Risk factors for hospital-acquired influenza A and patient characteristics: a matched case-control study

Efficacy of air cleaning units for preventing SARS-CoV-2 and other hospital-acquired infections on medicine for older people wards: a quasi-experimental controlled before-and-after study

BACKGROUND

Nosocomial infections are costly, and airborne transmission is increasingly recognized as important for spread. Air cleaning units (ACUs) may reduce transmission, but little research has focused on their effectiveness on open wards.

AIM

To assess whether ACUs reduce nosocomial severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), or other, infections on older adult inpatient wards.

METHODS

This was a quasi-experimental before-and-after study on two intervention-control ward pairs in a UK teaching hospital. Infections were identified using routinely collected electronic health record data during 1 year of ACU implementation and the preceding year ('core study period'). Extended analyses included 6 months of additional data from one ward pair following ACU removal. Hazard ratios (HRs) were estimated through Cox regression controlling for age, sex, ward and background infection risk. The time that the ACUs were switched on was also recorded for Intervention Ward 2.

FINDINGS

ACUs were initially feasible, but compliance reduced towards the end of the study (average operation in first vs second half of ACU time on Intervention Ward 2: 77% vs 53%). In total, 8171 admissions for >48 h (6112 patients, median age 85 years) were included. Overall, the incidence of ward-acquired SARS-CoV-2 was 3.8%. ACU implementation was associated with a non-significant trend of lower hazard for SARS-CoV-2 infection [HR core study period 0.90, 95% confidence interval (CI) 0.53-1.52; HR extended study period 0.78, 95% CI 0.53-1.14]. Only 1.5% of admissions resulted in other notable ward-acquired infections.

CONCLUSION

ACUs may reduce SARS-CoV-2 infection to a clinically meaningfully degree. Larger studies could reduce uncertainty, perhaps using a crossover design, and factors influencing acceptability to staff and patients should be explored further.

Prediction of hospital-acquired influenza using machine learning algorithms: a comparative study

BACKGROUND

Hospital-acquired influenza (HAI) is under-recognized despite its high morbidity and poor health outcomes. The early detection of HAI is crucial for curbing its transmission in hospital settings.

AIM

This study aimed to investigate factors related to HAI, develop predictive models, and subsequently compare them to identify the best performing machine learning algorithm for predicting the occurrence of HAI.

METHODS

This retrospective observational study was conducted in 2022 and included 111 HAI and 73,748 non-HAI patients from the 2011-2012 and 2019-2020 influenza seasons. General characteristics, comorbidities, vital signs, laboratory and chest X-ray results, and room information within the electronic medical record were analysed. Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGB), and Artificial Neural Network (ANN) techniques were used to construct the predictive models. Employing randomized allocation, 80% of the dataset constituted the training set, and the remaining 20% comprised the test set. The performance of the developed models was assessed using metrics such as the area under the receiver operating characteristic curve (AUC), the count of false negatives (FN), and the determination of feature importance.

RESULTS

Patients with HAI demonstrated notable differences in general characteristics, comorbidities, vital signs, laboratory findings, chest X-ray result, and room status compared to non-HAI patients. Among the developed models, the RF model demonstrated the best performance taking into account both the AUC (83.3%) and the occurrence of FN (four). The most influential factors for prediction were staying in double rooms, followed by vital signs and laboratory results.

CONCLUSION

This study revealed the characteristics of patients with HAI and emphasized the role of ventilation in reducing influenza incidence. These findings can aid hospitals in devising infection prevention strategies, and the application of machine learning-based predictive models especially RF can enable early intervention to mitigate the spread of influenza in healthcare settings.

In Support of Universal Admission Testing for SARS-CoV-2 During Significant Community Transmission

Many hospitals have stopped or are considering stopping universal admission testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We discuss reasons why admission testing should still be part of a layered system to prevent hospital-acquired SARS-CoV-2 infections during times of significant community transmission. These include the morbidity of SARS-CoV-2 in vulnerable patients, the predominant contribution of presymptomatic and asymptomatic people to transmission, the high rate of transmission between patients in shared rooms, and data suggesting surveillance testing is associated with fewer nosocomial infections. Preferences of diverse patient populations, particularly the hardest-hit communities, should be surveyed and used to inform prevention measures. Hospitals' ethical responsibility to protect patients from serious infections should predominate over concerns about costs, labor, and inconvenience. We call for more rigorous data on the incidence and morbidity of nosocomial SARS-CoV-2 infections and more research to help determine when to start, stop, and restart universal admission testing and other prevention measures.

