Predictors of fatality in pandemic influenza A (H1N1) virus infection among adults

What can we learn from historical pandemics? A systematic review of the literature

What are the insights from historical pandemics for policymaking today? We carry out a systematic review of the literature on the impact of pandemics that occurred since the Industrial Revolution and prior to Covid-19. Our literature searches were conducted between June 2020 and September 2023, with the final review encompassing 169 research papers selected for their relevance to understanding either the demographic or economic impact of pandemics. We include literature from across disciplines to maximise our knowledge base, finding many relevant articles in journals which would not normally be on the radar of social scientists. Our review identifies two gaps in the literature: (1) the need to study pandemics and their effects more collectively rather than looking at them in isolation; and (2) the need for more study of pandemics besides 1918 Spanish Influenza, especially milder pandemic episodes. These gaps are a consequence of academics working in silos, failing to draw on the skills and knowledge offered by other disciplines. Synthesising existing knowledge on pandemics in one place provides a basis upon which to identify the lessons in preparing for future catastrophic disease events.

Risk Factors Associated with 30-Day Mortality in Older Patients with Influenza

Background: Influenza is a common viral condition, but factors related to short-term mortality have not been fully studied in older adults. Our objective was to determine whether there is an association between geriatric factors and 30-day mortality. Methods: This was a retrospective cohort design. All patients aged 75 years and over, with a diagnosis of influenza confirmed by a positive RT-PCR, were included. The primary endpoint was death within the 30 days after diagnosis. Results: 114 patients were included; 14 (12.3%) patients died within 30 days. In multivariate analysis these patients were older (OR: 1.37 95% CI (1.05, 1.79), p = 0.021), and had a lower ADL score (OR: 0.36 95% CI (0, 17; 0.75), p = 0.006), and a higher SOFA score (OR: 2.30 95% CI (1.07, 4.94), p = 0.03). Oseltamivir treatment, initiated within the first 48 h, was independently associated with survival (OR: 0.04 95% CI (0.002, 0.78), p = 0.034). Conclusions: Identification of mortality risk factors makes it possible to consider specific secondary prevention measures such as the rapid introduction of antiviral treatment. Combined with primary prevention, these measures could help to limit the mortality associated with influenza in older patients.

New insights into the role of the Nrf2 signaling pathway in green tea catechin applications

Nuclear factor-erythroid 2-related factor 2 (Nrf2) is a transcriptional signaling pathway that plays a crucial role in numerous clinical complications. Pivotal roles of Nrf2 have been proved in cancer, autoimmune diseases, neurodegeneration, cardiovascular diseases, diabetes mellitus, renal injuries, respiratory conditions, gastrointestinal disturbances, and general disorders related to oxidative stress, inflammation, apoptosis, gelatinolysis, autophagy, and fibrogenesis processes. Green tea catechins as a rich source of phenolic compounds can deal with various clinical problems and manifestations. In this review, we attempted to focus on intervention between green tea catechins and Nrf2. Green tea catechins especially epigallocatechin gallate (EGCG) elucidated the protective role of Nrf2 and its downstream molecules in various disorders through Keap-1, HO-1, NQO-1, GPx, GCLc, GCLm, NF-kB cross-link, kinases, and apoptotic proteins. Subsequently, we compiled an updated expansions of the Nrf2 role as a gate to manage and protect different disorders and feasible indications of green tea catechins through this signaling pathway. The present review highlighted recent evidence-based data in silico, in vitro, and in vivo studies on an outline for future clinical trials.

Outcome of Patients Admitted to Intensive Care Units due to Influenza-Related Severe Acute Respiratory Illness in 2017-2018 Flu Season: A Multicenter Study from Turkey

BACKGROUND

Influenza can cause severe acute respiratory illness (SARI), which occurs as local outbreaks or seasonal epidemics with high intensive care unit (ICU) admission and mortality rates. Mortality is mainly due to SARI.

