| 1. |
- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 2. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 3. |
- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 6. |
- Khatri, C, et al.
(författare)
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Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study
- 2021
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Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 11:11, s. e050830-
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Tidskriftsartikel (refereegranskat)abstract
- Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.SettingProspective, international, multicentre, observational cohort study.ParticipantsPatients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.ResultsThis study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p<0.001), age >80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).ConclusionsPatients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration numberNCT04323644
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| 7. |
- Emerging Risk Factors, Collaboration, et al.
(författare)
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The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases
- 2007
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Ingår i: Eur J Epidemiol. - 0393-2990. ; 22:12, s. 839-69
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Tidskriftsartikel (refereegranskat)abstract
- Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age- and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily, with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.
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| 8. |
- Burgess, S., et al.
(författare)
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Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables
- 2010
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Ingår i: Statistics in medicine. - : Wiley. - 1097-0258 .- 0277-6715. ; 29:12, s. 1298-311
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Tidskriftsartikel (refereegranskat)abstract
- Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.
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