Case Fatality Rates for Patients with COVID-19 Requiring Invasive Mechanical Ventilation. A Meta-analysis
1,* Ashwin Subramaniam,2,3,* Mallikarjuna Ponnapa Reddy,2,4 Gabriel Blecher,5,6 Umesh Kadam,7,8 Afsana Afroz,9,10 Baki Billah,9 Sushma Ashwin,11 Mark Kubicki,1 Federico Bilotta,12 J. Randall Curtis,13,14 and Francesca Rubulotta15Associated Data
Abstract
Rationale: Initial reports of case fatality rates (CFRs) among adults with coronavirus disease (COVID-19) receiving invasive mechanical ventilation (IMV) are highly variable.
Objectives: To examine the CFR of patients with COVID-19 receiving IMV.
Methods: Two authors independently searched PubMed, Embase, medRxiv, bioRxiv, the COVID-19 living systematic review, and national registry databases. The primary outcome was the “reported CFR” for patients with confirmed COVID-19 requiring IMV. “Definitive hospital CFR” for patients with outcomes at hospital discharge was also investigated. Finally, CFR was analyzed by patient age, geographic region, and study quality on the basis of the Newcastle-Ottawa Scale.
Measurements and Results: Sixty-nine studies were included, describing 57,420 adult patients with COVID-19 who received IMV. Overall reported CFR was estimated as 45% (95% confidence interval [CI], 39–52%). Fifty-four of 69 studies stated whether hospital outcomes were available but provided a definitive hospital outcome on only 13,120 (22.8%) of the total IMV patient population. Among studies in which age-stratified CFR was available, pooled CFR estimates ranged from 47.9% (95% CI, 46.4–49.4%) in younger patients (age ≤40 yr) to 84.4% (95% CI, 83.3–85.4%) in older patients (age >80 yr). CFR was also higher in early COVID-19 epicenters. Overall heterogeneity is high (I2 >90%), with nonsignificant Egger’s regression test suggesting no publication bias.
Conclusions: Almost half of patients with COVID-19 receiving IMV died based on the reported CFR, but variable CFR reporting methods resulted in a wide range of CFRs between studies. The reported CFR was higher in older patients and in early pandemic epicenters, which may be influenced by limited ICU resources. Reporting of definitive outcomes on all patients would facilitate comparisons between studies.
Systematic review registered with PROSPERO (CRD42020186997).
The novel coronavirus disease (COVID-19) pandemic, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has severely burdened healthcare system capacities in many parts of the world (1). The World Health Organization reports the global crude mortality rate to be 3.9% (2).
The care of critically ill patients with COVID-19 has been rapidly evolving (3). Although there have been promising therapies such as remdesivir (4) and dexamethasone (5), mechanical ventilation continues to be the mainstay of management of severe COVID-19 (6). Hypoxemia (PaO2 <60 mm Hg) has been commonly reported in hospitalized patients with COVID-19 (7). Early invasive mechanical ventilation (IMV) was promoted early in the pandemic because of concerns of aerosol generation from noninvasive oxygenation therapies facilitating nosocomial viral transmission (8–10).
The case fatality rate (CFR) is defined as the proportion of a population with a disease that dies during a specific period (11). The reported CFRs of critically ill patients with COVID-19 receiving IMV have been observed to be highly variable (12). Causes of this inconsistency likely include the heterogeneity in the management of these patients and in the presentation of outcome data (12, 13). Addressing this knowledge gap will assist in intensive care resource planning and public health strategies.
The aim of this systematic review and meta-analysis was to report the CFR of critically ill adult patients with COVID-19 who received IMV based on the available evidence. The variability in CFR by patient age, geographic region, and study quality was also analyzed in this study.
Methods
This systematic review and meta-analysis was reported using the preferred reporting items for systematic reviews and meta-analyses framework (14) and has been registered on PROSPERO (CRD42020186997). The majority of patients receiving IMV are admitted to the ICU; however, not all ICU patients receive IMV. We therefore included studies explicitly reporting on patients receiving IMV to limit heterogeneity in illness severity. The review process is illustrated in a flow diagram (Figure 1).
Eligibility Criteria
Only studies reporting on consecutive adult patients (≥18 yr of age) with laboratory-confirmed COVID-19 receiving IMV were included. Studies were excluded if 1) the sample size of the cohort was less than 10, 2) they did not report the results of original research, or 3) the cohort consisted only of deceased patients. Studies were also excluded if a significant overlap in patient cohorts was identified.
