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We investigated the predictors of delay in the diagnosis and mortality of patients with COVID-19 in Rio de Janeiro, Brazil. A cohort of 3,656 patients were evaluated (Feb-Apr 2020) and patients’ sociodemographic characteristics, and social development index (SDI) were used as determinant factors of diagnosis delays and mortality. Kaplan-Meier survival analyses, time-dependent Cox regression models, and multivariate logistic regression analyses were conducted. The median time from symptoms onset to diagnosis was eight days (interquartile range [IQR] 7.23-8.99 days). Half of the patients recovered during the evaluated period, and 8.3% died. Mortality rates were higher in men. Delays in diagnosis were associated with male gender (p = 0.015) and patients living in low SDI areas (p < 0.001). The age groups statistically associated with death were: 70-79 years, 80-89 years, and 90-99 years. Delays to diagnosis greater than eight days were also risk factors for death. Delays in diagnosis and risk factors for death from COVID-19 were associated with male gender, age under 60 years, and patients living in regions with lower SDI. Delays superior to eight days to diagnosis increased mortality rates.

An observational retrospective study was conducted over a 5-year period to assess survival and predictors of death in people with HIV-positive serology undergoing antiretroviral treatment with first-line regimens at the Military Hospital of Nampula, Mozambique. We collected data from 332 patient records. Kaplan-Meier boundary product estimator, log-rank, Gehan-Breslow, Tarone-Ware, time-dependent Cox models and estimates of hazard ratios (HR), with 95% confidence interval (CI) were calculated. Meantime survival for females and males was 54.8 months [95% CI 50.32-55.40] and 49.7 months [95% CI 45.89-53.53], respectively. Cox regressions indicated higher death rates significantly or potentially associated with: male sex (HR = 1.3; [95% CI 0.7-2.39]); suspected diagnosis reported only by the physician (HR = 3.6; [95% CI 1.8-7.4]); disease stages III (HR=1.2 [95% CI 0.3-3.6]) or IV (HR 1.4 [95% CI 0.4-5.8]); first TCD4+ lymphocyte count lower than 350 cells per ml (HR = 3.2; [95% CI 0.9-11.2]) or between 350-500 cells per ml (HR = 1.3; [95% CI 0.3-5.8]); or do not present cells count (HR = 3.6; [95% CI 1.2-10.2]). The above variables were significant for HIV prognosis and as predictors of death and should be considered in the clinical care of these patients.

Purpose To quantitatively assess the benefit-risk ratio on the efficacy and safety of all phosphodiesterase type 5 inhibitors (PDE5i) in men with erectile dysfunction. Methods A systematic review with network meta-analysis, surface under the cumulative ranking analysis and stochastic multicriteria acceptability analyses were performed. Searches were conducted in Pubmed, Scopus, Web of Science without limits for time-frame or language. Randomized controlled trials evaluating the efficacy or safety of any PDE5i compared to a placebo or to other PDE5i in males with erectile disfunction were included. Results Overall, 184 articles representing 179 randomized controlled trials (50,620 patients) were included. All PDE5i were significantly more efficient than placebo. Sildenafil 25 mg was statistically superior to all interventions in enhancing IIEF (with a 98% probability of being the most effective treatment), followed by sildenafil 50 mg (80% of probability). Taladafil 10 mg and 20 mg also presented good profiles (73% and 76%, respectively). Avanafil and lodenafil were less effective interventions. Mirodenafil 150 mg was the treatment that caused more adverse events, especially flushing and headaches. Sildenafil 100 mg was more related to visual disorders, while vardenafil and udenafil were more prone to cause nasal congestion. Conclusion Sildenafil at low doses and tadalafil should be the first therapeutic options. Avanafil, lodenafil and mirodenafil use are hardly justified given the lack of expressive efficacy or high rates of adverse events.

