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Yildiray Topcu,1 Robbert JJ Gobbens,2– 5 Tjeerd van der Ploeg,2 Fatih Tufan6 1Prof. Dr. Cemil Taşcıoğlu Şehir Hastanesi, Istanbul, Turkiye; 2Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, Amsterdam, the Netherlands; 3Zonnehuisgroep Amstelland, Amstelveen, the Netherlands; 4Department Family Medicine and Population Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; 5Tranzo, Tilburg University, Tilburg, the Netherlands; 6Istanbul Esenler Avicenna Hospital, Department of Internal Medicine and Geriatrics, Istanbul, TurkiyeCorrespondence: Fatih Tufan, Assoc. Prof. of Geriatrics, Istanbul Esenler Avicenna Hospital, Department of Internal Medicine and Geriatrics, Istanbul, Turkiye, Tel +90 5331683458, Email fatihtufan@gmail.comPurpose: To our knowledge, there have been no comparative studies evaluating the associations of frailty defined using the Tilburg Frailty Indicator (TFI), frailty phenotype by Fried et al, and FRAIL scale with all-cause mortality in Turkiye. In this study, we aimed to evaluate the ability of these instruments in predicting all-cause mortality in outpatients admitted to the outpatient geriatrics clinic of a university hospital.Patients and Methods: This historical prospective study was performed in the geriatrics outpatient clinic of a university hospital in Istanbul, Turkiye. Consecutive older adults (aged ≥ 70 years) who provided written informed consent were enrolled in the study. The survival status of participants was checked electronically using the official death registry system. Univariate analyses and multivariate Cox regression analyses were performed to determine the independent predictors of mortality.Results: A total of 198 participants with a median age of 77 years were enrolled. During the median follow-up period of 2236 days, 54 (27.3%) patients died. In univariate analyses, male sex, history of falls in the previous year, dependency in instrumental activities of daily living, malnutrition, and frailty with respect to the phenotype by Fried et al, FRAIL scale, and TFI were associated with mortality. In multivariate Cox regression analyses, frailty according to each of the three frailty instruments, male sex, older age, history of falls, and malnutrition or malnutrition risk were independently associated with mortality. The Fried scale was the best frailty tool among the three frailty instruments used to predict all-cause mortality.Conclusion: The findings of this study suggest that frailty, determined using each of the three instruments used in the present study, is independently associated with all-cause mortality in patients admitted to the outpatient geriatrics clinic of a university hospital in Turkiye. The Fried scale appears to be the best for predicting all-cause mortality.Keywords: Turkiye, frailty, mortality, malnutrition, falls, dependency

Tjeerd van der Ploeg,1 René Schalk,2– 4 Robbert J J Gobbens1,2,5,6 1Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, Amsterdam, the Netherlands; 2Tranzo, Tilburg University, Tilburg, the Netherlands; 3Human Resource Studies, Tilburg University, Tilburg, the Netherlands; 4Economic and Management Science, North West University, Potchefstroom, South Africa; 5Zonnehuisgroep Amstelland, Amstelveen, the Netherlands; 6Department Family Medicine and Population Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, BelgiumCorrespondence: Tjeerd van der Ploeg, Inholland University of Applied Sciences, Faculty of Health, Sports and Social Work, De Boelelaan 1109, Amsterdam, 1081 HV, the Netherlands, Tel +31 6 53519264, Email tvdploeg@quicknet.nlBackground: Advanced statistical modeling techniques may help predict health outcomes. However, it is not the case that these modeling techniques always outperform traditional techniques such as regression techniques. In this study, external validation was carried out for five modeling strategies for the prediction of the disability of community-dwelling older people in the Netherlands.Methods: We analyzed data from five studies consisting of community-dwelling older people in the Netherlands. For the prediction of the total disability score as measured with the Groningen Activity Restriction Scale (GARS), we used fourteen predictors as measured with the Tilburg Frailty Indicator (TFI). Both the TFI and the GARS are self-report questionnaires. For the modeling, five statistical modeling techniques were evaluated: general linear model (GLM), support vector machine (SVM), neural net (NN), recursive partitioning (RP), and random forest (RF). Each model was developed on one of the five data sets and then applied to each of the four remaining data sets. We assessed the performance of the models with calibration characteristics, the correlation coefficient, and the root of the mean squared error.Results: The models GLM, SVM, RP, and RF showed satisfactory performance characteristics when validated on the validation data sets. All models showed poor performance characteristics for the deviating data set both for development and validation due to the deviating baseline characteristics compared to those of the other data sets.Conclusion: The performance of four models (GLM, SVM, RP, RF) on the development data sets was satisfactory. This was also the case for the validation data sets, except when these models were developed on the deviating data set. The NN models showed a much worse performance on the validation data sets than on the development data sets.Keywords: prediction models, modeling techniques, external validation, performance, calibration, correlation coefficient, root of the mean squared error