Search Strategy, Information Sources, and Study Selection
Two authors (Z.J.L. and A.S.) independently searched on the publicly available COVID-19 living systematic review. This dynamic systematic review contains a daily updated list of preprint and published articles relating to COVID-19 obtained from PubMed, EMBASE, medRxiv, and bioRxiv (15). The workflow for obtaining these articles is freely available and has been used previously during the Zika virus epidemic (16). This living platform has been recently validated against an Ovid search relating to COVID-19 (17). Two authors (Z.J.L. and M.P.R.) independently extracted the content of this living systematic review and national registry databases between January 1, 2020, and July 8, 2020. Conflicts in data extraction were resolved by discussion between the reviewers or adjudication by a third author (A.S.). Corresponding authors for all the selected papers were contacted by e-mail for outcome data for patients who were still in the hospital at the time the manuscript was published. The search terms “mortality,” “fatality,” “ICU,” “characteristic,” “invasive,” “mechanical,” “ventilation,” “death,” and “died” were used within the title and abstract columns of the systematic review list. The searching criteria were combined with the Boolean operator “OR.” All studies, including preprint and non-English language articles, were considered. A separate search for COVID-19 national registries was also conducted. Study period and location were analyzed as part of the data collection process.
Definitions
Reported CFR
“Reported CFR” was defined as the CFR among all patients who received IMV, before accounting for patients who were still receiving care in hospital.
Range of estimates for CFR
We also provided a sensitivity analysis of the best possible and worse possible CFRs, assuming all remaining hospitalized patients either lived (lowest possible) or died (highest possible) in the subset of studies that reported the number of patients who received IMV who were still hospitalized at the time of study conclusion.
Definitive CFR
We examined the number of patients receiving IMV who died divided by the number of patients with a known hospital outcome (died or discharged alive) to calculate the definitive CFR.
Quality Assessment and Risk of Bias in Individual Studies
The Newcastle-Ottawa Scale (NOS) is a quality assessment tool used to evaluate nonrandomized studies on the basis of an eight-item score divided into three domains. The NOS has been selected for the purpose of this study because these domains assess selection, comparability, and ascertainment of the outcome of interest. The NOS is the most suitable for the purpose of comparing both reported and definitive CFR values. The NOS was used by the two reviewers (Z.J.L. and U.K.) to independently evaluate the quality of included studies and assess for risk of bias (18). The same set of decision rules was used by each reviewer to score the studies. Any discrepancies from the NOS were reviewed and resolved by two additional authors (A.S. and M.P.R.).
Study Outcomes
The primary outcome was the reported CFR for patients with COVID-19 receiving IMV based on the published studies. However, multiple methods of reporting CFR existed across different studies. Studies have reported the CFR of patients receiving IMV out of all patients receiving IMV, including those still hospitalized, whereas other studies have reported the CFR among patients who have completed their hospital course. This variance in reporting methods therefore resulted in variance in the CFRs reported by authors. As a secondary outcome, we examined the “definitive hospital CFR” for the subgroup of studies for whom we were able to ascertain hospital discharge outcomes. For all studies, we also present a sensitivity analysis that includes all patients showing “lowest possible” CFR for each study (assuming all patients still hospitalized lived) and a “highest possible” CFR (assuming all patients still hospitalized died). Within the appendix, the definitive hospital CFR is calculated by excluding patients who were still hospitalized to report the CFR only among patients with a known hospital outcome. Studies were also stratified based on geographical location (continent), economy (based on United Nations classification 2020), mean age, and study quality.
