Abstract
Background: Early intubation versus use of conventional or high-flow nasal cannula oxygen therapy (COT/HFNC), continuous positive airway pressure (CPAP), and non-invasive ventilation (NIV) has been debated throughout the COVID-19 pandemic. Our centre followed a stepwise approach, in concordance with German national guidelines, escalating non-invasive modalities prior to invasive mechanical ventilation (IMV) or extracorporeal membrane oxygenation (ECMO), rather than early or late intubation. Objectives: The aims of the study were to investigate the real-life usage of these modalities and analyse patient characteristics and survival. Method: A retrospective monocentric observation was conducted of all consecutive COVID-19 hospital admissions between March 2020 and December 2021 at a university-affiliated pulmonary centre in Germany. Anthropometric data, therapy, and survival status were descriptively analysed. Results: From 1,052 COVID-19-related admissions, 835 patients were included (54% male, median 58 years). Maximum therapy was as follows: 34% (n = 284) no therapy, 40% (n = 337) COT, 3% (n = 22) HFNC, 9% (n = 73) CPAP, 7% (n = 56) NIV, 4% (n = 34) IMV, and 3% (n = 29) ECMO. Of 551 patients treated with at least COT, 12.3% required intubation. Overall, 183 patients required intensive unit care, and 106 (13%) died. Of the 68 patients who received IMV/ECMO, 48 died (74%). The strategy for non-pharmacological therapy was individual but remained consistent throughout the studied period. Conclusions: This study provides valuable insight into COVID-19 care in Germany and shows how the majority of patients could be treated with the maximum treatment required according to disease severity following the national algorithm. Escalation of therapy modality is interlinked with disease severity and thus associated with mortality.
Introduction
Infection with the SARS-CoV-2 virus can have an asymptomatic or mildly symptomatic course or lead to multi-organ involvement. Respiratory disease is common and typically causes lung changes with consolidation and ground glass opacities being the most common features on chest X-ray [1]. Severe COVID-19 develops approximately 1 week after the beginning of symptoms and occurs in 5–8% [2, 3]. It can lead to acute respiratory distress syndrome (ARDS), necessitating invasive mechanical ventilation (IMV) among other modes of intensive care support, which is associated with a high mortality [4]. There is a growing evidence base for the use of conventional oxygen therapy (COT), high-flow nasal cannula (HFNC) [5, 6], continuous positive airway pressure (CPAP) [7], and non-invasive ventilation (NIV) [8, 9] to improve oxygenation and treat respiratory distress in COVID-19, potentially delaying intubation and, in some cases, making intubation unnecessary [10, 11].
The earliest clinical insights from the first wave of the pandemic brought reports of sudden clinical deterioration, causing some international experts at the time to call for early intubation when oxygen supplementation reached rates of 5–6 L/min [12‒14]. Timely intubation was therefore advocated in some centres [15]. One reason for this was staff safety; concerns were raised at the time over the aerosol formation associated with the use of CPAP and NIV as well as during emergency intubation [14, 16]. Another rationale for prioritising intubation over NIV in a patient with increasing respiratory effort was the somewhat unknown lung morphology and respiratory mechanics associated with severe COVID-19, leading to the theory that early intubation avoids excess intrathoracic pressures and self-inflicted lung damage [17, 18]. Since then, ARDS related to COVID-19 has been shown to be similar to classical ARDS [19], and it has been shown that COVID-19 can be managed safely, both in and out of the intensive care unit (ICU), with appropriate measures in place. A systematic review and meta-analysis from December 2021 showed no influence of the timing of intubation (when early intubation was defined as <24 h following ICU admission) on clinical outcome [20]. The discussion over the optimal timing of intubation in COVID-19 is ongoing [21], perhaps explained by the fact that the timing of intubation within the field of intensive care medicine has always been controversial [22].
A German position paper published online in April 2020 recommended a trial of HFNC/CPAP/NIV prior to intubation [23]. National experts advocated a stepwise treatment strategy, under appropriate intensive care monitoring and with the observance of all relevant anti-infectious precautions, acknowledging the risks of both “early” and “late” intubation [24].
In our centre, the timing of transfer to the ICU was the physician’s decision in accordance with patient wishes, based on a combination of factors later outlined in the national guidelines [23], such as the partial pressure of oxygen on room air or the level of COT support, together with signs of clinical respiratory distress (breathing rate >30/min) and severity and progression of COVID-19-related chest X-ray findings. Severe COVID-19 patients were monitored intensively in an ICU setting, with the use of HFNC in combination with CPAP and NIV. Deterioration under non-invasive therapy led to intubation or therapy withdrawal in individual cases. An early intubation strategy was not followed nor was intubation actively avoided.
In this study, we aimed to evaluate the validity of this individualised approach in terms of patient outcome as well as to evaluate the development of the approach in the course of the pandemic. Finally, we compared the statistics in our centre with the German databank to look for differences in approach and outcome.
