C5a elevation in convalescents from severe COVID-19 is not associated with early complement activation markers C3bBbP or C4d.

Numerous publications have underlined the link between complement C5a and the clinical course of COVID-19. We previously reported that levels of C5a remain high in the group of severely ill patients up to 90 days after hospital discharge. We have now evaluated which complement pathway fuels the elevated levels of C5a during hospitalization and follow-up. The alternative pathway (AP) activation marker C3bBbP and the soluble fraction of C4d, a footprint of the classical/lectin (CP/LP) pathway, were assessed by immunoenzymatic assay in a total of 188 serial samples from 49 patients infected with SARS-CoV-2. Unlike C5a, neither C3bBbP nor C4d readouts rose proportionally to the severity of the disease. Detailed correlation analyses in hospitalization and follow-up samples collected from patients of different disease severity showed significant positive correlations of AP and CP/LP markers with C5a in certain groups, except for the follow-up samples of the patients who suffered from highly severe COVID-19 and presented the highest C5a readouts. In conclusion, there is not a clear link between persistently high levels of C5a after hospital discharge and markers of upstream complement activation, suggesting the existence of a non-canonical source of C5a in patients with a severe course of COVID-19.

Controversies around the statistical presentation of data on mRNA-COVID 19 vaccine safety in pregnant women.

The work entitled "Preliminary Findings of mRNA Covid-19 Vaccine Safety in Pregnant Persons" published on April 21, 2021, in The New England Journal of Medicine, presented data collected from American surveillance systems and registries. However, problems with an unanimous interpretation of those results appeared in the public debate and citing articles. Some stated that the risk of miscarriage in vaccinated women was similar to historical values reported before the vaccines' approval. The others stated that risk was highly above-normative in women vaccinated during the first and second trimesters. We found several problems with the statistical treatment/interpretation of the originally presented values: a substantial percentage (up to 95.6%) of missing data, an incorrect denominator used for risk estimation, and too short follow-up that disabled the evaluation of the study's endpoint in numerous participants. Eventually, the Authors published a corrigendum on September 8, 2021, and pointed to updated data. Herein, we explain the statistical controversies raised by the original presentation and stress that analyzing the trade-off between knowledge and confusion brought by the release of incomplete results of such a high social interest, should aid in solving the dilemma of whether to publish preliminary data or none.

Persistence of High Levels of Serum Complement C5a in Severe COVID-19 Cases After Hospital Discharge.

Evidence supports a role of complement anaphylatoxin C5a in the pathophysiology of COVID-19. However, information about the evolution and impact of C5a levels after hospital discharge is lacking. We analyzed the association between circulating C5a levels and the clinical evolution of hospitalized patients infected with SARS-CoV-2. Serum C5a levels were determined in 32 hospitalized and 17 non-hospitalized patients from Clinica Universidad de Navarra. One hundred and eighty eight serial samples were collected during the hospitalization stay and up to three months during the follow-up. Median C5a levels were 27.71 ng/ml (25th to 75th percentile: 19.35-34.96) for samples collected during hospitalization, versus 16.76 ng/ml (12.90-25.08) for samples collected during the follow-up (p<0.001). There was a negative correlation between serum C5a levels and the number of days from symptom onset (p<0.001). C5a levels also correlated with a previously validated clinical risk score (p<0.001), and was associated with the severity of the disease (p<0.001). An overall reduction of C5a levels was observed after hospital discharge. However, elevated C5a levels persisted in those patients with high COVID-19 severity (i.e. those with a longest stay in the hospital), even after months from hospital discharge (p=0.020). Moreover, high C5a levels appeared to be associated with the presence of long-term respiratory symptoms (p=0.004). In conclusion, serum C5a levels remain high in severe cases of COVID-19, and are associated with the presence of respiratory symptoms after hospital discharge. These results may suggest a role for C5a in the long-term effects of COVID-19 infection.

Are official confirmed cases and fatalities counts good enough to study the COVID-19 pandemic dynamics? A critical assessment through the case of Italy.

As the COVID-19 outbreak is developing the two most frequently reported statistics seem to be the raw confirmed case and case fatalities counts. Focusing on Italy, one of the hardest hit countries, we look at how these two values could be put in perspective to reflect the dynamics of the virus spread. In particular, we find that merely considering the confirmed case counts would be very misleading. The number of daily tests grows, while the daily fraction of confirmed cases to total tests has a change point. It (depending on region) generally increases with strong fluctuations till (around, depending on region) 15-22 March and then decreases linearly after. Combined with the increasing trend of daily performed tests, the raw confirmed case counts are not representative of the situation and are confounded with the sampling effort. This we observe when regressing on time the logged fraction of positive tests and for comparison the logged raw confirmed count. Hence, calibrating model parameters for this virus's dynamics should not be done based only on confirmed case counts (without rescaling by the number of tests), but take also fatalities and hospitalization count under consideration as variables not prone to be distorted by testing efforts. Furthermore, reporting statistics on the national level does not say much about the dynamics of the disease, which are taking place at the regional level. These findings are based on the official data of total death counts up to 15 April 2020 released by ISTAT and up to 10 May 2020 for the number of cases. In this work, we do not fit models but we rather investigate whether this task is possible at all. This work also informs about a new tool to collect and harmonize official statistics coming from different sources in the form of a package for the R statistical environment and presents the "COVID-19 Data Hub."