Data Analysis and Data Collection Process
Statistical analyzes were performed using the statistical software package Stata, version 16.1 (StataCorp). Mean and SD were used for numerical data and proportion was used for categorical data. The random-effects model and the Hartung-Knapp-Sidik-Jonkman method for meta-analysis (19) were used for the pooled prevalence of CFR because these demonstrate better properties in the presence of heterogeneity, accounting for both within-study and between-study variances (20). Results were presented in forest plots. Heterogeneity was tested by using the χ2 test on Cochran’s Q statistic, which was calculated by means of H and I2 indices. The I2 index estimates the percentage of total variation across studies on the basis of true between-study differences rather than on chance. Conventionally, I2 values of 0–25% indicate low heterogeneity, values of 26–75% indicate moderate heterogeneity, and values of 76–100% indicate substantial heterogeneity. Authors conducted subgroup analyzes to identify the possible causes of substantial heterogeneity (21). Univariable metaregression was used, symmetry of the funnel plots was evaluated, and the Egger’s regression test was used to examine for publication bias (22). Confidence interval (CI) was used to evaluate whether differences in CFRs were statistically significant. The 95% CI of prevalence including 0.0% and 100% were calculated using the standard equation (23). As prevalence cannot fall below 0% or above 100%, the CI is trimmed at 0% and 100% (20).
Additional Analyses
We also examined the reported CFR based on age stratification for the subset of studies that reported outcomes by patient age. In addition, we compared the CFRs in studies from different geographic regions and examined difference between reports from cities with an early and dramatic pandemic outbreak, such as Hubei, China, and New York, United States, compared with studies from other cities in the same country.
Results
A total of 5,322 studies were obtained from the living systematic review with 662 unique studies assessed for eligibility via full-text screening (Figure 1). Sixty-nine studies across 23 countries with reported CFRs were included in the final analysis (13, 24–91), including publicly available national registry data from seven countries (29, 56, 59, 65, 66, 80, 90). A summary of the reported CFRs for adult patients receiving IMV is outlined in Table 1. A total of 121,009 patients with confirmed COVID-19 were reported across 69 studies, with 89,405 patients (73.9%) from national registry data. Across 69 studies, 66,900 patients were male (55.3%). The patients’ mean age, as derived by the estimation formula to convert median to mean values (92), was 59.9 years. IMV was administered to 57,420 patients. Fifty-four of the 69 studies reported on the number of patients receiving IMV still hospitalized at the time of study conclusion.
Table 1.
The 69 Studies Selected for the Systematic Review and Meta-analysis
| Study | Location of Study | Sample Size (N) | Mean Age (yr) | Sex, M (n) | Received IMV (n) | IMV Patients Still Receiving Care (n) | Died after IMV (n) | IMV Patients with Definitive Hospital Outcome [n (%)] | Primary Outcome: CFR of Patients Requiring IMV by Reported Outcome [% (95% CI)] | |
|---|---|---|---|---|---|---|---|---|---|---|
| Chen et al., May 2020 (24) | Hubei, China | 135 | NR | 78 | 9 | 0 | 6 | 9 (100) | 67 (40–93) | |
