Impact of ICU transfers on the mortality rate of patients with COVID-19: insights from comprehensive national database in France

Interfacility transfer of the critically ill: Transfer status does not influence survival

PURPOSE

To estimate differences in case-mix adjusted hospital mortality between adult ICU patients who are transferred during their ICU-stay and those who are not.

METHODS

19,260 visits to 12 ICUs in Nova Scotia (NS), Canada April 2018-September 2023 were analyzed. Data were obtained from the NS Provincial ICU database. Generalized additive models (GAMs) were used to estimate differences in case-mix adjusted hospital mortality between patients who underwent transfer and those who did not.

RESULTS

1040/19,260 (5%) ICU visits involved interfacility-transfer. No difference in hospital mortality was identified between transferred and non-transferred patients by GAM (OR, 0.99, 95% CI, 0.82 to 1.19; p = 0.91). No mortality difference was observed between patients undergoing a single transfer versus multiple (OR, 0.87; 95% CI, 0.45 to -1.69; p = 0.68). A GAM including the categories no transfer, one transfer, and multiple transfers identified a difference in hospital mortality for patients that underwent multiple transfers compared to non-transferred patients (OR, 0.68; 95% CI, 0.46 to 1.00, p = 0.05), but no difference was identified in a post-hoc matched cohort sensitivity analysis (OR, 0.68; 95% CI, 0.46 to 1.01, p = 0.05).

CONCLUSION

The transfer of critically ill patients between ICUs in Nova Scotia did not impact case-mix adjusted hospital mortality.

Effect of the Implementation of the French Hospital Regionalization Policy on Patient Mobility

A new law was voted in France in 2016 to increase cooperation between public sector hospitals. Hospitals were encouraged to work under the leadership of local referral centers and to share their support functions (e.g., information systems) with newly created hospital groups, called "Regional Hospital Groups." The law made it compulsory for each public sector hospital to become affiliated with one of 136 newly created hospital groups. The policy's aim was to ensure that all patients were sent to the hospital best qualified to treat their unique condition, among the hospitals available at the regional level. Therefore, we aimed to assess whether this regionalization policy was associated with changes in observed patterns of patient mobility between hospitals. This nationwide observational study followed an interrupted time series design. For each stay occurring from 2014 to 2019, we ascertained whether or not the stay was followed by mobility toward another hospital within 90 days, and whether or not the receiving hospital was part of the same Regional Hospital Group as the sender hospital. The proportion of mobility directed toward the same regional hospital group increased from 22.9% in 2014 (95% CI 22.7-23.1) to 24.6% in 2019 (95% CI 24.4-24.8). However, the absence of discontinuity during the policy change year was consistent with the hypothesis of a preexisting trend toward regionalization. Therefore, the policy did not achieve major changes in patterns of mobility between hospitals. Other objectives of the reform, including long-term consequences on the healthcare offer, remain to be assessed.

Forecasting local hospital bed demand for COVID-19 using on-request simulations

Accurate forecasting of hospital bed demand is crucial during infectious disease epidemics to avoid overwhelming healthcare facilities. To address this, we developed an intuitive online tool for individual hospitals to forecast COVID-19 bed demand. The tool utilizes local data, including incidence, vaccination, and bed occupancy data, at customizable geographical resolutions. Users can specify their hospital's catchment area and adjust the initial number of COVID-19 occupied beds. We assessed the model's performance by forecasting ICU bed occupancy for several university hospitals and regions in Germany. The model achieves optimal results when the selected catchment area aligns with the hospital's local catchment. While expanding the catchment area reduces accuracy, it improves precision. However, forecasting performance diminishes during epidemic turning points. Incorporating variants of concern slightly decreases precision around turning points but does not significantly impact overall bed occupancy results. Our study highlights the significance of using local data for epidemic forecasts. Forecasts based on the hospital's specific catchment area outperform those relying on national or state-level data, striking a better balance between accuracy and precision. These hospital-specific bed demand forecasts offer valuable insights for hospital planning, such as adjusting elective surgeries to create additional bed capacity promptly.