Robbert JJ Gobbens,1– 3 Tjeerd van der Ploeg4 1Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, Amsterdam, the Netherlands; 2Zonnehuisgroep Amstelland, Amstelveen, the Netherlands; 3Department of Primary and Interdisciplinary Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; 4Faculty of Engineering, Design and Computer Technology, Inholland University of Applied Sciences, Alkmaar, the NetherlandsCorrespondence: Robbert JJ GobbensFaculty of Health, Sports and Social Work, Inholland University of Applied Sciences, De Boelelaan 1109, Amsterdam 1081 HV, the NetherlandsTel +31 6 21115578Email robbert.gobbens@inholland.nlObjective: To predict mortality by disability in a sample of 479 Dutch community-dwelling people aged 75 years or older.Methods: A longitudinal study was carried out using a follow-up of seven years. The Groningen Activity Restriction Scale (GARS), a self-reported questionnaire with good psychometric properties, was used for data collection about total disability, disability in activities in daily living (ADL) and disability in instrumental activities in daily living (IADL). The mortality dates were provided by the municipality of Roosendaal (a city in the Netherlands). For analyses of survival, we used Kaplan–Meier analyses and Cox regression analyses to calculate hazard ratios (HR) with 95% confidence intervals (CI).Results: All three disability variables (total, ADL and IADL) predicted mortality, unadjusted and adjusted for age and gender. The unadjusted HRs for total, ADL and IADL disability were 1.054 (95%-CI: [1.039;1.069]), 1.091 (95%-CI: [1.062;1.121]) and 1.106 (95%-CI: [1.077;1.135]) with p-values < 0.001, respectively. The AUCs were < 0.7, ranging from 0.630 (ADL) to 0.668 (IADL). Multivariate analyses including all 18 disability items revealed that only “Do the shopping” predicted mortality. In addition, multivariate analyses focusing on 11 ADL items and 7 IADL items separately showed that only the ADL item “Get around in the house” and the IADL item “Do the shopping” significantly predicted mortality.Conclusion: Disability predicted mortality in a seven years follow-up among Dutch community-dwelling older people. It is important that healthcare professionals are aware of disability at early stages, so they can intervene swiftly, efficiently and effectively, to maintain or enhance the quality of life of older people.Keywords: disability, mortality, community-dwelling older people, activities of daily living

Christina A Mosk,1 Marnix Mus,1 Jos PAM Vroemen,1 Tjeerd van der Ploeg,2 Dagmar I Vos,1 Leon HGJ Elmans,3 Lijckle van der Laan1 1Department of Surgery, Amphia Hospital, Breda, 2Department of Public Health, Erasmus MC–University Medical Center, Rotterdam, 3Department of Orthopedic Surgery, Amphia Hospital, Breda, the Netherlands Background: Delirium in hip fractured patients is a frequent complication. Dementia is an important risk factor for delirium and is common in frail elderly. This study aimed to extend the previous knowledge on risk factors for delirium and the consequences. Special attention was given to patients with dementia and delirium.Methods: This is a retrospective cohort study performed in the Amphia Hospital, Breda, the Netherlands. A full electronic patient file system (Hyperspace Version IU4: Epic, Inc., Verona, WI, USA) was used to assess data between January 2014 and September 2015. All patients presented were aged ≥70 years with a hip fracture, who underwent surgery with osteosynthesis or arthroplasty. Patients were excluded in case of a pathological or a periprosthetic hip fracture, multiple traumatic injuries, and high-energy trauma. Patient and surgical characteristics were documented. Postoperative outcomes were noted. Delirium was screened using Delirium Observation Screening Scale and dementia was assessed from medical notes.Results: Of a total of 566 included patients, 75% were females. The median age was 84 years (interquartile range: 9). Delirium was observed in 35%. Significant risk factors for delirium were a high American Society of Anesthesiology score, delirium in medical history, functional dependency, preoperative institutionalization, low hemoglobin level, and high amount of blood transfusion. Delirium was correlated with a longer hospital stay (P=0.001), increased association with complications (P

