Improving the Care of Severe, Open Fractures and Postoperative Infections of the Lower Extremities: Protocol for an Interdisciplinary Treatment Approach
Bibliographic record
Abstract
BACKGROUND: Patients with open fractures often experience complications during their injury. The treatments incur high costs. Interdisciplinary cooperation between different medical disciplines may improve treatment outcomes. Such cooperation has not yet been envisaged in the German health care system. OBJECTIVE: The aim of the study is to improve the treatment of fractures with open soft tissue damage or postoperative complications in terms of duration and sustainability in a region in northwest Germany. Largely standardized diagnostics and therapy are intended to optimize processes in hospitals. In addition, a reduction in the duration of treatment and treatment costs is to be achieved. METHODS: Using a digital platform, physicians from 31 hospitals present patient cases to an interdisciplinary group of experts from the fields of plastic surgery, infectiology, hygiene, and others. The group of experts from the environment of the University Hospital Münster promptly makes a joint treatment recommendation for the individual case. The plan is to examine 3300 patients with open fractures or surgical complications. As consortium partners, there are also 3 statutory health insurance companies. The extent to which the therapy recommendations are effective and contribute to cost reduction in the health care system will be empirically investigated in a stepped-wedge cluster-randomized design. In addition, medical and nonmedical professional groups involved in the project will be asked about their work in the project (in total, 248 clinic employees). The primary outcome is the complication rate of open fractures or the occurrence of postoperative complications. As secondary outcomes, the number of antibiotics administered, limb function, and quality of life will be assessed. The health economic evaluation refers to the costs of health services and absenteeism. For the work-related evaluation, workload, work engagement, work-related resources, readiness for technology, and ergonomic aspects of the new telemedical technology will be collected. In addition, clinic employees will give their assessments of the success of the project in a structured telephone interview based on scaled and open-ended questions. RESULTS: The project started in June 2022; data collection started in April 2023. As of mid-June 2024, data from 425 patients had been included. In total, 146 members of staff had taken part in the questionnaire survey and 15 had taken part in the interviews. CONCLUSIONS: Standardized treatment pathways in the standard care of patients with open fractures and postoperative infections will be established to reduce complications, improve chances of recovery, and reduce costs. Unnecessary and redundant treatment steps will be avoided through standardized diagnostics and therapy. The interdisciplinary treatment perspective allows for a more individualized therapy. In the medium term, outpatient or inpatient treatment centers specialized in the patient group could be set up where the new diagnostic and therapeutic pathways could be competently applied. TRIAL REGISTRATION: German Clinical Trials Register DRKS00031308; https://drks.de/search/de/trial/DRKS00031308. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57820.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".