Literature DB >> 32930099

Clinical Mortality in a Large COVID-19 Cohort: Observational Study.

Mark Jarrett1, Susanne Schultz2, Julie Lyall2, Jason Wang1, Lori Stier2, Marcella De Geronimo3, Karen Nelson2.   

Abstract

BACKGROUND: Northwell Health, an integrated health system in New York, has treated more than 15,000 inpatients with COVID-19 at the US epicenter of the SARS-CoV-2 pandemic.
OBJECTIVE: We describe the demographic characteristics of patients who died of COVID-19, observation of frequent rapid response team/cardiac arrest (RRT/CA) calls for non-intensive care unit (ICU) patients, and factors that contributed to RRT/CA calls.
METHODS: A team of registered nurses reviewed the medical records of inpatients who tested positive for SARS-CoV-2 via polymerase chain reaction before or on admission and who died between March 13 (first Northwell Health inpatient expiration) and April 30, 2020, at 15 Northwell Health hospitals. The findings for these patients were abstracted into a database and statistically analyzed.
RESULTS: Of 2634 patients who died of COVID-19, 1478 (56.1%) had oxygen saturation levels ≥90% on presentation and required no respiratory support. At least one RRT/CA was called on 1112/2634 patients (42.2%) at a non-ICU level of care. Before the RRT/CA call, the most recent oxygen saturation levels for 852/1112 (76.6%) of these non-ICU patients were at least 90%. At the time the RRT/CA was called, 479/1112 patients (43.1%) had an oxygen saturation of <80%.
CONCLUSIONS: This study represents one of the largest reviewed cohorts of mortality that also captures data in nonstructured fields. Approximately 50% of deaths occurred at a non-ICU level of care despite admission to the appropriate care setting with normal staffing. The data imply a sudden, unexpected deterioration in respiratory status requiring RRT/CA in a large number of non-ICU patients. Patients admitted at a non-ICU level of care suffered rapid clinical deterioration, often with a sudden decrease in oxygen saturation. These patients could benefit from additional monitoring (eg, continuous central oxygenation saturation), although this approach warrants further study. ©Mark Jarrett, Susanne Schultz, Julie Lyall, Jason Wang, Lori Stier, Marcella De Geronimo, Karen Nelson. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.09.2020.

Entities:  

Keywords:  COVID-19; ICU; cohort; hypoxemia; intensive care unit; mortality; observational; respiratory failure; review

Mesh:

Substances:

Year:  2020        PMID: 32930099      PMCID: PMC7537718          DOI: 10.2196/23565

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


Introduction

Downstate New York was the first epicenter of the SARS-CoV-2 pandemic in the United States [1,2]. Northwell Health, an integrated health system, has treated more than 15,000 inpatients with COVID-19. Comprehensively analyzing the characteristics of patients who die of COVID-19 can help define the clinical nature of COVID-19 infection and potentially suggest new care protocols. For 7 years, Northwell Health has used a centralized mortality review process with data validated through rigorous internal review and high interrater reliability (92% to 96%). This robust process was applied to a customized database to review all 2634 patients who died of COVID-19 in Northwell Health’s adult acute care hospitals between March and April 2020. During this overwhelming surge, documentation was made in various notes as well as in structured fields in the electronic health record (EHR) systems. This study describes the demographic characteristics of patients who died of COVID-19 and the observation of frequent rapid response team/cardiac arrest (RRT/CA) calls for patients not in the intensive care unit (ICU). We also discuss factors that contributed to the RRT/CA calls, which may be a significant element in planning for a resurgence of the pandemic.

Methods

Study Design

Northwell Health is New York State’s largest health care provider and private employer. With 23 hospitals (including specialty hospitals) and nearly 800 outpatient practice sites, the organization cares for over 2 million people in greater metropolitan New York. A team of registered nurses in the corporate quality department retrospectively reviewed medical records from 15 acute care hospitals. This team routinely conducts clinical reviews of all adult acute inpatient mortalities (approximately 5000 per year). A physician advisor was available to the team to consult on clinical questions. Database elements were based on Northwell Health’s experience with treating patients with COVID-19, literature review from countries that had early experience in treating patients, and clinical trials being conducted at the Feinstein Institutes for Medical Research. Also, the data were captured in the database established under the direction of critical care intensivists at the epicenter of the pandemic, other subject matter experts, and quality leadership. During data abstraction, modifications and enhancements were made to the database based on trends and emerging information. The demographic data, comorbidities, clinical findings, and management of COVID-19 patients who died were analyzed.

Patient Characteristics

The analyzed cases included inpatients who tested positive for SARS-CoV-2 via polymerase chain reaction before or on admission and who then died between March 13 (first Northwell Health inpatient death) and April 30, 2020. Emergency department (ED) mortalities were excluded. Demographic data and comorbidities were abstracted from the medical records of admitted patients. Initially, data were collected on 10 patient comorbidities that were deemed important and were then narrowed down to 6 comorbidities for inclusion based on our initial analysis. Transfers from one in-system hospital to another were merged and considered as a single visit. Notable patient outcomes that were measured were the level of ICU care (validated and abstracted from the provider order) and a call for RRT/CA. The Institutional Review Board of Northwell Health deemed this study as exempt and waived the requirement for informed consent.

