Evidence map›Paper›PMID 42169690›Full record

ArticleOpen forum infectious diseases2026

Two-Year Outcomes of Postoperative Spine Infection: Implant Retention and Predictors of Treatment Failure.

P J Davis, I Hassan, T P W Jones, R Kaiser, E Stirling, M Scarborough, M I Andersson

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

P J DavisDepartment of Microbiology, Oxford University Hospitals NHS Trust, Oxford, UK.ORCID https://orcid.org/0000-0002-1027-2566
I HassanDepartment of Microbiology, Oxford University Hospitals NHS Trust, Oxford, UK.
T P W JonesDepartment of Microbiology, Oxford University Hospitals NHS Trust, Oxford, UK.ORCID https://orcid.org/0000-0001-6147-6748
R KaiserDepartment of Spinal Surgery, Oxford University Hospitals NHS Trust, Oxford, UK.ORCID https://orcid.org/0000-0002-5985-9595
E StirlingDepartment of Spinal Surgery, Oxford University Hospitals NHS Trust, Oxford, UK.
M ScarboroughDepartment of Microbiology, Oxford University Hospitals NHS Trust, Oxford, UK.
M I AnderssonDepartment of Microbiology, Oxford University Hospitals NHS Trust, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postoperative spine infection (PSI) after surgery occurs in approximately 1%-2% of cases and is associated with significant morbidity. High-quality evidence to guide optimal prevention and management of PSI is limited. Methods: We retrospectively identified all adult patients over a 3-year period (2020-2023) who required reoperation for deep PSI. Clinical, microbiological therapy, and 24-month outcome data were collected. Treatment failure was defined as unplanned return to the operating room secondary to persistent infection or infection-related implant failure requiring removal. Descriptive statistics and univariate logistic regression were used to identify factors associated with failure. Results: Sixty-three deep PSI cases were identified (range 18-91 years, median 59 years, 56% female). Onset of infection ranged from 4 days to 30 weeks postoperatively (median 20 days). Conclusions: Most PSIs were effectively managed in this cohort with surgical debridement and targeted antibiotics, allowing implant retention in most patients with instrumentation.

Indexed as

antibioticsimplant-associated infectionspinal surgerysurgical site infection

Identifiers

PMID42169690
PMCPMC13187830

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.