| Hu et al., May 2020 (25) | Hubei, China | 323 | 59.0 | 166 | 34 | NR | 31 | NR | 91 (80–100) | |
| Hu and Li, May 2020 (26) | Hubei, China | 105 | 58.2 | 66 | 67 | NR | 39 | NR | 58 (47–70) | |
| Hua et al., June 2020 (27) | Hubei, China | 469 | 68.0 | 76 | 113 | 0 | 104 | 113 (100) | 92 (87–97) | |
| Huang et al., June 2020 (28) | Changsha, China | 238 | 45.0 | 117 | 4 | NR | 2 | NR | 50 (15–85) | |
| Japan registry, July 2020 (29) | Japan | 575 | NR | NR | 575 | 67 | 133 | 508 (88) | 23 (20–27) | |
| Jung et al., May 2020 (30) | South Korea | 5,179 | 44.6 | 2,295 | 36 | NR | 21 | NR | 58 (43–74) | |
| Liao et al., April 2020 (31) | Sichuan, China | 81 | 51.3 | 66 | 10 | 7 | 3 | 3 (30) | 30 (5–55) | |
| Nasir et al., June 2020 (32) | Karachi, Pakistan | 30 | 62.5 | 25 | 10 | 0 | 5 | 10 (100) | 50 (24–76) | |
| Ratanarat et al., July 2020 (33) | Bangkok, Thailand | 13 | 58.0 | 8 | 5 | 0 | 0 | 5 (100) | 0 (0–27) | |
| Ruan et al., March 2020 (34) | Hubei, China | 150 | NR | 102 | 25 | 0 | 25 | 25 (100) | 100 (91–100) | |
| Shi et al., June 2020 (35) | Hubei, China | 671 | 61.7 | 322 | 36 | NR | 29 | NR | 81 (68–93) | |
| Sirivongrangson et al., June 2020 (36) | Bangkok, Thailand | 19 | 52.0 | 15 | 10 | 2 | 0 | 8 (80) | 0 (0–18) | |
| Wang et al., April 2020 (37) | Anhui, China | 125 | 38.8 | 71 | 4 | 3 | 0 | 1 (25) | 0 (0–30) | |
| Wang, June 2020 (38) | Nationwide, China | 141 | 63.0 | 99 | 50 | 25 | 25 | 25 (50) | 50 (37–63) | |
| Wang, March 2020 (39) | Hubei, China | 18 | 70.4 | 10 | 18 | 12 | 5 | 6 (33) | 28 (8–47) | |
| Yang et al., May 2020 (40) | Hubei, China | 59 | 66.1 | 40 | 59 | NR | 36 | NR | 61 (49–73) | |
| Yang et al., May 2020 (41) | Hubei, China | 52 | 59.7 | 35 | 22 | 3 | 19 | 19 (86) | 86 (71–100) | |
| Ye et al., June 2020 (42) | Zhejiang, China | 856 | 46.0 | 439 | 29 | NR | 1 | NR | 3 (0–13) | |
| Young et al., March 2020 (43) | Singapore | 18 | 49.5 | 9 | 1 | 0 | 0 | 1 (100) | 0 (0–44) | |
| Yu et al., May 2020 (44) | Hubei, China | 226 | 63.0 | 139 | 121 | 6 | 79 | 115 (95) | 65 (57–74) | |
| Zhao et al., June 2020 (45) | Henan, China | 29 | 51.2 | 14 | 5 | 0 | 1 | 5 (100) | 20 (0–51) | |
| Zheng et al., May 2020 (46) | Hangzhou, China | 34 | 66.7 | 23 | 15 | 13 | 0 | 2 (13) | 0 (0–14) | |
| Zhu et al., June 2020 (47) | Hubei, China | 102 | 65.2 | 59 | 29 | 0 | 25 | 29 (100) | 86 (73–99) | |
| Almazeedi et al., May 2020 (48) | South Surra, Kuwait | 1,096 | 41 | 888 | 31 | 16 | 13 | 15 (48) | 42 (26–58) | |
| Goshayeshi et al., May 2020 (49) | Mashhad, Iran | 1,067 | 56.9 | 663 | 231 | 32 | 81 | 199 (86) | 35 (29–41) | |
| Khamis et al., July 2020 (50) | Oman | 63 | 48.0 | 53 | 16 | NR | 5 | NR | 31 (10–52) | |
| Rinott et al., June 2020 (51) | Israel | 403 | 44.0 | 220 | 17 | NR | 12 | NR | 71 (50–91) | |
| Shahriarirad et al., June 2020 (52) | South Iran, Iran | 113 | 53.8 | 71 | 2 | 0 | 2 | 2 (100) | 100 (62–100) | |
| Alfano et al., June 2020 (53) | Modena, Italy | 307 | 65.2 | 219 | 53 | 14 | 17 | 39 (74) | 32 (20–44) | |
| Busetto et al., May 2020 (54) | Veneto, Italy | 92 | 70.5 | 57 | 9 | 0 | 0 | 9 (100) | 0 (0–20) | |
| Ceruti et al., May 2020 (55) | Lugano, Switzerland | 41 | 64.0 | 35 | 34 | 4 | 7 | 30 (88) | 21 (7–34) | |
| France registry, June 2020 (56) | France | 4,007 | 65.0 | 2,925 | 2,357 | NR | 480 | NR | 20 (19–22) | |
| Giacomelli et al., May 2020 (57) | Lombardy, Italy | 233 | 61.0 | 72 | 8 | 0 | 7 | 8 (100) | 88 (63–100) | |
