The increasing age of respiratory syncytial virus-related hospitalisation during COVID-19 pandemic in Lyon was associated with reduced hospitalisation costs.

BACKGROUND: Preventive measures applied during the COVID-19 pandemic have modified the age distribution, the clinical severity and the incidence of Respiratory Syncytial Virus (RSV) hospitalisations during the 2020/21 RSV season. The aim of the present study was to estimate the impact of these aspects on RSV-associated hospitalisations (RSVH) costs stratified by age group between pre-COVID-19 seasons and 2020/21 RSV season. METHODS: We compared the incidence, the median costs, and total RSVH costs from the national health insurance perspective in children < 24 months of age during the COVID-19 period (2020/21 RSV season) with a pre-COVID-19 period (2014/17 RSV seasons). Children were born and hospitalised in the Lyon metropolitan area. RSVH costs were extracted from the French medical information system (Programme de Médicalisation des Systémes d'Information). RESULTS: The RSVH-incidence rate per 1000 infants aged < 3 months decreased significantly from 4.6 (95 % CI [4.1; 5.2]) to 3.1 (95 % CI [2.4; 4.0]), and increased in older infants and children up to 24 months of age during the 2020/21 RSV season. Overall, RSVH costs for RSVH cases aged below 2 years old decreased by €201,770 (31 %) during 2020/21 RSV season compared to the mean pre-COVID-19 costs. CONCLUSIONS: The sharp reduction in costs of RSVH in infants aged < 3 months outweighed the modest increase in costs observed in the 3-24 months age group. Therefore, conferring a temporal protection through passive immunisation to infants aged < 3 months should have a major impact on RSVH costs even if it results in an increase of RSVH in older children infected later in life. Nevertheless, stakeholders should be aware of this potential increase of RSVH in older age groups presenting with a wider range of disease to avoid any bias in estimating the cost-effectiveness of passive immunisation strategies.

Excess mortality among non-COVID-19 surgical patients attributable to the exposure of French intensive and intermediate care units to the pandemic.

PURPOSE: The mobilization of most available hospital resources to manage coronavirus disease 2019 (COVID-19) may have affected the safety of care for non-COVID-19 surgical patients due to restricted access to intensive or intermediate care units (ICU/IMCUs). We estimated excess surgical mortality potentially attributable to ICU/IMCUs overwhelmed by COVID-19, and any hospital learning effects between two successive pandemic waves. METHODS: This nationwide observational study included all patients without COVID-19 who underwent surgery in France from 01/01/2019 to 31/12/2020. We determined pandemic exposure of each operated patient based on the daily proportion of COVID-19 patients among all patients treated within the ICU/IMCU beds of the same hospital during his/her stay. Multilevel models, with an embedded triple-difference analysis, estimated standardized in-hospital mortality and compared mortality between years, pandemic exposure groups, and semesters, distinguishing deaths inside or outside the ICU/IMCUs. RESULTS: Of 1,870,515 non-COVID-19 patients admitted for surgery in 655 hospitals, 2% died. Compared to 2019, standardized mortality increased by 1% (95% CI 0.6-1.4%) and 0.4% (0-1%) during the first and second semesters of 2020, among patients operated in hospitals highly exposed to pandemic. Compared to the low-or-no exposure group, this corresponded to a higher risk of death during the first semester (adjusted ratio of odds-ratios 1.56, 95% CI 1.34-1.81) both inside (1.27, 1.02-1.58) and outside the ICU/IMCU (1.98, 1.57-2.5), with a significant learning effect during the second semester compared to the first (0.76, 0.58-0.99). CONCLUSION: Significant excess mortality essentially occurred outside of the ICU/IMCU, suggesting that access of surgical patients to critical care was limited.

Additional value of chest CT AI-based quantification of lung involvement in predicting death and ICU admission for COVID-19 patients.

