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Record W4308626991 · doi:10.5281/zenodo.7306724

Assessment of factors affecting the outcome of elderly blunt trauma in Emergency Department

2022· article· en· W4308626991 on OpenAlexaboutno aff
Botros Wagih Latif, Habashy Abd El Baset Al Hammady, Alaa Hussien Abd El Razek, Wael Nabil Abd El Salam

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmergency departmentBluntOutcome (game theory)Medical emergencyMedicineBlunt traumaEmergency medicineSurgeryNursing

Abstract

fetched live from OpenAlex

ABSTRACT The purpose of this study is to evaluate factors affecting the outcome of elderly blunt trauma in emergency department. The study was conducted on 100 elderly patients age above 60 years with blunt trauma admitted to Emergency Department of Alexandria Main University Hospital. Primary survey, secondary survey and radiological investigations were done for these patients. Evaluation of patient injury severity by injury severity score (ISS) .Patient outcome as regard death, discharge, transfer and complications due to trauma or treatment were reported. Falling down was the most common mechanism of injury in our study occurred in 49% of cases followed by RTA in 27 % of cases but RTA was the most common cause of injury leading to death. 93% of cases had systolic blood pressure ≥ 90 mmHg who considered hemodynamically stable on admission and 7% of cases had systolic blood pressure <90 mmHg who considered hemodynamically unstable on admission. Systolic blood pressure on admission was directly proportional with the outcome (p<0.001). GCS of our patients in this study ranged between 4 and 15 with a mean± SD of 13.98 ± 2.72 and median of 15. There were 88 % of cases with GCS more than 12 .4% of cases with GCS between 9 and 12 while 8% of cases had a GCS less than or equal to 8, the mortality is inversely proportion to GCS (p<0.001) ISS in our study ranged between 1.0 - 35.0 with mean ± SD of 8.54 ± 9.70 and median of 5, ISS was directly proportional with the outcome and higher ISS was associated with higher mortality. As regard past illness 22 patients had no past illness while the most common past illness was hypertension which presented in 31 patients and the least common past illness was cerebrovascular stroke and psychosis each present in 5 % of cases .Regarding lines of treatment, 55 patients had conservative treatment and 8 patients were unfit for surgery while surgical interventions were done for 37 patients. According to complications in our study, 76 patients (76%) had no complications while 24 patients (24%) had complications where the most common complication was pneumonia which presented in 7 patients (7%) followed by DKA and DIC which presented in 5 patients (5%) in each of them and the most common complication which associated with the highest ratio for mortality after geriatric trauma was DIC. Key words : outcome, elderly, blunt trauma REFERENCES Mitchell RJ, Chong S. (2010 )Comparison of injury-related hospitalized morbidity and mortality in urban and rural areas in Australia. Rural Remote Health ;10(1):1326-1340 Richmond TS, Kauder D, Strumpf N, Meredith T (2002) Characteristics and outcomes of serious traumatic injury in older adults. J Am GeriatrSoc ; 50: 215–22. Pudelek B (2002) Geriatric trauma: special needs for a special population. AACN Clin Issues;13:61–72. McMahon DJ, Shapiro MB, Kauder DR (2000). The injured elderly in the trauma intensive care unit.SurgClin North Am ;80:1005–19. Taylor MD, Tracy JK, Meyer W, et al. (2002) Trauma in the elderly: intensive care unit resource use and outcome. J Trauma;53:407–14 Broos P(1993) Multiple trauma in elderly patients: factors influencing outcome. Injury ; 24(6):365–8. Rob Gowing, Minto K. Jain (2007). Injury patterns and outcomes associated with elderly trauma victims in Kingston, Ontario Can J Surg, December ; 50(6):437–44 Yılmaz S, karcıoglu O, Sener S (2006). The impact of associated diseases on the etiology, course and mortality in geriatric trauma patients. Eur J Emerg Med ; 13: 295-298 Donmez L, Gokkoca Z. (2003)Accident profile of olderpeople in Antalya City Center, Turkey. ArchGerontol Geriatr ; 37: 99-108. José Gustavo , Silvia C , Jaqueline A. Giannini, Camila C. Padovese, et al (2010 ). comparative analysis of the characteristics of traumassuffered by elderly and younger patients. Rev Assoc Med Bras ; 56(5): 541-6. Rogério Silva Lima, Maria Luíza Pesse Campos (2011). Profile of the elderly trauma victims assisted at an Emergency Unit. Rev Esc Enferm USP ; 45(3):657-62. Cheng-Shyuan Rau, Tsan-Shiun Lin, Shao-Chun Wu, Johnson Chia-Shen Yang, Shiun-Yuan Hsu et al. (2014 ) Geriatric hospitalizations in fall-related injuries. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine , 22:63. Knudson MM, Lieberman J, Morris J. (1994) Mortality factors in geriatric blunt trauma patients.Arch Surg ;129(4):448–53 Horst HM, Obeid FN, Sorensen VJ (1986 ). Factors influencing survival of elderly trauma patients. Crit Care Med ;14(8):681–4. Rozzelle CJ, Wofford JL, Branch CL.( 1995 )Predictors of hospital mortality in older patients with subdural hematoma. J Am Geriatr Soc ;43:240–4 Reuter F. (1989) Traumatic intracranial hemorrhages in elderly people. Advances in Neurosurgery ;17:43–8.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.064
GPT teacher head0.327
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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