| Grasselli et al., April 2020 (58) | Lombardy, Italy | 1,591 | 63.0 | 1,304 | 1,150 | NR | 329 | NR | 29 (26–31) | |
| ICNARC, 10 July 2020 (59) | United Kingdom | 10,421 | 58.8 | 320 | 7,185 | 426 | 3,479 | 6,759 (94) | 48 (47–50) | |
| Israelsen et al., May 2020 (60) | Hvidovre, Denmark | 175 | 69.0 | 85 | 27 | 8 | 17 | 19 (70) | 63 (46–80) | |
| Pavoni et al., May, 2020 (61) | Tuscany, Italy | 40 | 61.0 | 24 | 4 | 1 | 3 | 3 (75) | 75 (41–100) | |
| Pedersen et al., April 2020 (62) | Zealand, Denmark | 17 | 69.8 | 12 | 17 | 6 | 7 | 11 (65) | 41 (20–62) | |
| Piano et al., June 2020 (63) | Northern Italy, Italy | 584 | 66.0 | 357 | 62 | 10 | 18 | 52 (84) | 29 (18–40) | |
| Regina et al., May 2020 (64) | Lausanne, Switzerland | 200 | 66.0 | 120 | 38 | NR | 11 | NR | 29 (15–43) | |
| Spain registry, July 2020 (65) | Spain | 7,695 | 60.3 | 5,344 | 3,867 | NR | 1,943 | NR | 50 (49–52) | |
| Sweden registry July, 2020 (66) | Sweden | 3,437 | 59.2 | 2,530 | 2,412 | 58 | 455 | 2,354 (98) | 19 (17–20) | |
| Zangrillo et al., April 2020 (67) | Lombardy, Italy | 73 | 61.3 | 61 | 73 | 33 | 17 | 40 (55) | 23 (14–33) | |
| Aggarwal et al., May 2020 (68) | Iowa, United States | 16 | 65.5 | 12 | 5 | 0 | 0 | 5 (100) | 0 (0–27) | |
| Arentz et al., March 2020 (69) | Washington/Seattle, United States | 21 | 70 | 11 | 15 | 3 | 10 | 12 (80) | 67 (45–88) | |
| Argenziano et al., May 2020 (70) | New York, United States | 1,000 | 62.7 | 596 | 233 | 86 | 111 | 147 (63) | 48 (41–54) | |
| Auld et al., May 2,020 (71) | Georgia, United States | 217 | 63.7 | 119 | 165 | 11 | 56 | 154 (93) | 34 (27–41) | |
| Bhatraju et al., March 2020 (72) | Washington/Seattle, United States | 24 | 64.0 | 15 | 18 | 3 | 9 | 15 (83) | 50 (29–71) | |
| Buckner et al., May 2020 (73) | Washington/Seattle, United States | 105 | 64.5 | 53 | 19 | 0 | 10 | 19 (100) | 53 (32–73) | |
| Ferguson et al., July 2020 (74) | California, United States | 72 | 58.1 | 38 | 13 | 4 | 3 | 9 (69) | 23 (1–45) | |
| Garibaldi et al., May 2020 (75) | Maryland, United States | 832 | 60.4 | 443 | 70 | 24 | 24 | 46 (66) | 34 (23–45) | |
| Gold et al., May 2020 (76) | Georgia, United States | 305 | 58.8 | 151 | 92 | 6 | 38 | 86 (93) | 41 (31–51) | |
| Goyal et al., April 2020 (77) | New York, United States | 393 | 61.5 | 238 | 130 | 88 | 19 | 42 (32) | 15 (8–21) | |
| Klang et al., May 2020 (78) | New York, United States | 3,406 | NR | 1,961 | 809 | 0 | 682 | 809 (100) | 84 (82–87) | |
| Mani et al., June 2020 (79) | New York, United States | 184 | 64.7 | 111 | 30 | 17 | 13 | 13 (43) | 43 (27–60) | |
| Mexico registry, July 2020 (80) | Mexico | 6,898 | 57.3 | 4,665 | 6,898 | NR | 4,724 | NR | 68 (67–70) | |
| Mitra et al., June 2020 (81) | Vancouver, Canada | 117 | 68.0 | 79 | 74 | 25 | 15 | 49 (66) | 20 (11–29) | |
| Palaiodimos et al., July 2020 (82) | New York, United States | 200 | 62.5 | 98 | 42 | 0 | 32 | 42 (100) | 76 (63–89) | |
| Petrilli et al., May 2020 (83) | New York, United States | 2,721 | 62.7 | 1,678 | 647 | 86 | 391 | 561 (87) | 60 (57–64) | |
| Reyes Gil et al., May 2020 (84) | New York, United States | 217 | NR | 126 | 55 | 0 | 45 | 55 (100) | 82 (72–92) | |
| Richardson et al., April 2020 (85) | New York, United States | 5,700 | 60.9 | 3,437 | 1,151 | 831 | 282 | 320 (28) | 25 (22–27) | |
| Salacup et al., July 2020 (86) | Philadelphia, United States | 242 | 66.0 | 123 | 54 | 0 | 38 | 54 (100) | 70 (58–82) | |
| Shekhar et al., May 2020 (87) | New Mexico, United States | 50 | 54.0 | 23 | 22 | 6 | 12 | 16 (73) | 55 (35–74) | |
