Baseline and pre-operative 1-year mortality risk factors in a cohort of 509 hip fracture patients consecutively admitted to a co-managed orthogeriatric unit (FONDA Cohort)

Injury ◽  
2018 ◽  
Vol 49 (3) ◽  
pp. 656-661 ◽  
Author(s):  
Rocío Menéndez-Colino ◽  
Teresa Alarcon ◽  
Pilar Gotor ◽  
Rocío Queipo ◽  
Raquel Ramírez-Martín ◽  
...  
2011 ◽  
Vol 41 (17) ◽  
pp. 2
Author(s):  
MARY ANN MOON
Keyword(s):  

2019 ◽  
Vol 38 (6) ◽  
pp. 589-594 ◽  
Author(s):  
Angela Gentile ◽  
María Florencia Lucion ◽  
María del Valle Juarez ◽  
María Soledad Areso ◽  
Julia Bakir ◽  
...  

Renal Failure ◽  
2007 ◽  
Vol 29 (7) ◽  
pp. 823-828 ◽  
Author(s):  
Beril Akman ◽  
Ayse Bilgic ◽  
Gulsah Sasak ◽  
Siren Sezer ◽  
Atilla Sezgin ◽  
...  

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A273-A273
Author(s):  
Xi Zheng ◽  
Ma Cherrysse Ulsa ◽  
Peng Li ◽  
Lei Gao ◽  
Kun Hu

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (>9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jacques P. Brown ◽  
Jonathan D. Adachi ◽  
Emil Schemitsch ◽  
Jean-Eric Tarride ◽  
Vivien Brown ◽  
...  

Abstract Background Recent studies are lacking reports on mortality after non-hip fractures in adults aged > 65. Methods This retrospective, matched-cohort study used de-identified health services data from the publicly funded healthcare system in Ontario, Canada, contained in the ICES Data Repository. Patients aged 66 years and older with an index fragility fracture occurring at any osteoporotic site between 2011 and 2015 were identified from acute hospital admissions, emergency and ambulatory care using International Classification of Diseases (ICD)-10 codes and data were analyzed until 2017. Thus, follow-up ranged from 2 years to 6 years. Patients were excluded if they presented with an index fracture occurring at a non-osteoporotic fracture site, their index fracture was associated with a trauma code, or they experienced a previous fracture within 5 years prior to their index fracture. This fracture cohort was matched 1:1 to controls within a non-fracture cohort by date, sex, age, geography and comorbidities. All-cause mortality risk was assessed. Results The survival probability for up to 6 years post-fracture was significantly reduced for the fracture cohort vs matched non-fracture controls (p < 0.0001; n = 101,773 per cohort), with the sharpest decline occurring within the first-year post-fracture. Crude relative risk of mortality (95% confidence interval) within 1-year post-fracture was 2.47 (2.38–2.56) in women and 3.22 (3.06–3.40) in men. In the fracture vs non-fracture cohort, the absolute mortality risk within one year after a fragility fracture occurring at any site was 12.5% vs 5.1% in women and 19.5% vs 6.0% in men. The absolute mortality risk within one year after a fragility fracture occurring at a non-hip vs hip site was 9.4% vs 21.5% in women and 14.4% vs 32.3% in men. Conclusions In this real-world cohort aged > 65 years, a fragility fracture occurring at any site was associated with reduced survival for up to 6 years post-fracture. The greatest reduction in survival occurred within the first-year post-fracture, where mortality risk more than doubled and deaths were observed in 1 in 11 women and 1 in 7 men following a non-hip fracture and in 1 in 5 women and 1 in 3 men following a hip fracture.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Fu Cheng Bian ◽  
Xiao Kang Cheng ◽  
Yong Sheng An

Abstract Background This study aimed to explore the preoperative risk factors related to blood transfusion after hip fracture operations and to establish a nomogram prediction model. The application of this model will likely reduce unnecessary transfusions and avoid wasting blood products. Methods This was a retrospective analysis of all patients undergoing hip fracture surgery from January 2013 to January 2020. Univariate and multivariate logistic regression analyses were used to evaluate the association between preoperative risk factors and blood transfusion after hip fracture operations. Finally, the risk factors obtained from the multivariate regression analysis were used to establish the nomogram model. The validation of the nomogram was assessed by the concordance index (C-index), the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curves. Results A total of 820 patients were included in the present study for evaluation. Multivariate logistic regression analysis demonstrated that low preoperative hemoglobin (Hb), general anesthesia (GA), non-use of tranexamic acid (TXA), and older age were independent risk factors for blood transfusion after hip fracture operation. The C-index of this model was 0.86 (95% CI, 0.83–0.89). Internal validation proved the nomogram model’s adequacy and accuracy, and the results showed that the predicted value agreed well with the actual values. Conclusions A nomogram model was developed based on independent risk factors for blood transfusion after hip fracture surgery. Preoperative intervention can effectively reduce the incidence of blood transfusion after hip fracture operations.


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