Variation in COVID-19 Mortality Across 117 US Hospitals in High- and Low-Burden Settings

Did COVID-19 ICU patient mortality risk increase as Colorado hospitals filled? A retrospective cohort study

OBJECTIVES

To assess whether increasing levels of hospital stress-measured by intensive care unit (ICU) bed occupancy (primary), ventilators in use and emergency department (ED) overflow-were associated with decreasing COVID-19 ICU patient survival in Colorado ICUs during the pre-Delta, Delta and Omicron variant eras.

DESIGN

A retrospective cohort study using discrete-time survival models, fit with generalised estimating equations.

SETTING

34 hospital systems in Colorado, USA, with the highest patient volume ICUs during the COVID-19 pandemic.

PARTICIPANTS

9196 non-paediatric SARS-CoV-2 patients in Colorado hospitals admitted once to an ICU between 1 August 2020 and 1 March 2022 and followed for 28 days.

OUTCOME MEASURES

Death or discharge to hospice.

RESULTS

For Delta-era COVID-19 ICU patients in Colorado, the odds of death were estimated to be 26% greater for patients exposed every day of their ICU admission to a facility experiencing its all-era 75th percentile ICU fullness or above, versus patients exposed for none of their days (OR: 1.26; 95% CI: 1.04 to 1.54; p=0.0102), adjusting for age, sex, length of ICU stay, vaccination status and hospital quality rating. For both Delta-era and Omicron-era patients, we also detected significantly increased mortality hazard associated with high ventilator utilisation rates and (in a subset of facilities) states of ED overflow. For pre-Delta-era patients, we estimated relatively null or even protective effects for the same fullness exposures, something which provides a meaningful contrast to previous studies that found increased hazards but were limited to pre-Delta study windows.

CONCLUSIONS

Overall, and especially during the Delta era (when most Colorado facilities were at their fullest), increasing exposure to a fuller hospital was associated with an increasing mortality hazard for COVID-19 ICU patients.

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.

Mortality for Time-Sensitive Conditions at Urban vs Rural Hospitals During the COVID-19 Pandemic

Importance

COVID-19 pandemic-related disruptions to the health care system may have resulted in increased mortality for patients with time-sensitive conditions.

Objective

To examine whether in-hospital mortality in hospitalizations not related to COVID-19 (non-COVID-19 stays) for time-sensitive conditions changed during the pandemic and how it varied by hospital urban vs rural location.

Design, Setting, and Participants

This cohort study was an interrupted time-series analysis to assess in-hospital mortality during the COVID-19 pandemic (March 8, 2020, to December 31, 2021) compared with the prepandemic period (January 1, 2017, to March 7, 2020) overall, by month, and by community COVID-19 transmission level for adult discharges from 3813 US hospitals in the State Inpatient Databases for the Healthcare Cost and Utilization Project.

Exposure

The COVID-19 pandemic.

Main Outcomes and Measures

The main outcome measure was in-hospital mortality among non-COVID-19 stays for 6 time-sensitive medical conditions: acute myocardial infarction, hip fracture, gastrointestinal hemorrhage, pneumonia, sepsis, and stroke. Entropy weights were used to align patient characteristics in the 2 time periods by age, sex, and comorbidities.