| Shi et al., July 2020 (88) | Michigan, United States | 172 | 61.5 | 97 | 61 | 2 | 16 | 59 (97) | 26 (15–37) | |
| Suleyman et al., June 2020 (89) | Michigan, United States | 355 | 57.5 | 204 | 114 | 6 | 91 | 108 (95) | 80 (45–100) | |
| Ziehr et al., June 2020 (13) | Massachusetts, United States | 66 | 56.5 | 43 | 66 | 0 | 11 | 66 (100) | 17 (8–26) | |
| Brazil registry, July 2020 (90) | Brazil | 56,372 | 68.2 | 32,940 | 27,748 | NR | 19,935 | NR | 72 (71–72) | |
| Olivares et al., June 2020 (91) | Valdivia, Chile | 21 | 58.9 | 5 | 9 | 0 | 2 | 9 (100) | 22 (0–47) | |
Definition of abbreviations: CFR = case fatality rate; CI = confidence interval; ICNARC = Intensive Care National Audit and Research Centre; IMV = invasive mechanical ventilation; NR = not reported.
Primary Outcome: Reported CFR of Patients with Severe COVID-19 Receiving IMV
The reported CFR across these studies was calculated at 45% (95% CI, 39–52%). Although a high heterogeneity was observed across all studies (I2 = 99.52%), our Egger’s regression test for publication bias was 0.43 (nonsignificant). High heterogeneity was observed when studies were analyzed by continent (I2 >90%). The reported CFRs varied between 36% (95% CI, 24–48%) and 52% (95% CI, 19–85%) among different continents, with no significant difference in CFRs. The forest plot is illustrated in Figure 2. Individual study NOS score is illustrated in Table E1 in the online supplement. There was no significant difference in CFR when studies were analyzed based on NOS score (Figure E1).
Range of Estimates for CFR
Fifty-four studies reported on the number of patients who were still hospitalized at the time of publication. Across these 54 studies, 15,064 of 35,880 patients (42.0%) received IMV. The sensitivity analysis comparing the “lowest possible” CFR (assuming all patients still hospitalized lived) with the “highest possible” CFR (assuming all patients still hospitalized died) ranged from 43% (95% CI, 36–51%) to 64% (95% CI, 56–72%) (Table E2).
Definitive CFR
A total of 13,120 of 15,064 (87.1%) patients (22.8% of the total IMV cohort) completed their hospital stay. Among these patients, 6,463 of 13,120 patients died (49.5%). The adjusted CFR among these patients was 56% (95% CI, 47–65%) (Figure E2). Within this subset of patients, no statistically significant differences in definitive hospital CFRs were observed when analyzing studies by geographical location (continent), economy, mean age (studies with main age >70 yr had a statistically lower CFR; however, the number of patients who received IMV was small [N = 10]), or study quality (Figures E2–E5). Heterogeneity continued to remain high (I2 >90%) across all analyses.
Analysis of CFR Based on Patient Age and Studies from Early COVID-19 Epicenters
Three studies and three national registries (39, 44, 58, 59, 80, 90) reported on 42,618 IMV patients, of whom 28,547 (67.0%) died, and stratified CFR by age. CFR was >70% among patients aged more than 60 years of age. CFR increased exponentially (y = 0.429e0.1162x) with increasing age (Figure 3).
Reported case fatality rates for patients receiving invasive mechanical ventilation stratified by age, reported in six studies. *Age stratification for ICNARC was 16–39, 40–49, 50–59, 60–69, 70–79, and ≥80. CFR = case fatality rate; CI = confidence interval; Expon. = exponential; ICNARC = Intensive Care National Audit and Research Centre; IMV = invasive mechanical ventilation.