ObjectiveWe assessed the extent of lag times in the publication and indexing of network meta-analyses (NMAs).Study designThis was a survey of published NMAs on drug interventions.SettingNMAs indexed in PubMed (searches updated in May 2020).Primary and secondary outcome measuresLag times were measured as the time between the last systematic search and the article submission, acceptance, online publication, indexing and Medical Subject Headings (MeSH) allocation dates. Time-to-event analyses were performed considering independent variables (geographical origin, Journal Impact Factor, Scopus CiteScore, open access status) (SPSS V.24, R/RStudio).ResultsWe included 1245 NMAs. The median time from last search to article submission was 6.8 months (204 days (IQR 95–381)), and to publication was 11.6 months. Only 5% of authors updated their search after first submission. There is a very slightly decreasing historical trend of acceptance (rho=−0.087; p=0.010), online publication (rho=−0.080; p=0.008) and indexing (rho=−0.080; p=0.007) lag times. Journal Impact Factor influenced the MeSH allocation process, but not the other lag times. The comparison between open access versus subscription journals confirmed meaningless differences in acceptance, online publication and indexing lag times.ConclusionEfforts by authors to update their search before submission are needed to reduce evidence production time. Peer reviewers and editors should ensure authors’ compliance with NMA standards. The accuracy of these findings depends on the accuracy of the metadata used; as we evaluated only NMA on drug interventions, results may not be generalisable to all types of studies.

Burkitt lymphoma/leukemia (BL/L) is an aggressive oncohematological disease. This study evaluated the population-based prognosis and survival on BL/L as well as if BL/L behaved as a risk factor for the development of second primary cancers (SPCs) and if other first tumors behaved as risk factors for the occurrence of BL/L as an SPC. A retrospective cohort using the Surveillance, Epidemiology and End Results (SEER) Program (2008–2016) was performed. Kaplan–Meier, time-dependent covariate Cox regression and Poisson regression models were conducted. Overall, 3094 patients were included (median, 45 years, IQR, 22–62). The estimated overall survival was 65.4 months (95% CI, 63.6–67.3). Significantly more deaths occurred for older patients, black race, disease at an advanced stage, patients without chemotherapy/surgery and patients who underwent radiotherapy. Hodgkin lymphomas (nodal) (RR, 7.6 (3.9–15.0, p &lt, 0.001)), Kaposi sarcomas (34.0 (16.8–68.9, 0.001)), liver tumors (3.4 (1.2–9.3, p = 0.020)) and trachea, mediastinum and other respiratory cancers (15.8 (2.2–113.9, p = 0.006)) behaved as risk factors for the occurrence of BL/L as an SPC. BL/L was a risk factor for the occurrence of SPCs as acute myeloid leukemias (4.6 (2.1–10.4, 0.001)), Hodgkin lymphomas (extranodal) (74.3 (10.0–549.8, 0.001)) and Kaposi sarcomas (35.1 (12.1–101.4, 0.001)). These results may assist the development of diagnostic and clinical recommendations for BL/L.

© 2019 The British Pharmacological Society Aims: Despite their overall favourable safety profile, tyrosine kinase inhibitors (TKIs) are related to severe adverse events including haematological toxicities such as anaemia, leucopenia, neutropenia and thrombocytopenia. We designed a systematic review and network meta-analysis of randomised controlled trials to compare safety among TKIs (bosutinib, dasatinib, imatinib, nilotinib, ponatinib and radotinib) used by patients diagnosed with chronic myeloid leukaemia. Methods: We obtained data from the PubMed, Scopus, Web of Science, and SciELO databases. The Bayesian approach was used for direct and indirect comparisons, and the treatments were ranked by the surface under the cumulative ranking curve (SUCRA). Results: Seventeen studies were included in the network meta-analysis. Our data show that dasatinib was generally considered worse than the other TKIs, with SUCRA values ​​for 140 mg dasatinib of 90.3% for anaemia, 87.4% for leucopenia, 90.6% for neutropenia and 97.2% for thrombocytopenia. In addition, nilotinib was shown to be safer, with SUCRA values ​​for 600 and 800 mg doses of 21.9 and 35.8% for anaemia, 23.8 and 14.6% for leucopenia, 33.0 and 17.7% for neutropenia, and 28.7 and 32.6% for thrombocytopenia, respectively. Conclusion: Dasatinib appeared as the least safe drug for chronic myeloid leukaemia, probably because it binds to multiple key kinase targets, being more prone to cause serious haematological adverse events. Nilotinib demonstrated a safer profile, mostly due to its selective binding capacity.