Abstract Background Prediction rules for intracranial traumatic findings in patients with minor head injury are designed to reduce the use of computed tomography (CT) without missing patients at risk for complications. This study investigates whether alternative modelling techniques might improve the applicability and simplicity of such prediction rules. Methods We included 3181 patients with minor head injury who had received CT scans between February 2002 and August 2004. Of these patients 243 (7.6%) had intracranial traumatic findings and 17 (0.5%) underwent neurosurgical intervention. We analyzed sensitivity, specificity and area under the ROC curve (AUC-value) to compare the performance of various modelling techniques by 10 × 10 cross-validation. The techniques included logistic regression, Bayes network, Chi-squared Automatic Interaction Detection (CHAID), neural net, support vector machines, Classification And Regression Trees (CART) and "decision list" models. Results The cross-validated performance was best for the logistic regression model (AUC 0.78), followed by the Bayes network model and the neural net model (both AUC 0.74). The other models performed poorly (AUC < 0.70). The advantage of the Bayes network model was that it provided a graphical representation of the relationships between the predictors and the outcome. Conclusions No alternative modelling technique outperformed the logistic regression model. However, the Bayes network model had a presentation format which provided more detailed insights into the structure of the prediction problem. The search for methods with good predictive performance and an attractive presentation format should continue.

The present study aimed to examine the prediction of quality of life by frailty and disability in a baseline sample of 479 Dutch community-dwelling people aged 75 years or older using a follow-up period of 8 years. Regarding frailty, we distinguish between physical, psychological, and social frailty. Concerning physical disability, we distinguish between limitations in performing activities in daily living (ADL) and instrumental activities in daily living (IADL). The Tilburg Frailty Indicator (TFI) and the Groningen Activity Restriction Scale (GARS) were used to assess frailty domains and types of disability, respectively. Quality of life was determined by the WHOQOL-BREF containing physical, psychological, social, and environmental domains. In our study, 53.9% of participants were woman, and the mean age was 80.3 years (range 75-93). The study showed that psychological frailty predicted four domains of quality of life and physical frailty three. Social frailty was only found to be a significant predictor of social quality of life and environmental quality of life. ADL and IADL disability proved to be the worst predictors. It is recommended that primary healthcare professionals (e.g., general practitioners, district nurses) focus their interventions primarily on factors that can prevent or delay psychological and physical frailty, thereby ensuring that people's quality of life does not deteriorate., Competing Interests: The authors declare no conflict of interest.

Disability is associated with lower quality of life and premature death in older people. Therefore, prevention and intervention targeting older people living with a disability is important. Frailty can be considered a major predictor of disability. In this study, we aimed to develop nomograms with items of the Tilburg Frailty Indicator (TFI) as predictors by using cross-sectional and longitudinal data (follow-up of five and nine years), focusing on the prediction of total disability, disability in activities of daily living (ADL), and disability in instrumental activities of daily living (IADL). At baseline, 479 Dutch community-dwelling people aged ≥75 years participated. They completed a questionnaire that included the TFI and the Groningen Activity Restriction Scale to assess the three disability variables. We showed that the TFI items scored different points, especially over time. Therefore, not every item was equally important in predicting disability. 'Difficulty in walking' and 'unexplained weight loss' appeared to be important predictors of disability. Healthcare professionals need to focus on these two items to prevent disability. We also conclude that the points given to frailty items differed between total, ADL, and IADL disability and also differed regarding years of follow-up. Creating one monogram that does justice to this seems impossible.