The analysis comparing CFR in Wuhan with that of studies from other regions of China, as well as New York versus other regions in the United States, is illustrated in Figures E6 and E7. The reported CFR across 17 studies (encompassing 640 patients receiving IMV) from China reported an overall CFR of 56% (95% CI, 39–74%). Studies from Wuhan reported a significantly higher CFR of 75% (95% CI, 63–87%) compared with studies from other regions of China (20%; 95% CI 0–45%). Among patients with a known hospital outcome (N = 11 studies), the CFR reported from Wuhan (87%; 95% CI 77–97%) was lower than the CFR reported from other regions in China (33%; 95% CI, 0–82%).
An overall reported CFR of 47% (95% CI, 36–57%) was reported across 21 studies encompassing 3,811 patients with COVID-19 receiving IMV in the United States. Studies from New York reported a CFR of 54% (95% CI, 36–72%) whereas other regions in the United States reported a CFR of 41% (95% CI, 30–53%). When considering definitive outcomes, the overall CFR across 21 studies from the United States was 61% (95% CI 50–72%), with eight studies from New York reporting a significantly higher CFR of 78% (95% CI, 68–88%) compared with other regions in United States (49%; 95% CI, 35–63%).
Univariate and Multivariate Analysis
A simple regression (univariate) analysis and multivariate regression analysis were conducted across the 46 studies with definitive hospital outcome (Table E3). Studies were analyzed by common variables, including geographical location (continent), study quality (NOS score), mean age, and economic status. Poor-quality studies reported significantly lower CFRs compared with good-quality studies (P = 0.035). Multivariate regression did not yield any further statistical significance in study quality. A univariate analysis of studies from earlier epicenters (Wuhan and New York) showed significantly higher CFRs within these epicenters compared with nonepicenter studies in the same country (P = 0.010 for Wuhan vs. other studies in China and P = 0.002 for New York vs. other studies in the United States).
Discussion
This is a large international systematic review and meta-analysis to examine global reports of CFRs for adult patients with COVID-19 receiving IMV. The reported CFR was 45% across all 69 studies, but this included patients still in the hospital. Among all 54 studies, lowest possible to best possible hospital CFR ranged from 43% to 67%. Among patients with a known hospital outcome, the definitive hospital CFR was 56%. We observed no statistical difference between continents. Older patients had a higher CFR, and the CFR was higher in the early COVID-19 epicenters of Wuhan and New York compared with that of other studies from the same country.
The CFR observed in this review of patients with COVID-19 is similar to that of previous outbreaks of severe respiratory infections. Studies from SARS-CoV in 2003 reported a CFR of 45–48% in patients receiving IMV (93, 94), and more recent studies from the Middle East respiratory syndrome reported a 60–74% CFR in critically ill patients (95, 96). In contrast, the CFR is lower in critically ill patients suffering from H1N1 influenza A, in which the CFR of patients receiving IMV was 24.2–26.5% (97). The reported CFR from severe acute respiratory distress syndrome before COVID-19 was lower at 45% (98, 99) when compared with the definitive CFR from COVID-19.
The CFR of patients receiving IMV among studies from Wuhan and New York was significantly higher than that of studies from other regions in China and the United States, respectively. This finding may reflect of the significant challenges faced in the initial stages of the COVID-19 outbreak (100, 101). Reports suggest that prone positioning was infrequent in the initial phase (41), with one Wuhan study reporting only 12% of patients receiving IMV were managed with prone positioning. Variable provider:patient ratios may also have contributed to higher CFR (102–104).
Several factors may account for the large variance in CFRs between studies. ICUs outside of outbreak epicenters may have had the opportunity of time to obtain equipment and consolidate resources before the pandemic (71). This has enabled ICUs to continue at standard patient:provider ratios (71). Closer monitoring and early intensive care for critically ill patients potentially improved patient prognosis (31). Differences in hospital facilities, patient preferences (for which limitations of care may have been in place), and indications for IMV may have also influenced the CFR (12). Finally, the change in triage process considering comorbidities, age, and frailty status in allocating ICU beds and ventilators during the pandemic may have contributed to a lower CFR among patients receiving IMV, in which younger and less frail patients were prioritized for IMV and ICU care (105–108), whereas older and frailer patients were less likely to receive ventilatory support. These older patients potentially died without IMV support, which is not captured in our findings. If significant numbers of older patients died without receiving IMV support that was indicated and desired, this would suggest our CFR estimates for older patients may be low.
