To our knowledge, this is the first study to report changes in the characteristics of critically ill patients with acute respiratory failure due to Covid-19 after the emergence of the VOC 20H/501Y.V2. Demographic characteristics were similar between both waves, and our multivariate analysis associated with a machine learning method found that patients of wave 2 had less fever and had a lower illness severity score (SAPS II) at admission, but they were also more hypoxemic and more mechanically ventilated at 24 hours after admission and finally developed more VAP during their ICU stay.
Experience gained during the first wave and specific therapies have been associated to a better outcome among critically ill Covid-19 patients admitted during second waves across the world.[20–22] Among these therapies, the introduction of corticosteroids have been associated to a lower proportion of patients requiring invasive mechanical ventilation and to reduced mortality . Interestingly, despite implementation of a protocol for corticosteroids in our ICU, we did not found difference of mortality between both waves.
It has been suggested that VOC 20H/501Y.V2 could be associated to a higher hospital morbidity and mortality rate [26,27], therefore in our study the expected gain in survival brought by improvements in critical care management could have been mitigated by increased severity of the new lineage. However, changes in morbidity and mortality rates of patients with SARS-CoV-2 infection should be interpreted with caution. Independently of virus virulence, Covid-19 outcomes can largely be affected by the epidemiological context i.e. population structure, climate, and social practice for example.  The observational nature of previous studies implies possible unmeasured confounders factors. Moreover, hospital mortality and ICU mortality can differ largely because of very different fatality rates. In our study, higher rate of VAP, increased duration of invasive mechanical ventilation and of ICU length of stay could have directly contributed to mitigate outcome improvement.
We observed that despite similar SOFA score and slightly decreased SAPS II at admission, patients in wave 2 needed more invasive mechanical ventilation (aOR 3.49, 95% CI 0.98 – 12.51, p=0.055) and had a lower pO2/FiO2 ratio at 24 hours (aOR 0.99, 95 % CI 0.98-0.99, p=0.0309). These results are in line with a recent study of Carbonell et al, comparing mortality in ICU between waves in a multicenter retrospective cohort. Authors found a significant lower illness severity at admission but also a trend for an increased severity of respiratory failure at admission (lower pO2/FiO2 ratio) during wave 2 and 3 in Europe when higher incidence of cases led to ICU overload.
During wave 2, when VOC 20H/501Y.V2 was the dominant lineage, Mayotte Island experienced a rapid and intense deterioration of the epidemiological situation. At the epidemic peak, reached in the first weeks of February, Incidence Rate (IR) was 851/100,000, (i.e., 2,378 new confirmed cases in the week) and Positive Rate (PR) was 28%. The unique hospital of Mayotte was rapidly overloaded with a peak of new admissions reached in W6-2021 (225 patients hospitalized including 30 to ICU). For comparison during the peak of wave 1, 54 patients were hospitalized including 8 in ICU in a week . This epidemiological situation could be explained by an increased transmissibility of VOC 20H/501Y.V2 compared to wild lineage.
We observed that delay between first signs and hospital admission was increased during wave 2, 7 days (4-9) vs 6 days (3-8). As previously suggested, in an overwhelmed health system, individuals might avoid seeking care until later stage of disease . Likewise, recent studies have reported association between hospital and ICU load and increased mortality.[30,31] Therefore, we hypothesize that increased transmissibility of VOC 20H/501Y.V2 during wave 2 led to hospital and ICU capacity overload and thus to admission of patients with more severe respiratory failure.
An important finding of the study was that, using the same definition of VAP between both cohorts, we found a much higher incidence of VAP during the second wave compared to the first wave (57.4% vs 26.8%, p=0.001). VAP was independently associated with wave 2 (aOR 4.64, 95 CI 1.54-13.93, p =0.0063) after adjusting for invasive ventilation and pO2/FiO2 ratio at 24 hours. In a recent multicentric cohort comparing mortality between three waves in critically ill patients, Carbonell et al, also found an increased rate of VAP during second and third waves in Europe.. The large use of immunosuppressive agents (corticosteroids) during wave 2 could explain this finding. However, Ritter et al, showed in an observational study, after adjusting for competing risks, that corticosteroids seemed to have no impact on the likelihood of developing VAP .
The higher rate of VAP during wave 2 could also be explained by an increased rate of invasive mechanical ventilation during the first 24 hours and with an increased duration of mechanical ventilation.
Finally, it is possible that VOC 20H/501Y.V2 itself played a role immunologically in the propensity for VAP. Indeed, it has been reported that critically-ill patients with Covid-19 patients suffered from a considerable burden of immunoparesis, due to impaired immune cell function [33,34]. Since the beginning of the surge, the incidence of VAP is found higher in patients with SARS‑CoV‑2 infection, as compared to patients with influenza pneumonia, or no viral infection.[35,36] However, to date, specific effect on immune response of variants in critically-ill patients remains non-investigated.
The rate of comorbidities in our population was in line with previous studies except for diabetes, more frequent than previously reported [21,37]. Mayotte is the poorest and most densely populated territory in France with poor socio-economic and health conditions and prevalence of comorbidities such as diabetes is high . Interestingly, although second waves across the world have been frequently associated to younger patients with fewer comorbidities  we did not observe difference in demographic data between both waves. It has been proposed that the most vulnerable patients as older people and those with comorbidities were likely to die during first waves . However, wave 1 in Mayotte was much less intense than in other regions of the world. Therefore, specificities of the epidemic in Mayotte could explain the absence of change in profile of Covid-19 critically-ill patients between both waves.
Our study has some important strengths. First, to our knowledge, we describe for the first-time clinical characteristics and outcomes of critically ill patients with VOC 20H/501Y.V2. Second, we performed a detailed report of physiological, clinical features, and ventilatory management using the recent recommended WHO Clinical Progression Scale that has been developed to facilitate data pooling across cohort studies and clinical trials.  Third, we found similar typology of the patients at admission during both waves making relevant the comparison of outcomes. Fourth, the proportion of missing data was very low. Fifth, we performed the comparison between both waves in the only ICU of the island avoiding hospital variability previously described for Covid-19 patients . Lastly, addition of a machine learning method to the logistic regression allowed to improve characterization of variables associated to wave 2. Contrary to other machine learning classification tools, the logic of RF algorithm is understandable for clinicians, moreover RF model can provide importance ranking of the variables.
We acknowledge several limitations to our study. First, we performed a retrospective analysis with risk of mis-classification bias. Second, our study took place Mayotte Island, potentially limiting generalizability to other hospitals. Indeed, this population is known to have higher prevalence of cardiometabolic comorbidities and socioeconomic vulnerabilities. Studies among more ethnically and geographically diverse cohorts are needed to confirm our hypothesis concerning VOC 20H/501Y.V2. Third, we performed a description of changes in the characteristics of critically ill patients with Covid-19 in the first and second wave as a proxy for dominant lineage and we have individual-level data on lineage only for 23 critically-ill patients. However, during two days in the first half of February, all usable SARS-Cov-2 positive samples were screened and more than 80% of them (150/172) pointed to 20H/501Y.V2 variant. Lastly, we could not assess statistically the association of the ICU overload and outcomes.