Objectives To analyse the characteristics and predictors of death in hospitalized patients with coronavirus disease 2019 (COVID-19) in Spain. Methods A retrospective observational study was performed of the first consecutive patients hospitalized with COVID-19 confirmed by real-time PCR assay in 127 Spanish centres until 17 March 2020. The follow-up censoring date was 17 April 2020. We collected demographic, clinical, laboratory, treatment and complications data. The primary endpoint was all-cause mortality. Univariable and multivariable Cox regression analyses were performed to identify factors associated with death. Results Of the 4035 patients, male subjects accounted for 2433 (61.0%) of 3987, the median age was 70 years and 2539 (73.8%) of 3439 had one or more comorbidity. The most common symptoms were a history of fever, cough, malaise and dyspnoea. During hospitalization, 1255 (31.5%) of 3979 patients developed acute respiratory distress syndrome, 736 (18.5%) of 3988 were admitted to intensive care units and 619 (15.5%) of 3992 underwent mechanical ventilation. Virus- or host-targeted medications included lopinavir/ritonavir (2820/4005, 70.4%), hydroxychloroquine (2618/3995, 65.5%), interferon beta (1153/3950, 29.2%), corticosteroids (1109/3965, 28.0%) and tocilizumab (373/3951, 9.4%). Overall, 1131 (28%) of 4035 patients died. Mortality increased with age (85.6% occurring in older than 65 years). Seventeen factors were independently associated with an increased hazard of death, the strongest among them including advanced age, liver cirrhosis, low age-adjusted oxygen saturation, higher concentrations of C-reactive protein and lower estimated glomerular filtration rate. Conclusions Our findings provide comprehensive information about characteristics and complications of severe COVID-19, and may help clinicians identify patients at a higher risk of death.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

Background Reports on the impact of some antiretrovirals against SARS-CoV-2 infection and disease severity are conflicting. Objectives We evaluated the effect of tenofovir as either tenofovir alafenamide/emtricitabine (TAF/FTC) or tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) against SARS-CoV-2 infection and associated clinical outcomes among people living with HIV (PLWH). Methods We conducted a propensity score-matched analysis in the prospective PISCIS cohort of PLWH (n = 14 978) in Catalonia, Spain. We used adjusted Cox regression models to assess the association between tenofovir and SARS-CoV-2 outcomes. Results After propensity score-matching, SARS-CoV-2 diagnosis rates were similar in TAF/FTC versus ABC/3TC recipients (11.6% versus 12.5%, P = 0.256); lower among TDF/FTC versus ABC/3TC recipients (9.6% versus 12.8%, P = 0.021); and lower among TDF/FTC versus TAF/FTC recipients (9.6% versus 12.1%, P = 0.012). In well-adjusted logistic regression models, TAF/FTC was no longer associated with reduced SARS-CoV-2 diagnosis [adjusted odds ratio (aOR) 0.90; 95% confidence interval (CI), 0.78–1.04] or hospitalization (aOR 0.93; 95% CI, 0.60–1.43). When compared with ABC/3TC, TDF/FTC was not associated with reduced SARS-CoV-2 diagnosis (aOR 0.79; 95% CI, 0.60–1.04) or hospitalization (aOR 0.51; 95% CI, 0.15–1.70). TDF/FTC was not associated with reduced SARS-CoV-2 diagnosis (aOR 0.79; 95% CI, 0.60–1.04) or associated hospitalization (aOR 0.33; 95% CI, 0.10–1.07) compared with TAF/FTC. Conclusions TAF/FTC or TDF/FTC were not associated with reduced SARS-CoV-2 diagnosis rates or associated hospitalizations among PLWH. TDF/FTC users had baseline characteristics intrinsically associated with more benign SARS-CoV-2 infection outcomes. Tenofovir exposure should not modify any preventive or therapeutic SARS-CoV-2 infection management.

Objectives To assess the clinical and immunovirological outcomes among naive patients with advanced HIV presentation starting an antiretroviral regimen in real-life settings. Methods This was a multicentre, prospective cohort study. We included all treatment-naive adults with advanced HIV disease (CD4+ T cell count &lt; 200 cells/mm3or presence of an AIDS-defining illness) who started therapy between 2010 and 2020. The main outcomes were mortality, virological effectiveness (percentage of patients with viral load of ≤50 copies/mL) and immune restoration (percentage of patients with CD4+ T cell count above 350 cells/mm3). Competing risk analysis and Cox proportional models were performed. A propensity score-matching procedure was applied to assess the impact of the antiretroviral regimen. Results We included 1594 patients with advanced HIV disease [median CD4+T cell count of 81 cells/mm3and 371 (23.3%) with AIDS-defining illness] and with a median follow-up of 4.44 years. The most common ART used was an integrase strand transfer inhibitor (InSTI) regimen (46.9%), followed by PI (35.7%) and NNRTI (17.4%), with adjusted mortality rates at 3 years of 3.1% (95% CI 1.8%–4.3%), 4.7% (95% CI 2.2%–7.1%) and 7.6% (95% CI 5.4%–9.7%) (P = 0.001), respectively. Factors associated with increased mortality included older age and history of injection drug use, whilst treatment with an InSTI regimen was a protective factor [HR 0.5 (95% CI 0.3–0.9)]. A sensitivity analysis with propensity score procedure confirms these results. Patients who started an InSTI achieved viral suppression and CD4+ T cell count above 350 cells/mm3significantly earlier. Conclusions In this large real-life prospective cohort study, a significant lower mortality, earlier viral suppression and earlier immune reconstitution were observed among patients with advanced HIV disease treated with InSTIs.

The main aim of this study is to describe the relationship between serum levels of atazanavir, renal toxicity, and lithiasis. This is a prospective observational study of patients being treated with atazanavir (ATV) at Son Espases Teaching Hospital, Palma de Mallorca, between 2011 and 2013. The study includes 98 patients. Sixteen were found to have a history of urolithiasis. During a median monitoring period of 23 months, nine patients suffered renal colic, in three of whom ATV crystals were evidenced in urine. Cumulative incidence of renal colic was 9.2 per 100 patients. The variables related to having renal colic were the presence of alkaline urine pH and lower basal creatinine clearance. The mean serum level of ATV was slightly higher in patients with renal colic—1,303 μg/L versus 1,161 μg/L—but did not reach statistical significance. Neither were any significant differences detected by analysing the levels according to the timetable for ATV dosage. Cumulative incidence of renal colic was high in patients being treated with ATV, in 33% of whom the presence of ATV crystals was evidenced in urine. We were unable to demonstrate a relationship between ATV serum levels and renal colic or progression towards renal failure.