Association of Surge Conditions with Mortality Among Critically Ill Patients with COVID-19

Measures and Impact of Caseload Surge During the COVID-19 Pandemic: A Systematic Review

OBJECTIVES

COVID-19 pandemic surges strained hospitals globally. We performed a systematic review to examine measures of pandemic caseload surge and its impact on mortality of hospitalized patients.

DATA SOURCES

PubMed, Embase, and Web of Science.

STUDY SELECTION

English-language studies published between December 1, 2019, and November 22, 2023, which reported the association between pandemic "surge"-related measures and mortality in hospitalized patients.

DATA EXTRACTION

Three authors independently screened studies, extracted data, and assessed individual study risk of bias. We assessed measures of surge qualitatively across included studies. Given multidomain heterogeneity, we semiquantitatively aggregated surge-mortality associations.

DATA SYNTHESIS

Of 17,831 citations, we included 39 studies, 17 of which specifically described surge effects in ICU settings. The majority of studies were from high-income countries ( n = 35 studies) and included patients with COVID-19 ( n = 31). There were 37 different surge metrics which were mapped into four broad themes, incorporating caseloads either directly as unadjusted counts ( n = 11), nested in occupancy ( n = 14), including additional factors (e.g., resource needs, speed of occupancy; n = 10), or using indirect proxies (e.g., altered staffing ratios, alternative care settings; n = 4). Notwithstanding metric heterogeneity, 32 of 39 studies (82%) reported detrimental adjusted odds/hazard ratio for caseload surge-mortality outcomes, reporting point estimates of up to four-fold increased risk of mortality. This signal persisted among study subgroups categorized by publication year, patient types, clinical settings, and country income status.

CONCLUSIONS

Pandemic caseload surge was associated with lower survival across most studies regardless of jurisdiction, timing, and population. Markedly variable surge strain measures precluded meta-analysis and findings have uncertain generalizability to lower-middle-income countries (LMICs). These findings underscore the need for establishing a consensus surge metric that is sensitive to capturing harms in everyday fluctuations and future pandemics and is scalable to LMICs.

COVID-19 Admission Rates and Changes in US Hospital Inpatient and Intensive Care Unit Occupancy

Importance

The COVID-19 pandemic had unprecedented effects on hospital occupancy, with consequences for hospital operations and patient care. Previous studies of occupancy during COVID-19 have been limited to small samples of hospitals.

Objective

To measure the association between COVID-19 admission rates and hospital occupancy in different US areas and at different time periods during 2020.

Design, Setting, and Participants

This cross-sectional study used data from the Healthcare Cost and Utilization Project State Inpatient Databases (2019-2020) for patients in nonfederal acute care hospitals in 45 US states, including the District of Columbia. Data analysis was performed between September 1, 2022, and April 30, 2023.

Exposures

Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds (<1 [low], 1-4.9, 5-9.9, 10-14.9, or ≥15 [high]).

Main Outcomes and Measures

The main outcomes were inpatient and intensive care unit (ICU) occupancy. We used regression analysis to estimate the average change in occupancy for each hospital-week in 2020 relative to the same hospital week in 2019.

Results

This study included 3960 hospitals and 54 355 916 admissions. Of the admissions in the 40 states used for race and ethnicity analyses, 15.7% were for Black patients, 12.9% were for Hispanic patients, 62.5% were for White patients, and 7.2% were for patients of other race or ethnicity; 1.7% of patients were missing these data. Weekly COVID-19 admission rates in 2020 were less than 4 per 100 beds for 63.9% of hospital-weeks and at least 10 in only 15.9% of hospital-weeks. Inpatient occupancy decreased by 12.7% (95% CI, 12.1% to 13.4%) during weeks with low COVID-19 admission rates and increased by 7.9% (95% CI, 6.8% to 9.0%) during weeks with high COVID-19 admission rates. Intensive care unit occupancy rates increased by 67.8% (95% CI, 60.5% to 75.3%) during weeks with high COVID-19 admissions. Increases in ICU occupancy were greatest when weighted to reflect the experience of Hispanic patients. Changes in occupancy were most pronounced early in the pandemic. During weeks with high COVID-19 admissions, occupancy decreased for many service lines, with occupancy by surgical patients declining by 43.1% (95% CI, 38.6% to 47.2%) early in the pandemic.

Conclusions and Relevance

In this cross-sectional study of US hospital discharges in 45 states in 2020, hospital occupancy decreased during weeks with low COVID-19 admissions and increased during weeks with high COVID-19 admissions, with the largest changes occurring early in the pandemic. These findings suggest that surges in COVID-19 strained ICUs and were associated with large decreases in the number of surgical patients. These occupancy fluctuations may have affected quality of care and hospital finances.