Objectives: We evaluated the contribution of lung lesion quantification on chest CT using a clinical Artificial Intelligence (AI) software in predicting death and intensive care units (ICU) admission for COVID-19 patients. Methods: For 349 patients with positive COVID-19-PCR test that underwent a chest CT scan at admittance or during hospitalization, we applied the AI for lung and lung lesion segmentation to obtain lesion volume (LV), and LV/Total Lung Volume (TLV) ratio. ROC analysis was used to extract the best CT criterion in predicting death and ICU admission. Two prognostic models using multivariate logistic regressions were constructed to predict each outcome and were compared using AUC values. The first model ("Clinical") was based on patients' characteristics and clinical symptoms only. The second model ("Clinical+LV/TLV") included also the best CT criterion. Results: LV/TLV ratio demonstrated best performance for both outcomes; AUC of 67.8% (95% CI: 59.5 - 76.1) and 81.1% (95% CI: 75.7 - 86.5) respectively. Regarding death prediction, AUC values were 76.2% (95% CI: 69.9 - 82.6) and 79.9% (95%IC: 74.4 - 85.5) for the "Clinical" and the "Clinical+LV/TLV" models respectively, showing significant performance increase (+ 3.7%; p-value<0.001) when adding LV/TLV ratio. Similarly, for ICU admission prediction, AUC values were 74.9% (IC 95%: 69.2 - 80.6) and 84.8% (IC 95%: 80.4 - 89.2) respectively corresponding to significant performance increase (+ 10%: p-value<0.001). Conclusions: Using a clinical AI software to quantify the COVID-19 lung involvement on chest CT, combined with clinical variables, allows better prediction of death and ICU admission.

Impact of the COVID-19 pandemic on non-COVID-19 hospital mortality in patients with schizophrenia: a nationwide population-based cohort study.

It remains unknown to what degree resource prioritization toward SARS-CoV-2 (2019-nCoV) coronavirus (COVID-19) cases had disrupted usual acute care for non-COVID-19 patients, especially in the most vulnerable populations such as patients with schizophrenia. The objective was to establish whether the impact of the COVID-19 pandemic on non-COVID-19 hospital mortality and access to hospital care differed between patients with schizophrenia versus without severe mental disorder. We conducted a nationwide population-based cohort study of all non-COVID-19 acute hospitalizations in the pre-COVID-19 (March 1, 2019 through December 31, 2019) and COVID-19 (March 1, 2020 through December 31, 2020) periods in France. We divided the population into patients with schizophrenia and age/sex-matched patients without severe mental disorder (1:10). Using a difference-in-differences approach, we performed multivariate patient-level logistic regression models (adjusted odds ratio, aOR) with adjustment for complementary health insurance, smoking, alcohol and substance addiction, Charlson comorbidity score, origin of the patient, category of care, intensive care unit (ICU) care, major diagnosis groups and hospital characteristics. A total of 198,186 patients with schizophrenia were matched with 1,981,860 controls. The 90-day hospital mortality in patients with schizophrenia increased significantly more versus controls (aOR = 1.18; p < 0.001). This increased mortality was found for poisoning and injury (aOR = 1.26; p = 0.033), respiratory diseases (aOR = 1.19; p = 0.008) and for both surgery (aOR = 1.26; p = 0.008) and medical care settings (aOR = 1.16; p = 0.001). Significant changes in the case mix were noted with reduced admission in the ICU and for several somatic diseases including cancer, circulatory and digestive diseases and stroke for patients with schizophrenia compared to controls. These results suggest a greater deterioration in access to, effectiveness and safety of non-COVID-19 acute care in patients with schizophrenia compared to patients without severe mental disorders. These findings question hospitals' resilience pertaining to patient safety and underline the importance of developing specific strategies for vulnerable patients in anticipation of future public health emergencies.

Undernourished patients do not have increased risk of severe COVID-19 outcomes.

