respiratory tract samples (2005-2018). We validated existing prediction models and updated the best discriminating model by revision, recalibration, and incremental value testing. We included 192 RSV-infected patients (median age 60.7 years, 57% male, 65% immunocompromised, and 43% with lower RTI). Sixteen patients (8%) died within 30 days. During hospitalization, 16 (8%) died, 30 (16%) were admitted to intensive care unit, 21 (11%) needed invasive mechanical ventilation, and 5 (3%) noninvasive positive pressure ventilation. Existing models performed moderately at external validation, with C-statistics 0.6 to 0.7 and moderate calibration. Updating to a model including lower RTI, chronic pulmonary disease, temperature, confusion and urea, increased the C-statistic to 0.76 (95% confidence interval, 0.61-0.91) to predict in-hospital mortality. In conclusion, existing models to predict poor prognosis among hospitalized RSV-infected adults perform moderately at external validation. A prognostic model may help to identify and treat RSV-infected adults at high-risk of death.

The PAndemic INfluenza Triage in the Emergency Department (PAINTED) pilot cohort study

BACKGROUND

Research needs to be undertaken rapidly in the event of an influenza pandemic to develop and evaluate triage methods for people presenting to the emergency department with suspected pandemic influenza.

OBJECTIVES

We aimed to pilot a research study to be undertaken in a pandemic to identify the most accurate triage method for patients presenting to the emergency department with suspected pandemic influenza. The objectives of the pilot study were to develop a standardised clinical assessment form and secure online database; test both using data from patients with seasonal influenza; seek clinician views on the usability of the form; and obtain all regulatory approvals required for the main study.

DESIGN

Study methods were piloted using an observational cohort study and clinician views were sought using qualitative, semistructured interviews.

SETTING

Six acute hospital emergency departments.

PARTICIPANTS

Patients attending the emergency department with suspected seasonal influenza during winter 2012-13 and clinicians working in the emergency departments.

MAIN OUTCOME MEASURES

Adverse events up to 30 days were identified, but analysis of the pilot data was limited to descriptive reporting of patient flow, data completeness and patient characteristics.

RESULTS

Some 165 patients were identified, of whom 10 withdrew their data, leaving 155 (94%) for analysis. Follow-up data were available for 129 of 155 (83%), with 50 of 129 (39%) being admitted to hospital. Three cases (2%) were recorded as having suffered an adverse outcome. There appeared to be variation between the hospitals, allowing for small numbers. Three of the hospitals identified 150 of 165 (91%) of the patients, and all 10 withdrawing patients were at the same hospital. The proportion with missing follow-up data varied from 8% to 31%, and the proportion admitted varied from 4% to 85% across the three hospitals with meaningful numbers of cases. All of the deaths were at one hospital. There was less variation between hospitals in rates of missing data, and for most key variables missing rates were between 5% and 30%. Higher missing rates were recorded for blood pressure (39%), inspired oxygen (43%), capillary refill (36%) and Glasgow Coma Scale score (43%). Chest radiography was performed in 51 of 118 cases, and electrocardiography in 40 of 111 cases with details recorded. Blood test results were available for 32 of 155 cases. The qualitative interviews revealed generally positive views towards the standardised assessment form. Concerns about lack of space for free text were raised but counterbalanced by appreciation that it fitted on to one A4 page. A number of amendments were suggested but only three of these were suggested by more than one participant, and no suggestions were made by more than two participants.

CONCLUSIONS

A standardised assessment form is acceptable to clinicians and could be used to collect research data in an influenza pandemic, but analysis may be limited by missing data.

FUTURE WORK

An observational cohort study to identify the most accurate triage method for predicting severe illness in emergency department attendees with suspected pandemic influenza is set up and ready to activate if, or when, a pandemic occurs.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN56149622.

FUNDING

This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 19, No. 3. See the NIHR Journals Library website for further project information.

Predictive factors of severe multilobar pneumonia and shock in patients with influenza

Purpose

To identify risk factors present at admission in adult patients hospitalised due to influenza virus infection during the 2009/10 and 2010/11 seasons—including whether infection was from pandemic or seasonal influenza A infections—that were associated with the likelihood of developing severe pneumonia with multilobar involvement and shock.

Methods

Prospective cohort study. Patients hospitalised due to influenza virus infection were recruited. We collected information on sociodemographic characteristics, pre-existing medical conditions, vaccinations, toxic habits, previous medications, exposure to social environments, and EuroQoL-5D (EQ-5D). Severe pneumonia with multilobar involvement and/or shock (SPAS) was the primary outcome of interest. We constructed two multivariate logistic regression models to explain the likelihood of developing SPAS and to create a clinical prediction rule for developing SPAS that includes clinically relevant variables.

Results

Laboratory-confirmed A(H1N1)pdm09, EQ-5D utility score 7 days before admission, more than one comorbidity, altered mental status, dyspnoea on arrival, days from onset of symptoms, and influenza season were associated with SPAS. In addition, not being vaccinated against seasonal influenza in the previous year, anaemia, altered mental status, fever and dyspnoea on arrival at hospital, difficulties in performing activities of daily living in the previous 7 days, and days from onset of symptoms to arrival at hospital were related to the likelihood of SPAS (area under the curve value of 0.75; Hosmer–Lemeshow p value of 0.84).

Conclusions

These variables should be taken into account by physicians evaluating a patient affected by influenza as additional information to that provided by the usual risk scores.