Background: COVID-19 was first identified in December 2019 in the city of Wuhan, China. The virus quickly spread and was declared a pandemic on March 11, 2020. After infection, symptoms such as fever, a (dry) cough, nasal congestion, and fatigue can develop. In some cases, the virus causes severe complications such as pneumonia and dyspnea and could result in death. The virus also spread rapidly in the Netherlands, a small and densely populated country with an aging population. Health care in the Netherlands is of a high standard, but there were nevertheless problems with hospital capacity, such as the number of available beds and staff. There were also regions and municipalities that were hit harder than others. In the Netherlands, there are important data sources available for daily COVID-19 numbers and information about municipalities., Objective: We aimed to predict the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants per municipality in the Netherlands, using a data set with the properties of 355 municipalities in the Netherlands and advanced modeling techniques., Methods: We collected relevant static data per municipality from data sources that were available in the Dutch public domain and merged these data with the dynamic daily number of infections from January 1, 2020, to May 9, 2021, resulting in a data set with 355 municipalities in the Netherlands and variables grouped into 20 topics. The modeling techniques random forest and multiple fractional polynomials were used to construct a prediction model for predicting the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants per municipality in the Netherlands., Results: The final prediction model had an R 2 of 0.63. Important properties for predicting the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants in a municipality in the Netherlands were exposure to particulate matter with diameters <10 μm (PM10) in the air, the percentage of Labour party voters, and the number of children in a household., Conclusions: Data about municipality properties in relation to the cumulative number of confirmed infections in a municipality in the Netherlands can give insight into the most important properties of a municipality for predicting the cumulative number of confirmed COVID-19 infections per 10,000 inhabitants in a municipality. This insight can provide policy makers with tools to cope with COVID-19 and may also be of value in the event of a future pandemic, so that municipalities are better prepared., (©Tjeerd van der Ploeg, Robbert J J Gobbens. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 20.10.2022.)

Nurses come into frequent contact with frail older people in all healthcare settings. However, few studies have specifically asked nurses about their views on frailty. The main aim of this study was to explore the opinions of nurses working with older people on the concept of frailty, regardless of the care setting. In addition, the associations between the background characteristics of nurses and their opinions about frailty were examined. In 2021, members of professional association of nurses and nursing assistants in the Netherlands (V&VN) received a digital questionnaire asking their opinions on frailty, and 251 individuals completed the questionnaire (response rate of 32.1%). The questionnaire contained seven topics: keywords of frailty, frailty domains, causes of frailty, consequences of frailty, reversing frailty, the prevention of frailty, and addressing frailty. Regarding frailty, nurses especially thought of physical deterioration and dementia. However, other domains of human functioning, such as the social and psychological domains, were often mentioned, pointing to a holistic approach to frailty. It also appears that nurses can identify many causes and consequences of frailty. They see opportunities to reverse frailty and an important role for themselves in this process.

[This corrects the article DOI: 10.2196/31480.]., (©Tjeerd van der Ploeg, Robbert Gobbens. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 08.04.2022.)

Background: Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques., Objective: In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty., Methods: We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping., Results: We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable "difficulty in walking" was important for all models., Conclusions: Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of "gender" and "age" variables. External validation is a necessary step before applying the prediction models in a new setting., (©Tjeerd van der Ploeg, Robbert Gobbens. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 30.03.2022.)

This study sought to provide insight into how art activities influence the well-being of long-term care residents, and how artists and caregivers collaborate in offering these activities. In two long-term care facilities for people with dementia and one for older people with chronic psychiatric disorders, an uncontrolled pre- and post-test study was conducted using a mixed-method design. Forty-six residents participated in the study. Three art activities-(a) dance, (b) music and movement, and (c) visual arts-were studied and co-created with the residents and executed by artists and caregivers together in eight to ten weeks. The Face expression scale (FACE) was used to examine the extent to which participating in the art activity influenced resident mood. Qualitative data were collected via group discussions with artists, caregivers, residents, and an informal caregiver. The results indicated that participating in an art activity positively influenced resident mood ( p < 0.000). p -values for the three art activities were: p < 0.000 for dance, p = 0.048 for music and movement, and p = 0.023 for visual arts. The qualitative data revealed that joining an art activity provided a positive effect, increased social relationships, and improved self-esteem for residents. The collaboration between artists and caregivers stimulated creativity, beauty, and learning from each other, as well as evoking emotions.