Despite stratifying studies on the basis of location and NOS score, high heterogeneity continued to exist across our meta-analysis. This has been reported in other meta-analyzes studying COVID-19 mortality (109–113). Heterogeneity was the lowest at 83.4% among definitive outcomes from Wuhan (Figure E6). Although the reasons for this are not clear, we believe that studies originating from the same geographical location may provide a less heterogeneous cohort, and hence, the I2 value was lower. Other potential factors influencing heterogeneity could be differences in illness severity, thresholds for IMV, admission criteria to the ICU, and regional differences in ICU care.
As demonstrated in a recent editorial, the CFR is substantially higher among older patients, with more than 70% of patients over 60 years of age receiving IMV dying (12). It has also been reported that the CFR for patients in their 80s and 90s receiving IMV with comorbidities has been higher (114). Our findings also suggest that older patients receiving IMV had significantly higher mortality.
There are several limitations to this systematic review. First, most of the included studies had very small numbers of patients; only 17 of 69 studies reported on more than 100 patients receiving IMV. Given the available evidence, we conducted a meta-analysis to account for this variability in sample size. Second, multiple studies may have covered similar patient cohorts. However, each study’s time period, hospital, and location were considered in the final inclusion of studies to minimize overlap in patient cohorts. Third, 14 studies were not peer reviewed, as they were prepublication articles. However, these studies still provided meaningful data on the CFR of the subgroup of patients with COVID-19 who receive IMV. Fourth, the overall heterogeneity was very high (I2 >90%), which may preclude a valid conclusion from pooled results. Although we performed various sensitivity and metaregression analyses, the heterogeneity could not be minimized. This is most likely due to the case mix and the structure of age within included populations. Finally, we were unable to examine the influence of timing in the pandemic because timing and region were highly correlated.
Conclusions
The reported CFR for existing studies of adult patients with COVID-19 receiving IMV was 45%, but many of these reports included patients still in the hospital at the time of publication. Accounting for patients still in the hospital, we found a best possible CFR of 43% and a worst possible CFR of 64%. The CFR increased exponentially in the elderly. Although CFRs did not vary between continents, higher CFRs were noted in early COVID-19 epicenters such as Wuhan and New York compared with other regions in the same country. Additional studies examining long-term CFRs beyond hospital discharge are needed.
Acknowledgment
The authors thank the following corresponding authors of the individual studies they reviewed for providing them with additional information to assist them with this meta-analysis: Drs. Frederick Buckner, Luca Busetto, Nina Kim, Won-Young Kim, Leonidas Palaiodimos, Dimitris Karamanis, Ranistha Ratanarat, Jason Knight, Shaoqiu Chen, Lara Gianesello, Yu (Ray) Zuo, Yogendra (Yogen) Kanthi, Benyamin Hoseini, Salvatore Piano, Nosheen Nasir, Gaetano Alfano, Shanti Kappagoda, Alberto Fica, Geehan Suleyman, Vishnu Mani, Lars Engerström, and Erik Svensk.
Footnotes
Author Contributions: Z.J.L. conceived the project idea, conducted the systematic review and statistical analysis, assisted with data analysis, wrote the initial drafts of the manuscript, created tables and figures, and finalized the manuscript. A.S. conceived the project idea, conducted the systematic review, assisted with data analysis, wrote the initial drafts of the manuscript, and finalized the manuscript. M.P.R. conducted the systematic review, assisted with data analysis, wrote the initial drafts of the manuscript, and finalized the manuscript. G.B. analyzed the data, wrote the initial drafts of the manuscript, and finalized the manuscript. U.K. conducted the systematic review, assisted with data analysis, wrote the initial drafts of the manuscript, and finalized the manuscript. A.A. conducted the statistical analysis and created the tables and figures. B.B. conducted the statistical analysis and wrote the statistical section in the methods. S.A. assisted with data collection and analysis and finalized the manuscript. M.K. analyzed the data, wrote the initial drafts of the manuscript, and finalized the manuscript. F.B. analyzed the data and finalized the manuscript. J.R.C. provided oversight for analysis of the data and edited the manuscript. F.R. analyzed the data and edited the manuscript. All authors critically reviewed the manuscript and approved the final version before submission.
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Originally Published in Press as DOI: 10.1164/rccm.202006-2405OC on October 29, 2020
Author disclosures are available with the text of this article at www.atsjournals.org.