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Record W4286560699 · doi:10.1007/s15010-022-01884-x

The association between bacteria and outcome and the influence of sampling method, in people with a diabetic foot infection

2022· article· en· W4286560699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInfection · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsInstitute of Infection and Immunity
FundersVrije Universiteit AmsterdamAmsterdam University Medical Centers
KeywordsMedicineHazard ratioInternal medicineAmputationEnterococcusProportional hazards modelMicrobiologyDiabetic footStaphylococcus aureusStaphylococcusRetrospective cohort studyDiabetic foot ulcerBacteriaSurgeryGastroenterologyBiologyDiabetes mellitusConfidence intervalAntibiotics

Abstract

fetched live from OpenAlex

PURPOSE: Different bacteria lead to divers diabetic foot infections (DFIs), and some bacteria probably lead to higher amputation and mortality risks. We assessed mortality and amputation risk in relation to bacterial profiles in people DFI and investigated the role of sampling method. METHODS: We included people (> 18 years) with DFI in this retrospective study (2011-2020) at a Dutch tertiary care hospital. We retrieved cultures according to best sampling method: (1) bone biopsy; (2) ulcer bed biopsy; and (3) swab. We aggregated data into a composite determinant, consisting of unrepeated bacteria of one episode of infection, clustered into 5 profiles: (1) Streptococcus and Staphylococcus aureus; (2) coagulase-negative Staphylococcus, Cutibacterium, Corynebacterium and Enterococcus; (3) gram-negative; (4) Anaerobic; and (5) less common gram-positive bacteria. We calculated Hazard Ratio's (HR's) using time-dependent-Cox regression for the analyses and investigated effect modification by sampling method. RESULTS: We included 139 people, with 447 person-years follow-up and 459 episodes of infection. Sampling method modified the association between bacterial profiles and amputation for profile 2. HR's (95% CI's) for amputation for bacterial profiles 1-5: 0.7 (0.39-1.1); stratified analysis for profile 2: bone biopsy 0.84 (0.26-2.7), ulcer bed biopsy 0.89 (0.34-2.3), swab 5.9*(2.9-11.8); 1.3 (0.78-2.1); 1.6 (0.91-2.6); 1.6 (0.58-4.5). HR's (95% CI's) for mortality for bacterial profiles 1-5: 0.89 (0.49-1.6); 0.73 (0.38-1.4); 2.6*(1.4-4.8); 1.1(0.58-2.2); 0.80(0.19-3.3). CONCLUSIONS: In people with DFI, there was no association between bacterial profiles in ulcer bed and bone biopsies and amputation. Only in swab cultures, low-pathogenic bacteria (profile 2), were associated with a higher amputation risk. Infection with gram-negative bacteria was associated with a higher mortality risk. This study underlined the possible negative outcome of DFI treatment based on swabs cultures.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.307
Teacher spread0.291 · 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