Statistical Analysis

Statistical analyses were performed using chi-square tests for categorical variables and t tests for continuous variables. A multivariable logistic regression model was created to determine independent risk factors for the outcome variables. Statistical significance was considered at P<.05. All statistical analyses were performed in SAS v9.4 (SAS Institute).

Data Sharing

The data that support the findings of this study are available on request from COVID19@northwell.edu. The data are not publicly available due to restrictions, as this could compromise the privacy of the research participants.

Results

The baseline characteristics of the 2634 patients who died of COVID-19 are described in Tables 1-3. The age range was 21-107 years in the following categories: 21 to 39 years (49/2634, 1.9%), 40 to 59 years (351/2634, 13.3%), 60 to 79 years (1241/2634, 47.1%), and ≥80 years (993/2634, 37.7%). In the patient cohort, 1664/2634 patients (63.2%) were male and 970/2634 (36.8%) were female. Among the 2634 patients, 1256 (47.7%) were White, 463 (17.6%) were Black, 230 (8.7%) were Asian, and 685 (26.0%) were of other/unknown race. The majority of patients (1839/2634, 69.8%) reported Medicare as their insurance. The most common comorbidities among these patients were hypertension (1719/2634, 65.3%), diabetes (1043/2634, 39.6%), and dementia (431/2634, 16.4%). Fewer patients had chronic obstructive pulmonary disease (385/2634, 14.6%), heart failure (291/2634, 11.1%), and end stage renal disease (166/2634, 6.3%). Of these six comorbidities, more than half of the patients (1350/2634, 51.3%) had 2 or more comorbidities, and 445/2634 (16.9%) had 0 comorbidities. The majority of patients with a known BMI, calculated as weight in kilograms divided by height in meters squared, of 25 or more were categorized as follows: 25 to 29.99 (732/2634, 27.8%), 30 to 34.99 (401/2634, 15.2%), 35 to 39.99 (190/2634, 7.2%), and ≥40 (147/2634, 5.6%).
Table 1

Baseline characteristics of patients hospitalized with COVID-19 who died (N=2634), n (%).

Baseline characteristicValue
Age (years)
21-3949 (1.86)
40-59351 (13.3)
60-791241 (47.1)
≥80993 (37.7)
Sex
Male1664 (63.2)
Female970 (36.8)
Race
White1256 (47.7)
Black463 (17.6)
Asian230 (8.7)
Other/unknown685 (26.0)
Payment method
Commercial insurance413 (15.7)
Medicaid341 (13.0)
Medicare1839 (69.8)
Self-pay41 (1.6)
Comorbidities
Hypertension1719 (65.3)
COPDa385 (14.6)
Diabetes1043 (39.6)
Heart failure291 (11.1)
Dementia431 (16.4)
End stage renal disease166 (6.3)
Number of comorbidities
0445 (16.9)
1839 (31.9)
2934 (35.5)
3343 (13.0)
466 (2.5)
57 (0.3)
60 (0.0)
BMI (kg/m2)
Unknown494 (18.8)
<18.582 (3.1)
18.5-24.99588 (22.3)
25-29.99732 (27.8)
30-34.99401 (15.2)
35-39.99190 (7.2)
≥40147 (5.6)

aCOPD: chronic obstructive pulmonary disease.

Table 3

Mechanical ventilation characteristics of patients hospitalized with COVID-19 who died.

Mechanical ventilation characteristicn%
Total patients (N=2634)Patients who were ventilated (n=1403)
Traditional ventilator125947.989.7
Converted BiPAPa1420.110.1
Anesthesia machine20.080.1
Increased oxygen requirement prior to mechanical ventilation133250.694.9
Mechanical ventilation length, days
0-785132.360.7
≥855220.939.3
Terminal wean27010.319.2

abiPAP: bilevel positive airway pressure.

Baseline characteristics of patients hospitalized with COVID-19 who died (N=2634), n (%). aCOPD: chronic obstructive pulmonary disease. Hospitalization characteristics of patients hospitalized with COVID-19 who died (N=2634), n (%). aICU: intensive care unit. bBiPAP: bilevel positive airway pressure cRRT/CA: rapid response team/cardiac arrest. dDNR: do not resuscitate. Mechanical ventilation characteristics of patients hospitalized with COVID-19 who died. abiPAP: bilevel positive airway pressure.