Results

There were 18 601 925 hospitalizations; 50.3% of patients were male, 38.5% were aged 18 to 64 years, 45.0% were aged 65 to 84 years, and 16.4% were 85 years or older for the selected time-sensitive medical conditions from 2017 through 2021. The odds of in-hospital mortality for sepsis increased 27% from the prepandemic to the pandemic periods at urban hospitals (odds ratio [OR], 1.27; 95% CI, 1.25-1.29) and 35% at rural hospitals (OR, 1.35; 95% CI, 1.30-1.40). In-hospital mortality for pneumonia had similar increases at urban (OR, 1.48; 95% CI, 1.42-1.54) and rural (OR, 1.46; 95% CI, 1.36-1.57) hospitals. Increases in mortality for these 2 conditions showed a dose-response association with the community COVID-19 level (low vs high COVID-19 burden) for both rural (sepsis: 22% vs 54%; pneumonia: 30% vs 66%) and urban (sepsis: 16% vs 28%; pneumonia: 34% vs 61%) hospitals. The odds of mortality for acute myocardial infarction increased 9% (OR, 1.09; 95% CI, 1.06-1.12) at urban hospitals and was responsive to the community COVID-19 level. There were significant increases in mortality for hip fracture at rural hospitals (OR, 1.32; 95% CI, 1.14-1.53) and for gastrointestinal hemorrhage at urban hospitals (OR, 1.15; 95% CI, 1.09-1.21). No significant change was found in mortality for stroke overall.

Conclusions and Relevance

In this cohort study, in-hospital mortality for time-sensitive conditions increased during the COVID-19 pandemic. Mobilizing strategies tailored to the different needs of urban and rural hospitals may help reduce the likelihood of excess deaths during future public health crises.

Characteristics and Outcomes of Stem Cell Transplant Patients during the COVID-19 Era: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis aims to identify the outcomes of stem cell transplant (SCT) patients during the COVID-19 era. Pooled event rates (PER) were calculated, and meta-regression was performed. A random effects model was utilized. In total, 36 eligible studies were included out of 290. The PER of COVID-19-related deaths and COVID-19-related hospital admissions were 21.1% and 55.2%, respectively. The PER of the use of hydroxychloroquine was 53.27%, of the receipt of immunosuppression it was 39.4%, and of the use of antivirals, antibiotics, and steroids it was 71.61%, 37.94%, and 18.46%, respectively. The PER of the time elapsed until COVID-19 infection after SCT of more than 6 months was 85.3%. The PER of fever, respiratory symptoms, and gastrointestinal symptoms were 70.9, 76.1, and 19.3%, respectively. The PER of acute and chronic GvHD were 40.2% and 60.9%, respectively. SCT patients are at a higher risk of severe COVID-19 infection and mortality. The use of dexamethasone improves the survival of hospitalized SCT patients with moderate to severe COVID-19 requiring supplemental oxygen or ventilation. The SCT patient group is a heterogeneous group with varying characteristics. The quality of reporting on these patients when infected with COVID-19 is not uniform and further prospective or registry studies are needed to better guide clinical care in this unique setting.

Inter-hospital Variation in COVID-19 Era Pediatric Hospitalizations by Age Group and Diagnosis

BACKGROUND

Mitigation strategies and public responses to coronavirus disease 2019 (COVID-19) varied geographically and may have differentially affected burden of pediatric disease and hospitalization practices. We aimed to quantify hospital-specific variation in hospitalizations during the COVID-19 era.

METHODS

Using Pediatric Health Information Systems data from 44 Children's Hospitals, this retrospective multicenter analysis compared hospitalizations of children (1 day-17 years) from the COVID-19 era (March 1, 2020-June 30, 2021) to prepandemic (January 1, 2017-December 31, 2019). Variation in the magnitude of hospital-specific decline between eras was determined using coefficients of variation (CV). Spearman's test was used to assess correlation of variation with community and hospital factors.

RESULTS

The COVID-19 era decline in hospitalizations varied between hospitals (CV 0.41) and was moderately correlated with declines in respiratory infection hospitalizations (r = 0.69, P < .001). There was no correlation with community or hospital factors. COVID-19 era changes in hospitalizations for mental health conditions varied widely between centers (CV 2.58). Overall, 22.7% of hospitals saw increased admissions for adolescents, and 29.5% saw increases for newborns 1 to 14 days, representing significant center-specific variation (CV 2.30 for adolescents and 1.98 for newborns).