Materials and Methods
Study Population
The study centre is affiliated with the University of Cologne and provides tertiary respiratory care in the region of North Rhine-Westphalia, Germany. From 1,052 consecutive COVID-19-related admissions during the period of March 2020 and December 2021, 835 cases were analysed. Only patients directly admitted to the centre from their private residence or care home with complete patient files were considered (shown in Fig. 1). Patients transferred from other centres from an in-patient setting were excluded.
Flow diagram showing eligibility for case analysis in the observational study.
Data Gathering
A manual medical record review was undertaken and demographic data and clinical data including smoking status, COVID-19 vaccination status, symptoms on admission, comorbidity, previous medication, previous oxygen or NIV therapy, radiological findings, pharmacological therapy, timing and duration of ICU stay and of intubation as well as overall survival were collated. The arterialised capillary blood gas upon admission taken at first contact with the admitting clinician, when sampled on room air, was analysed. When patients received supplementary oxygen directly on admission before blood gas was sampled, the oxygen flow rate was documented and categorised as less than or equal to 2 L/min or greater than 2 L/min. The use of all non-pharmacological therapy – COT, HFNC, CPAP, NIV, IMV, and extracorporeal membrane oxygenation (ECMO) – and its order was documented. Patients were placed into cohorts for analysis based on the “maximum” step of therapy that was reached using the following hierarchical order: COT > HFNC > CPAP > NIV > IMV > ECMO. For example, a patient receiving COT who was switched to HFNC and then finally NIV was allocated into the NIV group.
Statistics
The data was descriptively analysed using IBM SPSS Statistics™ for Windows (version 28.0; IBM Corp., Armonk, NY, USA). Frequencies are given by absolute number and percentage; continuous data are represented with both the median and the 1st and 3rd quartiles.
Results
A total of 835 patients were included in the final evaluation, as shown in Figure 1. 54% of the overall patient population were male (n = 452), with an overall median age of 58 years [56; 75], as shown in Table 1. During the studied period of March 2020 until December 2021, the maximum therapy of the greatest proportion of patients was oxygen (COT or HFNC), while one quarter ended with either non-invasive or invasive ventilatory or pressure support (CPAP, NIV or IMV) or additional ECMO.
Baseline characteristics and outcome of the maximum treatment modalities
. | All (n = 835) . | No therapy (n = 284) . | COT (n = 337) . | HFNC (n = 22) . | CPAP (n = 73) . | NIV (n = 56) . | IMV (n = 34) . | ECMO (n = 29) . |
---|---|---|---|---|---|---|---|---|
Age, years | 58 [46; 75] | 50 [34; 63] | 60 [50; 78] | 81 [76; 83] | 63 [51; 74] | 63 [53; 78] | 74 [64; 79] | 57 [52; 65] |
Female, n (%) | 383 (45) | 146 (51) | 174 (50) | 12 (55) | 26 (36) | 18 (32) | 9 (26) | 9 (31) |
Smoking status, n (%) | ||||||||
Current or ex | 236 (28) | 86 (30) | 89 (26) | 4 (18) | 22 (30) | 19 (34) | 8 (24) | 8 (28) |
Never | 415 (50) | 144 (51) | 178 (53) | 12 (55) | 40 (55) | 19 (34) | 11 (32) | 11 (38) |
