| Literature DB >> 36192763 |
Ashwin Subramaniam1,2,3, Kiran Shekar4,5,6, Christopher Anstey7, Ravindranath Tiruvoipati8,9, David Pilcher10,11,12.
Abstract
BACKGROUND: It is unclear if the impact of frailty on mortality differs between patients with viral pneumonitis due to COVID-19 or other causes. We aimed to determine if a difference exists between patients with and without COVID-19 pneumonitis.Entities:
Keywords: ANZICS-APD; CFS; COVID-19; Clinical Frailty Scale; Frailty; Pandemic
Mesh:
Year: 2022 PMID: 36192763 PMCID: PMC9527725 DOI: 10.1186/s13054-022-04177-9
Source DB: PubMed Journal: Crit Care ISSN: 1364-8535 Impact factor: 19.334
Baseline characteristics of patients with and without COVID-19
| Variable | Patients with COVID-19 | Patients without COVID-19 | |
|---|---|---|---|
| Number | 3077 | 1543 | – |
| Frailty status, | |||
| CFS-1–3 | 2298 (74.7%) | 620 (40.2%) | < 0.001 |
| CFS-4 | 410 (13.3%) | 408 (26.4%) | |
| CFS-5 | 157 (5.1%) | 206 (13.4%) | |
| CFS-6 | 144 (4.7%) | 203 (13.2%) | |
| CFS-7–8 | 68 (2.2%) | 106 (6.9%) | |
| CFS—Frailty score (median [IQR]) | 3 (2, 4) | 4 (3, 5) | < 0.001 |
| Age (years) [median (IQR)] | 57.0 (44.7, 68.3) | 66.1 (52.0, 76.2) | < 0.001 |
| Male sex, | 1887 (61.3%) | 792 (51.3%) | < 0.001 |
| Indigenous status, | 79 (2.7%) | 139 (9.3%) | < 0.001 |
| Jurisdiction, | |||
| New South Wales | 1486 (48.3%) | 466 (30.2%) | < 0.001 |
| Victoria | 1387 (45.1%) | 396 (25.7%) | |
| Queensland | 37 (1.2%) | 257 (16.7%) | |
| Western Australia | 37 (1.2%) | 117 (7.6%) | |
| South Australia | 2 (0.1%) | 62 (4.0%) | |
| Tasmania | 2 (0.1%) | 25 (1.6%) | |
| Australian Capital Territory | 60 (1.9%) | 62 (4.0%) | |
| Northern Territory | 4 (0.1%) | 49 (3.2%) | |
| New Zealand, | 62 (2.0%) | 109 (7.1%) | |
| Admission source, | |||
| Home | 2483 (80.7%) | 1199 (77.7%) | < 0.001 |
| Other acute hospital | 280 (8.4%) | 251 (16.3%) | |
| Nursing home or chronic care | 15 (0.5%) | 21 (1.4%) | |
| Other hospital ICU | 260 (8.4%) | 52 (3.4%) | |
| Rehabilitation | 3 (0.1%) | 6 (0.4%) | |
| Missing | 36 (1.2%) | 14 (0.9%) | |
| ICU admission source, | |||
| Emergency department (ED) | 1198 (38.9%) | 660 (42.8%) | < 0.001 |
| Ward | 1486 (48.3%) | 714 (46.3%) | |
| Other hospital (ED and ICU) | 378 (12.2%) | 161 (10.4%) | |
| Operating theatre/recovery | 1 (0.0%) | 2 (0.1%) | |
| Direct admit | 14 (0.5%) | 6 (0.4%) | |
| Documented co-morbidities, | |||
| Chronic respiratory condition | 201 (6.5%) | 305 (19.8%) | < 0.001 |
| Chronic cardiovascular condition | 180 (5.8%) | 189 (12.2%) | < 0.001 |
| Chronic renal failure | 74 (2.4%) | 183 (11.9%) | < 0.001 |
| Chronic liver disease | 22 (0.7%) | 37 (2.4%) | < 0.001 |
| Diabetes mellitus | 866 (29.3%) | 415 (28.4%) | 0.019 |
| Immune suppressive therapy | 147 (4.8%) | 182 (11.8%) | < 0.001 |
| Lymphoma | 13 (0.4%) | 29 (1.9%) | < 0.001 |
| Leukaemia | 26 (0.8%) | 77 (5.0%) | < 0.001 |
| Metastatic cancer | 25 (0.8%) | 59 (3.8%) | < 0.001 |
| Obese (BMI ≥ 30 kg m−2) | 1,061 (34.5%) | 412 (26.7%) | < 0.001 |