In Situ Simulation as a Quality Improvement Tool to Identify and Mitigate Latent Safety Threats for Emergency Department SARS-CoV-2 Airway Management: A Multi-Institutional Initiative

BACKGROUND

In situ simulation has emerged as a powerful quality improvement (QI) tool in the identification of latent safety threats (LSTs). Following the first wave of SARS-CoV-2 at an urban epicenter of the disease, a multi-institutional collaborative was formed to integrate an in situ simulation protocol across five emergency departments (EDs) for systems improvement of acute airway management.

METHODS

A prospective, multi-institutional QI initiative using two Plan-Do-Study-Act (PDSA) cycles was implemented across five EDs. Each institution conducted simulations involving mannequins in acute respiratory failure requiring definitive airways. Simulations and systems-based debriefs were standardized. LSTs were collected in an online database, focused on (1) equipment availability, (2) infection control, and (3) communication.

RESULTS

From June 2020 through May 2021, 58 of 70 (82.9%) planned simulations were completed across five sites with 328 unique individual participants. Overall LSTs per simulation (7.00-4.69, p < 0.001) and equipment LSTs (3.00-1.46, p < 0.001) decreased from cycle 1 to cycle 2. Changes in mean LSTs for infection control and communication categories varied among sites. There was no correlation between total LSTs or any of the categories and team size. Number of beds occupied was significantly negatively correlated with total and infection control LSTs.

CONCLUSION

This study was unique in simultaneously running a structured in situ protocol across numerous diverse institutions during a global pandemic. This initiative found similar categories of threats across sites, and the protocol developed empowered participants to implement changes to mitigate identified threats.

Intensive Care and Organ Support Related Mortality in Patients With COVID-19: A Systematic Review and Meta-Analysis

To perform a systematic review and meta-analysis to generate estimates of mortality in patients with COVID-19 that required hospitalization, ICU admission, and organ support.

DATA SOURCES

A systematic search of PubMed, Embase, and the Cochrane databases was conducted up to December 31, 2021.

STUDY SELECTION

Previously peer-reviewed observational studies that reported ICU, mechanical ventilation (MV), renal replacement therapy (RRT) or extracorporeal membrane oxygenation (ECMO)-related mortality among greater than or equal to 100 individual patients.

DATA EXTRACTION

Random-effects meta-analysis was used to generate pooled estimates of case fatality rates (CFRs) for in-hospital, ICU, MV, RRT, and ECMO-related mortality. ICU-related mortality was additionally analyzed by the study country of origin. Sensitivity analyses of CFR were assessed based on completeness of follow-up data, by year, and when only studies judged to be of high quality were included.

DATA SYNTHESIS

One hundred fifty-seven studies evaluating 948,309 patients were included. The CFR for in-hospital mortality, ICU mortality, MV, RRT, and ECMO were 25.9% (95% CI: 24.0-27.8%), 37.3% (95% CI: 34.6-40.1%), 51.6% (95% CI: 46.1-57.0%), 66.1% (95% CI: 59.7-72.2%), and 58.0% (95% CI: 46.9-68.9%), respectively. MV (52.7%, 95% CI: 47.5-58.0% vs 31.3%, 95% CI: 16.1-48.9%; p = 0.023) and RRT-related mortality (66.7%, 95% CI: 60.1-73.0% vs 50.3%, 95% CI: 42.4-58.2%; p = 0.003) decreased from 2020 to 2021.

CONCLUSIONS

We present updated estimates of CFR for patients hospitalized and requiring intensive care for the management of COVID-19. Although mortality remain high and varies considerably worldwide, we found the CFR in patients supported with MV significantly improved since 2020.

Assessment of Symptom, Disability, and Financial Trajectories in Patients Hospitalized for COVID-19 at 6 Months

Importance

Individuals who survived COVID-19 often report persistent symptoms, disabilities, and financial consequences. However, national longitudinal estimates of symptom burden remain limited.

Objective

To measure the incidence and changes over time in symptoms, disability, and financial status after COVID-19-related hospitalization.

Design, Setting, and Participants

A national US multicenter prospective cohort study with 1-, 3-, and 6-month postdischarge visits was conducted at 44 sites participating in the National Heart, Lung, and Blood Institute Prevention and Early Treatment of Acute Lung Injury Network's Biology and Longitudinal Epidemiology: COVID-19 Observational (BLUE CORAL) study. Participants included hospitalized English- or Spanish-speaking adults without severe prehospitalization disabilities or cognitive impairment. Participants were enrolled between August 24, 2020, and July 20, 2021, with follow-up occurring through March 30, 2022.