Patient Outcomes

Most patients were admitted from home (1895/2634, 71.9%). The remaining patients were admitted from a skilled nursing facility (411/2634, 15.6%), an acute care facility (201/2634, 7.6%), or a rehabilitation facility (127/2634, 4.8%). The percentage of patients with a prior ED visit within 7 days of admission was 4.8% (125/2634), and that of patients with a prior ED visit within 48 hours of admission was 1.9% (51/2634). The percentage of patients readmitted within 30 days was 7.4% (194/2634), 2.9% (75/2634) were readmitted within 7 days, and 0.8% (20/2634) were readmitted within 24 hours. On presentation, most patients (1478/2634, 56.1%) had an oxygen saturation level greater than or equal to 90%, and more than half (1397/2634, 53.0%) required no respiratory support. Others required a nasal cannula (363/2634, 13.8%), a nonrebreather mask (742/2634, 28.2%), or mechanical ventilation (24/2634, 0.9%). More than half of the patients who died (1403/2634, 53.2%) required mechanical ventilation during their clinical course. Of those 1403 patients, 1332 (94.9%) had increasing oxygen requirements before intubation, 1259 (89.7%) were on traditional ventilators, 142 (10.1%) were on converted BiPAP machines, and 2 (0.1%) were on anesthesia machines. The length of time on mechanical ventilation was 0 to 7 days for 851/1403 patients (60.7%) and 8 days or more for 552/1403 patients (39.3%). Prone positioning was documented for 756/2634 patients (28.7%), and 270/2634 patients (10.3%) patients were terminally weaned. Do not resuscitate (DNR) orders were completed for 1631/2634 patients (61.9%). A palliative care consult was provided to 1014/2634 patients (38.5%). At the time of death, the level of care was ICU for 1299/2634 patients (49.3%) and non-ICU for 1335/2634 patients (50.7%).

Patient Outcomes Based on RRT/CA Calls

Of the 2634 patients, 1112 (42.2%) had an RRT/CA call at a non-ICU level of care, while 1522 (57.8%) did not. As shown in Tables 4-6, the RRT/CA group was significantly different from the non-RRT/CA group in terms of age, race, and comorbidities. Among patients between 60 and 79 years of age, 618/1112 (55.6%) were in the RRT/CA group and 623/1522 (40.9%) were in the non-RRT/CA group. In terms of race, there were significantly fewer White patients in the RRT/CA group (404/1112, 36.3%, versus 852/1522, 56.0%; P<.001). The RRT/CA cohort had a significantly higher rate of patients with diabetes (491/1112, 44.2%, versus 552/1522, 36.3%; P<.001). Patients in the RRT/CA cohort were more likely to be admitted from home (926/1112, 83.3%) than patients in the non-RRT/CA cohort (969/1522, 63.7%). Patients in the RRT/CA cohort were more likely than patients in the non-RRT/CA cohort to be admitted to a medical/surgical unit (576/1112, 51.8%, versus 654/1522, 42.9%) or telemetry/step-down unit (455/1112, 40.9%, versus 408/1522, 26.8%), and to die at an ICU level of care (671/1112, 60.3%, versus 628/1522, 41.3%). An overall length of stay (LOS) of 8 days or more was more common in the RRT/CA cohort (645/1112, 58.0%) than in the non-RRT/CA cohort (569/1522, 37.4%), as was an ICU LOS of 0 to 7 days (472/1112, 42.0%, versus 400/1522, 26.3%) and of 8 days or more (271/1112, 24.4%, versus 303/1522, 19.9%). After adjusting for demographic and clinical characteristics, oxygen saturation levels at presentation were significant for the RRT/CA cohort at oxygen saturation levels of 80% to 89% (odds ratio [OR] 1.988, 95% CI 1.511-2.616) and of ≥90% (OR 2.517, 95% CI 1.962-3.230). For the logistic regression results, see Table 7.
Table 4

Baseline characteristics of patients who died of COVID-19 who experienced an RRT/CA call at a non-ICU level of care (N=2634).

Baseline characteristics RRT/CAa call
Yes (n=1112), n (%)No (n=1522), n (%)P value
Age (years) <.001
21-3919 (1.7)30 (2.0)
40-59194 (17.5)157 (10.3)
60-79618 (55.6)623 (40.9)
≥80281 (25.3)712 (40.8)
Sex .35
Male714 (64.2)950 (62.4)
Female398 (35.8)572 (37.6)
Race <.001
White404 (36.3)852 (56.0)
Black235 (21.1)228 (15.0)
Asian125 (11.2)105 (6.9)
Other/unknown348 (31.3)337 (22.1)
Payment method <.001
Commercial insurance226 (20.3)187 (12.3)
Medicaid166 (14.9)175 (11.5)
Medicare702 (63.1)1137 (74.7)
Self-pay18 (1.6)23 (1.5)
Comorbidities
Hypertension .24
Yes740 (66.5)979 (64.3)
No372 (33.5)543 (35.7)
COPDb .08
Yes147 (13.2)238 (15.6)
No965 (86.8)1284 (84.4)
Diabetes <.001
Yes491 (44.2)552 (36.3)
No621 (55.9)970 (63.7)
Heart failure .03
Yes106 (9.5)185 (12.2)
No1006 (90.5)1337 (87.8)
Dementia <.001
Yes98 (8.8)333 (21.9)
No1014 (91.2)1189 (78.1)
End stage renal disease .02
Yes85 (7.6)81 (5.3)
No1027 (92.4)1441 (94.7)
Number of comorbidities .47
0202 (18.2)243 (15.9)
1355 (31.9)484 (31.8)
2388 (34.9)546 (35.9)
3134 (12.1)209 (13.7)
431 (2.8)35 (2.3)
52 (0.2)5 (0.3)
BMI (kg/m2) <.001
Unknown136 (12.2)358 (23.5)
<18.522 (1.9)60 (3.9)
18.5-24.99236 (21.2)352 (23.1)
25-29.99352 (31.7)380 (24.9)
30-34.99206 (18.5)195 (12.8)
35-39.9988 (7.9)102 (6.7)
≥4072 (6.5)75 (4.9)