The aim of this cross-sectional study was to develop a Frailty at Risk Scale (FARS) incorporating ten well-known determinants of frailty: age, sex, marital status, ethnicity, education, income, lifestyle, multimorbidity, life events, and home living environment. In addition, a second aim was to develop an online calculator that can easily support healthcare professionals in determining the risk of frailty among community-dwelling older people. The FARS was developed using data of 373 people aged ≥ 75 years. The Tilburg Frailty Indicator (TFI) was used for assessing frailty. Multivariate logistic regression analysis showed that the determinants multimorbidity, unhealthy lifestyle, and ethnicity (ethnic minority) were the most important predictors. The area under the curve (AUC) of the model was 0.811 (optimism 0.019, 95% bootstrap CI = -0.029; 0.064). The FARS is offered on a Web site, so that it can be easily used by healthcare professionals, allowing quick intervention in promoting quality of life among community-dwelling older people., Competing Interests: Conflict of interestThe authors report no conflict of interest for this work., (© The Author(s), under exclusive licence to Springer Nature B.V. 2021.)

Background: Several adjuvants have been proposed to prolong the effect of peripheral nerve blocks, one of which is buprenorphine. In this randomized double blinded placebo controlled trial we studied whether the addition of buprenorphine to a femoral nerve block prolongs analgesia in patients undergoing total knee arthroplasty in a fast track surgery protocol., Methods: The treatment group (B) was given an ultrasound-guided femoral nerve block with ropivacaine 0.2% and 0.3mg buprenorphine. We choose to use 2 control groups. Group R was given a femoral nerve block with ropivacaine 0.2% only. Group S also received 0.3 mg buprenorphine subcutaneously. Only patients with a successful block were enrolled in the study., Results: We found no difference in our primary outcome parameter of time to first rescue analgesic. We found lower opioid use and better sleep quality the first postoperative night in patients receiving buprenorphine perineurally or subcutaneously. Buprenorphine did not lead to any significant change in pain or mobilization. We found a high overall incidence of nausea and vomiting., Conclusion: In patients undergoing total knee arthroplasty, in the setting of a fast track surgery protocol, the addition of buprenorphine to a femoral nerve block did not prolong analgesia.

Background: The number of viral pathogens associated with pediatric acute respiratory tract infection (ARI) has grown since the introduction of reverse transcription real-time polymerase chain reaction (RT-PCR) assays. Multiple viruses are detected during a single ARI episode in approximately a quarter of all cases. The clinical relevance of these multiple detections is unclear, as is the role of the individual virus. We therefore investigated the correlation between clinical data and RT-PCR results in children with single- and multiple viral ARI., Methods: Data from children with ARI were prospectively collected during two winter seasons. RT-PCR testing for 15 viruses was performed in 560 ARI episodes. In the patients with a single-viral etiology, clinical data, laboratory findings, patient management- and outcome data were compared between the different viruses. With this information, we compared data from children of whom RT-PCR data were negative, with children with single- and multiple viral positive results., Results: The viral detection rate was 457/560 (81.6%) of which 331/560 (59.1%) were single infections and 126/560 (22.5%) were multiple infections. In single viral infections, some statistically significant differences in demographics, clinical findings, disease severity and outcome were found between children with different viral etiologies. However, no clinically recognizable pattern was established to be virus-specific. In a multivariate analysis, the only variables that were correlated with longer hospital stay were the use of oxygen and nebulizer therapy, irrespective of the viral pathogen. Children with RT-PCR positive test results had a significant higher disease severity, fever, length of hospital stay, days of extra oxygen supply, and days of antibiotic treatment than children with a negative RT-PCR test result. For children with single- versus children with multiple positive RT-PCR test results, these differences were not significant., Conclusions: Disease (severity), management and outcome in pediatric ARI are not associated with a specific virus. Single- and multiple viral ARI do not significantly differ with regard to clinical outcome and patient management. For general pediatrics, RT-PCR assays should be restricted to pathogens for which therapy is available or otherwise may have clinical consequences. Further research with an extended panel of RT-PCR assays and a larger number of inclusions is necessary to further validate our findings.