Unknown | 184 (22) | 54 (19) | 70 (21) | 6 (27) | 11 (15) | 18 (32) | 15 (44) | 10 (34) |
Pre-existing device therapy, n (%) | ||||||||
LTOT | 16 (2) | 1 (0) | 8 (2) | 1 (5) | 2 (3) | 3 (5) | 1 (3) | 0 (0) |
CPAP | 22 (3) | 5 (2) | 8 (2) | 1 (5) | 4 (5) | 2 (4) | 1 (3) | 1 (3) |
NIV | 12 (1) | 1 (0) | 6 (2) | 0 (0) | 0 (0) | 4 (7) | 1 (3) | 0 (0) |
Comorbidities, n (%) | ||||||||
Adiposity | 316 (38) | 74 (26) | 133 (39) | 11 (50) | 35 (48) | 33 (59) | 14 (41) | 16 (55) |
Arterial hypertension | 446 (53) | 104 (37) | 186 (55) | 21 (95) | 48 (66) | 39 (70) | 29 (85) | 19 (66) |
Chronic renal failure | 86 (10) | 12 (4) | 56 (17) | 4 (18) | 7 (10) | 14 (25) | 7 (21) | 4 (14) |
Coronary heart disease | 94 (11) | 18 (6) | 44 (13) | 5 (23) | 9 (12) | 7 (13) | 7 (21) | 2 (7) |
Myocardial infarction | 22 (3) | 2 (<1) | 9 (3) | 4 (18) | 1 (1) | 2 (4) | 3 (9) | 1 (3) |
Valvular heart disease | 41 (5) | 9 (3) | 20 (6) | 3 (14) | 3 (4) | 2 (4) | 2 (6) | 2 (7) |
Cardiac arrhythmia | 10 (11) | 1 (<1) | 4 (1) | 0 (0) | 4 (5) | 0 (0) | 1 (3) | 0 (0) |
Stroke | 42 (5) | 10 (4) | 24 (7) | 2 (9) | 1 (1) | 3 (5) | 0 (0) | 2 (7) |
Heart failure | 69 (8) | 11 (4) | 28 (8) | 7 (33) | 6 (8) | 5 (9) | 4 (12) | 7 (24) |
Atrial fibrillation | 114 (14) | 25 (9) | 40 (12) | 8 (38) | 9 (12) | 10 (18) | 15 (44) | 7 (24) |
Cerebrovascular disease | 68 (8) | 13 (5) | 28 (8) | 8 (36) | 7 (10) | 4 (7) | 6 (18) | 2 (7) |
Diabetes mellitus | 180 (22) | 27 (9) | 76 (23) | 8 (36) | 25 (34) | 15 (27) | 14 (41) | 15 (52) |
Asthma | 89 (11) | 27 (10) | 43 (13) | 1 (5) | 9 (12) | 4 (7) | 3 (9) | 2 (7) |
COPD | 59 (7) | 4 (1) | 35 (10) | 2 (9) | 4 (5) | 8 (14) | 5 (15) | 1 (3) |
OSA | 44 (5) | 9 (3) | 17 (5) | 1 (5) | 4 (5) | 6 (11) | 4 (12) | 3 (10) |
Pulmonary fibrosis | 8 (1) | 1 (<1) | 3 (1) | 1 (5) | 3 (4) | 0 (0) | 0 (0) | 0 (0) |
Pulmonary hypertension | 7 (1) | 1 (<1) | 1 (<1) | 2 (9) | 0 (0) | 3 (5) | 0 (0) | 0 (0) |
Psychiatric disorders# | 132 (16) | 35 (12) | 57 (17) | 7 (32) | 12 (16) | 9 (16) | 8 (24) | 4 (14) |
Dyslipidaemia | 568 (68) | 166 (58) | 243 (72) | 21 (95) | 57 (78) | 36 (64) | 23 (68) | 22 (76) |
Atherosclerosis | 46 (6) | 8 (3) | 21 (6) | 5 (23) | 6 (8) | 2 (4) | 3 (9) | 1 (3) |
Neurological disorders§ | 109 (13) | 26 (9) | 59 (18) | 5 (23) | 8 (11) | 6 (11) | 4 (12) | 1 (3) |
Hypothyroidism | 123 (15) | 37 (13) | 52 (15) | 1 (5) | 16 (22) | 10 (18) | 5 (15) | 2 (7) |
Blood gas analysis on admission, n/n available (%) | ||||||||
Available | 632 (76) | 198 (70) | 254 (75) | 16 (73) | 61 (84) | 49 (88) | 26 (76) | 28 (97) |
On room air | 382/632 (60) | 196/198 (99) | 137/254 (54) | 6/16 (38) | 19/61 (31) | 12/49 (24) | 3/26 (12) | 9/28 (32) |
>2 L/min O2 | 162/632 (26) | 0/198 (0) | 52/254 (20) | 8/16 (50) | 33/61 (54) | 31/49 (63) | 20/26 (77) | 18/28 (64) |
Blood gas analysis on admission on room air | ||||||||
pO2, mm Hg | 64.8 [56.4; 75.9] | 73.6 [65.9; 87.1] | 61.8 [55.2; 68.8] | 59.9 [53.6; 74.7] | 58.2 [53.8; 65.0] | 57.4 [50.9; 69.3] | 62.3 [47.9; 76.7] | 62.3 [55.6; 77.1] |
pCO2, mm Hg | 33.1 [29.9; 37.0] | 34.3 [31.6; 37.5] | 32.7 [29.7; 36.7] | 32.4 [28.3; 37.2] | 3.1 [28.8; 34.0] | 34.9 [30.8; 38.3] | 30.9 [28.1; 34.8] | 32.5 [29.1; 36.9] |
Chest X-ray, n/n available (%) | ||||||||
Loss of transparency on admission | 493/763 (65) | 99/246 (40) | 220/314 (70) | 17/20 (85) | 57/71 (80) | 42/51 (82) | 32/34 (94) | 25/27 (93) |