aRRT/CA: rapid response team/cardiac arrest.

bCOPD: chronic obstructive pulmonary disease.

Table 6

Additional characteristics associated with RRT/CA calls for patients at a non–intensive care unit level of care (n=1112), n (%).

CharacteristicValue
Required escalation in level of care following initial RRT/CAa call716 (64.4)
Oxygen saturation at time RRT/CA call initiated (%)
<80479 (43.1)
80-89407 (36.6)
≥90128 (11.5)
Unable to determine98 (8.8)
Oxygen supplement at time RRT/CA call initiated
Nonrebreather mask with or without nasal cannula868 (78.1)
Nasal cannula147 (13.2)
Room air40 (3.6)
Ventimask18 (1.6)
Ventilator11 (1.0)
High-flow nasal cannula9 (0.8)
BiPAPb5 (0.4)
Unable to determine14 (1.3)
Most recent oxygen saturation before RRT/CA initiated (%)
<8043 (3.9)
80-89211 (18.9)
90≤852 (76.6)
Unable to determine6 (0.5)
Documented timing of most recent oxygen saturation before RRT/CA initiated (hours)
<1263 (23.7)
1-2191 (17.2)
2-3140 (12.6)
3-4109 (9.8)
>4409 (36.8)

aRRT/CA: rapid response team/cardiac arrest.

bBiPAP: bilevel positive airway pressure.

Table 7

Regression analysis of patients who died of COVID-19 who experienced a rapid response team/cardiac arrest call at a non–intensive care unit level of care (N=2634).

Baseline characteristicsEstimateP valueOdds ratio95% CI
Age (years)
50-690.2653.201.3040.872-1.949
70-790.1721.441.1880.766-1.842
≥80–0.3179.170.7280.460-1.151
Sex
Male–0.2299.020.7950.658-0.960
Race
Black0.6134<.0011.8471.445-2.361
Asian0.6548<.0011.9251.395-2.655
Other/unknown0.5333<.0011.7041.362-2.133
Payment method
Medicaid–0.0458.780.9550.691-1.321
Medicare–0.0107.940.9890.750-1.305
Self-pay–0.3020.400.7390.367-1.488
Comorbidities
Heart failure0.1429.341.1540.860-1.547
End stage renal disease0.6184.0021.8561.262-2.729
COPDa–0.1216.350.8860.687-1.141
Hypertension0.1239.211.1320.931-1.376
Diabetes mellitus0.0833.381.0870.902-1.310
BMI (kg/m2)
Unknown–0.4645<.0010.6280.491-0.804
≥30–0.0545.620.9470.765-1.173
Admit source
Home0.9060<.0012.4741.850-3.310
Rehabilitation0.2904.251.3370.813-2.199
Transfer from acute care hospital0.0544.801.0560.691-1.614
Oxygen saturation on presentation (%)
80-890.6871<.0011.9881.511 2.616
≥900.9232<.0012.5171.962 3.230
Proning1.1840<.0013.2672.667 4.003

aCOPD: chronic obstructive pulmonary disease.

Baseline characteristics of patients who died of COVID-19 who experienced an RRT/CA call at a non-ICU level of care (N=2634). aRRT/CA: rapid response team/cardiac arrest. bCOPD: chronic obstructive pulmonary disease. Hospitalization characteristics of patients who died of COVID-19 who experienced an RRT/CA call at a non-ICU level of care (N=2634). aRRT/CA: rapid response team/cardiac arrest. bN/A: not applicable. cICU: intensive care unit. dBiPAP: bilevel positive airway pressure. eDNR: do not resuscitate. Additional characteristics associated with RRT/CA calls for patients at a non–intensive care unit level of care (n=1112), n (%). aRRT/CA: rapid response team/cardiac arrest. bBiPAP: bilevel positive airway pressure. Regression analysis of patients who died of COVID-19 who experienced a rapid response team/cardiac arrest call at a non–intensive care unit level of care (N=2634). aCOPD: chronic obstructive pulmonary disease.