Background: Genetic comparisons of clinical and environmental Legionella strains form an essential part of outbreak investigations. DNA microarrays often comprise many DNA markers (features). Feature selection and the development of prediction models are particularly challenging in this domain with many variables and comparatively few subjects or data points. We aimed to compare modeling strategies to develop prediction models for classifying infections as clinical or environmental., Methods: We applied a bootstrap strategy for preselecting important features to a database containing 222 Legionella pneumophila strains with 448 continuous markers and a dichotomous outcome (clinical or environmental). Feature selection was done with 50 bootstrap samples resulting in a top 10 of most important features for each of four modeling techniques: classification and regression trees (CART), random forests (RF), support vector machines (SVM) and least absolute shrinkage and selection operator (LASSO). Validation was done in a second bootstrap re-sampling loop (200×) for evaluation of discriminatory model performance according to the AUC., Results: The top 5 of selected features differed considerably between the various modeling techniques, with only one common feature ("LePn.007B8"). The mean validated AUC-values of the SVM model and the CART model were 0.859 and 0.873 respectively. The LASSO and the RF model showed higher validated AUC-values (0.925 and 0.975 respectively)., Conclusions: In the domain of Legionella pneumophila, which comprises many potential features for classifying of infections as clinical or environmental, the RF and LASSO techniques provide good prediction models. The identification of potentially biologically relevant features is highly dependent on the technique used, and should hence be interpreted with caution.

Introduction: External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting., Methods: We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury., Results: The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2., Conclusion: The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Background: Modern modelling techniques may potentially provide more accurate predictions of binary outcomes than classical techniques. We aimed to study the predictive performance of different modelling techniques in relation to the effective sample size ("data hungriness")., Methods: We performed simulation studies based on three clinical cohorts: 1282 patients with head and neck cancer (with 46.9% 5 year survival), 1731 patients with traumatic brain injury (22.3% 6 month mortality) and 3181 patients with minor head injury (7.6% with CT scan abnormalities). We compared three relatively modern modelling techniques: support vector machines (SVM), neural nets (NN), and random forests (RF) and two classical techniques: logistic regression (LR) and classification and regression trees (CART). We created three large artificial databases with 20 fold, 10 fold and 6 fold replication of subjects, where we generated dichotomous outcomes according to different underlying models. We applied each modelling technique to increasingly larger development parts (100 repetitions). The area under the ROC-curve (AUC) indicated the performance of each model in the development part and in an independent validation part. Data hungriness was defined by plateauing of AUC and small optimism (difference between the mean apparent AUC and the mean validated AUC <0.01)., Results: We found that a stable AUC was reached by LR at approximately 20 to 50 events per variable, followed by CART, SVM, NN and RF models. Optimism decreased with increasing sample sizes and the same ranking of techniques. The RF, SVM and NN models showed instability and a high optimism even with >200 events per variable., Conclusions: Modern modelling techniques such as SVM, NN and RF may need over 10 times as many events per variable to achieve a stable AUC and a small optimism than classical modelling techniques such as LR. This implies that such modern techniques should only be used in medical prediction problems if very large data sets are available.

Background: The use of alternative modeling techniques for predicting patient survival is complicated by the fact that some alternative techniques cannot readily deal with censoring, which is essential for analyzing survival data. In the current study, we aimed to demonstrate that pseudo values enable statistically appropriate analyses of survival outcomes when used in seven alternative modeling techniques., Methods: In this case study, we analyzed survival of 1282 Dutch patients with newly diagnosed Head and Neck Squamous Cell Carcinoma (HNSCC) with conventional Kaplan-Meier and Cox regression analysis. We subsequently calculated pseudo values to reflect the individual survival patterns. We used these pseudo values to compare recursive partitioning (RPART), neural nets (NNET), logistic regression (LR) general linear models (GLM) and three variants of support vector machines (SVM) with respect to dichotomous 60-month survival, and continuous pseudo values at 60 months or estimated survival time. We used the area under the ROC curve (AUC) and the root of the mean squared error (RMSE) to compare the performance of these models using bootstrap validation., Results: Of a total of 1282 patients, 986 patients died during a median follow-up of 66 months (60-month survival: 52% [95% CI: 50%-55%]). The LR model had the highest optimism corrected AUC (0.791) to predict 60-month survival, followed by the SVM model with a linear kernel (AUC 0.787). The GLM model had the smallest optimism corrected RMSE when continuous pseudo values were considered for 60-month survival or the estimated survival time followed by SVM models with a linear kernel. The estimated importance of predictors varied substantially by the specific aspect of survival studied and modeling technique used., Conclusions: The use of pseudo values makes it readily possible to apply alternative modeling techniques to survival problems, to compare their performance and to search further for promising alternative modeling techniques to analyze survival time.