The convergent evolution of influenza A virus: Implications, therapeutic strategies and what we need to know

Influenza virus infection, more commonly known as the 'cold flu', is an etiological agent that gives rise to recurrent annual flu and many pandemics. Dated back to the 1918- Spanish Flu, the influenza infection has caused the loss of many human lives and significantly impacted the economy and daily lives. Influenza virus can be classified into four different genera: influenza A-D, with the former two, influenza A and B, relevant to humans. The capacity of antigenic drift and shift in Influenza A has given rise to many novel variants, rendering vaccines and antiviral therapies useless. In light of the emergence of a novel betacoronavirus, the SARS-CoV-2, unravelling the underpinning mechanisms that support the recurrent influenza epidemics and pandemics is essential. Given the symptom similarities between influenza and covid infection, it is crucial to reiterate what we know about the influenza infection. This review aims to describe the origin and evolution of influenza infection. Apart from that, the risk factors entail the implication of co-infections, especially regarding the COVID-19 pandemic is further discussed. In addition, antiviral strategies, including the potential of drug repositioning, are discussed in this context. The diagnostic approach is also critically discussed in an effort to understand better and prepare for upcoming variants and potential influenza pandemics in the future. Lastly, this review encapsulates the challenges in curbing the influenza spread and provides insights for future directions in influenza management.

Influenza A subtype H3N2 is associated with an increased risk of hospital dissemination - an observational study over six influenza seasons

BACKGROUND

Previous studies on hospital-acquired influenza (HAI) have not systematically evaluated the possible impact of different influenza subtypes. HAI has historically been associated with high mortality, but clinical consequences may be less severe in a modern hospital setting.

AIMS

To identify and quantify HAI for each season, investigate possible associations with varying influenza subtypes, and to determine HAI-associated mortality.

METHODS

All influenza-PCR-positive adult patients (>18 years old) hospitalized in Skåne County during 2013-2019, were prospectively included in the study. Positive influenza samples were subtyped. Medical records of patients with suspected HAI were examined to confirm a nosocomial origin and to determine 30-day mortality.

RESULTS

Of 4110 hospitalized patients with a positive influenza PCR, 430 (10.5%) were HAI. Influenza A(H3N2) infections were more often HAI (15.1%) than influenza A(H1N1)pdm09, and influenza B (6.3% and 6.8% respectively, P<0.001). The majority of HAI caused by H3N2 were clustered (73.3 %) and were the cause of all 20 hospital outbreaks consisting of ≥4 affected patients. In contrast, the majority of HAI caused by influenza A(H1N1)pdm09 and influenza B were solitary cases (60% and 63.2%, respectively, P<0.001). Mortality associated with HAI was 9.3% and similar between subtypes.

CONCLUSIONS

HAI caused by influenza A(H3N2) was associated with an increased risk of hospital dissemination. Our study is relevant for future seasonal influenza infection control preparedness and shows that subtyping of influenza may help to define relevant infection control measures. Mortality in HAI remains substantial in a modern hospital setting.

Nationwide Survey on Seasonal Influenza Vaccination among Health Care Workers during the COVID-19 Pandemic in Greece: Determinants, Barriers and Peculiarities

BACKGROUND

Seasonal influenza vaccination (SIV) of health care workers (HCWs) is critical in protecting patients' and HCWs' health. Our objective was to examine HCW SIV coverage and related determinants.

METHODS AND MATERIALS

A nationwide cross-sectional questionnaire survey was conducted among HCWs during the first half of 2021. The questionnaire (online or paper-based) included knowledge, attitude and practice questions regarding SIV, COVID-19 vaccines and vaccination.