CONCLUSIONS

Pandemic-era change in hospitalizations varied across institutions, partially because of hospital-specific changes in respiratory infections. Residual variation exists for mental health conditions and in groups least likely to be admitted for respiratory infections, suggesting that noninfectious conditions may be differentially and uniquely affected by local policies and hospital-specific practices enacted during the COVID-19 era.

Variation in Hospitalization Costs, Charges, and Lengths of Hospital Stay for Coronavirus Disease 2019 Patients Treated With Venovenous Extracorporeal Membrane Oxygenation in the United States: A Cohort Study

OBJECTIVES

The aim was to characterize hospitalization costs, charges, and lengths of hospital stay for COVID-19 patients treated with venovenous (VV) extracorporeal membrane oxygenation (ECMO) in the United States during 2020. Secondarily, differences in hospitalization costs, charges, and lengths of hospital stay were explored based on hospital-level factors.

DESIGN

Retrospective cohort study.

SETTING

Multiple hospitals in the United States.

PARTICIPANTS

Adult patients with COVID-19 who were on VV ECMO in 2020 and had data in the national inpatient sample.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Demographics and baseline comorbidities were recorded for patients. Primary study outcomes were hospitalization costs, charges, and lengths of hospital stay. Study outcomes were compared after stratification by hospital region, bed size, and for-profit status. The median hospitalization cost for the 3,315-patient weighted cohort was $200,300 ($99,623, $338,062). Median hospitalization charges were $870,513 ($438,228, $1,553,157), and the median length of hospital stay was 30 days (17, 46). Survival to discharge was 54.4% for all patients in the cohort. Median hospitalization cost differed by region (p = 0.01), bed size (p < 0.001), and for-profit status (p = 0.02). Median hospitalization charges also differed by region (p = 0.04), bed size (p = 0.002), and for-profit status (p < 0.001). Length of hospital stay differed by region (p = 0.03) and bed size (p < 0.001), but not for-profit status (p = 0.40). Hospitalization costs were the lowest, and charges were highest in private-for-profit hospitals. Large hospitals also had higher costs, charges, and hospital stay lengths than small hospitals.

CONCLUSIONS

In this retrospective cohort study, hospitalization costs and charges for patients with COVID-19 on VV ECMO were found to be substantial but similar to what has been reported previously for patients without COVID-19 on VV ECMO. Significant variation was observed in costs, charges, and lengths of hospital stay based on hospital-level factors.

Changes in Poison Center Calls for Intentional Exposure During Public Health Emergencies: COVID-19 and Winter Storm Uri in Dallas County, Texas

OBJECTIVE

This study aimed to: (1) explore changes in the volume of calls to poison control centers (PCs) for intentional exposures (IEs) in Dallas County, Texas, overall and by gender and age, and (2) examine the association between 2 different public health emergencies (PHEs) and changes in IE call volume.

METHODS

PCs categorize calls they receive by intentionality of the exposure, based on information from the caller. We analyzed data on PC calls categorized as intentional in Dallas County, Texas, from March 2019 - April 2021. This period includes the COVID-19 pandemic declaration (March 2020), a surge in COVID-19 cases (July 2020), and Winter Storm Uri (February 2021). Changes in IE call volume (overall and by age and gender), were explored, and interrupted time series analysis was used to examine call volume changes after PHE onset.

RESULTS

The summer surge in COVID-19 cases was associated with 1.9 additional IE calls/day (95% CI 0.7 to 3.1), in the context of a baseline unadjusted mean of 6.2 calls per day (unadjusted) before November 3, 2020. Neither the pandemic declaration nor Winter Storm Uri was significantly associated with changes in call volume. Women, on average, made 1.2 more calls per day compared to men during the study period. IE calls for youth increased after the pandemic declaration, closing the longstanding gap between adults and youth by early 2021.

CONCLUSIONS

Changes in IE call volume in Dallas County varied by gender and age. Calls increased during the local COVID-19 surge. Population-level behavioral health may be associated with local crisis severity.

