Hospital-acquired influenza infections detected by a surveillance system over six seasons, from 2010/2011 to 2015/2016

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.

Traditional definition of healthcare-associated influenza underestimates cases associated with other healthcare exposures in a population-based surveillance system

OBJECTIVE

To provide comprehensive population-level estimates of the burden of healthcare-associated influenza.

DESIGN

Retrospective cross-sectional study.

SETTING

US Influenza Hospitalization Surveillance Network (FluSurv-NET) during 2012-2013 through 2018-2019 influenza seasons.

PATIENTS

Laboratory-confirmed influenza-related hospitalizations in an 8-county catchment area in Tennessee.

METHODS

The incidence of healthcare-associated influenza was determined using the traditional definition (ie, positive influenza test after hospital day 3) in addition to often underrecognized cases associated with recent post-acute care facility admission or a recent acute care hospitalization for a noninfluenza illness in the preceding 7 days.

RESULTS

Among the 5,904 laboratory-confirmed influenza-related hospitalizations, 147 (2.5%) had traditionally defined healthcare-associated influenza. When we included patients with a positive influenza test obtained in the first 3 days of hospitalization and who were either transferred to the hospital directly from a post-acute care facility or who were recently discharged from an acute care facility for a noninfluenza illness in the preceding 7 days, we identified an additional 1,031 cases (17.5% of all influenza-related hospitalizations).

CONCLUSIONS

Including influenza cases associated with preadmission healthcare exposures with traditionally defined cases resulted in an 8-fold higher incidence of healthcare-associated influenza. These results emphasize the importance of capturing other healthcare exposures that may serve as the initial site of viral transmission to provide more comprehensive estimates of the burden of healthcare-associated influenza and to inform improved infection prevention strategies.

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.

Comparison of 28-Day Mortality Between Hospital- and Community-Acquired Influenza Patients

Objective

This study aimed to compare 28-day mortality between patients have hospital-acquired influenza (HAI) and those have community-acquired influenza (CAI) during the 2017-2019 influenza seasons in a tertiary care center in İstanbul, Türkiye.

Materials and Methods

This retrospective cohort included all hospitalized patients who had confirmed influenza infection and were over 17 years old. HAI was defined as a case of influenza that tested negative in a PCR test or had no signs of influenza on admission but with a positive test result at any point after 72 hours of admission. CAI was defined as a case of influenza diagnosed within 72 hours of admission or before admission. The primary outcome was 28-day mortality after diagnosis. Biological sex, admission to the intensive care unit (ICU), presence of chronic obstructive pulmonary disease, cardiovascular and immunosuppressive comorbidities, influenza subtype, and other variables identified with univariate analyses (p<0.25) were entered into logistic regression analysis.

Results

During the study period, 92 (46%) of 201 hospitalized patients who tested positive for influenza were identified as HAI, and the rest (109) were identified as CAI. Univariate analysis showed no differences between survivors and non-survivors in patient characteristics, except non-survivors were more likely to have an ICU admission. The multivariable logistic regression analysis results showed that HAI was associated with 5.6-fold increased odds of mortality (95% confidence interval [CI]=1.6-19.3; p=0.006), after adjustment for age, gender, comorbidity, and ICU admission.

Conclusion

The results of this study revealed that patients who had HAI were more likely to die within 28 days compared to those who had CAI after controlling for key confounders. The high rate of HAI underscores the critical importance of robust infection control measures for hospital-acquired viral infections. Additional research and targeted interventions are necessary to improve the HAI prognosis.

Respiratory Viruses in Nosocomial Pneumonia: An Evolving Paradigm

Nosocomial pneumonia (NP) represents a leading cause of morbidity and mortality in hospitalized patients. Historically, clinicians have considered hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), which comprise NP, to be essentially bacterial processes. As such, patients suspected of having either HAP or VAP are initially treated with broad-spectrum antibiotics, and few clinicians search for a possible culprit virus. Recent reports which build on earlier studies, however, indicate that viruses likely play an important role in NP. Studies employing viral diagnostics as part of the evaluation for NP indicate that common respiratory viruses can spread nosocomially and lead to HAP and VAP. Similarly, studies of the general epidemiology of respiratory viral infections, such as influenza, respiratory syncytial virus, adenovirus, and rhinovirus, confirm that these pathogens are important causes of NP, especially among immunosuppressed and pediatric patients. More importantly, these more contemporary analyses reveal that one cannot, based on clinical characteristics, distinguish a viral from a bacterial cause of NP. Additionally, viral HAP and VAP result in crude mortality rates that rival or exceed those reported in bacterial NP. Rigorous prospective, multicenter trials are needed to confirm the significance of respiratory viruses in NP, as are studies of novel therapeutics for these viral infections.