Discussion

Summary of Findings

This study represents a review of one of the largest cohorts of COVID-19 mortality that includes data documented in nonstructured fields within the EHR. An experienced team of registered nurses was able to extract detailed information from the medical record that is typically not included in a structured data set analysis. The demographics of the patients who died are similar to those in other published studies: age predominately over 69, male majority, payor mix (reflecting age and Medicare along with a low number of self-paying patients, namely 41/2634, 1.6%), and multiple comorbidities [3-12].

Circumstances Preceding Patient Deterioration

This study provides a detailed clinical picture of the circumstances that precede the sudden deterioration in non-ICU patients reported by clinicians, which have not been fully examined in the literature. A striking reported feature of COVID-19 is the rapid progression of respiratory failure soon after the onset of dyspnea and hypoxemia [13]. The US National Institutes of Health (NIH) has reported that hypoxemia is common in hospitalized patients with COVID-19 and that the criteria for hospital admission, ICU admission, and mechanical ventilation differ between countries [14]. In some hospitals in the United States, more than 25% of hospitalized patients require ICU care, mostly due to acute respiratory failure. The NIH recommends close monitoring for worsening respiratory status for adults with COVID-19 who are receiving supplemental oxygen. These recommendations align with our findings in the non-ICU patient population. Approximately half of the deaths (1335/2634, 50.7%) occurred at a non-ICU level of care despite admission to the appropriate care setting with normal staffing. Our analysis of patients who experienced at least one RRT/CA call at a non-ICU level of care revealed that 716/1112 (64.4%) required an escalation in their level of care. Of the RRT/CA patients, 664/1112 (59.7%) presented to the hospital with oxygen saturation levels greater than or equal to 90%. In addition, 687/1112 (61.8%) had no oxygen support. Of the RTT/CA patients, 1031/1112 (92.7%) were admitted to a non-ICU level of care with normal staffing levels, which was appropriate based on their care needs. At presentation to the ED, the oxygen saturation levels for these patients were significantly higher than those for patients admitted to the ICU. Before the RRT/CA call, the most recent oxygen saturation levels recorded for the non-ICU patients remained high, at ≥90% for 852/1112 (76.6%) of patients. Oxygen saturations were documented within two hours of the RRT/CA call in 454/1112 (40.9%) of patients in the RRT/CA cohort. When the RRT/CA was called, 479/1112 (43.1%) of patients had an oxygen saturation less than 80%, and 78.1% (868/1112) were on a nonrebreather mask or a nonrebreather mask with nasal cannula. These data imply a sudden, unexpected deterioration in respiratory status requiring an RRT/CA call in a large number of non-ICU patients.

Limitations

This study includes the following limitations. First, the study focuses on the demographic and clinical characteristics of in-hospital COVID-19 patients who died between March 13 and April 30, 2020; it does not provide a comparison group of similar patients who survived during the same time period. Second, data were obtained from the EHR and manually abstracted from medical records through retrospective review; however, some routine documentation was less detailed due to the volume of patients being treated. Third, race was documented as other/unknown in 685/2634 (26%) of patients; therefore, conclusions about race could not be drawn. Fourth, missing BMI data were included in the category of “unknown” BMI. Finally, the study does not recognize a specific trigger that can distinguish which non-ICU patients in the cohort should be monitored.

Conclusions

Patients admitted to a non-ICU level of care appear to suffer rapid clinical deterioration, often with the hallmark of a sudden decrease in oxygen saturation. This finding suggests that non-ICU patients could benefit from additional monitoring, such as continuous central oxygenation saturation. The availability of wireless patch monitoring should be considered along with other methods, such as carbon dioxide and cardiac monitoring. Although this approach does not ensure reduced mortality, the number of RRT/CA calls infers that this area warrants further study.
Table 2

Hospitalization characteristics of patients hospitalized with COVID-19 who died (N=2634), n (%).

Hospitalization characteristicValue
Admission source
Home1895 (72.0)
Rehabilitation127 (4.8)
Skilled nursing facility411 (15.6)
Transfer from another acute care hospital201 (7.6)
Emergency department visit
Within 48 hours of this admission51 (1.9)
Within 7 days of this admission125 (4.8)
Readmission
Within 24 hours20 (0.8)
Within 7 days75 (2.9)
Within 30 days194 (7.4)
Level of care at time of death
ICUa1299 (49.3)
Non-ICU1335 (50.7)
Level of care at time of admission
ICU541 (20.5)
Medical/surgical unit1230 (46.7)
Telemetry/stepdown unit863 (32.8)
Overall length of stay (days)
0-71420 (53.9)
≥81214 (46.1)
ICU length of stay (days)
0-7872 (33.1)
≥8574 (21.8)
Oxygen saturation on presentation (%)
<80459 (17.4)
80-89.9667 (25.3)
≥901478 (56.1)
Unable to determine30 (1.2)
Initial respiratory support on presentation
None1397 (53.0)
Nasal cannula363 (13.8)
Nonrebreather mask742 (28.2)
Ventilator24 (0.9)
High-flow nasal cannula8 (0.3)
Ventimask11 (0.4)
BiPAPb13 (0.5)
Other27 (1.0)
Unable to determine49 (1.9)
RRT/CAd while not at ICU level of care1112 (42.2)
Proning
Yes756 (28.7)
No1878 (71.3)
Proning without mechanical ventilation (n=756)191 (25.3)
Proning prior to mechanical ventilation (n=756)213 (28.2)
Proning during mechanical ventilation (n=756)214 (28.3)
Proning prior to and during mechanical ventilation(n=756)138 (18.3)
DNRd complete1631 (61.9)
Palliative care consult1014 (38.5)
Clinical trial inclusion114 (4.3)