RESULTS

Out of 6500 questionnaires administered, 2592 were completed (response rate: 39.9%). SIV coverage reached 69.4% (95% CI: 67.6-71.2%) based on self-reported vaccine uptake. Nurses and administrative staff were found to be more skeptical and have lower vaccine acceptance in comparison with physicians (aOR = 0.66 and aQR = 0.59, respectively). Other SIV hesitancy risk factors included working in secondary health care (aOR = 0.59) and working in northern Greece (aQR = 0.66). Determinants for SIV acceptance included being or living with high-risk people due to medical history (aOR = 1.84 and aOR = 1.46, respectively), positive attitudes towards routine vaccinations (aOR: 1.86), knowledge about COVID-19 vaccines (aOR = 1.53) and COVID-19 vaccine uptake (aOR = 3.45). The primary reason for SIV refusal was low risk perception (58.7%).

CONCLUSIONS

SIV coverage (2020/2021) was relatively high, but remained far from formal recommendations. Specific occupational groups were skeptical and low-risk perception was the main reason for vaccine refusal. Targeted policies should be developed and enforced.

Risk factors for in-hospital mortality and secondary bacterial pneumonia among hospitalized adult patients with community-acquired influenza: a large retrospective cohort study

BACKGROUND

Secondary bacterial pneumonia is an important complication of seasonal influenza, but little data is available about impact on death and risk factors. This study identified risk factors for all-cause in-hospital mortality and secondary bacterial pneumonia among hospitalized adult patients with community-acquired influenza.

METHODS

A retrospective cohort study was performed at a tertiary teaching hospital in southwest China. The study cohort included all adult hospitalized patients with a laboratory-confirmed, community-acquired influenza virus infection during three consecutive influenza seasons from 2017 to 2020. Cause-specific Cox regression was used to analyze risk factors for mortality and secondary bacterial pneumonia, respectively, accounting for competing events (discharge alive and discharge alive or death without secondary bacterial pneumonia, respectively).

RESULTS

Among 174 patients enrolled in this study, 14.4% developed secondary bacterial pneumonia and 11.5% died during hospitalization. For all-cause in-hospital mortality, time-varying secondary bacterial pneumonia was a direct risk factor of death (cause-specific hazard ratio [csHR] 3.38, 95% confidence interval [CI] 1.25-9.17); underlying disease indirectly increased death risk through decreasing the hazard of being discharged alive (csHR 0.55, 95% CI 0.39-0.77). For secondary bacterial pneumonia, the final model only confirmed direct risk factors: age ≥ 65 years (csHR 2.90, 95% CI 1.27-6.62), male gender (csHR 3.78, 95% CI 1.12-12.84) and mechanical ventilation on admission (csHR 2.96, 95% CI 1.32-6.64).

CONCLUSIONS

Secondary bacterial pneumonia was a major risk factor for in-hospital mortality among adult hospitalized patients with community-acquired influenza. Prevention strategies for secondary bacterial pneumonia should target elderly male patients and critically ill patients under mechanical ventilation.

Clinical impact of nosocomial infection with pandemic influenza A (H1N1) 2009 in a respiratory ward in Guangzhou

Background

Nosocomial outbreaks of pandemic influenza A (H1N1) 2009 virus [A(H1N1)pdm09] easily develop due to its high transmissibility. This study aimed to investigate the clinical impacts of a nosocomial outbreak of A(H1N1)pdm09 between 21 January and 17 February 2016.

Methods

Patients who developed influenza-like illness (ILI) more than 48 hours after hospitalization in the index ward were enrolled as suspected patients, defined as group A and quarantined. Patients in other wards were defined as group B. A phylogenetic tree was constructed to determine the origins of the hemagglutinin and neuraminidase genes.

Results

After the implementation of an infection control measure bundle, the outbreak was limited to eight patients with ILIs in group A. Nasal swabs from seven patients were positive for A(H1N1)pdm09. All the patients recovered after treatment. Prolonged viral shedding was observed in a patient with bronchiectasis and Penicillium marneffei infection. Compared to the expected duration of hospitalization in patients without fever, those with fever had a median 7-day delay in discharge and a mean excess cost of 3,358 RMB. The four influenza strains identified were genetically identical to the A/California/115/2015 strain. Six of the 54 patients in group B who underwent bronchoscopy developed transient fever. These patients were hospitalized in various wards of the hospital and recovered after a short-term course of empirical antibiotics.

Conclusions

After the implementation of infection control measures, the nosocomial A(H1N1)pdm09 outbreak was rapidly contained; infected patients had a delay in discharge and excess costs, but no deaths occurred.