Patient influenza vaccination reduces the risk of hospital-acquired influenza: An incident test negative-case control study in Lyon university hospital, France (2004-2020)

BACKGROUND

Literature is limited on the impact of patient vaccination on the risk of hospital-acquired influenza (HAI). This test negative case-control study nested in a surveillance program aimed at evaluating the effectiveness of influenza vaccination in reducing the risk of HAI in hospitalized patients during 15 influenza seasons (2004-05 to 2019-20).

METHODS

HAI cases were those who developed influenza like illness (ILI) symptoms at least 72 h after hospitalization and had a positive reverse transcriptase-polymerase chain reaction (RT-PCR). Controls were those with ILI symptoms and a negative RT-PCR test. A nasal swab as well as socio-demographic, clinical data and information on influenza vaccination were collected.

RESULTS

Of the 296 patients included, 67 were confirmed HAI cases. Influenza vaccine coverage was significantly higher among controls compared to HAI cases (p = 0.002). The risk of HAI was reduced by almost 60 % in vaccinated patients.

CONCLUSIONS

A better control of HAI can be achieved by vaccinating hospitalized patients.

Clinical impact of healthcare-associated respiratory syncytial virus in hospitalized adults

OBJECTIVE

To describe the clinical impact of healthcare-associated (HA) respiratory syncytial virus (RSV) in hospitalized adults.

DESIGN

Retrospective cohort study within a prospective, population-based, surveillance study of RSV-infected hospitalized adults during 3 respiratory seasons: October 2017-April 2018, October 2018-April 2019, and October 2019-March 2020.

SETTING

The study was conducted in 2 academically affiliated medical centers.

PATIENTS

Each HA-RSV patient (in whom RSV was detected by PCR test ≥4 days after hospital admission) was matched (age, sex, season) with 2 community-onset (CO) RSV patients (in whom RSV was detected ≤3 days of admission).

METHODS

Risk factors and outcomes were compared among HA-RSV versus CO-RSV patients using conditional logistic regression. Escalation of respiratory support associated with RSV detection (day 0) from day -2 to day +4 was explored among HA-RSV patients.

RESULTS

In total, 84 HA-RSV patients were matched to 160 CO-RSV patients. In HA-RSV patients, chronic kidney disease was more common, while chronic respiratory conditions and obesity were less common. HA-RSV patients were not more likely to be admitted to an ICU or require mechanical ventilation, but they more often required a higher level of care at discharge compared with CO-RSV patients (44% vs 14%, respectively). Also, 29% of evaluable HA-RSV patients required respiratory support escalation; these patients were older and more likely to have respiratory comorbidities, to have been admitted to intensive care, and to die during hospitalization.

CONCLUSIONS

HA-RSV in adults may be associated with escalation in respiratory support and an increased level of support in living situation at discharge. Infection prevention and control strategies and RSV vaccination of high-risk adults could mitigate the risk of HA-RSV.

Vaccine mandates for healthcare workers beyond COVID-19

We provide ethical criteria to establish when vaccine mandates for healthcare workers are ethically justifiable. The relevant criteria are the utility of the vaccine for healthcare workers, the utility for patients (both in terms of prevention of transmission of infection and reduction in staff shortage), and the existence of less restrictive alternatives that can achieve comparable benefits. Healthcare workers have professional obligations to promote the interests of patients that entail exposure to greater risks or infringement of autonomy than ordinary members of the public. Thus, we argue that when vaccine mandates are justified on the basis of these criteria, they are not unfairly discriminatory and the level of coercion they involve is ethically acceptable-and indeed comparable to that already accepted in healthcare employment contracts. Such mandates might be justified even when general population mandates are not. Our conclusion is that, given current evidence, those ethical criteria justify mandates for influenza vaccination, but not COVID-19 vaccination, for healthcare workers. We extend our arguments to other vaccines.

Investigating Epidemiologic and Molecular Links Between Patients With Community- and Hospital-Acquired Influenza A: 2017-2018 and 2019-2020, Michigan

Background

Hospital-acquired influenza virus infection (HAII) can cause severe morbidity and mortality. Identifying potential transmission routes can inform prevention strategies.

Methods

We identified all hospitalized patients testing positive for influenza A virus at a large, tertiary care hospital during the 2017-2018 and 2019-2020 influenza seasons. Hospital admission dates, locations of inpatient service, and clinical influenza testing information were retrieved from the electronic medical record. Time-location groups of epidemiologically linked influenza patients were defined and contained ≥1 presumed HAII case (first positive ≥48 hours after admission). Genetic relatedness within time-location groups was assessed by whole genome sequencing.

Results

During the 2017-2018 season, 230 patients tested positive for influenza A(H3N2) or unsubtyped influenza A including 26 HAIIs. There were 159 influenza A(H1N1)pdm09 or unsubtyped influenza A-positive patients identified during the 2019-2020 season including 33 HAIIs. Consensus sequences were obtained for 177 (77%) and 57 (36%) of influenza A cases in 2017-2018 and 2019-2020, respectively. Among all influenza A cases, there were 10 time-location groups identified in 2017-2018 and 13 in 2019-2020; 19 of 23 groups included ≤4 patients. In 2017-2018, 6 of 10 groups had ≥2 patients with sequence data, including ≥1 HAII case. Two of 13 groups met this criteria in 2019-2020. Two time-location groups from 2017-2018 each contained 3 genetically linked cases.

