Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.

/pdf/integrating-host-response-and-unbiased-microbe-detection-for-d158ogv406.pdf

Integrating host response and unbiased microbe detection for lower respiratory tract infection diagnosis in critically ill adults

Antibiotic-resistant infections are a global health care concern. The Centers for Disease Control and Prevention estimates that 23,000 Americans with these infections die each year. Rising infection rates add to the costs of health care and compromise the quality of medical and surgical procedures provided. Little is known about the national health care costs attributable to treating the infections. Using data from the Medical Expenditure Panel Survey, we estimated the incremental health care costs of treating a resistant infection as well as the total national costs of treating such infections. To our knowledge, this is the first national estimate of the costs for treating the infections. We found that antibiotic resistance added $1,383 to the cost of treating a patient with a bacterial infection. Using our estimate of the number of such infections in 2014, this amounts to a national cost of $2.2 billion annually. The need for innovative new infection prevention programs, antibiotics, and vaccines to pre...

/pdf/antibiotic-resistant-infection-treatment-costs-have-doubled-v6a0l1g8hw.pdf

Antibiotic-Resistant Infection Treatment Costs Have Doubled Since 2002, Now Exceeding $2 Billion Annually

Mesoporous bioactive glasses: Promising platforms for antibacterial strategies

Objectives Previous work based on guidelines and expert opinion identified 'ideal' prescribing proportions-the overall proportion of consultations that should result in an antibiotic prescription-for common infectious conditions. Here, actual condition-specific prescribing proportions in primary care in England were compared with ideal prescribing proportions identified by experts. Methods All recorded consultations for common infectious conditions (cough, bronchitis, exacerbations of asthma or chronic obstructive pulmonary disease, sore throat, rhinosinusitis, otitis media, lower respiratory tract infection, upper respiratory tract infection, influenza-like illness, urinary tract infection, impetigo, acne, gastroenteritis) for 2013-15 were extracted from The Health Improvement Network (THIN) database. The proportions of consultations resulting in an antibiotic prescription were established, concentrating on acute presentations in patients without relevant comorbidities. These actual prescribing proportions were then compared with previously established 'ideal' proportions by condition. Results For most conditions, substantially higher proportions of consultations resulted in an antibiotic prescription than was deemed appropriate according to expert opinion. An antibiotic was prescribed in 41% of all acute cough consultations when experts advocated 10%. For other conditions the proportions were: bronchitis (actual 82% versus ideal 13%); sore throat (actual 59% versus ideal 13%); rhinosinusitis (actual 88% versus ideal 11%); and acute otitis media in 2- to 18-year-olds (actual 92% versus ideal 17%). Substantial variation between practices was found. Conclusions This work has identified substantial overprescribing of antibiotics in English primary care, and highlights conditions where this is most pronounced, particularly in respiratory tract conditions.

/pdf/actual-versus-ideal-antibiotic-prescribing-for-common-2wdyjnhok6.pdf

Actual versus ‘ideal’ antibiotic prescribing for common conditions in English primary care

Background

The prevalence of reported penicillin allergy (PenA) and the impact these records have on health outcomes in the UK general population are unknown. Without such data, justifying and planning enhanced allergy services is challenging.



Objectives

To determine: (i) prevalence of PenA records; (ii) patient characteristics associated with PenA records; and (iii) impact of PenA records on antibiotic prescribing/health outcomes in primary care.



Methods

We carried out cross-sectional/retrospective cohort studies using patient-level data from electronic health records. Cohort study: exact matching across confounders identified as affecting PenA records. Setting: English NHS general practices between 1 April 2013 and 31 March 2014. Participants: 2.3 million adult patients. Outcome measures: prevalence of PenA, antibiotic prescribing, mortality, MRSA infection/colonization and Clostridioides difficile infection.