The impact of key secular trends during the first three waves the COVID-19 pandemic

IMPORTANCE

Patient age, comorbidity burden, and disease severity at presentation are the major factors associated with surviving COVID-19. Hospital-level factors including ICU occupancy may confer additional risk to individual patients, particularly at times of maximal stress on healthcare systems. The interaction of patient- and hospital-level factors over time during pandemic disease remains an area of active exploration.

OBJECTIVE

To determine the impact of patient and hospital risk factors during episodic surges, characterize severity distribution between waves, and evaluate patient-level impact of ICU capacity on COVID-19 survivorship.

DESIGN

Retrospective cohort study.

SETTING

Four acute care hospitals within an integrated healthcare network in San Diego, California.

PARTICIPANTS

All patients (18+ y.o.) admitted with a positive PCR test for SARS-CoV-2 or ICD-10 code for COVID-19 from March 1, 2020 through June 30, 2021.

MAIN OUTCOME(S) AND MEASURE(S)

Patient survivorship and length of stay.

RESULTS

Six thousand eight hundred fifty-one patients were evaluated in this large cohort series. Patient level factors associated with mortality included: severity at admission (WHO Clinical Progression Score [WCPS]), age, gender, BMI, marital status, language preference, Elixhauser score, elevated laboratory (d-dimer, ferritin, LDH) or lower absolute lymphocyte count. When adjusting for patient age alone, survivorship during surges was also inversely associated with ICU occupancy, though this correlation was not present when adjusted for patient-level factors.

CONCLUSIONS AND RELEVANCE

Patient age, comorbidity burden, and severity at the time of presentation are the major factors associated with surviving COVID-19. Hospital-level factors including ICU occupancy may confer additional risk to individual patients, particularly at times of maximal stress on healthcare systems.

Fatality assessment and variant risk monitoring for COVID-19 using three new hospital occupancy related metrics

BACKGROUND

Though case fatality rate (CFR) is widely used to reflect COVID-19 fatality risk, its use is limited by large temporal and spatial variation. Hospital mortality rate (HMR) is also used to assess the severity of COVID-19, but HMR data is not directly available globally. Alternative metrics are needed for COVID-19 severity and fatality assessment.

METHODS

We introduce new metrics for COVID-19 fatality risk measurements/monitoring and a new mathematical model to estimate average hospital length of stay for deaths (L_dead) and discharges (L_dis). Multiple data sources were used for our analyses.

FINDINGS

We propose three, new metrics: hospital occupancy mortality rate (HOMR), ratio of total deaths to hospital occupancy (TDHOR), and ratio of hospital occupancy to cases (HOCR), for dynamic assessment of COVID-19 fatality risk. Estimated L_dead and L_dis for 501,079 COVID-19 hospitalizations in 34 US states between 7 August 2020 and 1 March 2021 were 18·2(95%CI:17·9-18·5) and 14·0(95%CI:13·9-14·0) days, respectively. We found the dramatic changes in COVID-19 CFR observed in 27 countries during early stages of the pandemic were mostly caused by undiagnosed cases. Compared to the first week of November 2021, the week mean HOCRs (mimics hospitalization-to-case ratio) for Omicron variant (58·6% of US new cases as of 25 December 2021) decreased 65·16% in the US as of 16 January 2022.

INTERPRETATION

The new and reliable measurements described here could be useful for COVID-19 fatality risk and variant-associated risk monitoring.

FUNDING

No specific funding was associated with the present study.