Introduction: Mitotic Activity Index (MAI) is an important independent prognostic factor and an integral part of the breast cancer grading system. Thus, correct estimation of this prognostically relevant feature is essential for guiding treatment decision and assessing patient prognosis. The aim of this study was to validate the use of high resolution Whole Slide Images (WSI) in estimating MAI in breast cancer specimens., Methods: MAI was evaluated in 100 consecutive breast cancer specimens by three observers on two occasions, microscopically and on WSI with a wash out period of 4 months. MAI was also translated to mitotic scores as in grading. Inter- and intra-observer agreement between microscopic and digital MAI counts and scores was measured., Results: Almost perfect inter-observer agreements were obtained from counting MAI using a conventional microscope (intra-class correlation coefficient (ICCC) 0.879) as well as on WSI (ICCC 0.924). K coefficients reflected good inter-observer agreements among observers' microscopic mitotic scores (average kappa 0.642). Comparable results were also observed among digital mitotic scores (average kappa 0.635). There was strong to perfect intra-observer agreements between MAI counts and mitotic scores for the two diagnostic modalities (ICCC 0.716-0.863, kappa 0.506-0.617). There were no significant differences in mitotic scores using both diagnostic modalities., Conclusion: Scoring mitoses using WSI in breast cancer seems to be just as reliable and reproducible as when using a microscope. Further development of software and image quality will definitely encourage the use of WSI in routine pathology practice.

Background. Features that may allow early identification of patients at risk of prolonged delirium, and therefore of poorer outcomes, are not well understood. The aim of this study was to determine if preoperative delirium risk factors and delirium symptoms (at onset and clinical symptomatology during the course of delirium) are associated with delirium duration. Methods. This study was conducted in prospectively identified cases of incident delirium. We compared patients experiencing delirium of short duration (1 or 2 days) with patients who had more prolonged delirium (≥3 days) with regard to DRS-R-98 (Delirium Rating Scale Revised-98) symptoms on the first delirious day. Delirium symptom profile was evaluated daily during the delirium course. Results. In a homogenous population of 51 elderly hip-surgery patients, we found that the severity of individual delirium symptoms on the first day of delirium was not associated with duration of delirium. Preexisting cognitive decline was associated with prolonged delirium. Longitudinal analysis using the generalised estimating equations method (GEE) identified that more severe impairment of long-term memory across the whole delirium episode was associated with longer duration of delirium. Conclusion. Preexisting cognitive decline rather than severity of individual delirium symptoms at onset is strongly associated with delirium duration.

Background: In chronic hemodialysis (HD) patients, the repetitive induction of the acute phase response (APR) may induce a chronic micro-inflammatory state, leading to various long-term complications., Methods: The present prospective study was designed to assess the alterations in the APR in 74 patients who were randomized to HD with a high-flux polysulfone (PS; F 60S), a super-flux PS (F 500S), or a super-flux cellulosic tri-acetate (CTA and CTA with filtered dialysate, CTA(f)) dialyzer. Blood samples collected at the start of the study and after twelve weeks were analyzed for interleukin-6 (IL-6) and C-reactive protein (CRP). In addition to the microbiological quality of the dialysate, the appearance of a "clinical event" was assessed., Results: At baseline, mean IL-6 levels were within the reference range whereas mean CRP levels were slightly elevated. Mean values did not change after 12 weeks of HD with either modality. After subdividing the patients in quartiles with increasing change in plasma CRP, 23.0% of the patients showed a change of more than 8.0 mg/L. In a multiple regression analysis, CRP levels appeared to be independent of the degree of dialysate contamination, the material and the flux characteristics of the devices. In fact, the variable "clinical events" was the only significant predictor of the plasma CRP levels (P < 0.001)., Conclusions: Based on these results, both PS and CTA super-flux dialyzers appear safe for clinical use. Whether changes in CRP values, which are associated with intercurrent clinical events, influence the long-term prognosis of chronic HD patients remains to be established.