OBJECTIVE

The aim of this study was to evaluate the outcome of patients admitted to ICU due to influenza-related SARI in 2017-2018 flu season in Turkey.

METHODS

A retrospective multicenter study was conducted in 13 ICUs with a total of 216 beds from 6 cities in Turkey. All adult patients (over 18 years) admitted to the ICUs in 2017-2018 flu season (between September 1, 2017, and April 30, 2018) because of SARI and with a positive nasopharyngeal swab for influenza were included in the study.

RESULTS

A total of 123 cases were included in the study. The mean age of patients was 64.5 ± 17.5 years, and 66 (53.7%) patients were older than 65 years. The ICU mortality was 33.9%, and hospital mortality was 35.6%. Invasive mechanical ventilation (IMV), acute kidney injury (AKI), hematologic malignancy, and >65 years of age were the factors affecting mortality in influenza.

CONCLUSION

SARI due to influenza carries a high mortality rate, and IMV, AKI, presence of hematologic malignancy, and older age are independent risk factors for mortality.

Viral Emerging Diseases: Challenges in Developing Vaccination Strategies

In the last decades, a number of infectious viruses have emerged from wildlife or re-emerged, generating serious threats to the global health and to the economy worldwide. Ebola and Marburg hemorrhagic fevers, Lassa fever, Dengue fever, Yellow fever, West Nile fever, Zika, and Chikungunya vector-borne diseases, Swine flu, Severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and the recent Coronavirus disease 2019 (COVID-19) are examples of zoonoses that have spread throughout the globe with such a significant impact on public health that the scientific community has been called for a rapid intervention in preventing and treating emerging infections. Vaccination is probably the most effective tool in helping the immune system to activate protective responses against pathogens, reducing morbidity and mortality, as proven by historical records. Under health emergency conditions, new and alternative approaches in vaccine design and development are imperative for a rapid and massive vaccination coverage, to manage a disease outbreak and curtail the epidemic spread. This review gives an update on the current vaccination strategies for some of the emerging/re-emerging viruses, and discusses challenges and hurdles to overcome for developing efficacious vaccines against future pathogens.

Predictors of mortality of influenza virus infections in a Swiss Hospital during four influenza seasons: Role of quick sequential organ failure assessment

BACKGROUND

Influenza infections have been associated with high morbidity. The aims were to determine predictors of mortality among patients with influenza infections and to ascertain the role of quick Sequential Organ Failure Assessment (qSOFA) in predicting poor outcomes.

METHODS

All adult patients with influenza infection at the Hospital of Jura, Switzerland during four influenza seasons (2014/15 to 2017/18) were included. Cepheid Xpert Xpress Flu/RSV was used during the first three influenza seasons and Cobas Influenza A/B and RSV during the 2017/18 season.

RESULTS

Among 1684 influenza virus tests performed, 441 patients with influenza infections were included (238 for influenza A virus and 203 for B). The majority of infections were community onset (369; 83.7%). Thirty-day mortality was 6.0% (25 patients). Multivariate analysis revealed that infection due to A virus (P 0.035; OR 7.1; 95% CI 1.1-43.8), malnutrition (P < 0.001; OR 25.0; 95% CI 4.5-138.8), hospital-acquired infection (P 0.003; OR 12.2; 95% CI 2.3-65.1), respiratory insufficiency (PaO₂/FiO₂ < 300) (P < 0.001; OR 125.8; 95% CI 9.6-1648.7) and pulmonary infiltrate on X-ray (P 0.020; OR 6.0; 95% CI 1.3-27.0) were identified as predictors of mortality. qSOFA showed a very good accuracy (0.89) equivalent to other more specific and burdensome scores such as CURB-65 and Pneumonia Severity Index (PSI).

CONCLUSION

qSOFA performed similarly to specific severity scores (PSI, CURB-65) in predicting mortality. Infection by influenza A virus, respiratory insufficiency and malnutrition were associated with worse prognosis.