Chemokines, soluble PD-L1, and immune cell hyporesponsiveness are distinct features of SARS-CoV-2 critical illness

Critically ill patients manifest many of the same immune features seen in coronavirus disease 2019 (COVID-19), including both "cytokine storm" and "immune suppression." However, direct comparisons of molecular and cellular profiles between contemporaneously enrolled critically ill patients with and without severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are limited. We sought to identify immune signatures specifically enriched in critically ill patients with COVID-19 compared with patients without COVID-19. We enrolled a multisite prospective cohort of patients admitted under suspicion for COVID-19, who were then determined to be SARS-CoV-2-positive (n = 204) or -negative (n = 122). SARS-CoV-2-positive patients had higher plasma levels of CXCL10, sPD-L1, IFN-γ, CCL26, C-reactive protein (CRP), and TNF-α relative to SARS-CoV-2-negative patients adjusting for demographics and severity of illness (Bonferroni P value < 0.05). In contrast, the levels of IL-6, IL-8, IL-10, and IL-17A were not significantly different between the two groups. In SARS-CoV-2-positive patients, higher plasma levels of sPD-L1 and TNF-α were associated with fewer ventilator-free days (VFDs) and higher mortality rates (Bonferroni P value < 0.05). Lymphocyte chemoattractants such as CCL17 were associated with more severe respiratory failure in SARS-CoV-2-positive patients, but less severe respiratory failure in SARS-CoV-2-negative patients (P value for interaction < 0.01). Circulating T cells and monocytes from SARS-CoV-2-positive subjects were hyporesponsive to in vitro stimulation compared with SARS-CoV-2-negative subjects. Critically ill SARS-CoV-2-positive patients exhibit an immune signature of high interferon-induced lymphocyte chemoattractants (e.g., CXCL10 and CCL17) and immune cell hyporesponsiveness when directly compared with SARS-CoV-2-negative patients. This suggests a specific role for T-cell migration coupled with an immune-checkpoint regulatory response in COVID-19-related critical illness.

Factors associated with, and variations in, COVID-19 hospital death rates in England's first two waves: observational study

OBJECTIVES

To assess patient-level and hospital-level predictors of death and variation in death rates following admission for COVID-19 in England's first two waves after accounting for random variation. To quantify the correlation between hospitals' first and second wave death rates.

DESIGN

Observational study using administrative data.

SETTING

Acute non-specialist hospitals in England.

PARTICIPANTS

All patients admitted with a primary diagnosis of COVID-19.

PRIMARY AND SECONDARY OUTCOMES

In-hospital death.

RESULTS

Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. In wave 1 (March to July 2020), there were 74 484 admissions and 21 883 deaths (crude rate 29.4%); in wave 2 (August 2020 to March 2021), there were 165 642 admissions and 36 040 deaths (21.8%). Wave 2 patients were younger, with more hypertension and obesity but lower rates of other comorbidities. Mortality improved for all ages; in wave 2, it peaked in December 2020 at 24.2% (lower than wave 1's peak) but halved by March 2021. In multiple multilevel modelling combining HES with hospital-level data from Situational Reports, wave 2 and wave 1 variables significantly associated with death were mostly the same. The median odds ratio for wave 1 was just 1.05 and for wave 2 was 1.07. At 99.8% control limits, 3% of hospitals were high and 7% were low funnel plot outliers in wave 1; these figures were 9% and 12% for wave 2. Four hospitals were (low) outliers in both waves. The correlation between hospitals' adjusted mortality rates between waves was 0.45 (p<0.0001). Length of stay was similar in each wave.

CONCLUSIONS

England's first two COVID-19 waves were similar regarding predictors and moderate interhospital variation. Despite the challenges, variation in death rates and length of stay between hospitals was modest and might be accounted for by unobserved patient factors.

Mortality trends and lengths of stay among hospitalized COVID-19 patients in Ontario and Québec (Canada): a population-based cohort study of the first three epidemic waves

Background

Epidemics of COVID-19 strained hospital resources. We describe temporal trends in mortality risk and length of stays in hospital and intensive care units (ICUs) among patients with COVID-19 hospitalized through the first three epidemic waves in Canada.

Methods

We used population-based provincial hospitalization data from the epicenters of Canada's epidemics (Ontario and Québec). Adjusted estimates were obtained using marginal standardization of logistic regression models, accounting for patient-level and hospital-level determinants.