Progressive changes at day 3–14 | 159/376 (42) | 10/38 (26) | 58/157 (37) | 3/9 (33) | 23/59 (39) | 15/42 (36) | 23/32 (72) | 22/29 (76) |
Drug therapy, n (%) | ||||||||
Antibiotics | 298 (36) | 35 (12) | 109 (32) | 15 (68) | 41 (56) | 35 (63) | 34 (100) | 29 (100) |
Dexamethason | 307 (37) | 31 (11) | 110 (33) | 17 (77) | 59 (81) | 42 (75) | 27 (79) | 21 (72) |
Remdesevir | 45 (5) | 5 (2) | 22 (7) | 1 (5) | 12 (16) | 1 (2) | 2 (6) | 2 (7) |
Other drugs* | 11 (1) | 5 (2) | 2 (<1) | 0 (0) | 0 (0) | 1 (2) | 3 (9) | 0 (0) |
Clinical course | ||||||||
Length of stay, days | 7 [3; 13] | 3.0 [2; 6] | 6.0 [4; 10] | 17.0 [10; 24] | 12 [9; 15] | 13.5 [9; 22] | 18 [13; 25] | 31 [21; 43] |
Acute renal failure, n (%) | 106 (13) | 13 (5) | 27 (8) | 6 (27) | 11 (15) | 10 (18) | 21 (62) | 18 (62) |
Days from admission until intubation | - | - | - | - | - | - | 6 [3; 10] | 8 [3; 12] |
Treatment on ward, n (%) | 650 (78) | 282 (99) | 311 (92) | 15 (68) | 34 (47) | 10 (18) | 0 (0) | 0 (0) |
Treatment on ICU, n (%) | 183 (22) | 2 (1) | 26 (8) | 7 (32) | 39 (53) | 46 (82) | 34 (100) | 29 (100) |
Mortality, n (%) | 106 (13) | 1 (<1) | 34 (10) | 5 (23) | 8 (11) | 10 (18) | 25 (74) | 23 (79) |
. | All (n = 835) . | No therapy (n = 284) . | COT (n = 337) . | HFNC (n = 22) . | CPAP (n = 73) . | NIV (n = 56) . | IMV (n = 34) . | ECMO (n = 29) . |
---|---|---|---|---|---|---|---|---|
Age, years | 58 [46; 75] | 50 [34; 63] | 60 [50; 78] | 81 [76; 83] | 63 [51; 74] | 63 [53; 78] | 74 [64; 79] | 57 [52; 65] |
Female, n (%) | 383 (45) | 146 (51) | 174 (50) | 12 (55) | 26 (36) | 18 (32) | 9 (26) | 9 (31) |
Smoking status, n (%) | ||||||||
Current or ex | 236 (28) | 86 (30) | 89 (26) | 4 (18) | 22 (30) | 19 (34) | 8 (24) | 8 (28) |
Never | 415 (50) | 144 (51) | 178 (53) | 12 (55) | 40 (55) | 19 (34) | 11 (32) | 11 (38) |
Unknown | 184 (22) | 54 (19) | 70 (21) | 6 (27) | 11 (15) | 18 (32) | 15 (44) | 10 (34) |
Pre-existing device therapy, n (%) | ||||||||
LTOT | 16 (2) | 1 (0) | 8 (2) | 1 (5) | 2 (3) | 3 (5) | 1 (3) | 0 (0) |
CPAP | 22 (3) | 5 (2) | 8 (2) | 1 (5) | 4 (5) | 2 (4) | 1 (3) | 1 (3) |
NIV | 12 (1) | 1 (0) | 6 (2) | 0 (0) | 0 (0) | 4 (7) | 1 (3) | 0 (0) |
Comorbidities, n (%) | ||||||||
Adiposity | 316 (38) | 74 (26) | 133 (39) | 11 (50) | 35 (48) | 33 (59) | 14 (41) | 16 (55) |
Arterial hypertension | 446 (53) | 104 (37) | 186 (55) | 21 (95) | 48 (66) | 39 (70) | 29 (85) | 19 (66) |
Chronic renal failure | 86 (10) | 12 (4) | 56 (17) | 4 (18) | 7 (10) | 14 (25) | 7 (21) | 4 (14) |
Coronary heart disease | 94 (11) | 18 (6) | 44 (13) | 5 (23) | 9 (12) | 7 (13) | 7 (21) | 2 (7) |
Myocardial infarction | 22 (3) | 2 (<1) | 9 (3) | 4 (18) | 1 (1) | 2 (4) | 3 (9) | 1 (3) |
Valvular heart disease | 41 (5) | 9 (3) | 20 (6) | 3 (14) | 3 (4) | 2 (4) | 2 (6) | 2 (7) |
Cardiac arrhythmia | 10 (11) | 1 (<1) | 4 (1) | 0 (0) | 4 (5) | 0 (0) | 1 (3) | 0 (0) |
Stroke | 42 (5) | 10 (4) | 24 (7) | 2 (9) | 1 (1) | 3 (5) | 0 (0) | 2 (7) |
Heart failure | 69 (8) | 11 (4) | 28 (8) | 7 (33) | 6 (8) | 5 (9) | 4 (12) | 7 (24) |
Atrial fibrillation | 114 (14) | 25 (9) | 40 (12) | 8 (38) | 9 (12) | 10 (18) | 15 (44) | 7 (24) |
Cerebrovascular disease | 68 (8) | 13 (5) | 28 (8) | 8 (36) | 7 (10) | 4 (7) | 6 (18) | 2 (7) |
Diabetes mellitus | 180 (22) | 27 (9) | 76 (23) | 8 (36) | 25 (34) | 15 (27) | 14 (41) | 15 (52) |