Conclusions

Our results suggest that HAIIs arise from outbreak transmission from nosocomial sources as well as single infections from unique community introductions.

Nosocomial SARS-CoV-2 transmission in multi-bedded hospital cubicles over successive pandemic waves: Lower mortality but wider spread with Omicron despite enhanced infection-prevention measures

Background

Increased transmissibility of severe-acute-respiratory-syndrome-coronavirus-2(SARS-CoV-2) variants, such as the Omicron-variant, presents an infection-control challenge. We contrasted nosocomial transmission amongst hospitalized inpatients across successive pandemic waves attributed to the Delta- and Omicron variants, over a 9-month period in which enhanced-infection-prevention-measures were constantly maintained.

Methods

Enhanced-infection-prevention-measures in-place at a large tertiary hospital included universal N95-usage, routine-rostered-testing (RRT) for all inpatient/healthcare-workers (HCWs), rapid-antigen-testing (RAT) for visitors, and outbreak-investigation coupled with enhanced-surveillance (daily-testing) of exposed patients. The study-period lasted from 21st June 2021–21st March 2022. Chi-square test and multivariate-logistic-regression was utilized to identify factors associated with onward transmission and 28d-mortality amongst inpatient cases of hospital-onset COVID-19.

Results

During the Delta-wave, hospital-onset cases formed 2.7% (47/1727) of all COVID-19 cases requiring hospitalisation; in contrast, hospital onset-cases formed a greater proportion (17.7%, 265/1483; odds-ratio, OR = 7.78, 95%CI = 5.65–10.70) during the Omicron-wave, despite universal N95-usage and other enhanced infection-prevention measures that remained unchanged. The odds of 28d-mortality were higher during the Delta-wave compared to the Omicron-wave (27.7%, 13/47, vs. 10.6%, 28/265, adjusted-odds-ratio, aOR = 2.78, 95%CI = 1.02–7.69). Onward-transmission occurred in 21.2% (66/312) of hospital-onset cases; being on enhanced-surveillance (daily-testing) was independently associated with lower odds of onward-transmission (aOR = 0.18, 95%CI = 0.09–0.38). Costs amounted to $USD7141 per-hospital-onset COVID-19 case.

Conclusion

A surge of hospital-onset COVID-19 cases was encountered during the Omicron-wave, despite continuation of enhanced infection-prevention measures; mortality amongst hospital-onset cases was reduced. The Omicron variant poses an infection-control challenge in contrast to Delta; surveillance is important especially in settings where infrastructural limitations make room-sharing unavoidable, despite the high risk of transmission.

Impact and characteristics of hospital-acquired influenza over 10 seasons in a third-level university hospital

OBJECTIVES

To analyze the characteristics of patients with nosocomial flu, to compare them with patients with community-acquired influenza to study possible differences and to identify possible risk factors associated with this type of flu.

PATIENTS AND METHODS

Observational, cross-sectional and retrospective study of hospitalized patients with a microbiological confirmation of influenza in a third-level university hospital over 10 seasons, from 2009 to 2019. Nosocomial influenza was defined as that infection whose symptoms began 72h after hospital admission, and its incidence, characteristics and consequences were further analyzed.

RESULTS

A total of 1260 hospitalized patients with a microbiological diagnosis of influenza were included, which 110 (8.7%) were nosocomial. Patients with hospital-acquired influenza were younger (71.74±16.03 years, P=0.044), had a longer hospital stay (24.25±20.25 days, P<0.001), had more frequently a history of chronic pulmonary pathologies (P=0.010), immunodeficiency (P<0.001), and were associated with greater development of bacterial superinfection (P<0.001), respiratory distress (P=0.003), and admission to the intensive care unit (ICU) (P<0.001). In the multivariate logistic regression analysis, the following characteristics were identified as independent risk factors: immunodeficiency (ORa=2.33; 95% CI: 1.47-3.60); ICU admission (ORa=4.29; 95% CI: 2.23-10.91); bacterial superinfection (ORa=1.64; 95% CI: 1.06-2.53) and respiratory distress (ORa=3.88; 95% CI: 1.23-12.23).

CONCLUSIONS

Nosocomial influenza is more common in patients with a history of immunodeficiency. In addition, patients with hospital-acquired influenza had an increased risk of bacterial superinfection, admission to the ICU, and development of respiratory distress.

Estimating the Nosocomial Transmission Rate of COVID-19 in Orthopaedic Surgery Patients During the Peak of the Pandemic

Purpose

To estimate the risk of hospital-acquired COVID-19 transmission in a population of orthopaedic trauma patients during the first wave of the pandemic.

