Expectant mothers and mothers of young children are especially vulnerable to intimate partner violence (IPV). The nurse-family partnership (NFP) is a home visitation program in the United States effective for the prevention of adverse child health outcomes. Evidence regarding the effect of nurse home visiting on IPV is inconsistent. This study aims to study the effect of VoorZorg, the Dutch NFP, on IPV.
A random sample of 460 eligible disadvantaged women <26 years, with no previous live births, was randomized. Women in the control group (C; n=223) received usual care; women in the intervention group (I; n=237) received usual care plus nurse home visits periodically during pregnancy and until the child’s second birthday.
At 32 weeks of pregnancy, women in the intervention group self-reported significantly less IPV victimization than women in the control group in: level 2 psychological aggression (C: 56% vs. I: 39%), physical assault level 1 (C: 58% vs. I: 40%) and level 2 (C: 31% vs. I: 20%), and level 1 sexual coercion (C: 16% vs. I: 8%). Furthermore, women in the intervention group reported significantly less IPV perpetration in: level 2 psychological aggression (C: 60% vs. I: 46%), level 1 physical assault (C: 65% vs. I: 52%), and level 1 injury (C: 27% vs. I: 17%). At 24 months after birth, IPV victimization was significantly lower in the intervention group for level 1 physical assault (C: 44% vs. I: 26%), and IPV perpetration was significantly lower for level 1 sexual assault (C: 18% vs. I: 3%). Multilevel analyses showed a significant improvement in IPV victimization and perpetration among women in the intervention group at 24 months after birth.
VoorZorg, compared with the usual care, is effective in reducing IPV during pregnancy and in the two years after birth among young high-risk women.
Dutch Trial Register NTR854 http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=854
Effective interventions to improve quality of life of cancer survivors are essential. Numerous randomized controlled trials have evaluated the effects of physical activity or psychosocial interventions on health-related quality of life of cancer survivors, with generally small sample sizes and modest effects. Better targeted interventions may result in larger effects. To realize such targeted interventions, we must determine which interventions that are presently available work for which patients, and what the underlying mechanisms are (that is, the moderators and mediators of physical activity and psychosocial interventions). Individual patient data meta-analysis has been described as the ‘gold standard’ of systematic review methodology. Instead of extracting aggregate data from study reports or from authors, the original research data are sought directly from the investigators. Individual patient data meta-analyses allow for adequate statistical analysis of intervention effects and moderators of such effects.
Here, we report the rationale and design of the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) Consortium. The primary aim of POLARIS is 1) to conduct meta-analyses based on individual patient data to evaluate the effect of physical activity and psychosocial interventions on the health-related quality of life of cancer survivors; 2) to identify important demographic, clinical, personal, or intervention-related moderators of the effect; and 3) to build and validate clinical prediction models identifying the most relevant predictors of intervention success.
We will invite investigators of randomized controlled trials that evaluate the effects of physical activity and/or psychosocial interventions on health-related quality of life compared with a wait-list, usual care or attention control group among adult cancer survivors to join the POLARIS consortium and share their data for use in pooled analyses that will address the proposed aims. We are in the process of identifying eligible randomized controlled trials through literature searches in four databases. To date, we have identified 132 eligible and unique trials.
The POLARIS consortium will conduct the first individual patient data meta-analyses in order to generate evidence essential to targeting physical activity and psychosocial programs to the individual survivor’s characteristics, capabilities, and preferences.
PROSPERO: International prospective register of systematic reviews, CRD42013003805
Physical activity; Exercise; Neoplasms; Psychotherapy; Health-related quality of life; Rehabilitation; Individual patient data meta-analysis
Smoking during pregnancy is a risk factor for various adverse birth outcomes. In order to develop effective interventions, insight is needed into the characteristics associated with pregnant women who smoke. Unknown is whether these characteristics differ for women who smoke daily and women who smoke occasionally. Our study sample, drawn from the DELIVER study (Sept 2009-March 2011), consisted of 6107 pregnant women in primary care in the Netherlands who were up to 34 weeks pregnant. The associations of thirteen socio-demographic or lifestyle-related characteristics with ‘any smoking’, ‘daily smoking’ and ‘occasional smoking’ during pregnancy were tested using multiple binary logistic regression with general estimating equations (GEE). Characteristics most strongly associated with any smoking were low education (OR 10.3; 95% confidence interval (CI) 7.0-15.4), being of Turkish ethnicity (OR 3.9; 95%CI 2.3-6.7) and having no partner (OR 3.7; 95%CI 2.3-6.0). Women of Dutch ethnicity were three times more likely to smoke than those from Dutch-speaking Caribbean countries and non-religious women were much more likely to smoke than religious women. Low education was markedly more strongly associated with daily smoking than with occasional smoking (OR 20.3; 95%CI 13.2-31.3 versus OR 6.0; 95%CI 3.4-10.5). Daily smokers were more likely to be associated with other unfavorable lifestyle-related characteristics, such as not taking folic acid, being underweight, and having had an unplanned pregnancy. There is still much potential for health gain with respect to smoking during pregnancy in the Netherlands. Daily and occasional smokers appear to differ in characteristics, and therefore possibly require different interventions.
Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to severity and outcome of BM. In this study it was determined whether host genetic risk factors improve the predictive abilities of an existing model regarding hearing loss after childhood BM.
Four hundred and seventy-one Dutch Caucasian childhood BM were genotyped for 11 single nucleotide polymorphisms (SNPs) in seven different genes involved in pathogen recognition. Genetic data were added to the original clinical prediction model and performance of new models was compared to the original model by likelihood ratio tests and the area under the curve (AUC) of the receiver operating characteristic curves.