Asthma | 89 (11) | 27 (10) | 43 (13) | 1 (5) | 9 (12) | 4 (7) | 3 (9) | 2 (7) |
COPD | 59 (7) | 4 (1) | 35 (10) | 2 (9) | 4 (5) | 8 (14) | 5 (15) | 1 (3) |
OSA | 44 (5) | 9 (3) | 17 (5) | 1 (5) | 4 (5) | 6 (11) | 4 (12) | 3 (10) |
Pulmonary fibrosis | 8 (1) | 1 (<1) | 3 (1) | 1 (5) | 3 (4) | 0 (0) | 0 (0) | 0 (0) |
Pulmonary hypertension | 7 (1) | 1 (<1) | 1 (<1) | 2 (9) | 0 (0) | 3 (5) | 0 (0) | 0 (0) |
Psychiatric disorders# | 132 (16) | 35 (12) | 57 (17) | 7 (32) | 12 (16) | 9 (16) | 8 (24) | 4 (14) |
Dyslipidaemia | 568 (68) | 166 (58) | 243 (72) | 21 (95) | 57 (78) | 36 (64) | 23 (68) | 22 (76) |
Atherosclerosis | 46 (6) | 8 (3) | 21 (6) | 5 (23) | 6 (8) | 2 (4) | 3 (9) | 1 (3) |
Neurological disorders§ | 109 (13) | 26 (9) | 59 (18) | 5 (23) | 8 (11) | 6 (11) | 4 (12) | 1 (3) |
Hypothyroidism | 123 (15) | 37 (13) | 52 (15) | 1 (5) | 16 (22) | 10 (18) | 5 (15) | 2 (7) |
Blood gas analysis on admission, n/n available (%) | ||||||||
Available | 632 (76) | 198 (70) | 254 (75) | 16 (73) | 61 (84) | 49 (88) | 26 (76) | 28 (97) |
On room air | 382/632 (60) | 196/198 (99) | 137/254 (54) | 6/16 (38) | 19/61 (31) | 12/49 (24) | 3/26 (12) | 9/28 (32) |
>2 L/min O2 | 162/632 (26) | 0/198 (0) | 52/254 (20) | 8/16 (50) | 33/61 (54) | 31/49 (63) | 20/26 (77) | 18/28 (64) |
Blood gas analysis on admission on room air | ||||||||
pO2, mm Hg | 64.8 [56.4; 75.9] | 73.6 [65.9; 87.1] | 61.8 [55.2; 68.8] | 59.9 [53.6; 74.7] | 58.2 [53.8; 65.0] | 57.4 [50.9; 69.3] | 62.3 [47.9; 76.7] | 62.3 [55.6; 77.1] |
pCO2, mm Hg | 33.1 [29.9; 37.0] | 34.3 [31.6; 37.5] | 32.7 [29.7; 36.7] | 32.4 [28.3; 37.2] | 3.1 [28.8; 34.0] | 34.9 [30.8; 38.3] | 30.9 [28.1; 34.8] | 32.5 [29.1; 36.9] |
Chest X-ray, n/n available (%) | ||||||||
Loss of transparency on admission | 493/763 (65) | 99/246 (40) | 220/314 (70) | 17/20 (85) | 57/71 (80) | 42/51 (82) | 32/34 (94) | 25/27 (93) |
Progressive changes at day 3–14 | 159/376 (42) | 10/38 (26) | 58/157 (37) | 3/9 (33) | 23/59 (39) | 15/42 (36) | 23/32 (72) | 22/29 (76) |
Drug therapy, n (%) | ||||||||
Antibiotics | 298 (36) | 35 (12) | 109 (32) | 15 (68) | 41 (56) | 35 (63) | 34 (100) | 29 (100) |
Dexamethason | 307 (37) | 31 (11) | 110 (33) | 17 (77) | 59 (81) | 42 (75) | 27 (79) | 21 (72) |
Remdesevir | 45 (5) | 5 (2) | 22 (7) | 1 (5) | 12 (16) | 1 (2) | 2 (6) | 2 (7) |
Other drugs* | 11 (1) | 5 (2) | 2 (<1) | 0 (0) | 0 (0) | 1 (2) | 3 (9) | 0 (0) |
Clinical course | ||||||||
Length of stay, days | 7 [3; 13] | 3.0 [2; 6] | 6.0 [4; 10] | 17.0 [10; 24] | 12 [9; 15] | 13.5 [9; 22] | 18 [13; 25] | 31 [21; 43] |
Acute renal failure, n (%) | 106 (13) | 13 (5) | 27 (8) | 6 (27) | 11 (15) | 10 (18) | 21 (62) | 18 (62) |
Days from admission until intubation | - | - | - | - | - | - | 6 [3; 10] | 8 [3; 12] |
Treatment on ward, n (%) | 650 (78) | 282 (99) | 311 (92) | 15 (68) | 34 (47) | 10 (18) | 0 (0) | 0 (0) |
Treatment on ICU, n (%) | 183 (22) | 2 (1) | 26 (8) | 7 (32) | 39 (53) | 46 (82) | 34 (100) | 29 (100) |
Mortality, n (%) | 106 (13) | 1 (<1) | 34 (10) | 5 (23) | 8 (11) | 10 (18) | 25 (74) | 23 (79) |
Continuous variables are given as median with interquartile range in square brackets, discrete variables as absolute number of cases. Percentage values represent the percentage of cases within each column, unless stated otherwise.