Results

Using all hospitalizations from Ontario (N = 26,538) and Québec (N = 23,857), we found that unadjusted in-hospital mortality risks peaked at 31% in the first wave and was lowest at the end of the third wave at 6–7%. This general trend remained after adjustments. The odds of in-hospital mortality in the highest patient load quintile were 1.2-fold (95% CI: 1.0–1.4; Ontario) and 1.6-fold (95% CI: 1.3–1.9; Québec) that of the lowest quintile. Mean hospital and ICU length of stays decreased over time but ICU stays were consistently higher in Ontario than Québec.

Conclusions

In-hospital mortality risks and length of ICU stays declined over time despite changing patient demographics. Continuous population-based monitoring of patient outcomes in an evolving epidemic is necessary for health system preparedness and response.

Racial and ethnic disparities in cardiometabolic disease and COVID-19 outcomes in White, Black/African American, and Latinx populations: Social determinants of health

Racial and ethnic-related health disparities in the United States have been intensified by the greater burden of Coronavirus Disease 2019 (COVID-19) in racial and ethnic minority populations. Compared to non-Hispanic White individuals, non-Hispanic Black and Hispanic/Latinx individuals infected by COVID-19 are at greater risk for hospitalization, intensive care unit admission, and death. There are several factors that may contribute to disparities in COVID-19-related severity and outcomes in these minority populations, including the greater burden of cardiovascular and metabolic diseases as discussed in our companion review article. Social determinants of health are a critical, yet often overlooked, contributor to racial and ethnic-related health disparities in non-Hispanic Black and Hispanic/Latinx individuals relative to non-Hispanic White individuals. Thus, the purpose of this review is to focus on the essential role of social factors in contributing to health disparities in chronic diseases and COVID-19 outcomes in minority populations. Herein, we begin by focusing on structural racism as a social determinant of health at the societal level that contributes to health disparities through downstream social level (e.g., occupation and residential conditions) and individual level health behaviors (e.g., nutrition, physical activity, and sleep). Lastly, we conclude with a discussion of practical applications and recommendations for future research and public health efforts that seek to reduce health disparities and overall disease burden.

Seasonal COVID-19 surge related hospital volumes and case fatality rates

BACKGROUND

Seasonal and regional surges in COVID-19 have imposed substantial strain on healthcare systems. Whereas sharp inclines in hospital volume were accompanied by overt increases in case fatality rates during the very early phases of the pandemic, the relative impact during later phases of the pandemic are less clear. We sought to characterize how the 2020 winter surge in COVID-19 volumes impacted case fatality in an adequately-resourced health system.

METHODS

We performed a retrospective cohort study of all adult diagnosed with COVID-19 in a large academic healthcare system between August 25, 2020 to May 8, 2021, using multivariable logistic regression to examine case fatality rates across 3 sequential time periods around the 2020 winter surge: pre-surge, surge, and post-surge. Subgroup analyses of patients admitted to the hospital and those receiving ICU-level care were also performed. Additionally, we used multivariable logistic regression to examine risk factors for mortality during the surge period.

RESULTS

We studied 7388 patients (aged 52.8 ± 19.6 years, 48% male) who received outpatient or inpatient care for COVID-19 during the study period. Patients treated during surge (N = 6372) compared to the pre-surge (N = 536) period had 2.64 greater odds (95% CI 1.46-5.27) of mortality after adjusting for sociodemographic and clinical factors. Adjusted mortality risk returned to pre-surge levels during the post-surge period. Notably, first-encounter patient-level measures of illness severity appeared higher during surge compared to non-surge periods.

CONCLUSIONS

We observed excess mortality risk during a recent winter COVID-19 surge that was not explained by conventional risk factors or easily measurable variables, although recovered rapidly in the setting of targeted facility resources. These findings point to how complex interrelations of population- and patient-level pandemic factors can profoundly augment health system strain and drive dynamic, if short-lived, changes in outcomes.