Patients and Methods

This is a retrospective cohort study of 109 patients who underwent an emergent orthopedic procedure by a single orthopedic traumatologist between March 1, 2020 and May 15, 2020 during the first peak of the pandemic. After applying inclusion and exclusion criteria, a total of 82 patients (67 inpatients and 15 ambulatory) were identified for final analysis. The primary outcome measured was postoperative Coronavirus (COVID-19) status. Secondary outcome measures included length of stay and discharge disposition.

Results

The mean age and length of stay in the hospital group was 59.5 years (± 21.7) and 4.3 days (± 4.6), respectively, versus 47.9 years (± 9.8) in the ambulatory group. 7.3% (6/82) of the inpatients subsequently tested or screened positive for COVID-19 at 2 weeks post-operatively, compared to 0/15 ambulatory patients (P=0.58). Of the 6 inpatients who tested positive, 4 (66.7%) were discharged to a rehabilitation center. Diabetes (P=0.05), hypertension (P=0.02), and congestive heart failure (P=0.005) were associated with transmission.

Conclusion

In this analysis, there was a nosocomial transmission rate of 7% compared to zero in the ambulatory surgery center, however this was not found to be statistically significant. This data supports the use of precautions such as frequent screening, hand washing, and masks to reduce transmission when COVID-19 rates are high. There is a lower risk of nosocomial COVID-19 transmission for patients treated as an outpatient and elective surgical procedures may be safer in this setting.

A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.

Outcomes of hospital-acquired SARS-CoV-2 infection in the Canadian first wave epicentre: a retrospective cohort study

BACKGROUND

During the first wave of the COVID-19 pandemic, a substantial number of Quebec hospitals were hit by hospital-acquired (HA) SARS-CoV-2 infections. Our objective was to assess whether mortality is higher in HA cases than in non-hospital-acquired (NHA) cases and determine the prevalence of HA-SARS-CoV-2 infection in our hospital.

METHODS

This retrospective single-centre cohort study included all adults (≥ 18 yr) who had COVID-19, admitted to Hôpital Maisonneuve-Rosemont (Montréal, Canada) from Mar. 1 to June 30, 2020. We collected data on demographic characteristics, comorbidities, treatment, admission to the intensive care unit (ICU) and mechanical ventilation requirements from electronic health records. We adjudicated hospital acquisition based on the timing of symptom onset, and polymerase chain reaction testing for and exposures to SARS-CoV-2. To evaluate the association between HA-SARS-CoV-2 infection and in-hospital mortality, we computed a multivariable logistic regression analysis including known risk factors for death in patients with COVID-19 as covariates.

RESULTS

Among 697 patients with SARS-CoV-2 infection, 253 (36.3%) were classified as HA. The mortality rate was higher in the HA group than in the NHA group (38.2% v. 26.4%, p = 0.001), while the rates of ICU admission (8.3% v. 19.1%, p = 0.001) and requirement for mechanical ventilation (3.6% v. 13.0%, p = 0.001) were lower. Multivariable logistic regression analysis showed that HA-SARS-CoV-2 infection in patients younger than 75 years is an independent risk factor for death (odds ratio 2.78, 95% confidence interval 1.44-5.38).

INTERPRETATION

Our results show that HA-SARS-CoV-2 infection in younger patients was associated with higher mortality. Future studies need to evaluate relevant patient-centred long-term outcomes in this population.

Real-Time Investigation of a Large Nosocomial Influenza A Outbreak Informed by Genomic Epidemiology

BACKGROUND

Nosocomial respiratory virus outbreaks represent serious public health challenges. Rapid and precise identification of cases and tracing of transmission chains is critical to end outbreaks and to inform prevention measures.

METHODS

We combined conventional surveillance with influenza A virus (IAV) genome sequencing to identify and contain a large IAV outbreak in a metropolitan healthcare system. A total of 381 individuals, including 91 inpatients and 290 healthcare workers (HCWs), were included in the investigation.

RESULTS

During a 12-day period in early 2019, infection preventionists identified 89 HCWs and 18 inpatients as cases of influenza-like illness (ILI), using an amended definition without the requirement for fever. Sequencing of IAV genomes from available nasopharyngeal specimens identified 66 individuals infected with a nearly identical strain of influenza A H1N1pdm09 (43 HCWs, 17 inpatients, and 6 with unspecified affiliation). All HCWs infected with the outbreak strain had received the seasonal influenza virus vaccination. Characterization of 5 representative outbreak viral isolates did not show antigenic drift. In conjunction with IAV genome sequencing, mining of electronic records pinpointed the origin of the outbreak as a single patient and a few interactions in the emergency department that occurred 1 day prior to the index ILI cluster.

