Changes in characteristics and outcomes of critically ill COVID-19 patients in Tyrol (Austria) over 1 year

As of May 2021, more than 600,000 patients tested positive and around 10,000 deaths are attributed to Coronavirus disease 19 (COVID-19) in Austria [1]. While in the beginning of the pandemic the number of SARS-CoV‑2 positive patients requiring intensive care was unknown, the rate settled at around 1–2% during the second period [2].

Due to numerous influencing factors different cohorts from various areas have demonstrated widely varying mortality rates and characteristics of intensive care unit (ICU) patients. A meta-analysis published in June 2020 found ICU mortality rates ranging from 14–84% [3], which has shown the importance of observing regional conditions separately in order to have a better understanding of major factors influencing outcome [4].

Since the beginning of the COVID-19 pandemic, countless studies about therapeutic strategies and the management of ICU patients have been initiated and published [5, 6]. With the RECOVERY trial corticosteroid treatment has shown a mortality benefit in patients requiring respiratory support and has changed therapeutic strategies for critically ill COVID-19 patients. Guidelines have been continuously updated, adapting recommendations based on the best available evidence.

In Tyrol, Austria, comprising 750,000 inhabitants we established the Tyrolean COVID-19 intensive care registry (Tyrol-CoV-ICU-Reg) at the beginning of the first surge of the pandemic in March 2020. Characteristics and outcomes of the first period have previously been published [4]. Since then, we continued the registry throughout the second period of the COVID-19 crisis.

We assumed that the rapid growth in knowledge as well as the dynamic of the ongoing pandemic may result in different and changing patient characteristics and outcomes of critically ill patients over time. Therefore, the aim of this study was to evaluate critically ill patients with COVID-19, treated in any of the 12 ICUs dedicated to COVID-19 in Tyrol, Austria and to identify important changes between the two waves in baseline characteristics, treatment strategies and outcomes.

This was a prospective observational register study of 508 critically ill patients treated at an ICU in Tyrol (Austria), between 9 March 2020 and 22 February 2021 with confirmed SARS-CoV‑2 infections. About four times more patients had to be treated in the ICU during the second period compared to the first one. While most baseline characteristics were similar, patients were significantly older in the second wave. Patients of the second period required less IMV, RRT and vasopressors, resulting in drastically reduced LOS. Despite that, hospital mortality increased, albeit being still lower than or similar to rates reported from other regions of Europe [10‐12]. Age, number of comorbidities and frailty have shown to be independent predictors of hospital mortality.

The most remarkable difference between the two periods is the higher number of patients in the second wave (401 vs. 107), with a new maximum of the peak in ICU occupancy with 82 patients (Fig. 1). These numbers correspond to the dynamics of the pandemic in Austria [1]. As mentioned in our previous paper we had established an ICU resource management, which avoided overcrowding of ICU and healthcare system decompensation. This was also successful during the second wave; however, to maintain unrestricted access to the ICU, improvements in the treatment of critically ill COVID-19 patients were necessary.

Major progress has been made in ventilation treatment, as reflected in lower rates and duration of IMV in the second period. Corresponding to the reduction of IMV, the number of patients who only required NIV or HFNC was higher during the second period (Table 2). A similar decrease of IMV use has been reported from other cohorts [13, 14]. Several factors may be responsible for this finding. First of all the change of the rate of IMV corresponds to the change of recommendations regarding timing of intubation [15]. High rates of mechanical ventilation in critically ill patients and a rapid deterioration have been reported from China [16] and Italy [10]. Therefore, in the beginning, early intubation was considered beneficial not only for ICU staff due to less aerosol exposure but also for the patients. Respiratory treatment with NIV and HFNC have been proven to avoid invasive ventilation in comparison to a standard oxygen mask [17]. Although NIV and HFNC are important and might have the ability to protect patients from IMV, late failure of NIV may increase mortality in these patients [18]; however, randomized controlled trials are necessary to answer the question of optimal timing of intubation. Additionally, the significantly increased use of corticosteroids in the second wave, after the results of the RECOVERY trial were published, may have contributed to a reduced need and duration of invasive ventilation [6, 19].