aICU: intensive care unit.

bBiPAP: bilevel positive airway pressure

cRRT/CA: rapid response team/cardiac arrest.

dDNR: do not resuscitate.

Table 5

Hospitalization characteristics of patients who died of COVID-19 who experienced an RRT/CA call at a non-ICU level of care (N=2634).

Baseline characteristicsRRT/CAa call
Yes (n=1112), n (%)No (n=1522), n (%)P value
Admission source <.001
Home926 (83.3)969 (63.7)
Rehabilitation34 (3.0)93 (6.1)
Skilled nursing facility80 (7.2)331 (21.7)
Transfer from another acute care hospital72 (6.5)129 (8.5)
Emergency department visit
Within 48 hours of this admission .03
Yes29 (2.6)22 (1.5)
No1083 (97.4)1500 (98.6)
Within 7 days of this admission .13
Yes61 (5.5)64 (4.2)
No1051 (94.5)1458 (95.8)
Readmission
Within 24 hours .51
Yes7 (0.6)13 (0.9)
No1105 (99.4)1509 (99.2)
Within 7 days .88
Yes31 (2.8)44 (2.9)
No1081 (97.2)1478 (97.1)
Within 30 days .10
Yes71 (6.4)123 (8.1)
No1041 (93.6)1399 (91.9)
Level of care at time of death N/Ab
ICUc671 (60.3)628 (41.3)
Non-ICU441 (39.7)894 (58.7)
Level of care at time of admission <.001
ICU81 (7.3)460 (30.2)
Medical/surgical unit576 (51.8)654 (42.9)
Telemetry/stepdown unit455 (40.9)408 (26.8)
Overall length of stay (days) <.001
0-7467 (42.0)953 (62.6)
≥8645 (58.0)569 (37.4)
ICU length of stay (days) <.001
0-7472 (42.4)400 (26.3)
≥8271 (24.4)303 (19.9)
Oxygen saturation on presentation (%) <.001
<80152 (13.7)307 (20.2)
80-89.9289 (26.0)378 (24.8)
≥90664 (59.7)814 (53.5)
Unable to determine7 (0.6)23 (1.5)
Initial respiratory support on presentation <.001
None687 (61.8)710 (46.7)
Nasal cannula161 (14.5)202 (13.3)
High-flow nasal cannula0 (0.0)8 (0.5)
Ventimask2 (0.2)9 (0.6)
BiPAPd2 (0.2)11 (0.7)
Nonrebreather mask239 (21.5)503 (33.1)
Ventilator1 (0.1)23 (1.5)
Other4 (0.4)23 (1.5)
Unable to determine16 (1.4)33 (2.2)
Mechanical ventilation723 (65.0)680 (44.7)<.001
Type of mechanical ventilation
Traditional ventilator650 (58.5)609 (40.0)
Converted BiPAP71 (6.4)71 (4.7)
Anesthesia machine2 (0.2)0 (0.0)
Increased oxygen requirement before mechanical ventilation699 (62.9)633 (41.6)<.001
Mechanical ventilation length (days)
0-7461 (41.5)390 (25.6)
≥8262 (23.6)290 (19.1)
Terminal wean .52
Yes109 (9.8)161 (10.6)
No1003 (90.2)1361 (89.4)
Proning <.001
Yes500 (45.0)256 (16.8)
No612 (54.9)1266 (83.2)
Proning without mechanical ventilation116 (10.4)75 (4.9)
Proning before mechanical ventilation171 (15.4)42 (2.7)
Proning during mechanical ventilation99 (8.9)115 (7.5)
Proning before and during mechanical ventilation114 (10.3)24 (1.6)
DNRe complete <.001
Yes558 (50.2)1073 (70.5)
No554 (49.8)449 (29.5)
Palliative care consult <.001
Yes385 (34.6)629 (41.3)
No727 (65.4)893 (58.7)
Clinical trial inclusion N/A
Yes91(8.2)23(1.5)
No1021(91.8)1499 (98.5)

aRRT/CA: rapid response team/cardiac arrest.

bN/A: not applicable.

cICU: intensive care unit.

dBiPAP: bilevel positive airway pressure.

eDNR: do not resuscitate.

