Biomedical subjects

Natalie Le Sage

Publications and source records attributed to Natalie Le Sage.

5 recordsLinked to original sources

PubMed2006

Unification of the revised trauma score.

BACKGROUND: The Revised Trauma Score (RTS) calculated with Major Outcome Trauma Study weights (MTOS-RTS) is currently the standard physiologic severity score in trauma research and quality control. It is often confused with the Triage-RTS (T-RTS), a version that is easier to calculate but only intended for clinical triage. OBJECTIVES: To compare the accuracy of the MTOS-RTS to the RTS calculated with weights derived from the study population (POP-RTS) and the T-RTS, for predicting mortality in a trauma population. METHODS: The study population consists of 22,388 patients, drawn from the trauma registries of three Level I trauma centers. The predictive accuracy of the MTOS-RTS, POP-RTS, and the T-RTS were compared using measures of discrimination and model fit from logistic regression models. RESULTS: The MTOS-RTS, the POP-RTS, and the T-RTS had the same discrimination (Area under the Receiver Operating Curve [AUC] = 0.841). The POP-RTS and the T-RTS had a slightly better model fit than the MTOS-RTS (AIC = 8010, 8010, and 8067, respectively). The T-RTS had equal discrimination and equal or better model fit than the MTOS-RTS in the whole sample, in each of the three trauma centers and in the population of patients with severe head trauma. The T-RTS was also equivalent to the POP-RTS in all of these population sub-groups. CONCLUSIONS: The T-RTS could replace the MTOS-RTS as the standard physiologic severity score for trauma outcome prediction. The advantages of using the T-RTS over the MTOS-RTS are ease of calculation, the need for only one measure for triage and mortality prediction purposes and universal adaptation to a broad range of trauma populations.

Aged↗

PubMed2006

Two worst injuries in different body regions are associated with higher mortality than two worst injuries in the same body region.

BACKGROUND: The Injury Severity Score (ISS) accounts for only one injury in each body region. The New Injury Severity Score (NISS) considers all injuries in a body region. Despite a big difference between the two scores in patients with multiple injuries, the NISS does not offer significant improvement in mortality prediction. This paper hypothesizes that two injuries in different body regions are associated with higher mortality than two injuries in the same body region, independently of injury severity. METHODS: The population consisted of 15,200 patients with two or more injuries from the Quebec Trauma Registry, Canada, abstracted between 1998 and 2004. The two worst injuries were considered. Logistic regression analysis was used to assess the mortality odds ratio of having two worst injuries in different body regions (DR) compared with two worst injuries in the same body region (SR), while adjusting for the severity and the body region of the two worst injuries and age. RESULTS: A total of 5,869 patients (49%) had their worst injuries in DR. DR patients had 75% higher risk of mortality than SR patients (odds ratio = 1.75, 95% confidence interval = 1.42-2.15). CONCLUSION: After accounting for differing injury severity, patients with their two worst injuries in different body regions have higher mortality than those with their two worst injuries in the same region. Results suggest that the observed effect is not due to a foible in the Abbreviated Injury Scale system but rather to physiologic, clinical, or organizational elements. The results of this study should be considered in the development of future injury severity instruments and may have implications for the care of patients with multiple injuries.

Aged↗

PubMed2006

Consensus or data-derived anatomical severity scoring?

We aimed to compare the predictive accuracy of consensus-derived and data-derived injury severity scores when considered alone and in combination with age and physiological status. Analyses were based on 25,111 patients. The predictive validity of each severity score was evaluated in logistic regression models predicting in-hospital mortality using measures of discrimination and calibration. Data-derived scores had consistently better predictive accuracy than consensus-derived scores in univariate models (p<0.0001) but very little difference between scores was observed in models including information on age and physiological status. Data-derived scores provide more accurate mortality prediction than consensus-derived scores when only anatomic injury severity is considered but offer little advantage if age and physiological status are taken into account.

Adolescent↗

PubMed2005

A second injury in the same body region is associated with lower mortality than a second injury in a different body region.

HYPOTHESIS: A second injury in the same body region is associated with lower mortality than a second injury in a different body region, independently of injury severity and body region. METHODS: The population consisted of 15,200 patients with two or more injuries from level I trauma centers in Quebec. The mortality odds ratio of having a same-region second injury (SR) as opposed to a different-region second injury (DR) was assessed. RESULTS: Patients with a SR had 43% lower odds of mortality when compared to patients with a DR. CONCLUSION: A second injury in the same body region is associated with lower mortality than a second injury in a different body region.

Accidents, Traffic↗

PubMed2004

Clinical factors predicting fractures associated with an anterior shoulder dislocation.

OBJECTIVES: To identify risk factors for fractures associated with an anterior shoulder dislocation treated in an emergency department (ED). METHODS: A retrospective case-control study over five years of patients with an anterior shoulder dislocation was accomplished in a university-affiliated ED. Chart review identified possible predictors of fractures. Comparing the profile of patients having a clinically important fracture associated with their shoulder dislocation (cases) with those sustaining a noncomplicated dislocation (controls) provided the outcome measure. RESULTS: A total of 334 patients were included in the study. Eighty-five (25.5%) had a clinically important fracture-dislocation, and the remaining 249 (74.5%) sustained a noncomplicated shoulder dislocation. Chi-square, logistic regression, and recursive partitioning analysis showed three significant factors for the presence of fracture-dislocation: 1) age 40 years or older, 2) a first episode of dislocation, and 3) mechanism of injury (i.e., a fall greater than one flight of stairs, a fight/assault episode, or a motor vehicle crash). A multiple logistic regression model estimated the significant adjusted odds ratios (and their 95% confidence intervals [95% CIs]) for each of the three factors: 5.18 (95% CI = 2.74 to 9.78), 4.23 (95% CI = 1.82 to 9.87), and 4.06 (95% CI = 1.95 to 8.48), respectively. A predictive model using any one of the three factors reached a sensitivity of 97.7% (95% CI = 91.8% to 99.4%), a specificity of 22.9% (95% CI = 18.1% to 28.5%), and a negative predictive value of 96.6% (95% CI = 88.3% to 99.6%). CONCLUSIONS: Three risk factors predict clinically important fractures that are associated with shoulder dislocation: age, first episode, and mechanism of dislocation. A prospective validation may lead to standardized use of prereduction radiographs of the shoulder in the ED.

Accidental Falls↗