Results

PenA prevalence was 5.9% (IQR = 3.8%–8.2%). PenA records were more common in older people, females and those with a comorbidity, and were affected by GP practice. Antibiotic prescribing varied significantly: penicillins were prescribed less frequently in those with a PenA record [relative risk (RR)  = 0.15], and macrolides (RR = 4.03), tetracyclines (RR = 1.91) nitrofurantoin (RR = 1.09), trimethoprim (RR = 1.04), cephalosporins (RR = 2.05), quinolones (RR = 2.10), clindamycin (RR = 5.47) and total number of prescriptions were increased in patients with a PenA record. Risk of re-prescription of a new antibiotic class within 28 days (RR = 1.32), MRSA infection/colonization (RR = 1.90) and death during the year subsequent to 1 April 2013 (RR = 1.08) increased in those with PenA records.



Conclusions

PenA records are common in the general population and associated with increased/altered antibiotic prescribing and worse health outcomes. We estimate that incorrect PenA records affect 2.7 million people in England. Establishing true PenA status (e.g. oral challenge testing) would allow more people to be prescribed first-line antibiotics, potentially improving health outcomes.

/pdf/warning-allergic-to-penicillin-association-between-41prfq98vf.pdf

'Warning: Allergic to penicillin': Association between penicillin allergy status in 2.3 million NHS general practice electronic health records, antibiotic prescribing and health outcomes

Objective:To assess the efficacy of fenofibrate and statin dual therapy versus a double or equivalent dose of statin monotherapy.Methods:A systematic literature search and meta-analysis was performed for publications before 1 January 2014 in MEDLINE, Embase, and BIOSIS Previews, among others.Results:The difference in percentage change from baseline was in favor of dual therapy versus a double dose of statin monotherapy for triglycerides (difference −20%; standard error [SE] 2.6%) and HDL-C (8.7%; SE 1.2%), but not for LDL-C (8.4%; SE 1.5%), non-HDL-C (2.8%; SE 1.1%), total cholesterol (4.5%; SE 1.0%) and apolipoprotein B (2.6%; SE 1.1%). For high intensity statins, the difference in percentage change from baseline was in favor of dual therapy versus equivalent statin monotherapy for triglycerides (−17%; SE 2.6%) and for HDL-C (8.7%; SE 1.9%). The difference in percentage change from baseline for LDL-C was 6% (SE 1.7%), implying a greater reduction in LDL-C with statin monotherapy. For moderate int...

Systematic literature review and meta-analysis of dual therapy with fenofibrate or fenofibric acid and a statin versus a double or equivalent dose of statin monotherapy

We aimed to investigate whether ibuprofen use, compared with other non-selective non-steroidal anti-inflammatory drugs (ns-NSAIDs), cyclooxygenase-2 inhibitors (COX-2i) or paracetamol, increases the risk of coronavirus disease 2019 (COVID-19) diagnosis or hospitalisation.A prevalent user and active comparator cohort study.Two US claims databases (Open Claims and PharMetrics Plus) mapped to the Observational Medical Outcomes Partnership Common Data Model.Insured patients with a history of osteoarthritis or back pain and receiving ibuprofen, other ns-NSAIDs, COX-2i or paracetamol between 1 November, 2019 and 31 January, 2020 (study enrolment window 1) or between 1 February, 2020 and 31 October, 2020 (study enrolment window 2).Large-scale propensity score matching and empirical calibration were used to minimise confounding. Incidence and hazard ratios of COVID-19 diagnosis and hospitalisation according to drug/s use were estimated and pooled in the same study period across data sources using a fixed-effects meta-analysis. Index treatment episode was the primary risk evaluation window, censored at the time of discontinuation.A total of 633,562 and 1,063,960 participants were included in periods 1 and 2, respectively, for the ibuprofen versus ns-NSAIDs comparison, 311,669 and 524,470 for ibuprofen versus COX-2i, and 492,002 and 878,598 for ibuprofen versus paracetamol. Meta-analyses of empirically calibrated hazard ratios revealed no significantly differential risk of COVID-19 outcomes in users of ibuprofen versus any of the other studied analgesic classes: hazard ratios were 1.13 (0.96-1.33) for the ibuprofen-ns-NSAIDs comparison, 1.03 (0.83-1.28) for the ibuprofen-COX-2i comparison and 1.13 (0.74-1.73) for ibuprofen-paracetamol comparison on COVID-19 diagnosis in the February 2020-October 2020 window. Similar hazard ratios were found on COVID-19 hospitalisation and across both study periods.In patients with osteoarthritis or back pain, we found no differential risks of incident COVID-19 diagnosis or COVID-19 hospitalisation for ibuprofen users compared with other ns-NSAIDs, COX-2i or paracetamol. Our findings support regulatory recommendations that NSAIDs, including ibuprofen, should be prescribed as indicated in the same way as before the COVID-19 pandemic, especially for those who rely on ibuprofen or NSAIDs to manage chronic arthritis or musculoskeletal pain symptoms. 

