Baricitinib improves respiratory function in patients treated with corticosteroids for SARS-CoV-2 pneumonia: an observational cohort study.

OBJECTIVES: The Janus kinase (JAK) inhibitor baricitinib may block viral entry into pneumocytes and prevent cytokine storm in patients with SARS-CoV-2 pneumonia. We aimed to assess whether baricitinib improved pulmonary function in patients treated with high-dose corticosteroids for moderate to severe SARS-CoV-2 pneumonia. METHODS: This observational study enrolled patients with moderate to severe SARS-CoV-2 pneumonia [arterial oxygen partial pressure (PaO2)/fraction of inspired oxygen (FiO2) <200 mmHg] who received lopinavir/ritonavir and HCQ plus either corticosteroids (CS group, n = 50) or corticosteroids and baricitinib (BCT-CS group, n = 62). The primary end point was the change in oxygen saturation as measured by pulse oximetry (SpO2)/FiO2 from hospitalization to discharge. Secondary end points included the proportion of patients requiring supplemental oxygen at discharge and 1 month later. Statistics were adjusted by the inverse propensity score weighting (IPSW). RESULTS: A greater improvement in SpO2/FiO2 from hospitalization to discharge was observed in the BCT-CS vs CS group (mean differences adjusted for IPSW, 49; 95% CI: 22, 77; P < 0.001). A higher proportion of patients required supplemental oxygen both at discharge (62.0% vs 25.8%; reduction of the risk by 82%, OR adjusted for IPSW, 0.18; 95% CI: 0.08, 0.43; P < 0.001) and 1 month later (28.0% vs 12.9%, reduction of the risk by 69%, OR adjusted for IPSW, 0.31; 95% CI: 0.11, 0.86; P = 0.024) in the CS vs BCT-CS group. CONCLUSIONS: . In patients with moderate to severe SARS-CoV-2 pneumonia a combination of baricitinib with corticosteroids was associated with greater improvement in pulmonary function when compared with corticosteroids alone. TRIAL REGISTRATION: European Network of Centres for Pharmacoepidemiology and Pharmacovigilance, ENCEPP (EUPAS34966, http://www.encepp.eu/encepp/viewResource.htm? id = 34967).

Activating Killer-Cell Immunoglobulin-Like Receptors Are Associated With the Severity of Coronavirus Disease 2019.

BACKGROUND: Etiopathogenesis of the clinical variability of the coronavirus disease 2019 (COVID-19) remains mostly unknown. In this study, we investigate the role of killer cell immunoglobulin-like receptor (KIR)/human leukocyte antigen class-I (HLA-I) interactions in the susceptibility and severity of COVID-19. METHODS: We performed KIR and HLA-I genotyping and natural killer cell (NKc) receptors immunophenotyping in 201 symptomatic patients and 210 noninfected controls. RESULTS: The NKcs with a distinctive immunophenotype, suggestive of recent activation (KIR2DS4low CD16low CD226low CD56high TIGIThigh NKG2Ahigh), expanded in patients with severe COVID-19. This was associated with a higher frequency of the functional A-telomeric activating KIR2DS4 in severe versus mild and/or moderate patients and controls (83.7%, 55.7% and 36.2%, P < 7.7 × 10-9). In patients with mild and/or moderate infection, HLA-B*15:01 was associated with higher frequencies of activating B-telomeric KIR3DS1 compared with patients with other HLA-B*15 subtypes and noninfected controls (90.9%, 42.9%, and 47.3%; P < .002; Pc = 0.022). This strongly suggests that HLA-B*15:01 specifically presenting severe acute respiratory syndrome coronavirus 2 peptides could form a neoligand interacting with KIR3DS1. Likewise, a putative neoligand for KIR2DS4 could arise from other HLA-I molecules presenting severe acute respiratory syndrome coronavirus 2 peptides expressed on infected an/or activated lung antigen-presenting cells. CONCLUSIONS: Our results support a crucial role of NKcs in the clinical variability of COVID-19 with specific KIR/ligand interactions associated with disease severity.

Generation and validation of in-hospital mortality prediction score in COVID-19 patients: Alba-score.

BACKGROUND: COVID-19 has a wide range of symptoms reported, which may vary from very mild cases (even asymptomatic) to deadly infections. Identifying high mortality risk individuals infected with the SARS-CoV-2 virus through a prediction instrument that uses simple clinical and analytical parameters at admission can help clinicians to focus on treatment efforts in this group of patients. METHODS: Data was obtained retrospectively from the electronic medical record of all COVID-19 patients hospitalized in the Albacete University Hospital Complex until July 2020. Patients were split into two: a generating and a validating cohort. Clinical, demographical and laboratory variables were included. A multivariate logistic regression model was used to select variables associated with in-hospital mortality in the generating cohort. A numerical and subsequently a categorical score according to mortality were constructed (A: mortality from 0% to 5%; B: from 5% to 15%; C: from 15% to 30%; D: from 30% to 50%; E: greater than 50%). These scores were validated with the validation cohort. RESULTS: Variables independently related to mortality during hospitalization were age, diabetes mellitus, confusion, SaFiO2, heart rate and lactate dehydrogenase (LDH) at admission. The numerical score defined ranges from 0 to 13 points. Scores included are: age ≥71 years (3 points), diabetes mellitus (1 point), confusion (2 points), onco-hematologic disease (1 point), SaFiO2 ≤ 419 (3 points), heart rate ≥ 100 bpm (1 point) and LDH ≥ 390 IU/L (2 points). The area under the curve (AUC) for the numerical and categorical scores from the generating cohort were 0.8625 and 0.848, respectively. In the validating cohort, AUCs were 0.8505 for the numerical score and 0.8313 for the categorical score. CONCLUSIONS: Data analysis found a correlation between clinical admission parameters and in-hospital mortality for COVID-19 patients. This correlation is used to develop a model to assist physicians in the emergency department in the COVID-19 treatment decision-making process.