CONCLUSIONS

We used precision surveillance to delineate a large nosocomial IAV outbreak, mapping the source of the outbreak to a single patient rather than HCWs as initially assumed based on conventional epidemiology. These findings have important ramifications for more-effective prevention strategies to curb nosocomial respiratory virus outbreaks.

Observational Study of Hand Hygiene Compliance at a Trauma Hospital in Iraqi Kurdistan

Healthcare-associated infections, commonly caused by poor hand hygiene, represent a significant source of disease and economic burden for healthcare systems, especially those in resource-limited settings. The few existing studies on hand hygiene compliance in resource-limited hospital settings suggest that compliance is insufficient. The difference in compliance rates between units in resource-limited trauma hospitals is largely unknown. We aimed to assess hand hygiene compliance rates among healthcare workers at a trauma hospital in Iraqi Kurdistan and compare the levels of compliance between the emergency room (ER), the intensive care unit (ICU), and the acute care ward (ACW). We carried out overt observations in 2018 using the validated World Health Organization ‘five moments for hand hygiene’ observational tool. We observed a total of 622 hand hygiene opportunities performed by 149 healthcare workers. Hand hygiene compliance was defined as handwashing with soap and water or the use of alcohol-based hand rub, in accordance with the ‘five moments for hand hygiene’ concept. Overall, the hand hygiene compliance rate was found to be 6.8% (95% confidence interval 5.0–9.1). Compliance was significantly lower in the ER (1.0%), compared with the ICU (8.1%) (p = 0.0012), and the ACW (11.1%) (p < 0.0001). In all three units, the availability of alcohol-based hand rub and handwashing sinks was insufficient in relation to the number of patient beds. We conclude that the overall level of hand hygiene compliance was low, with the lowest level of compliance in the ER. Our findings call for improved resource allocation and strengthened hand hygiene routines. These relatively simple measures could potentially lower the incidence of healthcare-associated infections and improve the mortality and morbidity of patients in already overburdened healthcare systems.

Predictors of growth of Escherichia coli on lab coats as part of hospital-acquired infection transmission through healthcare personnel attire

OBJECTIVES

Previous research has documented the presence of microbes on healthcare personnel (HCP) attire. This study aimed to explore the bacterial contamination and predictors of Escherichia coli (E coli) growth, as well as, hygiene and handling practices of HCP attire that could influence growth of E coli.

METHODS

Descriptive, cross-sectional study was used in this study. Convenience sampling of the 188 HCP was recruited from a main comprehensive hospital in the northern part of Jordan. Three swab samples were collected from three different parts of lab coats used by each participant. The generalised mixed linear model was used for the categorical variables and to identify the predictors of E coli growth on HCP attire.

RESULTS

Enterococcus faecalis was the most common species of bacteria found on lab coat. The HCP attire coming from the emergency department (ED) was highlighted with slightly higher contamination of E coli compared with other departments, such as critical care units. Factors associated with significant E coli growth on HCP attire were lab coat use over scrubs and borrowing of lab coats. The predictors of positive E coli growth were working in the ED, storing HCP attire in hospital lockers, believing the transmission of pathogens by HCP attire and carrying attire wrapped around arms.

IMPLICATIONS

Hygiene practices and policies, including a washing facility on the hospital premises, are a must to keep the lab coats clean.

CONCLUSION

HCP should be cautious about the method of use and storage of lab coats they wear.

A Systematic Review and Meta-Analysis of Inpatient Mortality Associated With Nosocomial and Community COVID-19 Exposes the Vulnerability of Immunosuppressed Adults

Background

Little is known about the mortality of hospital-acquired (nosocomial) COVID-19 infection globally. We investigated the risk of mortality and critical care admission in hospitalised adults with nosocomial COVID-19, relative to adults requiring hospitalisation due to community-acquired infection.

Methods

We systematically reviewed the peer-reviewed and pre-print literature from 1/1/2020 to 9/2/2021 without language restriction for studies reporting outcomes of nosocomial and community-acquired COVID-19. We performed a random effects meta-analysis (MA) to estimate the 1) relative risk of death and 2) critical care admission, stratifying studies by patient cohort characteristics and nosocomial case definition.

Results

21 studies were included in the primary MA, describing 8,251 admissions across 8 countries during the first wave, comprising 1513 probable or definite nosocomial COVID-19, and 6738 community-acquired cases. Across all studies, the risk of mortality was 1.3 times greater in patients with nosocomial infection, compared to community-acquired (95% CI: 1.005 to 1.683). Rates of critical care admission were similar between groups (Relative Risk, RR=0.74, 95% CI: 0.50 to 1.08). Immunosuppressed patients diagnosed with nosocomial COVID-19 were twice as likely to die in hospital as those admitted with community-acquired infection (RR=2.14, 95% CI: 1.76 to 2.61).