Critical care and pandemic preparedness and response

Critical care was established partially in response to a polio epidemic in the 1950s. In the intervening 70 yr, several epidemics and pandemics have placed critical care and allied services under extreme pressure. Pandemics cause wholesale changes to accepted standards of practice, require reallocation and retargeting of resources and goals of care. In addition to clinical acumen, mounting an effective critical care response to a pandemic requires local, national, and international coordination in a diverse array of fields from research collaboration and governance to organisation of critical care networks and applied biomedical ethics in the eventuality of triage situations. This review provides an introduction to an array of topics that pertain to different states of pandemic acuity: interpandemic preparedness, alert, surge activity, recovery and relapse through the literature and experience of recent pandemics including COVID-19, H1N1, Ebola, and SARS.

The association of intensive care capacity transfers with survival in COVID-19 patients from a Scottish district general hospital: A retrospective cohort study

Background: During the second wave of COVID-19 cases within Scotland, local evidence suggested that a large number of interhospital transfers occurred due to both physical capacity and staff shortages. Although there are inherent risks with transferring critically ill patients between hospitals, there are signals in the literature that mortality is not affected in COVID-19 patients when transferred between intensive care units. With a lack of evidence in the Scottish population, and as the greatest source of capacity transfers in our critical care network at that time, we sought to determine whether these transfers impacted on survival to hospital discharge.Methods: We conducted a retrospective cohort study of all patients admitted to our unit between the 1st October 2020 and the 31st March 2021 with a primary diagnosis of COVID-19 pneumonia. Patients were grouped according to whether they underwent an interhospital capacity transfer or not, either for unit shortage of beds or unit shortage of staff. The primary outcome measure was survival to ultimate hospital discharge, and secondary outcomes included total ventilator days and total intensive care unit length of stay. Baseline characteristic data were also collected for all patients. Survival data were entered into a backward stepwise logistic regression analysis that included transfer status, and coefficients transformed into odds ratios and 95% confidence intervals.Results: A total of 108 patients were included. Of these, 30 were transferred to another intensive care unit due to capacity issues at the base hospital. From the baseline characteristic data, age was significantly higher in those transferred out, while other characteristics were similar. Unadjusted mortality rates were 30.8% for those not transferred, and 40% for those transferred out. However, when entered into a logistic regression analysis to attempt to control for confounders in the baseline characteristics, being transferred had an odds ratio of 1.14 (95% confidence interval 0.43-3.1) for survival to hospital discharge. Total ventilator days and total ICU length of stay were both higher in the transferred patients.Conclusion: This unique study of COVID-19 patients transferred from a Scottish district general hospital did not show an association between transfer status and survival to hospital discharge. However, the study was likely underpowered to detect small differences. As the situation continues to evolve, a prospective regional multi-centre study may help to provide more robust findings.

The positive impact of COVID-19 on critical care: from unprecedented challenges to transformative changes, from the perspective of young intensivists

Over the past 2 years, SARS-CoV-2 infection has resulted in numerous hospitalizations and deaths worldwide. As young intensivists, we have been at the forefront of the fight against the COVID-19 pandemic and it has been an intense learning experience affecting all aspects of our specialty. Critical care was put forward as a priority and managed to adapt to the influx of patients and the growing demand for beds, financial and material resources, thereby highlighting its flexibility and central role in the healthcare system. Intensivists assumed an essential and unprecedented role in public life, which was important when claiming for indispensable material and human investments. Physicians and researchers around the world worked hand-in-hand to advance research and better manage this disease by integrating a rapidly growing body of evidence into guidelines. Our daily ethical practices and communication with families were challenged by the massive influx of patients and restricted visitation policies, forcing us to improve our collaboration with other specialties and innovate with new communication channels. However, the picture was not all bright, and some of these achievements are already fading over time despite the ongoing pandemic and hospital crisis. In addition, the pandemic has demonstrated the need to improve the working conditions and well-being of critical care workers to cope with the current shortage of human resources. Despite the gloomy atmosphere, we remain optimistic. In this ten-key points review, we outline our vision on how to capitalize on the lasting impact of the pandemic to face future challenges and foster transformative changes of critical care for the better.

Inter-hospital transfer and clinical outcomes for people with COVID-19 admitted to intensive care units in Australia: an observational cohort study

OBJECTIVES

To examine the association between inter-hospital transfer and in-hospital mortality among people with coronavirus disease 2019 (COVID-19) admitted to intensive care units (ICUs) in Australia.

DESIGN

Retrospective cohort study; analysis of data collected for the Short Period Incidence Study of Severe Acute Respiratory Illness (SPRINT-SARI) Australia study.