  11 in total

1.  Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area.

Authors:  Safiya Richardson; Jamie S Hirsch; Mangala Narasimhan; James M Crawford; Thomas McGinn; Karina W Davidson; Douglas P Barnaby; Lance B Becker; John D Chelico; Stuart L Cohen; Jennifer Cookingham; Kevin Coppa; Michael A Diefenbach; Andrew J Dominello; Joan Duer-Hefele; Louise Falzon; Jordan Gitlin; Negin Hajizadeh; Tiffany G Harvin; David A Hirschwerk; Eun Ji Kim; Zachary M Kozel; Lyndonna M Marrast; Jazmin N Mogavero; Gabrielle A Osorio; Michael Qiu; Theodoros P Zanos
Journal:  JAMA       Date:  2020-05-26       Impact factor: 56.272

2.  COVID-19 and African Americans.

Authors:  Clyde W Yancy
Journal:  JAMA       Date:  2020-05-19       Impact factor: 56.272

Review 3.  Severe Covid-19.

Authors:  David A Berlin; Roy M Gulick; Fernando J Martinez
Journal:  N Engl J Med       Date:  2020-05-15       Impact factor: 91.245

4.  Characteristics of Persons Who Died with COVID-19 - United States, February 12-May 18, 2020.

Authors:  Jonathan M Wortham; James T Lee; Sandy Althomsons; Julia Latash; Alexander Davidson; Kevin Guerra; Kenya Murray; Emily McGibbon; Carolina Pichardo; Brian Toro; Lan Li; Marc Paladini; Meredith L Eddy; Kathleen H Reilly; Lisa McHugh; Deepam Thomas; Stella Tsai; Mojisola Ojo; Samantha Rolland; Maya Bhat; Katherine Hutchinson; Jennifer Sabel; Seth Eckel; Jim Collins; Catherine Donovan; Anna Cope; Breanna Kawasaki; Sarah McLafferty; Nisha Alden; Rachel Herlihy; Bree Barbeau; Angela C Dunn; Charles Clark; Pamela Pontones; Meagan L McLafferty; Dean E Sidelinger; Anna Krueger; Leslie Kollmann; Linnea Larson; Stacy Holzbauer; Ruth Lynfield; Ryan Westergaard; Richard Crawford; Lin Zhao; Jonathan M Bressler; Jennifer S Read; John Dunn; Adele Lewis; Gillian Richardson; Julie Hand; Theresa Sokol; Susan H Adkins; Brooke Leitgeb; Talia Pindyck; Taniece Eure; Karen Wong; Deblina Datta; Grace D Appiah; Jessica Brown; Rita Traxler; Emilia H Koumans; Sarah Reagan-Steiner
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-07-17       Impact factor: 17.586

5.  Coronavirus Disease 2019 Case Surveillance - United States, January 22-May 30, 2020.

Authors:  Erin K Stokes; Laura D Zambrano; Kayla N Anderson; Ellyn P Marder; Kala M Raz; Suad El Burai Felix; Yunfeng Tie; Kathleen E Fullerton
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-06-19       Impact factor: 17.586

6.  A novel coronavirus outbreak of global health concern.

Authors:  Chen Wang; Peter W Horby; Frederick G Hayden; George F Gao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

7.  Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study.

Authors:  Christopher M Petrilli; Simon A Jones; Jie Yang; Harish Rajagopalan; Luke O'Donnell; Yelena Chernyak; Katie A Tobin; Robert J Cerfolio; Fritz Francois; Leora I Horwitz
Journal:  BMJ       Date:  2020-05-22

8.  Preliminary Estimates of the Prevalence of Selected Underlying Health Conditions Among Patients with Coronavirus Disease 2019 - United States, February 12-March 28, 2020.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-04-03       Impact factor: 17.586

9.  Hospitalization Rates and Characteristics of Patients Hospitalized with Laboratory-Confirmed Coronavirus Disease 2019 - COVID-NET, 14 States, March 1-30, 2020.

Authors:  Shikha Garg; Lindsay Kim; Michael Whitaker; Alissa O'Halloran; Charisse Cummings; Rachel Holstein; Mila Prill; Shua J Chai; Pam D Kirley; Nisha B Alden; Breanna Kawasaki; Kimberly Yousey-Hindes; Linda Niccolai; Evan J Anderson; Kyle P Openo; Andrew Weigel; Maya L Monroe; Patricia Ryan; Justin Henderson; Sue Kim; Kathy Como-Sabetti; Ruth Lynfield; Daniel Sosin; Salina Torres; Alison Muse; Nancy M Bennett; Laurie Billing; Melissa Sutton; Nicole West; William Schaffner; H Keipp Talbot; Clarissa Aquino; Andrea George; Alicia Budd; Lynnette Brammer; Gayle Langley; Aron J Hall; Alicia Fry
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-04-17       Impact factor: 17.586