Predictive Value of an Age-Based Modification of the National Early Warning System in Hospitalized Patients With COVID-19

BACKGROUND

Early recognition of high-risk patients with coronavirus disease 2019 (COVID-19) may improve outcomes. Although many predictive scoring systems exist, their complexity may limit utility in COVID-19. We assessed the prognostic performance of the National Early Warning Score (NEWS) and an age-based modification (NEWS+age) among hospitalized COVID-19 patients enrolled in a prospective, multicenter US Military Health System (MHS) observational cohort study.

METHODS

Hospitalized adults with confirmed COVID-19 not requiring invasive mechanical ventilation at admission and with a baseline NEWS were included. We analyzed each scoring system's ability to predict key clinical outcomes, including progression to invasive ventilation or death, stratified by baseline severity (low [0-3], medium [4-6], and high [≥7]).

RESULTS

Among 184 included participants, those with low baseline NEWS had significantly shorter hospitalizations (P < .01) and lower maximum illness severity (P < .001). Most (80.2%) of low NEWS vs 15.8% of high NEWS participants required no or at most low-flow oxygen supplementation. Low NEWS (≤3) had a negative predictive value of 97.2% for progression to invasive ventilation or death; a high NEWS (≥7) had high specificity (93.1%) but low positive predictive value (42.1%) for such progression. NEWS+age performed similarly to NEWS at predicting invasive ventilation or death (NEWS+age: area under the receiver operating characteristics curve [AUROC], 0.69; 95% CI, 0.65-0.73; NEWS: AUROC, 0.70; 95% CI, 0.66-0.75).

CONCLUSIONS

NEWS and NEWS+age showed similar test characteristics in an MHS COVID-19 cohort. Notably, low baseline scores had an excellent negative predictive value. Given their easy applicability, these scoring systems may be useful in resource-limited settings to identify COVID-19 patients who are unlikely to progress to critical illness.

Supervision, Interprofessional Collaboration, and Patient Safety in Intensive Care Units during the COVID-19 Pandemic

Background: To meet coronavirus disease (COVID-19) demands in the spring of 2020, many intensive care (IC) units (ICUs) required help of redeployed personnel working outside their regular scope of practice, causing an expansion and change of staffing ratios. Objective: How did this composite alternative ICU workforce experience supervision, interprofessional collaboration, and quality and safety of care under the unprecedented clinical circumstances at the height of the first pandemic wave as lived experiences uniquely captured during the first peak of the pandemic? Methods: An international, cross-sectional survey was conducted among physicians, nurses, and allied personnel deployed or redeployed to ICUs in Utrecht, New York, and Dublin from April to May of 2020. Data were analyzed separately for the three sites. Quantitative data were treated for descriptive statistics; qualitative data were analyzed thematically and combined for general interpretations. Results: On the basis of 234, 83, and 34 responses (response rates of 68%, 48%, and 41% in Utrecht, New York, and Dublin, respectively), we found that the amount of supervision and the quality and safety of care were perceived as being lower than usual but still acceptable. The working atmosphere was overwhelmingly felt to be collaborative and supportive. Where IC-certified nurse-to-patient ratios had decreased most (Utrecht), nurses voiced criticism about supervision and quality of care. Continuity within the work environment, team composition, and informal ("curbside") consultations were critical mediators of success. Conclusion: In the exceptional circumstances encountered during the COVID-19 pandemic, many ICUs were managed by a composite workforce of IC-certified and redeployed personnel. Although supervision is critical for safe care, supervisory roles were not clearly related to the amount of prior ICU experience. Vital for satisfaction with the quality of care was the span of control for those who assumed supervisory roles (i.e., the ratio of certified to noncertified personnel). Stable teams that matched less experienced personnel with more experienced personnel; a strong, interprofessional, collaborative atmosphere; a robust culture of informal consultation; and judicious, more flexible use of rules and regulations proved to be essential.