COT, conventional oxygen therapy; HFNC, high-flow nasal cannula; CPAP, continuous positive airway pressure; NIV, non-invasive ventilation; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation; LTOT, long-term oxygen therapy; COPD, chronic obstructive pulmonary disease; OSA, obstructive sleep apnoea; ICU, intensive care unit.
#Anxiety disorder, schizophrenia, alcohol dependence syndrome in decreasing order of frequency.
§ Dementia, epilepsy, Parkinson disease in decreasing order of frequency.
*Janus kinase (JAK) inhibitor/interleukin-6 (IL-6) antagonist/neutralizing antibodies.
The distribution of the various therapy modalities as a percentage of use over the entire 22-month observation period was compared to the number of COVID-19 admissions to the centre in the given month (shown in Fig. 2a). Admissions were highest in November/December 2020 as well as in April 2021, reflecting the second and third waves of the pandemic. The overall therapy distribution was similar in times of high hospital admissions and in quieter periods.
The percentage use of non-pharmacological therapy in the period of March 2020 until December 2021 in relation to the overall number of hospital admissions for COVID-19 at the studied centre for all patients (a) and in n = 551 receiving at least oxygen therapy (b). COT, conventional oxygen therapy; HFNC, high-flow nasal cannula; CPAP, continuous positive airway pressure; NIV, non-invasive ventilation; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation.
The percentage use of non-pharmacological therapy in the period of March 2020 until December 2021 in relation to the overall number of hospital admissions for COVID-19 at the studied centre for all patients (a) and in n = 551 receiving at least oxygen therapy (b). COT, conventional oxygen therapy; HFNC, high-flow nasal cannula; CPAP, continuous positive airway pressure; NIV, non-invasive ventilation; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation.
The weekly COVID-19 admission at the studied centre reflected COVID-related hospital admissions in Germany as a whole in the studied period (shown in Fig. 3). The individual therapy escalation pathway of the studied patients was variable (shown in Fig. 4). The final step reached by the patient was classified as the maximum therapy (described in detail in the Method section).
The number of hospital admission per week for COVID-19 at the studied centre (orange bars) in relation to average weekly admission for COVID-19 across Germany (blue line) over time. Source: European Centre for Disease Prevention and Control [25].
The number of hospital admission per week for COVID-19 at the studied centre (orange bars) in relation to average weekly admission for COVID-19 across Germany (blue line) over time. Source: European Centre for Disease Prevention and Control [25].
Individual therapy pathway for the use of non-pharmacological therapy in the 835 in-patient COVID-19 patients within the studied period. COT, conventional oxygen therapy; HFNC, high-flow nasal cannula; CPAP, continuous positive airway pressure; NIV, non-invasive ventilation; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation.
Individual therapy pathway for the use of non-pharmacological therapy in the 835 in-patient COVID-19 patients within the studied period. COT, conventional oxygen therapy; HFNC, high-flow nasal cannula; CPAP, continuous positive airway pressure; NIV, non-invasive ventilation; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation.
Patients were divided into cohorts based on the maximum therapy used for analysis of differences in characteristics and overall outcome (shown in Table 1). Patients were older in the HFNC and IMV groups (median 81 and 74 years, respectively). The sub-group of intubated patients placed on ECMO was younger, with a median age of 57 [52; 65]. Adiposity, arterial hypertension, and diabetes were the most common comorbidities in the whole cohort.
