ReviewDer Unfallchirurg2020
[Computer-assisted decision-making for trauma patients].
Review in Der Unfallchirurg, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- [Digital operating room-From dream to workflow].Unfallchirurgie (Heidelberg, Germany) · 2026Review
- Clinical evaluation of a computer-assisted decision support and documentation system for the primary care of polytrauma patients.Frontiers in digital health · 2026Article
- In vitro evaluation of a computer-assisted decision support system for the primary care of polytrauma patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2023Article
- [Competence, creativity and communication: basics for quality improvement in traumatology : Reality and future challenges].Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the management of trauma patients in the resuscitation room many time-pressured and critical decisions must continuously be made in complex situations. Even experienced teams frequently make errors in this context. Computer-assisted decision-making systems can predict critical situations based on patient data continuously acquired online. Based on the calculated predictions these systems can suggest the next steps in managing the patient. This review summarizes the current literature on computer-assisted decision-making in the management of trauma patients.
objectiveA literature review summarizing existing concepts and applications of computer-assisted decision-making support for the management of trauma patients.
methodsNarrative review article based on an analysis of literature in the German and English languages from the last 10 years.
resultsThere exist numerous computer-assisted decision-making systems in the field of trauma care. Several studies could show that computer-assisted decision-making can improve the outcome in the preclinical setting, the resuscitation room and in the intensive care unit. For further validation and implementation of these systems, information technological barriers have to be overcome, existing systems need to be adapted to current data protection regulations and large multicenter studies are necessary.
conclusionComputer-assisted decision-making can help to improve the management of trauma patients; however, before a ubiquitous implementation a number of technological and legislative barriers have to be overcome.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.