Background: Undernutrition has been previously identified as a deleterious factor in acute infections. In covid-19 infection, obesity is a risk-factor of severe evolution, but initial undernutrition has not been evaluated yet. Methods: We retrospectively analyzed correlation between nutritional status at admission and severe outcomes (intensive care unit admission, invasive mechanical ventilation requirement and death) of patients hospitalized for confirmed covid-19 infection. Results: Risk of intensive care unit admission and invasive mechanical ventilation requirement was not significantly different between undernutrition and normoweight sub-groups, but increased in excessive weight sub-group (ODDR (IC 95%) 1.048 (1.011-1.086), p = 0.011). Risk of death was the same in all sub-groups. Conclusion: Undernutrition didn't appear as a factor of severe outcomes in covid-19 infection.

Case fatality inequalities of critically ill COVID-19 patients according to patient-, hospital- and region-related factors: a French nationwide study.

BACKGROUND: The COVID-19 sanitary crisis inflicted different challenges regarding the reorganization of the human and logistic resources, particularly in intensive care unit (ICU). Interdependence between regional pandemic burden and individual outcome remains unknown. The study aimed to assess the association between ICU bed occupancy and case fatality rate of critically ill COVID-19 patients. METHODS: A cross-sectional study was performed in France, using the national hospital discharge database from March to May, 2020. All patients admitted to ICU for COVID-19 were included. Case fatality was described according to: (i) patient's characteristics (age, sex, comorbid conditions, ICU interventions); (ii) hospital's characteristics (baseline ICU experience assessed by the number of ICU stays in 2019, number of ICU physicians per bed), and (iii) the regional outbreak-related profiles (workload indicator based on ICU bed occupancy). The determinants of lethal outcome were identified using a logistic regression model. RESULTS: 14,513 COVID-19 patients were admitted to ICU; 4256 died (29.3%), with important regional inequalities in case fatality (from 17.6 to 33.5%). Older age, multimorbidity and clinical severity were associated with higher mortality, as well as a lower baseline ICU experience of the health structure. Regions with more than 10 days with ≥ 75% of ICU occupancy by COVID-19 patients experienced an excess of mortality (up to adjusted OR = 2.2 [1.9-2.6] for region with the highest occupancy rate of ICU beds). CONCLUSIONS: The regions with the highest burden of care in ICU were associated with up to 2.2-fold increase of death rate.

Mortality Among Noncoronavirus Disease 2019 Critically Ill Patients Attributable to the Pandemic in France.

OBJECTIVES: We investigated whether the risk of death among noncoronavirus disease 2019 critically ill patients increased when numerous coronavirus disease 2019 cases were admitted concomitantly to the same hospital units. DESIGN: We performed a nationwide observational study based on the medical information system from all public and private hospitals in France. SETTING: Information pertaining to every adult admitted to ICUs or intermediate care units from 641 hospitals between January 1, 2020, and June 30, 2020 was analyzed. PATIENTS: A total of 454,502 patients (428,687 noncoronavirus disease 2019 and 25,815 coronavirus disease 2019 patients) were included. INTERVENTIONS: For each noncoronavirus disease 2019 patient, pandemic exposure during their stay was calculated per day using the proportion of coronavirus disease 2019 patients among all patients treated in ICU. MEASUREMENTS AND MAIN RESULTS: We computed a multivariable logistic regression model to estimate the influence of pandemic exposure (low, moderate, and high exposure) on noncoronavirus disease 2019 patient mortality during ICU stay. We adjusted on patient and hospital confounders. The risk of death among noncoronavirus disease 2019 critically ill patients increased in case of moderate (adjusted odds ratio, 1.12; 95% CI, 1.05-1.19; p < 0.001) and high pandemic exposures (1.52; 95% CI, 1.33-1.74; p < 0.001). CONCLUSIONS: In hospital units with moderate or high levels of coronavirus disease 2019 critically ill patients, noncoronavirus disease deaths were at higher levels.