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1.
Eur J Epidemiol ; 38(6): 605-615, 2023 Jun.
Article in English | MEDLINE | ID: mdl-37099244

ABSTRACT

Data discovery, the ability to find datasets relevant to an analysis, increases scientific opportunity, improves rigour and accelerates activity. Rapid growth in the depth, breadth, quantity and availability of data provides unprecedented opportunities and challenges for data discovery. A potential tool for increasing the efficiency of data discovery, particularly across multiple datasets is data harmonisation.A set of 124 variables, identified as being of broad interest to neurodegeneration, were harmonised using the C-Surv data model. Harmonisation strategies used were simple calibration, algorithmic transformation and standardisation to the Z-distribution. Widely used data conventions, optimised for inclusiveness rather than aetiological precision, were used as harmonisation rules. The harmonisation scheme was applied to data from four diverse population cohorts.Of the 120 variables that were found in the datasets, correspondence between the harmonised data schema and cohort-specific data models was complete or close for 111 (93%). For the remainder, harmonisation was possible with a marginal a loss of granularity.Although harmonisation is not an exact science, sufficient comparability across datasets was achieved to enable data discovery with relatively little loss of informativeness. This provides a basis for further work extending harmonisation to a larger variable list, applying the harmonisation to further datasets, and incentivising the development of data discovery tools.


Subject(s)
Datasets as Topic , Knowledge Discovery , Humans , Reference Standards
2.
South Med J ; 103(6): 532-40, 2010 Jun.
Article in English | MEDLINE | ID: mdl-20710136

ABSTRACT

Obesity is a worldwide epidemic and public health crisis associated with severe comorbidity leading to end organ dysfunction and poorer transplant outcome. Large population studies show decreased patient and graft survival in obese kidney transplant patients. Despite the poorer outcomes, kidney transplant is considered because of the survival benefit as compared to the wait-listed dialysis patients. In liver transplantation, the benefit of transplant as compared to remaining on the list is obvious because there is no viable liver dialysis at this time.Obesity in potential organ donors impacts both medical and surgical issues. Obesity-related kidney disease affects both the remaining and transplanted kidney. Pancreas donor organs are associated with decreased early graft survival. Liver donor organs with significant steatosis lead to an increased risk for delayed function or nonfunction of the organ.Immunosuppressive drugs with variable lipophilicity and altered volume of distribution can greatly affect the therapeutic usefulness of these drugs.Transplant candidates benefit from a multidisciplinary team approach to their care. As the epidemic progresses and less invasive treatments for metabolic surgery evolve, we are likely to see more patients lose weight before transplant as we continue to strive for improved outcomes.


Subject(s)
Obesity/complications , Organ Transplantation , Postoperative Complications/etiology , Bariatric Surgery , Body Mass Index , Comorbidity , Cross-Sectional Studies , Delayed Graft Function/epidemiology , Delayed Graft Function/etiology , Graft Rejection/epidemiology , Graft Rejection/etiology , Humans , Immunosuppressive Agents/adverse effects , Immunosuppressive Agents/pharmacokinetics , Immunosuppressive Agents/therapeutic use , Kidney Transplantation , Obesity/epidemiology , Postoperative Complications/epidemiology , Preoperative Care , Risk Factors , Tissue Donors , United States , Weight Loss
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