ArticleMedical journal of the Islamic Republic of Iran2024
Which Demographic and Clinical Characteristics Can Better Predict the Length of Hospital Stay among Traumatic Patients? A Retrospective Single-Center, Registry-Based Study.
Article in Medical journal of the Islamic Republic of Iran, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Predicting Hospital Length of Stay in Orthopedic Trauma Patients Using Fracture-Specific Machine Learning Models: A Multicenter Retrospective Prediction-Modeling Study.Health science reports · 2026Article
- Early Factors Related to Healthcare Utilization by Infection Status among Combat Injured.Military medicine · 2026Article
- The Pattern of Fractures in Road Traffic Crashes: Findings From the National Trauma Registry in Iran.Journal of research in health sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lengthy hospitalization may lead to an increased hospital-acquired patient complication, including infections, as well as increased costs for both healthcare systems and patients. A few studies evaluated the impact of various clinical and demographic variables on patients' length of stay (LOS). Hence, in this study, we aimed to investigate the impact of various variables on traumatic patients' LOS. Methods: This is a retrospective single-center, registry-based study of traumatic patients admitted to Taleqani, a major trauma center in Kermanshah, Iran. A Minimal Dataset (MDS) was developed to retrieve traumatic data on demographic and clinical aspects. We used univariable and multiple quantile regression models to evaluate the association between independent variables, including ISS, GCS, and SBP, with LOS. LOS is practically defined as the time interval between hospital admission and discharge. The LOS durations have been presented as median (Q1 to Q3) hours. A p-value of <0.05 was considered statistically significant. Results: A total of 2708 cases were included in this study, with 1989 (73.4%) of them being male. The median LOS was 87.00 (48.00 to 144.00) hours. When adjusted for systolic blood pressure (SBP), Glasgow Coma Scale (GCS), Injury Severity Score (ISS), and cause of injury, the two characteristics of spine/back and multiple trauma were significantly associated with the higher LOS, with 43 (20.5 to 65.48) and 24 (10.39 to 37.60) hours more than extremities ( Conclusion: Determining independent determinants of prolonged LOS may lead to better identifying at-risk patients on admission. Trauma care providers should consider the following risk factors for increased LOS: higher ISS, Lower GCS, and SBP, multiple trauma or spine injury, and trauma resulting from falling or cutting/stabbing. As a result, the impact of extended LOS might be reduced by intervening in the related influencing factors.
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.