Overall, only 61 patients had received at least 1 vaccination against COVID-19 as the vaccine was either not yet available or the patients were not eligible. The medical treatment of COVID-19 in this cohort consisted mainly of systemic corticosteroids in combination with empirical antibiotic therapy. COVID-19-specific drugs were centrally restricted and applied on a case-to-case basis following national guidelines, explaining the minimal usage.
The proportion of patients where a blood gas analysis on room air was available was highest in patients receiving no specific therapy or oxygen therapy as the maximal therapy. As the intensity of therapy progressed, patients were more likely to have been put on supplementary oxygen therapy directly after clinical assessment, before the first sampling of blood gas took place. The partial pressure of oxygen on room air on admission was lower in the patients escalated to non-invasive and invasive ventilation. The level of initial oxygen supplementation on admission was also higher in these groups. 90% of the available chest X-rays of patients going on to be non-invasively or invasively ventilated had chest X-ray findings compatible with COVID-19 upon hospital admission. The length of hospital stay was highest in the group with HFNC, IMV, and ECMO. Patients were intubated at a median of 6 days after admission.
106 of the 835 patients died in hospital. 284 patients received no form of non-pharmacological therapy during their hospital stay. This cohort was made up of 51 asymptomatic/oligosymptomatic patients referred for quarantine on public health grounds both from private households and care homes, and the remaining patients were referred from primary care providers for further evaluation in a secondary care setting. The median length of hospital stay in this group was 3 days. 2 of these patients were admitted to the ICU due to issues unrelated to COVID-19.
Overall, 551 patients were treated with at least COT or more during the hospital stay. Figure 2b shows the distribution of therapy modalities over time in this group. 11.4% of these patients were intubated, and 19.1% died. The mortality rate of the 181 patients admitted to ICU for COVID-19 was 35.4%. Of the 63 patients who received therapy with IMV and ECMO, 48 died (74%).
Discussion
We found an overwhelmingly stable pattern in the use and escalation of non-pharmacological therapy throughout various phases of the global pandemic in the studied centre. Therapy usage appears to be based on the stepwise approach, with all but 1 patient receiving at least a trial of HFNC and more likely CPAP and/or NIV prior to intubation. The minor variation in therapy usage reflects the individual variations which are bound to occur when patient preference and compliance, anatomical differences, variability in clinical response, and availability of resources are considered. However, at no point was a decision against therapy escalation taken due to lack of resources. Equally, in concordance with the national guidelines, there was neither a push for early intubation nor for delayed intubation. Following this hospital’s internal standard of care, 11% of the 551 patients requiring at least oxygen therapy were treated with and 89% without the need for invasive ventilation or ECMO.
Overall Outcome according to Therapy Modality
No Therapy
58 of the 488 patients in whom therapy was not escalated beyond oxygen therapy and/or non-invasive pressure support died. The median age of these 58 patients was 85 years (82; 90). Therapy escalation did not take place due to futility of mechanical ventilation (and other invasive intensive medicine measures) and patient wishes.
HFNC Oxygen Therapy
From a total of 144 patients who received HFNC at some point in the clinical pathway, 22 were not escalated further. The majority of these patients were managed on a normal ward. This group was older with a median age of 80 years, most likely explained by the better tolerance and higher degree of patient comfort of HFNC compared with NIV and better treatment of dyspnoea than with COT [26] in the elderly and those with a do not intubate status. HFNC was thus an important component of the toolkit, particularly in these cases.
Pressure Support/NIV
Half of the patients needing CPAP and the vast majority of NIV patients were transferred to IMC or ICU. These patients requiring ventilatory support were sicker when they arrived: they displayed significantly more hypoxaemia (requiring greater levels of supplementary oxygen therapy), appear to almost always have had chest X-ray findings on admission – suggesting more severe disease at the outset – and appear to have more comorbid disease. Around 50% of patients treated with NIV (shown in Fig. 4) eventually required intubation.
IMV with or without ECMO
Of the 63 patients who did receive therapy with IMV and ECMO, 48 died (74%). The patients receiving ECMO in this cohort were younger than those who were mechanically ventilated but were not put on ECMO (57 vs. 74 years old), reflecting the selection process involved when it came to this therapy. Despite this attempt at identifying the patients likely to benefit, the majority died on ECMO or mechanical ventilation. Disease progression cannot be stopped through ECMO or mechanical ventilation, but these modalities can be used to gain time for critically ill patients to recover. This was achieved in one quarter of the patients, whose death would have been expected without treatment escalation.
Some centres have reported similar ECMO survival rates for COVID-19 compared to ECMO for bacterial pneumonia and influenza [27]. A systematic review and meta-analysis showed an in-hospital mortality of 37.1% in patients receiving ECMO support for COVID-19 [28]. An analysis of 768 patients on ECMO by Karagiannidis et al. [29] in Germany showed mortality similar to the studied cohort of 73%. The authors hypothesised that the high mortality in Germany is due to the potentially less restrictive use of ECMO due to the amplitude of resources.