Predictors of fatality in influenza A virus subtype infections among inpatients in the 2015-2016 season

BACKGROUND

Infection with the influenza A virus can cause severe disease and mortality. The effect of the different subtypes of influenza on morbidity and mortality is not yet known in Turkey. The aim of this study was to describe the predictors of fatality related to influenza A infection among hospitalized patients in Istanbul during the 2015-2016 influenza season, and to detail the differences between infections caused by H3N2 and H1N1.

METHODS

This was a multicenter study performed by the Istanbul Respiratory Infections Study Group of The Turkish Society of Clinical Microbiology and Infectious Diseases (KLİMİK), among patients hospitalized for influenza in Istanbul during the 2015-2016 influenza season.

RESULTS

A total of 222 patients hospitalized with laboratory-confirmed influenza during the 2015-2016 season were included in the study, of whom 25 (11.2%) died. The fatality rate was significantly higher among patients older than 65 years of age and those with chronic heart and kidney diseases (p<0.001), chronic neurological diseases (p=0.009), and malignancies (p=0.021). Thrombocyte counts were lower in those who died than in those who survived (p<0.004). The median alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, creatinine phosphokinase, and C-reactive protein levels were higher among fatal cases. In the multivariate analysis for the prediction of fatality, being >65years old (odds ratio (OR) 6.9, 95% confidence interval (CI) 2.07-23.08, p=0.002), being infected with influenza A(H3N2) (OR 4.2, 95% CI 1.27-14.38, p=0.019), and a 1-day delay in antiviral use (OR 1.28, 95% CI 1.01-1.63, p=0.036) were found to be associated with an increased likelihood of fatality.

CONCLUSIONS

The case fatality rate of influenza A(H3N2) was significantly higher than that of influenza A(H1N1). Detection of the infection, allowing the opportunity for the early use of antiviral agents, was found to be important for the prevention of fatality. The vaccination should be prioritized for at-risk groups.

Significance of the detection of influenza and other respiratory viruses for antibiotic stewardship: Lessons from the post-pandemic period

OBJECTIVE

The aim was to describe the factors associated with antibiotic use in upper respiratory tract infections (URTI) in the post-pandemic influenza period.

METHODS

All consecutive patients who attended the emergency and outpatient departments of a private 265-bed hospital in Istanbul, Turkey with symptoms of an influenza-like illness (ILI) between January and June 2011 were included.

RESULTS

Out of 1270 patients, 100 were tested for Streptococcus A infection and 16 (16%) were found to be positive; 36 patients were tested for respiratory syncytial virus and five were found to be positive. A rapid influenza test (chromatographic) was performed for 325 patients and 45% were found to be positive for influenza A or B. In total, 500 patients (40%) were prescribed antibiotics; these were fluoroquinolones (12%), macrolides (10%), amoxicillin-clavulanate (10%), cefuroxime (7%), and third-generation cephalosporins (3%). On multivariate analysis, antibiotic prescription was found to be decreased by the diagnosis of influenza, whereas antibiotic prescription increased with age >65years, C-reactive protein (CRP) >20mg/L, polymorphonuclear leukocytes >80%, the detection of rales on auscultation, the presence of cough, comorbidities, and having infiltrations on a X-ray.

CONCLUSIONS

The diagnosis of influenza is important for the implementation of antimicrobial stewardship programs. Each institution should implement an algorithm for the diagnosis and management of upper respiratory tract infections. Biomarkers such as CRP and procalcitonin should be used more effectively.

An Overview of the 2009 A(H1N1) Pandemic in Europe: Efficiency of the Vaccination and Healthcare Strategies

2009 A(H1N1) data for 13 European countries obtained from the weekly influenza surveillance overview (WISO) reports of European Centre for Disease Prevention and Control (ECDC) in the form of weekly cumulative fatalities are analyzed. The variability of relative fatalities is explained by the health index of analyzed countries. Vaccination and healthcare practices as reported in the literature are used to explain the departures from this model. The timing of the vaccination with respect to the peak of the epidemic and its role in the efficiency of the vaccination is discussed. Simulations are used to show that on-time vaccination reduces considerably the final value of R(t), R_f, but it has little effect on the shape of normalized curve R(t)/R_f.

