Survivors of COVID-19 may present with long-lasting symptoms. 1 Some factors have been associated with the development of post-COVID conditions (also referred to as "long COVID"), 2 including hospitalization. 3 A study of older US veterans showed 15% reduction of long COVID after vaccination; however, study limitations included the low number of women and suboptimal vaccination schedules. 4 Methods | The study was approved by the Humanitas Research Hospital institutional review board. Each participant provided written informed consent.
Currently approved COVID-19 vaccines based on mRNA or adenovirus require a first jab followed by recall immunization. There is no indication as to whether individuals who have recovered from COVID-19 should be vaccinated, and if so, if they should receive one or two vaccine doses.
Here, we tested the antibody response developed after the first dose of the mRNA based vaccine encoding the SARS-CoV-2 full-length spike protein (BNT162b2) in 124 healthcare professionals of which 57 had a previous history of COVID-19 (ExCOVID). Post-vaccine antibodies in ExCOVID individuals increase exponentially within 7-15 days after the first dose compared to naive subjects (p<0.0001). We developed a multivariate Linear Regression (LR) model with l2 regularization to predict the IgG response for SARS-COV-2 vaccine. We found that the antibody response of ExCOVID patients depends on the IgG pre-vaccine titer and on the symptoms that they developed during the disorder, with anosmia/dysgeusia and gastrointestinal disorders being the most significantly positively correlated in the LR. Thus, one vaccine dose is sufficient to induce a good antibody response in ExCOVID subjects. On the contrary, a second dose might switch-off the immune response due to antigen exhaustion, which occurs in response to several viruses or drive the development of low-affinity antibodies for SARS-CoV-2 which may foster an antibody dependent enhancement (ADE) reaction when re-exposed to the virus. These results question whether a second shot in ExCOVID subjects is indeed required and suggest to post-pone it while monitoring antibody response longevity.
ObjectiveGastrointestinal (GI) bleeding commonly requires intensive care unit (ICU) in cases of potentialhaemodynamiccompromise or likely urgent intervention. However, manypatientsadmitted to the ICU stop bleeding and do not require further intervention, including blood transfusion. The present work proposes an artificial intelligence (AI) solution for the prediction of rebleeding in patients with GI bleeding admitted to ICU.MethodsA machine learning algorithm was trained and tested using two publicly available ICU databases, the Medical Information Mart for Intensive Care V.1.4 database and eICU Collaborative Research Database using freedom from transfusion as a proxy for patients who potentially did not require ICU-level care. Multiple initial observation time frames were explored using readily available data including labs, demographics and clinical parameters for a total of 20 covariates.ResultsThe optimal model used a 5-hour observation period to achieve an area under the curve of the receiving operating curve (ROC-AUC) of greater than 0.80. The model was robust when tested against both ICU databases with a similar ROC-AUC for all.ConclusionsThe potential disruptive impact of AI in healthcare innovation is acknowledge, but awareness of AI-related risk on healthcare applications and current limitations should be considered before implementation and deployment. The proposed algorithm is not meant to replace but to inform clinical decision making. Prospective clinical trial validation as a triage tool is warranted.
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