/pdf/risk-of-covid-19-diagnosis-and-hospitalisation-in-patients-3jrm2jit.pdf

Risk of COVID-19 Diagnosis and Hospitalisation in Patients with Osteoarthritis or Back Pain Treated with Ibuprofen Compared to Other NSAIDs or Paracetamol: A Network Cohort Study

php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Open Access Medical Statistics 2018:8 1–9 Open Access Medical Statistics Dovepress

/pdf/preferred-s-adenosylmethionine-prescription-in-routine-1008xawdoh.pdf

Preferred S-adenosylmethionine prescription in routine practice for intrahepatic cholestasis management: results of a multinomial logistic regression grid-optimization approach

Objective To characterise failure of antibiotic treatment in primary care in the United Kingdom in four common infection classes from 1991 to 2012.

Design Longitudinal analysis of failure rates for first line antibiotic monotherapies associated with diagnoses for upper and lower respiratory tract infections, skin and soft tissue infections, and acute otitis media.

Setting Routine primary care data from the UK Clinical Practice Research Datalink (CPRD).

Main outcome measures Adjusted rates of treatment failure defined by standardised criteria and indexed to year 1 (1991=100).

Results From 58 million antibiotic prescriptions in CPRD, we analysed 10 967 607 monotherapy episodes for the four indications: 4 236 574 (38.6%) for upper respiratory tract infections; 3 148 947 (28.7%) for lower respiratory tract infections; 2 568 230 (23.4%) for skin and soft tissue infections; and 1 013 856 (9.2%) for acute otitis media. In 1991, the overall failure rate was 13.9% (12.0% for upper respiratory tract infections; 16.9% for lower respiratory tract infections; 12.8% for skin and soft tissue infections; and 13.9% for acute otitis media). By 2012, the overall failure rate was 15.4%, representing an increase of 12% compared with 1991 (adjusted value indexed to first year (1991) 112, 95% confidence interval 112 to 113). The highest rate was seen in lower respiratory tract infections (135, 134 to 136). While failure rates were below 20% for most commonly prescribed antibiotics (amoxicillin, phenoxymethylpenicillin (penicillin-V), and flucloxacillin), notable increases were seen for trimethoprim in the treatment of upper respiratory tract infections (from 29.2% in 1991-95 to 70.1% in 2008-12) and for ciprofloxacin (from 22.3% in 1991-95 to 30.8% in 2008-12) and cefalexin (from 22.0% in 1991-95 to 30.8% in 2008-12) in the treatment of lower respiratory tract infections. Failure rates for broad spectrum penicillins, macrolides, and flucloxacillin remained largely stable.

Conclusions From 1991 to 2012, more than one in 10 first line antibiotic monotherapies for the selected infections were associated with treatment failure. Overall failure rates increased by 12% over this period, with most of the increase occurring in more recent years, when antibiotic prescribing in primary care plateaued and then increased.

https://www.bmj.com/content/bmj/349/bmj.g5493.full.pdf

Antibiotic treatment failure in four common infections in UK primary care 1991-2012: longitudinal analysis

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Stefan Driessen

Author Tools

Chat about Author

Papers

Systematic literature review and meta-analysis of dual therapy with fenofibrate or fenofibric acid and a statin versus a double or equivalent dose of statin monotherapy

Risk of COVID-19 Diagnosis and Hospitalisation in Patients with Osteoarthritis or Back Pain Treated with Ibuprofen Compared to Other NSAIDs or Paracetamol: A Network Cohort Study

Preferred S-adenosylmethionine prescription in routine practice for intrahepatic cholestasis management: results of a multinomial logistic regression grid-optimization approach

Antibiotic treatment failure in four common infections in UK primary care 1991-2012: longitudinal analysis