Interestingly, the rate of AKI was lower in all KDIGO stages in the second wave (Table 3). Lung-kidney interactions seem to play an important role in critically ill patients [20] and IMV is an important risk factor for AKI. Therefore, the lower rate of IMV may be also responsible for the decline in the AKI incidence [21]. These changes are also reflected in the lower rate of RRT in the second wave, which may be an important factor influencing ICU LOS. Since the immune response plays an important role in the pathophysiology of AKI [22] and the RECOVERY trial showed a reduced rate of RRT in the dexamethasone group [6], the widespread use of corticosteroids may also have positively influenced these results.

These reduced rates of IMV and RRT were associated with a significantly reduced median ICU LOS by 8 days (18 vs. 10 days, p ≤ 0.001); however, this did not end up in a reduced hospital mortality. While ICU mortality did not change significantly, hospital mortality increased. Some studies found improved mortality rates over time, whereas others found no differences [13, 14, 23, 24]; however, comparison to different ICU cohorts may be difficult due to the numerous influencing factors on the ICU population [25]. Additionally, the mortality we found in our first wave was already very low with 22.4% [4]. This remarkably low mortality rate has been discussed in detail [4]. Furthermore, a hospital mortality of 33.4% (second wave) in critically ill patients is still lower or similar compared to other studies [10, 12, 26] and was below the Austrian average. This indicates a successful ICU resource management as was already the case in the first wave.

When correcting for other baseline characteristics in a propensity-matched analysis, there was no significant association between the period of presentation (first or second wave) and hospital mortality. While an influence of the period cannot be completely excluded, other factors seem to be more important. When patient characteristics were analyzed to find possible explanations for the slight increase in hospital mortality, the most important difference between the two groups was an 8‑year increase in median age in the second period (72 years vs. 64 years). In our logistic regression model age was an independent predictor of hospital mortality after adjustment for other baseline characteristics (Table 4). In other studies, age was the strongest predictor for mortality in critically ill patients [27]. This is also supported by the Kaplan-Meier analysis, showing a significant association between older age and impaired hospital survival (Fig. 4).

This raises the question why the median age changed in our cohort. To date, few studies have looked at the differences between the first and second wave of hospitalized and ICU patients in the COVID-19 pandemic [13, 14, 23, 24]; however, no analysis found similar changes of age distribution over time [13, 14, 23, 24]. Our overall median age was relatively high compared to other cohorts from the first wave [10, 16, 28]. A country comparable in terms of overall age distribution such as Germany had similar median age in patients requiring invasive mechanical ventilation [26]. Furthermore, it cannot be ruled out that a change in admission policy over time contributed to the changing age patterns. The increased use of NIV and HFNC may have influenced ICU admissions, especially in old patients. Despite the higher median age, the frequency of treatment limitations remained constant and thus probably did not affect mortality; however, of all patients who died, the majority (70.3%) had a documented treatment limitation.

Factors other than age may also be important. In the logistic regression analysis, the number of comorbidities also remained significant after adjustment for other characteristics and seems to be a relevant risk factor for hospital mortality. The number of comorbidities was higher during the second wave, without reaching significance. While most studies focused on the evaluation of selected comorbidities [10, 12, 26, 28], the overall number of comorbidities might be an even more important indicator of hospital mortality. The third significant risk factor for hospital mortality in our cohort was frailty. Especially in older patients, frailty is an important outcome predictor in critically ill COVID-19 patients [29].

Our study has limitations due to its observational design. Therefore, potential biases from changing strategies over time and other influencing factors exist. Some important information like the severity of ARDS was missing; however SAPS III and SOFA scores at admission were available. We cannot exclude influence from the virus variants of concern; however, the largest period of the second wave was before the appearance of these variants in Austria (1 January 2021).

The strength of our study consists in its multicenter character, which includes both ICUs from peripheral and central university hospitals. Although other cohort studies reached higher patient numbers, the very similar baseline characteristics reflect good comparability. We included all critically ill patients from a region with 750,000 inhabitants.

Therapeutic strategies for patients with COVID-19 at the ICU improved over time, which lead to a reduction of IMV, AKI and RRT and subsequently to a reduced ICU LOS in the second period. Age is an important predictor of hospital mortality, with a strong influence on outcomes of critically ill COVID-19 patients.