Nationwide Comparison
This is a retrospective monocentric analysis of 835 hospitalised COVID-19 patients in a university-affiliated tertiary care centre for pulmonary medicine that provided respiratory specialist in-patient and out-patient services for COVID-19 from the start of the pandemic for a large and densely populated region in North Rhine-Westphalia. The pattern of hospital admissions at this centre reflected the rate of COVID-19 infection within the German population at the time.
A retrospective analysis of in-patient hospital mortality in Germany shows an overall mortality of 16.7% (n = 93,668) and an ICU mortality rate of 33.36% (n = 45,947) [30]. Karagiannidis et al. [29] described over 10,000 cases in Germany from February until April 2020 and reported a mortality of 21% [31].
A direct comparison of these published mortality figures with those of the studied cohort is difficult due to the 284 patients who did not require a specific therapy upon hospital admission. The median length of hospital stay was just 3 days in this group, supporting the presumption that illness remained mild and a specific therapy was either not wanted or not required. When the 51 asymptomatic/oligosymptomatic patients are discounted, it results in an overall mortality of 13.5% for hospitalised COVID-19 patients. When the 284 admissions receiving no form of therapy support are fully discounted, there is a mortality of 19%.
A nationwide German study in a cohort of over 17,000 patients showed reduced duration of invasive ventilation but not reduced mortality with the use of NIV prior to intubation in 7,490 critically ill patients [32]. A smaller German study of 50 patients showed the use of NIV prior to ICU in 23 patients of whom 16 went on to be intubated, 13 of whom died [33].
Our findings confirm that there is a role for NIV in the treatment of COVID-19, but that intubation as a further escalation is not avoidable. The current study provides indirect evidence that this treatment approach or “algorithm” – which established itself organically in the centre but was soon validated in a publication by the national pulmonology society in Germany and adhered to in the studied centre throughout the course of the pandemic – might reflect clinical practice in Germany overall.
Limitation
The retrospective nature of the study and the monocentric design must be regarded as limitations, particularly on a global scale. The advantage of the manual medical review approach compared to analysis of data sets provided, for example, by health care providers such as that used in the large-scale study by Karagiannidis et al. [29], was the ability to closely study the non-pharmacological treatment pathway and escalation strategy.
Conclusion
We believe that the management of hospitalised COVID-19 based on the clinical algorithm (supported by national guidelines) seen in this study of real-life treatment offers an effective and patient-centred approach, possibly reflecting the clinical care provided to COVID-19 patients in other German hospitals. The individualised use of non-pharmacological therapy did not exhaust resources and allowed the majority of COVID in-patients to be treated with the maximum therapy required according to the disease severity. The goal of establishing normoxaemia early on following hospitalisation – but without rules of early intubation or general avoidance of intubation – limited overall mortality of COVID-19.
Statement of Ethics
As this study was a purely retrospective, epidemiological study, no professional consultation with an ethics committee and no written informed consent were required in accordance with the locally applicable professional code of conduct for physicians (see “Berufsordnung für die nordrheinischen Ärztinnen und Ärzte vom 14. November 1998 in der Fassung vom 16. November 2019”, Article 15, available online via https://www.aekno.de/aerzte/berufsordnung#_15, accessed July 7, 2023).
Conflict of Interest Statement
W.R. reports grants and personal fees from Philips Respironics, Loewenstein Medical, Resmed, Bayer Vital, Bioprojet, and Vanda Pharma, outside the submitted work. L.H. reports grants and personal fees from Boehringer, Pfizer, Roche, Novartis, AstraZeneca, and Chiesi, outside the submitted work. S.M., J.H., J.R., M.T., G.S., M.B., J.K., U.O., and S.H. have no conflicts of interest to declare.
Funding Sources
This study received financial support from VitalAire GmbH, Norderstedt, Germany. The funders had no role in study design, data collection, analysis, interpretation, and preparation of the manuscript, or the submission process.
Author Contributions
W.R. serves as a guarantor of the paper, taking responsibility for the integrity of the work as a whole, from inception to the published article. S.M., J.H., M.T., J.R., L.H., G.S., M.B., U.O., J.K., S.H., and W.R. contributed to the study concept and design. S.M., J.S., J.R., G.S., M.B., U.O., J.K., and S.H. performed data acquisition. S.M., J.H., J.R., L.H., M.T., and W.R. contributed to analysis and interpretation of data. S.M., J.H., J.R., M.T., and W.R. drafted the submitted article. All authors revised the manuscript critically for important intellectual content and have provided final approval of the version to be published.
Data Availability Statement
The data that support the findings of this study are openly available in “figshare” at http://doi.org/10.6084/m9.figshare.23642034. Further enquiries can be directed to the corresponding author.
References
Additional information
Sandhya Matthes and Johannes Holl have equally contributed as first author.