Christine Wallisch
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View article: Machine learning-based tool to assess risk of hemodynamically significant PDA in extremely premature infants
Machine learning-based tool to assess risk of hemodynamically significant PDA in extremely premature infants Open
Background A patent ductus arteriosus (PDA) is associated with complications in extremely preterm infants and its assessment requires trained personnel and equipment not always available. A prediction tool might guide the urgency and clini…
View article: Evaluating variable selection methods for multivariable regression models: A simulation study protocol
Evaluating variable selection methods for multivariable regression models: A simulation study protocol Open
Researchers often perform data-driven variable selection when modeling the associations between an outcome and multiple independent variables in regression analysis. Variable selection may improve the interpretability, parsimony and/or pre…
View article: Survival Benefit of First Single-Organ Deceased Donor Kidney Transplantation Compared With Long-term Dialysis Across Ages in Transplant-Eligible Patients With Kidney Failure
Survival Benefit of First Single-Organ Deceased Donor Kidney Transplantation Compared With Long-term Dialysis Across Ages in Transplant-Eligible Patients With Kidney Failure Open
Importance Kidney transplant is considered beneficial in terms of survival compared with continued dialysis for patients with kidney failure. However, randomized clinical trials are infeasible, and available evidence from cohort studies is…
View article: Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study
Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study Open
Ovarian cancer (OC) is the most lethal genital malignancy in women. We aimed to develop and validate new proteomic-based models for non-invasive diagnosis of OC. We also compared them to the modified Risk of Ovarian Malignancy Algorithm (R…
View article: Review of guidance papers on regression modeling in statistical series of medical journals
Review of guidance papers on regression modeling in statistical series of medical journals Open
Although regression models play a central role in the analysis of medical research projects, there still exist many misconceptions on various aspects of modeling leading to faulty analyses. Indeed, the rapidly developing statistical method…
View article: The roles of predictors in cardiovascular risk models - a question of modeling culture?
The roles of predictors in cardiovascular risk models - a question of modeling culture? Open
Background While machine learning (ML) algorithms may predict cardiovascular outcomes more accurately than statistical models, their result is usually not representable by a transparent formula. Hence, it is often unclear how specific valu…
View article: Development and internal validation of an algorithm to predict intraoperative risk of inadvertent hypothermia based on preoperative data
Development and internal validation of an algorithm to predict intraoperative risk of inadvertent hypothermia based on preoperative data Open
Intraoperative hypothermia increases perioperative morbidity and identifying patients at risk preoperatively is challenging. The aim of this study was to develop and internally validate prediction models for intraoperative hypothermia occu…
View article: Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol Open
In the last decades, statistical methodology has developed rapidly, in particular in the field of regression modeling. Multivariable regression models are applied in almost all medical research projects. Therefore, the potential impact of …
View article: Selection of variables for multivariable models: Opportunities and limitations in quantifying model stability by resampling
Selection of variables for multivariable models: Opportunities and limitations in quantifying model stability by resampling Open
Statistical models are often fitted to obtain a concise description of the association of an outcome variable with some covariates. Even if background knowledge is available to guide preselection of covariates, stepwise variable selection …
View article: Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal Open
Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 i…
View article: Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection
Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection Open
Objective To review and critically appraise published and preprint reports of models that aim to predict either (i) presence of existing COVID-19 infection, (ii) future complications in individuals already diagnosed with COVID-19, or (iii)…
View article: Predicting donor, recipient and graft survival in living donor kidney transplantation to inform pretransplant counselling: the donor and recipient linked iPREDICTLIVING tool – a retrospective study
Predicting donor, recipient and graft survival in living donor kidney transplantation to inform pretransplant counselling: the donor and recipient linked iPREDICTLIVING tool – a retrospective study Open
Although separate prediction models for donors and recipients were previously published, we identified a need to predict outcomes of donor/recipient simultaneously, as they are clearly not independent of each other. We used characteristics…
View article: Variable selection – A review and recommendations for the practicing statistician
Variable selection – A review and recommendations for the practicing statistician Open
Statistical models support medical research by facilitating individualized outcome prognostication conditional on independent variables or by estimating effects of risk factors adjusted for covariates. Theory of statistical models is well‐…