| Delirium | 261 (8.5%) | 116 (7.5%) | < 0.001 |
| Pregnancy status | 72 (2.3%) | 13 (0.8%) | < 0.001 |
| Pre-ICU (days) (median [IQR]) | 0.35 (0.13, 1.63) | 0.38 (0.14, 1.39) | 0.90 |
| Organ failure scores | |||
| APACHE III (mean [SD]) | 50.1 (20.0) | 58.4 (21.7) | < 0.001 |
| ANZROD (%) (mean [SD]) | 9.6 (12.3) | 16.0 (18.2) | < 0.001 |
| ICU admission post MET call | 1107 (36.2%) | 603 (39.3%) | 0.045 |
| Treatment limitations | 248 (8.1%) | 299 (19.4%) | < 0.001 |
| Cardiac arrest, | 6 (0.2%) | 8 (0.5%) | 0.08 |
| ICU Supports | |||
| Mechanical ventilation (MV), | 1314 (43.2%) | 328 (22.1%) | < 0.001 |
| MV duration (hours), median (IQR) | 178.0 (68.0, 348.8) | 92.0 (37.0, 204.5) | < 0.001 |
| Non-invasive ventilation (NIV), | 1268 (41.9%) | 750 (50.0%) | < 0.001 |
| NIV duration (hours), median (IQR) | 21.0 (4.3, 66.0) | 11.0 (3.0, 30.0) | < 0.001 |
| Vasopressor and inotropes, | 1197 (39.3%) | 461 (30.8%) | < 0.001 |
| Renal replacement therapy, | 182 (6.0%) | 162 (10.9%) | < 0.001 |
| Extracorporeal membrane oxygenation | 106 (3.5%) | 25 (1.7%) | < 0.001 |
| Tracheostomy, | 190 (6.3%) | 38 (2.6%) | < 0.001 |
CFS: Clinical Frailty Scale, SD: standard deviation, IQR: interquartile range, BMI: body mass index, MET: medical emergency team, APACHE: Acute Physiology and Chronic Health Evaluation, ED: emergency department, ICU: intensive care unit, ROD: risk of death, ANZROD: Australia and New Zealand Risk of Death
Please refer to Additional file 2: Tables 3a and S3b for baseline characteristics based on CFS categories
Fig. 1Hospital mortality according to Clinical Frailty Scale (CFS) score for all patients with (red lines) with and without (black lines) COVID-19. The top panel is unadjusted hospital mortality, while the bottom panel is adjusted for ANZROD and sex
Unadjusted hospital mortality in patients with and without COVID-19 (overall and at different levels of frailty) (Also refer to Fig. 2)
| Patients with COVID-19, OR (95% CI) | Patients without COVID-19, OR (95% CI) | |||
|---|---|---|---|---|
| CFS | 1.29 (1.19–1.41) | < 0.001 | 1.24 (1.11–1.37) | < 0.001 |
| Male sex | 1.59 (1.25–2.04) | < 0.001 | 1.29 (0.94–1.77) | 0.12 |
| ANZROD | 1.07 (1.06–1.08) | < 0.001 | 1.05 (1.04–1.06) | < 0.001 |
CFS: Clinical Frailty Scale; ANZROD: Australian and New Zealand Risk of Death
Fig. 2Area under the receiver operating curve with the Clinical Frailty Scale (CFS) treated as categories (CFS-1–3, CFS-4, CFS-5, CFS-6, and CFS-7–8). The comparison between models was assessed using chi-square tests and presented as p values
Fig. 3Hospital mortality according to Clinical Frailty Scale (CFS) categories for patients with (red) and without (black) COVID-19: a male sex, b female sex, c ≥ 65 years of age, and d those needing mechanical ventilation. The top panel is unadjusted hospital mortality, while the bottom panel is adjusted analysis. Biological sex was adjusted only for ANZROD, while others are adjusted for ANZROD and sex