SETTING, PARTICIPANTS

People with COVID-19 admitted to 63 ICUs, 1 January 2020 - 1 April 2022.

MAIN OUTCOME MEASURES

Primary outcome: in-hospital mortality; secondary outcomes: ICU and hospital lengths of stay and frequency of selected complications.

RESULTS

Of 5207 people with records in the SPRINT-SARI Australia database at 1 April 2022, 328 (6.3%) had been transferred between hospitals, 305 (93%) during the third pandemic wave. Compared with patients not transferred, their median age was lower (53 years; interquartile range [IQR], 45-61 years v 60 years; IQR, 46-70 years), their median body mass index higher (32.5 [IQR, 27.2-39.0] kg/m² v 30.1 [IQR, 25.7-35.7] kg/m² ), and fewer had received a COVID-19 vaccine (22% v 44.9%); their median APACHE II scores were similar (14.0; IQR, 12.0-18.0 v 14.0; IQR, 10.0-19.0). Bacterial pneumonia (64.7% v 29.0%) and bacteraemia (27% v 8%) were more frequent in transferred patients, as was the need for more intensive ICU interventions, including invasive mechanical ventilation (71.2% v 38.1%) and extra-corporeal membrane oxygenation (26% v 1.7%). Crude ICU (19% v 14.9%) and in-hospital mortality (19% v 18.4%) were similar for patients who were or were not transferred; median lengths of ICU (20.0 [IQR, 11.2-40.3] days v 4.6 [IQR, 2.1-10.1] days) and hospital stay (29.7 [IQR, 18.1-49.6] days v 12.3 [IQR, 7.3-21.0] days) were longer for transferred patients. In the multivariable regression analysis, in-hospital mortality risk was lower for transferred patients (risk difference [RD], -5.0 percentage points; 95% confidence interval [CI] -10 to -0.03 percentage points), but not in the propensity score-adjusted analysis (RD, -3.4 [95% CI, -8.9 to 2.1] percentage points).

CONCLUSIONS

Among people with COVID-19 admitted to ICUs, patients transferred from another hospital required more intense interventions and remained in hospital longer, but were not at greater risk of dying in hospital than the patients who were not transferred.

Avdoralimab (Anti-C5aR1 mAb) Versus Placebo in Patients With Severe COVID-19: Results From a Randomized Controlled Trial (FOR COVID Elimination [FORCE])

OBJECTIVES

Severe COVID-19 is associated with exaggerated complement activation. We assessed the efficacy and safety of avdoralimab (an anti-C5aR1 mAb) in severe COVID-19.

DESIGN

FOR COVID Elimination (FORCE) was a double-blind, placebo-controlled study.

SETTING

Twelve clinical sites in France (ICU and general hospitals).

PATIENTS

Patients receiving greater than or equal to 5 L oxygen/min to maintain Sp o2 greater than 93% (World Health Organization scale ≥ 5). Patients received conventional oxygen therapy or high-flow oxygen (HFO)/noninvasive ventilation (NIV) in cohort 1; HFO, NIV, or invasive mechanical ventilation (IMV) in cohort 2; and IMV in cohort 3.

INTERVENTIONS

Patients were randomly assigned, in a 1:1 ratio, to receive avdoralimab or placebo. The primary outcome was clinical status on the World Health Organization ordinal scale at days 14 and 28 for cohorts 1 and 3, and the number of ventilator-free days at day 28 (VFD28) for cohort 2.

MEASUREMENTS AND MAIN RESULTS

We randomized 207 patients: 99 in cohort 1, 49 in cohort 2, and 59 in cohort 3. During hospitalization, 95% of patients received glucocorticoids. Avdoralimab did not improve World Health Organization clinical scale score on days 14 and 28 (between-group difference on day 28 of -0.26 (95% CI, -1.2 to 0.7; p = 0.7) in cohort 1 and -0.28 (95% CI, -1.8 to 1.2; p = 0.6) in cohort 3). Avdoralimab did not improve VFD28 in cohort 2 (between-group difference of -6.3 (95% CI, -13.2 to 0.7; p = 0.96) or secondary outcomes in any cohort. No subgroup of interest was identified.

CONCLUSIONS

In this randomized trial in hospitalized patients with severe COVID-19 pneumonia, avdoralimab did not significantly improve clinical status at days 14 and 28 (funded by Innate Pharma, ClinicalTrials.gov number, NCT04371367).