Derivation of a clinical prediction rule to predict hospitalization for influenza in EDs

A systematic review of tools for predicting complications in patients with influenza-like illness

Objective

To identify tools that predict the risk of complications for patients presenting to an outpatient clinic or an emergency department (ED) with influenza-like illness.

Methods

We searched Medline, Embase, Cochrane Library and CINAHL from inception to July 2023. We included articles reporting on the derivation or validation of a score or algorithm used to stratify the risk of hospitalization or mortality among patients with influenza-like illness in the ED or outpatient clinic.

Results

Twelve articles reporting on eight scores and six predictive models were identified. For predicting the need for hospitalization, the area under the curve (AUC) of the PMEWS and the CURB-65 ranged respectively from 0.76 to 0.94, and 0.65 to 0.88. The Community Assessment Tool had an AUC of 0.62. For predicting inpatient mortality, AUC was 0.66 for PMEWS and 0.79 for CURB-65, 0.79 for the SIRS criteria and 0.86 for the qSOFA score. Two scores were developed without external validation during the Covid-19 pandemic. The CovHos score and the Canadian Covid discharge score had an AUC ranged from 0.70 to 0.91. The predictive models performed adequately (AUC from 0.76 to 0.92) but will require external validation for clinical use. Tool diversity and study population heterogeneity precluded meta-analysis.

Conclusion

Although the CURB, PMEWS and qSOFA scores appear to predict accurately the risk of complications of influenza-like illness, none were reliable enough to justify their widespread ED use. Refinement of an existing tool or development of a new tool to optimize the management of these patients is needed.

Factors associated with hospitalization for seasonal influenza in a Japanese nonelderly cohort

BACKGROUND

Nonelderly patients may require hospitalization if their symptoms of influenza are severe. However, little evidence is available about the risk factors for hospitalization for influenza.

METHODS

We used a multicenter outpatient and inpatient database to obtain patients' characteristics and clinical procedures. We identified patients aged <65 years with a confirmed diagnosis of influenza between October 2013 and December 2014. We used a Cox regression model to identify the risk factors for hospitalization, using a comparison group of individuals with a confirmed diagnosis of influenza but who were not hospitalized.

RESULTS

Of 88,054 patients diagnosed with influenza, 276 (0.3 %) patients were hospitalized. With reference to patients aged 18-64 years, the hazard ratio (95 % confidence interval) for hospitalization in patients aged <2, 2-4, and 5-17 years was 12.25 (8.37-17.93), 4.56 (3.10-6.72) and 1.45 (1.03-2.05), respectively. Anemia, chronic obstructive pulmonary disease, neurologic disease, and regular steroid use were significantly associated with hospitalization. Hazard ratios were adjusted for age, sex, comorbidities, respiratory co-infection, virus type, and influenza season.

CONCLUSIONS

Our findings suggest that younger age and several comorbidities are associated with higher probability of hospitalization for influenza.

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.