Risk factors for nosocomial infection among hospitalised severe influenza A(H1N1)pdm09 patients

BACKGROUND AND OBJECTIVE

Nosocomial infections following influenza are important causes of death, requiring early implementation of preventive measures, but predictors for nosocomial infection in the early stage remained undetermined. We aimed to determine risk factors that can help clinicians identify patients with high risk of nosocomial infection following influenza on admission.

METHOD

Using a database prospectively collected through a Chinese national network for hospitalised severe influenza A(H1N1)pdm09 patients, we compared the characteristics on admission between patients with and without nosocomial infection.

RESULT

A total of 2146 patients were enrolled in the final analysis with a median age of 36.0 years, male patients comprising 50.2% of the sample and 232 (10.8%) patients complicated with nosocomial infection. Acinetobacter baumannii, Pseudomonas aeruginosa, Stenotrophomonas maltophilia and Staphylococcus aureus were the leading pathogens, and invasive fungal infection was found in 30 cases (12.9%). The in-hospital mortality was much higher in patients with nosocomial infection than those without (45.7% vs 11.8%, P < 0.001). Need for mechanical ventilation (OR: 3.336; 95% CI 2.362-4.712), sepsis (OR: 2.125; 95% CI 1.236-3.651), ICU admission on first day (OR: 2.074; 95% CI 1.425-3.019), lymphocytopenia (OR: 1.906; 95% CI 1.361-2.671), age > 65 years (OR: 1.83; 95% CI 1.04-3.21) and anaemia (OR: 1.39; 95% CI 1.39-2.79) were independently associated with nosocomial infection.

CONCLUSION

Need for mechanical ventilation, sepsis, ICU admission on first day, lymphocytopenia, older age and anaemia were independent risk factors that can help clinicians identify severe influenza A(H1N1)pdm09 patients at high risk of nosocomial infection.

Safety and effectiveness of neuraminidase inhibitors in situations of pandemic and/or novel/variant influenza: a systematic review of the literature, 2009-15

Objectives

To review systematically the published literature evaluating neuraminidase inhibitor (NI) safety and effectiveness in situations of pandemic and novel/variant influenza.

Methods

We searched six online databases using comprehensive search criteria for observational studies and randomized controlled trials investigating the effects of NI treatment, prophylaxis or outbreak control in patients of all ages.

Results

Overall, 165 studies were included (95% observational), which were generally of low methodological quality due to lack of adjustment for confounding variables. In studies reporting adjusted estimates in general populations, NI treatment appeared likely to be effective against mortality (primarily if administered within 48 h of symptom onset) and potentially effective in reducing pneumonia. NIs appeared effective in reducing secondary transmission when indicated for prophylaxis. Limited, low-quality data suggest NIs are likely safe in general populations and may be safe in pregnant women and children. Data are scarce regarding safety of NIs in adults and high-risk individuals.

Conclusions

Most included studies were observational, statistically underpowered and at high risk of reporting biased and/or confounded effect estimates. NI treatment appeared likely effective in reducing mortality (cause unspecified) and pneumonia in general populations, with increasing benefit when administered with 48 h of symptom onset. NI pre- or post-exposure prophylaxis is likely effective in reducing secondary transmission of influenza in a general population. Our evidence suggests NIs are likely safe to use in the general population; however, data for children and pregnant women are limited. Knowledge gaps persist in specific populations such as Aboriginals, high-risk individuals and the elderly.

Possible explanations for why some countries were harder hit by the pandemic influenza virus in 2009 - a global mortality impact modeling study

BACKGROUND

A global pandemic mortality study found prominent regional mortality variations in 2009 for Influenza A(H1N1)pdm09. Our study attempts to identify factors that explain why the pandemic mortality burden was high in some countries and low in others.

