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Record W2528299860 · doi:10.1080/00325481.2017.1246055

An update on the management of urinary tract infections in the era of antimicrobial resistance

2016· review· en· W2528299860 on OpenAlexaff
Mazen S. Bader, Mark Loeb, Annie Brooks

Bibliographic record

VenuePostgraduate Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsHamilton Health SciencesMcMaster UniversityJuravinski Hospital
Fundersnot available
KeywordsMedicineAntimicrobialUrinary systemAntibiotic resistanceIntensive care medicineAnti-Infective AgentsMicrobiologyAntibioticsInternal medicine

Abstract

fetched live from OpenAlex

Urinary tract infections (UTIs) caused by antibiotic-resistant Gram-negative bacteria are a growing concern due to limited therapeutic options. Gram-negative bacteria, specifically Enterobacteriaceae, are common causes of both community-acquired and hospital acquired UTIs. These organisms can acquire genes that encode for multiple antibiotic resistance mechanisms, including extended-spectrum-lactamases (ESBLs), AmpC- β -lactamase, and carbapenemases. The assessment of suspected UTI includes identification of characteristic symptoms or signs, urinalysis, dipstick or microscopic tests, and urine culture if indicated. UTIs are categorized according to location (upper versus lower urinary tract) and severity (uncomplicated versus complicated). Increasing rates of antibiotic resistance necessitate judicious use of antibiotics through the application of antimicrobial stewardship principles. Knowledge of the common causative pathogens of UTIs including local susceptibility patterns are essential in determining appropriate empiric therapy. The recommended first-line empiric therapies for acute uncomplicated bacterial cystitis in otherwise healthy adult nonpregnant females is a 5-day course of nitrofurantion or a 3-g single dose of fosfomycin tromethamine. Second-line options include fluoroquinolones and β-lactams, such as amoxicillin-clavulanate. Current treatment options for UTIs due to AmpC- β -lactamase-producing organisms include fosfomycin, nitrofurantion, fluoroquinolones, cefepime, piperacillin-tazobactam and carbapenems. In addition, treatment options for UTIs due to ESBLs-producing Enterobacteriaceae include nitrofurantion, fosfomycin, fluoroquinolones, cefoxitin, piperacillin-tazobactam, carbapenems, ceftazidime-avibactam, ceftolozane-tazobactam, and aminoglycosides. Based on identification and susceptibility results, alternatives to carbapenems may be used to treat mild-moderate UTIs caused by ESBL-producing Enterobacteriaceae. Ceftazidime-avibactam, colistin, polymixin B, fosfomycin, aztreonam, aminoglycosides, and tigecycline are treatment options for UTIs caused by carbapenem-resistant Enterobacteriaceae (CRE). Treatment options for UTIs caused by multidrug resistant (MDR)-Pseudomonas spp. include fluoroquinolones, ceftazidime, cefepime, piperacillin-tazobactam, carbapenems, aminoglycosides, colistin, ceftazidime-avibactam, and ceftolozane-tazobactam. The use of fluoroquinolones for empiric treatment of UTIs should be restricted due to increased rates of resistance. Aminoglycosides, colistin, and tigecycline are considered alternatives in the setting of MDR Gram-negative infections in patients with limited therapeutic options.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.351
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations263
Published2016
Admission routes1
Has abstractyes

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