Back

Organism spectrum and no-growth fraction of deep specimens in code-defined orthopedic infection: a reproducible, cross-sectional MIMIC-IV benchmark

Adiniaev, Y.; Gorenshtein, A.; Timor, T. M.; Klang, E.; Geftler, A.

2026-07-10 infectious diseases
10.64898/2026.07.09.26357616 medRxiv
Show abstract

Abstract Introduction. Culture data guide orthopedic-infection management, yet the organism spectrum, resistance, and no-growth fraction are reported inconsistently and mostly within proprietary registries. We characterized these in a public, reproducible dataset. Methods. Retrospective cross-sectional study using MIMIC-IV version 3.1, a de-identified single-center US database. Episodes with an International Classification of Diseases diagnosis of prosthetic joint infection (PJI) or native osteomyelitis were identified; organism-spectrum and no-growth analyses were restricted to the 46% with at least one deep musculoskeletal culture (tissue or bone, synovial or joint fluid, implant sonication), so the benchmark describes culture-sampled, not all, coded episodes. Proportions carry exact 95% CIs; variation was tested by logistic regression with Benjamini-Hochberg control, and an out-of-fold logistic model quantified how well no-growth was anticipated by structured data. Results. Of 7697 episodes (median age, 60 years; 35.5% female), 1089 were PJI, 5715 native osteomyelitis, and 893 other device infection. Among 7700 deep specimens (3560 episodes; 2603 patients), 35.7% showed no growth (patient-clustered 95% CI, 34.0%-37.3%). The fraction was higher in PJI than osteomyelitis (48.6% vs 26.6%) but rose with sampling intensity (24.5% to 50.7%), indicating differential ascertainment. S. aureus led (32.5%; 43.3% methicillin-resistant), and PJI was less often polymicrobial than osteomyelitis (adjusted OR, 0.44). No-growth was weakly anticipated by structured data (out-of-fold AUROC, 0.63). Conclusions. About one-third of deep specimens from code-defined orthopedic infection showed no growth. This specimen-level fraction differs from a criterion-confirmed culture-negative-infection rate and depends on sampling intensity; it is released as a re-runnable benchmark on identical open data, not a transferable rate.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
Microbiology Spectrum
469 papers in training set
Top 2%
6.7%
2
Nature Communications
5641 papers in training set
Top 23%
6.7%
3
PLOS ONE
5266 papers in training set
Top 26%
6.2%
4
BMJ Open
601 papers in training set
Top 4%
5.5%
5
The Lancet Microbe
44 papers in training set
Top 0.1%
5.2%
6
Clinical Microbiology and Infection
62 papers in training set
Top 0.1%
3.5%
7
The Journal of Infectious Diseases
202 papers in training set
Top 1%
3.4%
8
Journal of Hospital Infection
29 papers in training set
Top 0.1%
3.2%
9
Scientific Reports
3612 papers in training set
Top 38%
2.7%
10
Nature Microbiology
155 papers in training set
Top 1%
2.6%
11
Science Translational Medicine
127 papers in training set
Top 1%
2.4%
12
The Lancet Infectious Diseases
73 papers in training set
Top 0.5%
2.4%
50% of probability mass above
13
Antimicrobial Resistance & Infection Control
11 papers in training set
Top 0.1%
2.1%
14
JAMA Network Open
130 papers in training set
Top 2%
2.1%
15
Eurosurveillance
83 papers in training set
Top 0.4%
2.1%
16
Infection Control & Hospital Epidemiology
17 papers in training set
Top 0.1%
1.7%
17
European Journal of Clinical Microbiology & Infectious Diseases
15 papers in training set
Top 0.1%
1.7%
18
American Journal of Infection Control
12 papers in training set
Top 0.1%
1.7%
19
Journal of Clinical Microbiology
130 papers in training set
Top 0.8%
1.7%
20
Journal of Infection
78 papers in training set
Top 0.6%
1.7%
21
Age and Ageing
28 papers in training set
Top 0.3%
1.5%
22
eLife
5828 papers in training set
Top 52%
1.5%
23
BMJ
51 papers in training set
Top 0.6%
1.4%
24
Annals of Internal Medicine
28 papers in training set
Top 0.3%
1.3%
25
Emerging Infectious Diseases
105 papers in training set
Top 1%
1.3%
26
Nature
645 papers in training set
Top 8%
1.1%
27
Science Advances
1243 papers in training set
Top 25%
1.1%
28
International Journal of Infectious Diseases
129 papers in training set
Top 2%
1.0%
29
mBio
833 papers in training set
Top 10%
1.0%
30
Clinical Infectious Diseases
235 papers in training set
Top 3%
0.8%