Exposure

Hospitalization for COVID-19 as identified with a positive SARS-CoV-2 molecular test.

Main Outcomes and Measures

New or worsened cardiopulmonary symptoms, financial problems, functional impairments, perceived return to baseline health, and quality of life. Logistic regression was used to identify factors associated with new cardiopulmonary symptoms or financial problems at 6 months.

Results

A total of 825 adults (444 [54.0%] were male, and 379 [46.0%] were female) met eligibility criteria and completed at least 1 follow-up survey. Median age was 56 (IQR, 43-66) years; 253 (30.7%) participants were Hispanic, 145 (17.6%) were non-Hispanic Black, and 360 (43.6%) were non-Hispanic White. Symptoms, disabilities, and financial problems remained highly prevalent among hospitalization survivors at month 6. Rates increased between months 1 and 6 for cardiopulmonary symptoms (from 67.3% to 75.4%; P = .001) and fatigue (from 40.7% to 50.8%; P < .001). Decreases were noted over the same interval for prevalent financial problems (from 66.1% to 56.4%; P < .001) and functional limitations (from 55.3% to 47.3%; P = .004). Participants not reporting problems at month 1 often reported new symptoms (60.0%), financial problems (23.7%), disabilities (23.8%), or fatigue (41.4%) at month 6.

Conclusions and Relevance

The findings of this cohort study of people discharged after COVID-19 hospitalization suggest that recovery in symptoms, functional status, and fatigue was limited at 6 months, and some participants reported new problems 6 months after hospital discharge.

Surging ICU during COVID-19 pandemic: an overview

PURPOSE OF REVIEW

The coronavirus disease 2019 (COVID-19) pandemic has posed great challenges to intensive care units (ICUs) across the globe. The objective of this review is to provide an overview on how ICU surging was managed during COVID-19 pandemic, with a special focus on papers published in the last 18 months.

RECENT FINDINGS

From the onset of the COVID-19 pandemic, it was apparent that the biggest challenge was the inequity of access to an adequately equipped and staffed ICU bed. The first wave was overwhelming; large surge of patients required critical care, resources were limited and non-COVID-19 care processes were severely compromised. Various approaches were used to address ICU staffing shortage and to expand the physical ICU space capacity. Because of restrictions to family visitations in most ICUs, the pandemic posed a threat to communication and family-centered ICU care. The pandemic, especially during the first wave, was accompanied by a high level of apprehension in the community, many uncertainties about clinical course and therapy and an influx of speculations and misinformation.

SUMMARY

Although healthcare systems learned how to face some of the challenges with subsequent waves, the pandemic had persistent effects on healthcare systems.

Hospital trajectories and early predictors of clinical outcomes differ between SARS-CoV-2 and influenza pneumonia

BACKGROUND

A comparison of pneumonias due to SARS-CoV-2 and influenza, in terms of clinical course and predictors of outcomes, might inform prognosis and resource management. We aimed to compare clinical course and outcome predictors in SARS-CoV-2 and influenza pneumonia using multi-state modelling and supervised machine learning on clinical data among hospitalised patients.

METHODS

This multicenter retrospective cohort study of patients hospitalised with SARS-CoV-2 (March-December 2020) or influenza (Jan 2015-March 2020) pneumonia had the composite of hospital mortality and hospice discharge as the primary outcome. Multi-state models compared differences in oxygenation/ventilatory utilisation between pneumonias longitudinally throughout hospitalisation. Differences in predictors of outcome were modelled using supervised machine learning classifiers.

FINDINGS

Among 2,529 hospitalisations with SARS-CoV-2 and 2,256 with influenza pneumonia, the primary outcome occurred in 21% and 9%, respectively. Multi-state models differentiated oxygen requirement progression between viruses, with SARS-CoV-2 manifesting rapidly-escalating early hypoxemia. Highly contributory classifier variables for the primary outcome differed substantially between viruses.

INTERPRETATION

SARS-CoV-2 and influenza pneumonia differ in presentation, hospital course, and outcome predictors. These pathogen-specific differential responses in viral pneumonias suggest distinct management approaches should be investigated.

FUNDING

This project was supported by NIH/NCATS UL1 TR002345, NIH/NCATS KL2 TR002346 (PGL), the Doris Duke Charitable Foundation grant 2015215 (PGL), NIH/NHLBI R35 HL140026 (CSC), and a Big Ideas Award from the BJC HealthCare and Washington University School of Medicine Healthcare Innovation Lab and NIH/NIGMS R35 GM142992 (PS).