What is known and objective Hyperprolactinemia is a neuroendocrine disease that is responsible for a quarter of cases of secondary amenorrhea, which can lead to infertility in women. Dopaminergic agonists (bromocriptine, cabergoline, quinagolide) can be used in the treatment. However, there is a lack of secondary studies that compare their efficacy and safety, especially through a network meta-analysis. Thus, to contribute to the decision-making, a systematic review and network meta-analyses (NMA) were performed to evaluate the efficacy and safety of dopaminergic agonists in the treatment of hyperprolactinemia. Methods Randomized clinical trials (RCT) were retrieved through PubMed, Web of Science and Scopus databases. The efficacy and safety of the drugs were compared, considering the following outcomes: prolactin (PRL) levels, number of patients with galactorrhoea, menstrual irregularities and adverse drug reactions. NMA was built for each outcome. Results were reported as odds ratios (OR) with 95% credibility intervals. Ranking probabilities were calculated by surface under the cumulative ranking analysis (SUCRA) and Stochastic multicriteria acceptability analysis (SMAA). Results and discussion Seventeen RCTs were included in the systematic review and fifteen in the meta-analyses. The drugs had similar efficacy, considering the PRL levels. The SUCRA analysis showed that quinagolide (0.075 and 0.05 mg/day) was superior for reducing irregular menstruation, whereas bromocriptine was the best (97%) for galactorrhoea. Cabergoline proved to be the safest drug, except for abdominal pain at a dose of 1 mg/week. The SMAA demonstrated similar results to SUCRA. What is new and conclusion This is the first network meta-analysis that evaluated the efficacy and safety of dopaminergic agonists in the treatment of hyperprolactinemia. The results of this review revealed that these drugs have similar efficacy, but cabergoline has a better safety profile.

Summary Background & aims COVID-19 is an emergency public health problem of global importance. This study aimed to investigate the effect of foods and nutrients as complementary approaches on the recovery from COVID-19 in 170 countries, especially considering the complexity of the disease and the current scarcity of active treatments. Methods A retrospective study was performed using the Kaggle database, which links the consumption of various foods with recovery from COVID-19 in 170 countries, using multivariate analysis based on a generalized linear model. Results The results showed that certain foods had a positive effect on recovery from COVID-19: eggs, fish and seafood, fruits, meat, milk, starchy roots, stimulants, vegetable products, nuts, vegetable oil and vegetables. In general, consumption of higher levels of proteins and lipids had a positive effect on COVID-19 recovery, whereas high consumption of alcoholic beverages had a negative effect. In developed countries, where hunger had been eradicated, the effect of food on recovery from COVID-19 had a greater magnitude than in countries with a higher global hunger index (GHI), where there was almost no identifiable effect. Conclusion Several foods had a positive effect on COVID-19 recovery in developed countries, especially food groups with a higher content of lipids, proteins, antioxidants and micronutrients (e.g., selenium and zinc). In countries with extreme poverty (high GHI), foods presented little effect on recovery from COVID-19.

Highlights • RT-PCR followed by CT shows high sensitivity for detecting COVID-19 • Immunological tests should use a combination of IgG and IgM • The genes E and RdRp present high analytical sensitivity to detect the virus • Assays for molecular diagnosis should employ two-target systems • Studies of diagnostic tests for COVID-19 are of moderate methodological quality, Objective . To collate the evidence on the accuracy parameters of all available diagnostic methods for detecting SARS-CoV-2. Methods . A systematic review with meta-analysis was performed. Searches were conducted in Pubmed and Scopus (April 2020). Studies reporting data on sensitivity or specificity of diagnostic tests for COVID-19 using any human biological sample were included. Results . Sixteen studies were evaluated. Meta-analysis showed that computed tomography has high sensitivity (91.9% [89.8–93.7%]), but low specificity (25.1% [21.0–29.5%]). The combination of IgM and IgG antibodies demonstrated promising results for both parameters (84.5% [82.2%-86.6%]; 91.6% [86.0%-95.4%], respectively). For RT-PCR tests, rectal stools/swab, urine, and plasma were less sensitive while sputum (97.2% [90.3–99.7%]) presented higher sensitivity for detecting the virus. Conclusions . RT-PCR remains the gold standard for the diagnosis of COVID-19 in sputum samples. However, the combination of different diagnostic tests is highly recommended to achieve adequate sensitivity and specificity.