Conclusions

Adults who acquire SARS-CoV-2 whilst already hospitalised are at greater risk of mortality compared to patients admitted following community-acquired infection; this finding is largely driven by a substantially increased risk of death in individuals with malignancy or who had undergone transplantation. These findings inform public health and infection control policy and argue for individualised clinical interventions to combat the threat of nosocomial COVID-19, particularly for immunosuppressed groups.

Systematic Review Registration

PROSPERO CRD42021249023.

Hospital-acquired influenza in the United States, FluSurv-NET, 2011-2012 through 2018-2019

OBJECTIVE

To estimate population-based rates and to describe clinical characteristics of hospital-acquired (HA) influenza.

DESIGN

Cross-sectional study.

SETTING

US Influenza Hospitalization Surveillance Network (FluSurv-NET) during 2011-2012 through 2018-2019 seasons.

METHODS

Patients were identified through provider-initiated or facility-based testing. HA influenza was defined as a positive influenza test date and respiratory symptom onset >3 days after admission. Patients with positive test date >3 days after admission but missing respiratory symptom onset date were classified as possible HA influenza.

RESULTS

Among 94,158 influenza-associated hospitalizations, 353 (0.4%) had HA influenza. The overall adjusted rate of HA influenza was 0.4 per 100,000 persons. Among HA influenza cases, 50.7% were 65 years of age or older, and 52.0% of children and 95.7% of adults had underlying conditions; 44.9% overall had received influenza vaccine prior to hospitalization. Overall, 34.5% of HA cases received ICU care during hospitalization, 19.8% required mechanical ventilation, and 6.7% died. After including possible HA cases, prevalence among all influenza-associated hospitalizations increased to 1.3% and the adjusted rate increased to 1.5 per 100,000 persons.

CONCLUSIONS

Over 8 seasons, rates of HA influenza were low but were likely underestimated because testing was not systematic. A high proportion of patients with HA influenza were unvaccinated and had severe outcomes. Annual influenza vaccination and implementation of robust hospital infection control measures may help to prevent HA influenza and its impacts on patient outcomes and the healthcare system.

New insights and antimicrobial stewardship opportunities in viral pneumonia: five lung ultrasound cases

Background

Antimicrobial stewardship is crucial to avoid antimicrobial resistance in microbes and adverse drug effects in patients. In respiratory infections, however, viral pneumonia is difficult to distinguish from bacterial pneumonia, which explains the overuse of antibiotic therapy in this indication.

Cases

Five cases of lung consolidation are presented. Lung ultrasound, in conjunction with procalcitonin levels, were used to exclude or corroborate bacterial pneumonia.

Conclusion

Lung ultrasound is easy to learn and perform and is helpful in guiding diagnosis in unclear cases of pneumonia and may also offer new insights into the spectrum of certain virus diseases. The use of lung ultrasound can raise awareness in clinicians of the need for antimicrobial stewardship and may help to avoid the unnecessary use of antibiotics.

Supplementary Information

The online version of this article (10.1007/s00508-021-01946-4) contains supplementary material, which is available to authorized users.

A Meta-Analysis on Evaluation of Nosocomial Infections Amongst Patients in a Tertiary Care Hospital

Background

Hospital-acquired infections, also known as nosocomial infections, are one of the many severe outcomes amongst patients in tertiary care hospitals. Hospital-acquired influenza is amongst the most common infection which has affected huge population.

Objective

We have performed a meta-analysis in order to summarize the effects of epidemiology and clinical characteristics in HAI.

Methods

We performed literature review with help of PubMed, Cochrane Library, Embase, Scopus, Web of Science, China National Knowledge Infrastructure (CNKI), The Global Index Medicus (GIM), and other clinical databases till 2021. Many random models were used in order to obtain pooled proportions, mean difference, odds ratio, and CI.

Results

A total of six studies were analyzed, where a total of 491 nosocomial and 4030 nonnosocomial infection cases were reported. The odds ratio of mortality was 0.02 with 95% CI and the risk ration for males was 1.08 with 95% CI.

Conclusion

The proportion of nosocomial infections in cases of influenza was higher in patients admitted in tertiary care hospitals. Thus, a surveillance system for vaccination for all the high-risk patients must be made mandatory.

Awareness, Attitude, and Current Practices Toward Influenza Vaccination Among Physicians in India: A Multicenter, Cross-Sectional Study

Background: Although annual influenza vaccination is recommended for healthcare providers (HCPs), vaccination rate among HCPs in India is generally low. This cross-sectional survey was conducted to evaluate physicians' awareness, attitude, and current practices toward influenza vaccination in high-risk groups in India.

Methods: The survey was performed in June–July 2020, wherein consulting physicians, pulmonologists, diabetologists, obstetricians/gynecologists, or cardiologists across 14 cities completed a 39-item questionnaire consisting of 3 sections, one each on awareness, attitude, and practice patterns. Descriptive statistics were used to summarize the study results. Statistical analysis was performed for comparison of subgroups by physician specialty, city of practice (metro/non-metro), and zone of practice (north/south/east/west). Level of statistical significance was set at p < 0.05.