METHODS

As a starting point, we identified possible risk factors worth investigating for Influenza A(H1N1)pdm09 mortality through a targeted literature search. We then used a modeling procedure (data simulations and regression models) to identify factors that could explain differences in respiratory mortality due to Influenza A(H1N1)pdm09. We ran sixteen models to produce robust results and draw conclusions. In order to assess the role of each factor in explaining differences in excess pandemic mortality, we calculated the reduction in between country variance, which can be viewed as an effect-size for each factor.

RESULTS

The literature search identified 124 publications and 48 possible risk factors, of which we were able to identify 27 factors with appropriate global datasets. The modelling procedure indicated that age structure (explaining 40% of the mean between country variance), latitude (8%), influenza A and B viruses circulating during the pandemic (3-8%), influenza A and B viruses circulating during the preceding influenza season (2-6%), air pollution (pm10; 4%) and the prevalence of other infections (HIV and TB) (4-6%) were factors that explained differences in mortality around the world. Healthcare expenditure, levels of obesity, the distribution of antivirals, and air travel did not explain global pandemic mortality differences.

CONCLUSIONS

Our study found that countries with a large proportion of young persons had higher pandemic mortality rates in 2009. The co-circulation of influenza viruses during the pandemic and the circulation of influenza viruses during the preceding season were also associated with pandemic mortality rates. We found that real time assessments of 2009 pandemic mortality risk factors (e.g. obesity) probably led to a number of false positive findings.

Influenza pathogenicity during pregnancy in women and animal models

Pregnant women are at the highest risk to develop severe and even fatal influenza. The high vulnerability of women against influenza A virus infections during pregnancy was repeatedly highlighted during influenza pandemics including the pandemic of this century. In 2009, mortality rates were particularly high among otherwise healthy pregnant women. However, our current understanding of the molecular mechanisms involved in severe disease development during pregnancy is still very limited. In this review, we summarize the knowledge on the clinical observations in influenza A virus-infected pregnant women. In addition, knowledge obtained from few existing experimental infections in pregnant animal models is discussed. Since clinical data do not provide in-depth information on the pathogenesis of severe influenza during pregnancy, adequate animal models are urgently required that mimic clinical findings. Studies in pregnant animal models will allow the dissection of involved molecular disease pathways that are key to improve patient management and care.

On the uniqueness of epidemic models fitting a normalized curve of removed individuals

The susceptible-infected-removed (SIR) and the susceptible-exposed-infected-removed (SEIR) epidemic models with constant parameters are adequate for describing the time evolution of seasonal diseases for which available data usually consist of fatality reports. The problems associated with the determination of system parameters starts with the inference of the number of removed individuals from fatality data, because the infection to death period may depend on health care factors. Then, one encounters numerical sensitivity problems for the determination of the system parameters from a correct but noisy representative of the number of removed individuals. Finally as the available data is necessarily a normalized one, the models fitting this data may not be unique. We prove that the parameters of the (SEIR) model cannot be determined from the knowledge of a normalized curve of "Removed" individuals and we show that the proportion of removed individuals, [Formula: see text], is invariant under the interchange of the incubation and infection periods and corresponding scalings of the contact rate. On the other hand we prove that the SIR model fitting a normalized curve of removed individuals is unique and we give an implicit relation for the system parameters in terms of the values of [Formula: see text] and [Formula: see text], where [Formula: see text] is the steady state value of [Formula: see text] and [Formula: see text] and [Formula: see text] are the values of [Formula: see text] and its derivative at the inflection point [Formula: see text] of [Formula: see text]. We use these implicit relations to provide a robust method for the estimation of the system parameters and we apply this procedure to the fatality data for the H1N1 epidemic in the Czech Republic during 2009. We finally discuss the inference of the number of removed individuals from observational data, using a clinical survey conducted at major hospitals in Istanbul, Turkey, during 2009 H1N1 epidemic.