This systematic review (number register: CRD42018112736) was performed to compare the sensitivity and specificity of leprosy diagnostic methods. The search was conducted in 3 electronic databases in January 2021. Studies evaluating leprosy diagnostic tests were included according the eligibility criteria. Meta-analysis was performed to calculate the sensibility and specificity of the groups. We included 36 studies. The test sensitivity for paucibacillary patients was 0.31 (95%CI: 0.29-0.33) and the specificity was 0.92 (95%CI: 0.92-0.93). In multibacillary patients, the sensitivity was 0.78 (95%CI: 0.77-0.80) and specificity was 0.92 (95%CI: 0.92-0.93). Comparing the sensitivity and specificity of the different techniques included, it should be noted that polymerase chain reaction (PCR) test presented the highest sensitivity for paucibacillary patients, while the western blot technique showed the highest sensitivity for multibacillary patients. However, further studies are needed to optimise the diagnosis of leprosy, requiring research with a larger number of samples and more uniform protocols.

Objective This study aimed to implement and evaluate machine learning based-models to predict COVID-19’ diagnosis and disease severity. Methods COVID-19 test samples (positive or negative results) from patients who attended a single hospital were evaluated. Patients diagnosed with COVID-19 were categorised according to the severity of the disease. Data were submitted to exploratory analysis (principal component analysis, PCA) to detect outlier samples, recognise patterns, and identify important variables. Based on patients’ laboratory tests results, machine learning models were implemented to predict disease positivity and severity. Artificial neural networks (ANN), decision trees (DT), partial least squares discriminant analysis (PLS-DA), and K nearest neighbour algorithm (KNN) models were used. The four models were validated based on the accuracy (area under the ROC curve). Results The first subset of data had 5,643 patient samples (5,086 negatives and 557 positives for COVID-19). The second subset included 557 COVID-19 positive patients. The ANN, DT, PLS-DA, and KNN models allowed the classification of negative and positive samples with >84% accuracy. It was also possible to classify patients with severe and non-severe disease with an accuracy >86%. The following were associated with the prediction of COVID-19 diagnosis and severity: hyperferritinaemia, hypocalcaemia, pulmonary hypoxia, hypoxemia, metabolic and respiratory acidosis, low urinary pH, and high levels of lactate dehydrogenase. Conclusion Our analysis shows that all the models could assist in the diagnosis and prediction of COVID-19 severity.

© 2018 Elsevier Ltd Background: The pharmacotherapy of chronic myeloid leukaemia (CML) is mainly based on tyrosine kinase inhibitors (TKIs). The aim of this study was to compare the efficacy and safety of all TKIs in CML patients. Methods: We conducted a systematic review with network meta-analysis (NMA) of randomised controlled trials (RCTs), including imatinib, nilotinib, dasatinib, bosutinib, radotinib and ponatinib. Searches were performed in PubMed, Scopus, Web of Science and SciELo (March 2018). The NMAs were built for six outcomes at 12 months: complete cytogenetic response (CCyR), major cytogenetic response (MCyR), deep molecular response, major molecular response (MMR), complete haematologic response and incidence of serious adverse events. We conducted rank order and surface under the cumulative ranking curve (SUCRA) analyses. Results: Thirteen RCTs were included (n = 5079 patients). Statistical differences were observed for some comparisons in all outcomes. Imatinib 400 mg was considered the safest drug (SUCRA values of 10.3%) but presented low efficacy. Overall, nilotinib 600 mg was superior to the other TKI in efficacy (SUCRA values of 61.1% for CCyR, 81.0% for MMR, 90.0% for MCyR); however, no data on its safety profile at 12 months were reported. Interpretation: Our results suggest that nilotinib should be upgraded to first-line therapy for CML, although further cost-effectiveness analyses, including the new TKI (i.e., ponatinib, radotinib), are needed.

Type 2 diabetes mellitus, a disease which prevalence has been progressively increasing worldwide, is characterized by chronic hyperglycemia resulting from the combination of inappropriate insulin secretion and/or resistance to insulin action. If left uncontrolled, diabetes is associated with complications such as dysfunction and failure of various organs, and even premature death. Along with lifestyle-modification strategies, several classes of oral antidiabetic agents can be employed for glycemic control. Thus, therapeutic drug monitoring of these drugs is essential to maintain appropriate treatment. This review discusses the most frequently employed analytical techniques and sample preparation systems to obtain a reliable and trustworthy method to quantify antidiabetic drugs in biological matrices. An adequate choice of internal standard, ideal chromatography conditions and most suitable analytical detector are reported.