Results: In all, 780 physicians completed the survey. Of these, 3.97, 53.08, and 42.95% had high, medium, and low level of awareness about influenza/influenza vaccination, respectively. Statistically significant (p < 0.05) between-group differences were found by physician specialty and zone of practice. In terms of attitude toward vaccination of high-risk group subjects, only 0.9% physicians were “extremely concerned,” while the majority (92.56%) were “quite concerned” and 6.54% were a “little concerned,” with no reported significant differences between different subgroups. With regard to practice patterns, 82.82% of physicians offered influenza vaccines to their patients, 32.69% vaccinated 10–25% of patients per month, and 38.85% required and offered the vaccine to their office staff. Physicians' reasons for not prescribing influenza vaccines to patients included fear of side effects (16.54%), cost (15.64%), lack of awareness about availability (15.38%), absence of belief that it is beneficial (14.36%), history of side effects (13.46%), and patients' fear of needles (11.28%).

Conclusion: These findings suggest the need to implement educational strategies among physicians to enhance their awareness about influenza vaccination and improve their attitudes and current practices toward influenza vaccination especially in high-risk groups in India.

The epidemiological and clinical characteristics of the hospital-acquired influenza infections: A systematic review and meta-analysis

BACKGROUND

The hospital-acquired influenza (HAI) were usually contributed to severe outcomes among the inpatients. Here, we performed a meta-analysis to summarize and quantify the epidemiological and clinical characteristics of HAI.

METHODS

We performed a literature search thorough PubMed, Web of Science, Cochrane Library, Embase, Scopus and China National Knowledge Infrastructure (CNKI), and Wanfang databases for observational studies. Random/fix-effects models were used to obtain pooled proportion, odds ratio (OR), and weighted mean difference (WMD).

RESULTS

A total of 14 studies involving 1483 HAI and 71849 non-hospital-acquired influenza infections (NHAI) cases were included.The proportion of the HAI among the influenza cases was 11.38% (95% confidence interval [CI]: 5.19%-19.55%) and it was increased after 2012 (6.15% vs 12.72%). The HAI cases were significantly older (WMD = 9.51, 95% CI: 0.04-18.98) and the patients with chronic medical diseases were at increased risk of HAI (OR = 1.85, 95% CI: 1.57-2.19). Among them, metabolic disorders (OR = 8.10, 95% CI: 2.46-26.64) ranked the highest danger, followed by malignancy (OR = 3.18, 95% CI: 2.12-4.76), any chronic diseases (OR = 2.81, 95% CI: 1.08-9.31), immunosuppression (OR = 2.13, 95% CI: 1.25-3.64), renal diseases (OR = 1.72, 95% CI:1.40-2.10), heart diseases (OR = 1.52, 95% CI: 1.03-1.44), and diabetes (OR = 1.22, 95% CI: 1.03-1.44). The HAI cases were more likely to experience longer hospital stay (WMD = 10.23, 95% CI: 4.60-15.85) and longer intensive care unit (ICU) stay (WMD = 2.99, 95% CI: 1.50-4.48). In the outcomes within 30 days, those population was still more likely to receive hospitalization (OR = 6.55, 95% CI: 5.19-8.27), death in hospital (OR = 1.99, 95% CI: 1.65-2.40) but less likely to discharged (OR = 0.20, 95% CI: 0.16-0.24).

CONCLUSION

The proportion of the HAI among the influenza cases was relatively high. Reinforcement of the surveillance systems and vaccination of the high-risk patients and their contacts are necessary for the HAI control.

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

BACKGROUND

While hospital-acquired influenza A results in an additional cost burden and considerable mortality in patients, its risk factors are unknown. We aimed to describe the characteristics of patients vulnerable to hospital-acquired influenza A and to identify its risk factors to assist clinicians control hospital-acquired infections and reduce the burden of treatment.

METHODS

A case-control study was conducted among hospitalized patients aged ≥18 years at a tertiary level teaching hospital during the 2018-2019 influenza A season. Patient data were retrieved from hospital-based electronic medical records. Hospital-acquired influenza A was defined as a case of influenza A diagnosed 7 days or more after admission, in a patient with no evidence of influenza A infection on admission. The controls without influenza A were selected among patients exposed to the same setting and time period. We identified risk factors using conditional logistic regression and described the characteristics of hospital-acquired influenza A by comparing the clinical data of infected patients and the controls.

