scholarly journals Propensity score analysis exploring the impact of smoking and drinking on the prognosis of patients with oral cancer

Head & Neck ◽  
2020 ◽  
Vol 42 (8) ◽  
pp. 1837-1847 ◽  
Author(s):  
Xiaodan Bao ◽  
Fengqiong Liu ◽  
Qing Chen ◽  
Lin Chen ◽  
Jing Lin ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Propensity Score ◽  
Propensity Score Analysis ◽  
Score Analysis ◽  
The Impact

scholarly journals Burden of motorcyclists without helmets in a state without a universal helmet law: a propensity score analysis

2020 ◽  
Vol 5 (1) ◽  
pp. e000583
Author(s):  
Michael D Jones ◽  
Joel G Eastes ◽  
Damjan Veljanoski ◽  
Kristina M Chapple ◽  
James N Bogert ◽  
...  
Keyword(s):  
Propensity Score ◽  
Propensity Score Analysis ◽  
Alcohol Intoxication ◽  
Civil Liberties ◽  
Hospital Charges ◽  
Trauma Patients ◽  
Level Of Evidence ◽  
Helmet Use ◽  
Score Analysis ◽  
The Impact

BackgroundAlthough helmets are associated with reduction in mortality from motorcycle collisions, many states have failed to adopt universal helmet laws for motorcyclists, in part on the grounds that prior research is limited by study design (historical controls) and confounding variables. The goal of this study was to evaluate the association of helmet use in motorcycle collisions with hospital charges and mortality in trauma patients with propensity score analysis in a state without a universal helmet law.MethodsMotorcycle collision data from the Arizona State Trauma Registry from 2014 to 2017 were propensity score matched by regressing helmet use on patient age, sex, race/ethnicity, alcohol intoxication, illicit drug use, and comorbidities. Linear and logistic regression models were used to evaluate the impact of helmet use.ResultsOur sample consisted of 6849 cases, of which 3699 (54.0%) were helmeted and 3150 (46.0%) without helmets. The cohort was 88.1% male with an average age of 40.9±16.0 years. Helmeted patients were less likely to be admitted to the intensive care unit (20.3% vs. 23.7%, OR 0.82 (0.72–0.93)) and ventilated (7.8% vs. 12.0%, OR 0.62 (0.52–0.75)). Propensity-matched analyses consisted of 2541 pairs and demonstrated helmet use to be associated with an 8% decrease in hospital charges (B −0.075 (0.034)) and a 56% decrease in mortality (OR 0.44 (0.31–0.58)).DiscussionIn a state without mandated helmet use for all motorcyclists, the burden of the unhelmeted rider is significant with respect to lives lost and healthcare charges incurred. Although the helmet law debate with respect to civil liberties is complex and unsettled, it appears clear that helmet use is strongly associated with both survival and less economic encumbrance on the state.Level of evidenceLevel III, prognostic and epidemiological.

scholarly journals Impact of polyclonal antithymocyte globulins on kidney transplant outcomes in real-life: a propensity score analysis

2020 ◽  
Author(s):  
Jamal Bamoulid ◽  
Thomas Crepin ◽  
Emilie Gaiffe ◽  
Bruno Moulin ◽  
Luc Frimat ◽  
...  
Keyword(s):  
Kidney Transplantation ◽  
Propensity Score ◽  
Acute Rejection ◽  
Propensity Score Analysis ◽  
Graft Loss ◽  
Real Life ◽  
Area Under The Curve ◽  
Life Conditions ◽  
Score Analysis ◽  
The Impact

Abstract Background: Randomized studies reported a marginal superiority of polyclonal antithymocyte globulins (ATG, Thymoglobulin®, Sanofi, Gentilly, France, or Fresenius®, Bad Homburg, Germany) to prevent acute rejection compared to monoclonal anti-CD25 antibodies (IL2Ra). Nevertheless, the representativeness and the generalizability of these studies are questionable. Methods: We studied the impact of ATG use in real-life conditions in a multicenter study. Propensity score analysis was performed to address potential confounding by indication. Results: 817 patients were included. Logistic regression revealed that age, male gender, a pre-transplant history of cancer, presence of anti-HLA antibodies, previous kidney transplantation, and transplant center were associated with ATG use. The area under the curve of the propensity score was 0.84 + 0.02. ATG use was not associated with a lower rate of acute rejection (18.2% in ATG-treated patients vs 15.8% in non-ATG-treated patients, p =0.356). Adjustment for propensity score slightly modified the relationship between ATG and acute rejection towards a more neutral effect ( p =0.913). Score match analysis recapitulated the previous result. ATG use was associated with the occurrence of opportunistic infection ( p =0.034). There was no difference in graft loss or death between the two groups. Conclusions: In real-life conditions, ATG does not substantially reduce the risk of acute rejection after kidney transplantation. A better discrimination of patients who may benefit from ATG is required.

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