10.  Clinical Characteristics of Covid-19 in New York City.

Authors:  Parag Goyal; Justin J Choi; Laura C Pinheiro; Edward J Schenck; Ruijun Chen; Assem Jabri; Michael J Satlin; Thomas R Campion; Musarrat Nahid; Joanna B Ringel; Katherine L Hoffman; Mark N Alshak; Han A Li; Graham T Wehmeyer; Mangala Rajan; Evgeniya Reshetnyak; Nathaniel Hupert; Evelyn M Horn; Fernando J Martinez; Roy M Gulick; Monika M Safford
Journal:  N Engl J Med       Date:  2020-04-17       Impact factor: 176.079

View more
  6 in total

Review 1.  Clinical update on COVID-19 for the emergency clinician: Cardiac arrest in the out-of-hospital and in-hospital settings.

Authors:  William J Brady; Summer Chavez; Michael Gottlieb; Stephen Y Liang; Brandon Carius; Alex Koyfman; Brit Long
Journal:  Am J Emerg Med       Date:  2022-04-27       Impact factor: 4.093

2.  The National COVID Cohort Collaborative: Clinical Characterization and Early Severity Prediction.

Authors:  Tellen D Bennett; Richard A Moffitt; Janos G Hajagos; Benjamin Amor; Adit Anand; Mark M Bissell; Katie Rebecca Bradwell; Carolyn Bremer; James Brian Byrd; Alina Denham; Peter E DeWitt; Davera Gabriel; Brian T Garibaldi; Andrew T Girvin; Justin Guinney; Elaine L Hill; Stephanie S Hong; Hunter Jimenez; Ramakanth Kavuluru; Kristin Kostka; Harold P Lehmann; Eli Levitt; Sandeep K Mallipattu; Amin Manna; Julie A McMurry; Michele Morris; John Muschelli; Andrew J Neumann; Matvey B Palchuk; Emily R Pfaff; Zhenglong Qian; Nabeel Qureshi; Seth Russell; Heidi Spratt; Anita Walden; Andrew E Williams; Jacob T Wooldridge; Yun Jae Yoo; Xiaohan Tanner Zhang; Richard L Zhu; Christopher P Austin; Joel H Saltz; Ken R Gersing; Melissa A Haendel; Christopher G Chute
Journal:  medRxiv       Date:  2021-01-23

3.  Role of IgG against N-protein of SARS-CoV2 in COVID19 clinical outcomes.

Authors:  Mayank Batra; Runxia Tian; Chongxu Zhang; Emile Clarence; Camila Sofia Sacher; Justin Nestor Miranda; Justin Rafa O De La Fuente; Megan Mathew; Desmond Green; Sayari Patel; Maria Virginia Perez Bastidas; Sara Haddadi; Mukunthan Murthi; Miguel Santiago Gonzalez; Shweta Kambali; Kayo H M Santos; Huda Asif; Farzaneh Modarresi; Mohammad Faghihi; Mehdi Mirsaeidi
Journal:  Sci Rep       Date:  2021-02-10       Impact factor: 4.379

4.  Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative.

Authors:  Tellen D Bennett; Richard A Moffitt; Janos G Hajagos; Benjamin Amor; Adit Anand; Mark M Bissell; Katie Rebecca Bradwell; Carolyn Bremer; James Brian Byrd; Alina Denham; Peter E DeWitt; Davera Gabriel; Brian T Garibaldi; Andrew T Girvin; Justin Guinney; Elaine L Hill; Stephanie S Hong; Hunter Jimenez; Ramakanth Kavuluru; Kristin Kostka; Harold P Lehmann; Eli Levitt; Sandeep K Mallipattu; Amin Manna; Julie A McMurry; Michele Morris; John Muschelli; Andrew J Neumann; Matvey B Palchuk; Emily R Pfaff; Zhenglong Qian; Nabeel Qureshi; Seth Russell; Heidi Spratt; Anita Walden; Andrew E Williams; Jacob T Wooldridge; Yun Jae Yoo; Xiaohan Tanner Zhang; Richard L Zhu; Christopher P Austin; Joel H Saltz; Ken R Gersing; Melissa A Haendel; Christopher G Chute
Journal:  JAMA Netw Open       Date:  2021-07-01

5.  Clinical Mortality Review of COVID-19 Patients at Sukraraj Tropical and Infectious Disease Hospital, Nepal; A Retrospective Study.

Authors:  Anup Bastola; Sanjay Shrestha; Richa Nepal; Kijan Maharjan; Bikesh Shrestha; Bimal Sharma Chalise; Pratistha Thapa; Pujan Balla; Alisha Sapkota; Priyanka Shah
Journal:  Trop Med Infect Dis       Date:  2021-07-19

Review 6.  Heart failure in COVID-19 patients: Critical care experience.

Authors:  Kevin John John; Ajay K Mishra; Chidambaram Ramasamy; Anu A George; Vijairam Selvaraj; Amos Lal
Journal:  World J Virol       Date:  2022-01-25
  6 in total

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