RESULTS

Of the 412 hospitalized patients with influenza A from all the departments in the study hospital, 93 (22.6%) cases were classified as hospital-acquired. The most common comorbidities of the 93 cases were hypertension (41.9%), coronary heart disease (21.5%), and cerebrovascular disease (20.4%). Before the onset of hospital-acquired influenza A, patients presented more lymphocytopenia (51.6% vs 35.5%, P = 0.027), hypoalbuminemia (78.5% vs 57.0%, P = 0.002), and pleural effusion (26.9% vs 9.7%, P = 0.002) than the matched controls. Infected patients also had longer hospital stays (18 days vs 14 days, P = 0.002), and higher mortality rates (10.8% vs 2.2%, P = 0.017) than the matched controls. Lymphocytopenia (odds ratio [OR]: 3.11; 95% confidence interval [CI]: 1.24-7.80; P = 0.016), hypoalbuminemia (OR: 2.24; 95% CI: 1.10-4.57; P = 0.027), and pleural effusion (OR: 3.09; 95% CI: 1.26-7.58; P = 0.014) were independently associated with hospital-acquired influenza A.

CONCLUSIONS

Lymphocytopenia, hypoalbuminemia and pleural effusion are independent risk factors that can help identify patients at high risk of hospital-acquired influenza A, which can extend hospital stay and is associated with a high mortality.

Epidemiological and clinical characteristics of community-acquired and nosocomial influenza cases and risk factors associated with complications: A four season analysis of all adult patients admitted in a tertiary hospital

Background

Information on the characteristics of patients with nosocomial influenza and associated complications is scarce. This study compared epidemiological and clinical characteristics of patients admitted with hospital‐acquired influenza (HAI) to those with community‐acquired influenza (CAI) and analyzed risk factors associated with complications.

Methods

This retrospective, observational study included all adult patients with confirmed influenza virus infection admitted to Son Espases University Hospital during the influenza season in Spain (October to May) from 2012‐2013 to 2015‐2016. Symptom onset before admission was included as CAI, and 2 days after admission or within 48 hours after previous discharge were considered as HAI.

Results

Overall, 666 patients with laboratory‐confirmed influenza were included; 590 (88.6%) and 76 (11.4%) had CAI and HAI, respectively. Baseline characteristics and vaccination rates were similar in both groups. Patients with HAI had significantly fewer symptoms, less radiological alterations, and earlier microbiological diagnosis than those with CAI. Eighty‐five (14.4%) and 20 (27.6%) CAI and HAI patients, respectively, experienced at least one complication, including septic shock, admission to the intensive care unit, mechanical ventilation or evolution to death (any one, P = .003). Univariate and multivariate binary logistic regression was performed to assess independent risk factors associated with the occurrence of complications: nosocomial infection, diabetes, oseltamivir treatment, having received no vaccination, microbiological delay, dyspnea, and the state of confusion were the most important significant factors.

Conclusions

Our study shows the need to implement microbiological diagnostic measures in the first 48 hours to reduce HAI frequency and associated complications.

Preventing infectious diseases in Intensive Care Unit by medical devices remote control: Lessons from COVID-19

The management of COVID-19 patients in the ICUs requires several and prolonged life-support systems (mechanical ventilation, continuous infusions of medications and nutrition, renal replacement therapy). Parameters have to be entered continuously into the device user interface by healthcare personnel according to the dynamic clinical condition. This leads to an increased risk of cross-contamination, use of personal protective equipment and the need for stringent and demanding protocols. Cables and tubing extensions have been utilized to make certain devices usable outside the patient's room but at the cost of introducing further hazards. Remote control of these devices decreases the frequency of unnecessary interventions and reduces the risk of exposure for both patients and healthcare personnel.

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healthcare-associated Infections (including respiratory viral and bacterial infections) are increasing especially in high-risk areas such as ICUs

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the management of critically ill patients requires several and prolonged life-support devices (ventilators, extracorporeal circuits, infusion pumps) increasing the risk of cross-contamination by aerosol, infected organic fluids or direct contact

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remote control of these devices, from a separated control-room, reduces unnecessary personnel biohazard exposure and contacts for both patients and healthcare workers

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bidirectional communication with medical equipment has potential to prevent contamination of patients and medical staff by limiting the spread of infections and allows for time and cost saving due to the reduced need of PPE

Care of patients with liver disease during the COVID-19 pandemic: EASL-ESCMID position paper

The coronavirus disease 2019 (COVID-19) pandemic poses an enormous challenge to healthcare systems in affected communities. Older patients and those with pre-existing medical conditions have been identified as populations at risk of a severe disease course. It remains unclear at this point to what extent chronic liver diseases should be considered as risk factors, due to a shortage of appropriate studies. However, patients with advanced liver disease and those after liver transplantation represent vulnerable patient cohorts with an increased risk of infection and/or a severe course of COVID-19. In addition, the current pandemic requires unusual allocation of healthcare resources which may negatively impact the care of patients with chronic liver disease that continue to require medical attention. Thus, the challenge hepatologists are facing is to promote telemedicine in the outpatient setting, prioritise outpatient contacts, avoid nosocomial dissemination of the virus to patients and healthcare providers, and at the same time maintain standard care for patients who require immediate medical attention.