Manchester Academic Health Science Centre

About: Manchester Academic Health Science Centre is a healthcare organization based out in Manchester, United Kingdom. It is known for research contribution in the topics: Population & Medicine. The organization has 4119 authors who have published 6108 publications receiving 175579 citations.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Abstract: Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

2020 International Society of Hypertension global hypertension practice guidelines

Abstract: Document reviewers: Hind Beheiry (Sudan), Irina Chazova (Russia), Albertino Damasceno (Mozambique), Anna Dominiczak (UK), Anastase Dzudie (Cameroon), Stephen Harrap (Australia), Hiroshi Itoh (Japan), Tazeen Jafar (Singapore), Marc Jaffe (USA), Patricio Jaramillo-Lopez (Colombia), Kazuomi Kario (Japan), Giuseppe Mancia (Italy), Ana Mocumbi (Mozambique), Sanjeevi N.Narasingan (India), Elijah Ogola (Kenya), Srinath Reddy (India), Ernesto Schiffrin (Canada), Ann Soenarta (Indonesia), Rhian Touyz (UK), Yudah Turana (Indonesia), Michael Weber (USA), Paul Whelton (USA), Xin Hua Zhang, (Australia), Yuqing Zhang (China).

Secukinumab in plaque psoriasis--results of two phase 3 trials.

Abstract: BACKGROUND: Interleukin-17A is considered to be central to the pathogenesis of psoriasis. We evaluated secukinumab, a fully human anti-interleukin-17A monoclonal antibody, in patients with moderate-to-severe plaque psoriasis. METHODS: In two phase 3, double-blind, 52-week trials, ERASURE (Efficacy of Response and Safety of Two Fixed Secukinumab Regimens in Psoriasis) and FIXTURE (Full Year Investigative Examination of Secukinumab vs. Etanercept Using Two Dosing Regimens to Determine Efficacy in Psoriasis), we randomly assigned 738 patients (in the ERASURE study) and 1306 patients (in the FIXTURE study) to subcutaneous secukinumab at a dose of 300 mg or 150 mg (administered once weekly for 5 weeks, then every 4 weeks), placebo, or (in the FIXTURE study only) etanercept at a dose of 50 mg (administered twice weekly for 12 weeks, then once weekly). The objective of each study was to show the superiority of secukinumab over placebo at week 12 with respect to the proportion of patients who had a reduction of 75% or more from baseline in the psoriasis area-and-severity index score (PASI 75) and a score of 0 (clear) or 1 (almost clear) on a 5-point modified investigator's global assessment (coprimary end points). RESULTS: The proportion of patients who met the criterion for PASI 75 at week 12 was higher with each secukinumab dose than with placebo or etanercept: in the ERASURE study, the rates were 81.6% with 300 mg of secukinumab, 71.6% with 150 mg of secukinumab, and 4.5% with placebo; in the FIXTURE study, the rates were 77.1% with 300 mg of secukinumab, 67.0% with 150 mg of secukinumab, 44.0% with etanercept, and 4.9% with placebo (P<0.001 for each secukinumab dose vs. comparators). The proportion of patients with a response of 0 or 1 on the modified investigator's global assessment at week 12 was higher with each secukinumab dose than with placebo or etanercept: in the ERASURE study, the rates were 65.3% with 300 mg of secukinumab, 51.2% with 150 mg of secukinumab, and 2.4% with placebo; in the FIXTURE study, the rates were 62.5% with 300 mg of secukinumab, 51.1% with 150 mg of secukinumab, 27.2% with etanercept, and 2.8% with placebo (P<0.001 for each secukinumab dose vs. comparators). The rates of infection were higher with secukinumab than with placebo in both studies and were similar to those with etanercept. CONCLUSIONS: Secukinumab was effective for psoriasis in two randomized trials, validating interleukin-17A as a therapeutic target. (Funded by Novartis Pharmaceuticals; ERASURE and FIXTURE ClinicalTrials.gov numbers, NCT01365455 and NCT01358578, respectively.).

Global burden of disease of HIV-associated cryptococcal meningitis: An updated analysis

Abstract: Summary Background Cryptococcus is the most common cause of meningitis in adults living with HIV in sub-Saharan Africa. Global burden estimates are crucial to guide prevention strategies and to determine treatment needs, and we aimed to provide an updated estimate of global incidence of HIV-associated cryptococcal disease. Methods We used 2014 Joint UN Programme on HIV and AIDS estimates of adults (aged >15 years) with HIV and antiretroviral therapy (ART) coverage. Estimates of CD4 less than 100 cells per μL, virological failure incidence, and loss to follow-up were from published multinational cohorts in low-income and middle-income countries. We calculated those at risk for cryptococcal infection, specifically those with CD4 less than 100 cells/μL not on ART, and those with CD4 less than 100 cells per μL on ART but lost to follow-up or with virological failure. Cryptococcal antigenaemia prevalence by country was derived from 46 studies globally. Based on cryptococcal antigenaemia prevalence in each country and region, we estimated the annual numbers of people who are developing and dying from cryptococcal meningitis. Findings We estimated an average global cryptococcal antigenaemia prevalence of 6·0% (95% CI 5·8–6·2) among people with a CD4 cell count of less than 100 cells per μL, with 278 000 (95% CI 195 500–340 600) people positive for cryptococcal antigen globally and 223 100 (95% CI 150 600–282 400) incident cases of cryptococcal meningitis globally in 2014. Sub-Saharan Africa accounted for 73% of the estimated cryptococcal meningitis cases in 2014 (162 500 cases [95% CI 113 600–193 900]). Annual global deaths from cryptococcal meningitis were estimated at 181 100 (95% CI 119 400–234 300), with 135 900 (75%; [95% CI 93 900–163 900]) deaths in sub-Saharan Africa. Globally, cryptococcal meningitis was responsible for 15% of AIDS-related deaths (95% CI 10–19). Interpretation Our analysis highlights the substantial ongoing burden of HIV-associated cryptococcal disease, primarily in sub-Saharan Africa. Cryptococcal meningitis is a metric of HIV treatment programme failure; timely HIV testing and rapid linkage to care remain an urgent priority. Funding None.