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.

The term “amyloidosis” encompasses the heterogeneous group of diseases caused by the extracellular deposition of autologous fibrillar proteins. The global incidence of amyloidosis is estimated at five to nine cases per million patient-years. While amyloid light-chain (AL) amyloidosis is more frequent in developed countries, amyloid A (AA) amyloidosis is more common in some European regions and in developing countries. The spectrum of AA amyloidosis has changed in recent decades owing to: an increase in the median age at diagnosis; a percent increase in the frequency of primary AL amyloidosis with respect to the AA type; and a substantial change in the epidemiology of the underlying diseases. Diagnosis of amyloidosis is based on clinical organ involvement and histological evidence of amyloid deposits. Among the many tinctorial characteristics of amyloid deposits, avidity for Congo red and metachromatic birefringence under unidirectional polarized light remain the gold standard. Once the initial diagnosis has been made, the amyloid subtype must be identified and systemic organ involvement evaluated. In this sense, the 123I-labeled serum amyloid P component scintigraphy is a safe and noninvasive technique that has revolutionized the diagnosis and monitoring of treatment in systemic amyloidosis. It can successfully identify anatomical patterns of amyloid deposition throughout the body and enables not only an initial estimation of prognosis, but also the monitoring of the course of the disease and the response to treatment. Given the etiologic diversity of AA amyloidosis, common therapeutic strategies are scarce. All treatment options should be based upon a greater control of the underlying disease, adequate organ support, and treatment of symptoms. Nevertheless, novel therapeutic strategies targeting the formation of amyloid fibrils and amyloid deposition may generate new expectations for patients with AA amyloidosis.

The continuous flow of new research articles on MDR-TB diagnosis, treatment, prevention and rehabilitation requires frequent update of existing guidelines. This review is aimed at providing clinicians and public health staff with an updated and easy-to-consult document arising from consensus of Global Tuberculosis Network (GTN) experts.The core published documents and guidelines have been reviewed, including the recently published MDR-TB WHO rapid advice and ATS/CDC/ERS/IDSA guidelines.After a rapid review of epidemiology and risk factors, the clinical priorities on MDR-TB diagnosis (including whole genome sequencing and drug-susceptibility testing interpretations) and treatment (treatment design and management, TB in children) are discussed. Furthermore, the review comprehensively describes the latest information on contact tracing and LTBI management in MDR-TB contacts, while providing guidance on post-treatment functional evaluation and rehabilitation of TB sequelae, infection control and other public health priorities.

The World Health Organization (WHO) recommends that countries implement pharmacovigilance and collect information on active drug safety monitoring (aDSM) and management of adverse events.The aim of this prospective study was to evaluate the frequency and severity of adverse events to anti-tuberculosis (TB) drugs in a cohort of consecutive TB patients treated with new (i.e. bedaquiline, delamanid) and repurposed (i.e. clofazimine, linezolid) drugs, based on the WHO aDSM project. Adverse events were collected prospectively after attribution to a specific drug together with demographic, bacteriological, radiological and clinical information at diagnosis and during therapy. This interim analysis included patients who completed or were still on treatment at time of data collection.Globally, 45 centres from 26 countries/regions reported 658 patients (68.7% male, 4.4% HIV co-infected) treated as follows: 87.7% with bedaquiline, 18.4% with delamanid (6.1% with both), 81.5% with linezolid and 32.4% with clofazimine. Overall, 504 adverse event episodes were reported: 447 (88.7%) were classified as minor (grade 1–2) and 57 (11.3%) as serious (grade 3–5). The majority of the 57 serious adverse events reported by 55 patients (51 out of 57, 89.5%) ultimately resolved. Among patients reporting serious adverse events, some drugs held responsible were discontinued: bedaquiline in 0.35% (two out of 577), delamanid in 0.8% (one out of 121), linezolid in 1.9% (10 out of 536) and clofazimine in 1.4% (three out of 213) of patients. Serious adverse events were reported in 6.9% (nine out of 131) of patients treated with amikacin, 0.4% (one out of 221) with ethionamide/prothionamide, 2.8% (15 out of 536) with linezolid and 1.8% (eight out of 498) with cycloserine/terizidone.The aDSM study provided valuable information, but implementation needs scaling-up to support patient-centred care.

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...