Addition of TLR9-1237 SNPs and the combination of TLR2 + 2477 and TLR4 + 896 SNPs improved the clinical prediction model, but not significantly (increase of AUC’s from 0.856 to 0.861 and from 0.856 to 0.875 (p = 0.570 and 0.335, respectively). Other SNPs analysed were not linked to hearing loss.
Although addition of genetic risk factors did not significantly improve the clinical prediction model for post-meningitis hearing loss, AUC’s of the pre-existing model remain high after addition of genetic factors. Future studies should evaluate whether more combinations of SNPs in larger cohorts has an additional value to the existing prediction model for post meningitis hearing loss.
Genetics; SNP; Risk; Prediction; Bacterial meningitis; Hearing loss; Child
Individuals at high risk for chronic cardiometabolic disease (cardiovascular disease [CVD], type 2 diabetes, and chronic kidney disease [CKD]) share many risk factors and would benefit from early intervention. We developed a nonlaboratory-based risk-assessment tool for identification of people at high cardiometabolic disease risk.
RESEARCH DESIGN AND METHODS
Data of three population-based cohorts from different regions of the Netherlands were merged. Participants were 2,840 men and 3,940 women, white, aged 28–85 years, free from CVD, type 2 diabetes, and CKD diagnosis at baseline. The outcome was developing cardiometabolic disease during 7 years follow-up.
Age, BMI, waist circumference, antihypertensive treatment, smoking, family history of myocardial infarction or stroke, and family history of diabetes were significant predictors, whereas former smoking, history of gestational diabetes, and use of lipid-lowering medication were not. The models showed acceptable calibration (Hosmer and Lemeshow statistics, P > 0.05) and discrimination (area under the receiver operating characteristic [ROC] curve 0.82 [95% CI 0.81–0.83] for women and 0.80 [0.78–0.82] for men). Discrimination of individual outcomes was lowest for diabetes (area under the ROC curve 0.70 for men and 0.73 for women) and highest for CVD mortality (0.83 for men and 0.85 for women).
We demonstrate that a single risk stratification tool can identify people at high risk for future CVD, type 2 diabetes, and/or CKD. The present risk-assessment tool can be used for referring the highest risk individuals to health care for further (multivariable) risk assessment and may as such serve as an important part of prevention programs targeting chronic cardiometabolic disease.
Many prognostic models have been developed. Different types of models, i.e. prognostic factor and outcome prediction studies, serve different purposes, which should be reflected in how the results are summarized in reviews. Therefore we set out to investigate how authors of reviews synthesize and report the results of primary outcome prediction studies.
Outcome prediction reviews published in MEDLINE between October 2005 and March 2011 were eligible and 127 Systematic reviews with the aim to summarize outcome prediction studies written in English were identified for inclusion.
Characteristics of the reviews and the primary studies that were included were independently assessed by 2 review authors, using standardized forms.
After consensus meetings a total of 50 systematic reviews that met the inclusion criteria were included. The type of primary studies included (prognostic factor or outcome prediction) was unclear in two-thirds of the reviews. A minority of the reviews reported univariable or multivariable point estimates and measures of dispersion from the primary studies. Moreover, the variables considered for outcome prediction model development were often not reported, or were unclear. In most reviews there was no information about model performance. Quantitative analysis was performed in 10 reviews, and 49 reviews assessed the primary studies qualitatively. In both analyses types a range of different methods was used to present the results of the outcome prediction studies.
Different methods are applied to synthesize primary study results but quantitative analysis is rarely performed. The description of its objectives and of the primary studies is suboptimal and performance parameters of the outcome prediction models are rarely mentioned. The poor reporting and the wide variety of data synthesis strategies are prone to influence the conclusions of outcome prediction reviews. Therefore, there is much room for improvement in reviews of outcome prediction studies.
Review; Systematic; Meta-analysis; Prediction; Prognosis; Forecasting; Methods
Within longitudinal epidemiological research, ‘count’ outcome variables with an excess of zeros frequently occur. Although these outcomes are frequently analysed with a linear mixed model, or a Poisson mixed model, a two-part mixed model would be better in analysing outcome variables with an excess of zeros. Therefore, objective of this paper was to introduce the relatively ‘new’ method of two-part joint regression modelling in longitudinal data analysis for outcome variables with an excess of zeros, and to compare the performance of this method to current approaches.
Within an observational longitudinal dataset, we compared three techniques; two ‘standard’ approaches (a linear mixed model, and a Poisson mixed model), and a two-part joint mixed model (a binomial/Poisson mixed distribution model), including random intercepts and random slopes. Model fit indicators, and differences between predicted and observed values were used for comparisons. The analyses were performed with STATA using the GLLAMM procedure.
Regarding the random intercept models, the two-part joint mixed model (binomial/Poisson) performed best. Adding random slopes for time to the models changed the sign of the regression coefficient for both the Poisson mixed model and the two-part joint mixed model (binomial/Poisson) and resulted into a much better fit.
This paper showed that a two-part joint mixed model is a more appropriate method to analyse longitudinal data with an excess of zeros compared to a linear mixed model and a Poisson mixed model. However, in a model with random slopes for time a Poisson mixed model also performed remarkably well.
Two-part joint model; Excess of zeros; Count; Mixed modelling; Longitudinal; Statistical methods
Distance lifestyle counseling for weight control is a promising public health intervention in the work setting. Information about the cost-effectiveness of such interventions is lacking, but necessary to make informed implementation decisions. The purpose of this study was to perform an economic evaluation of a six-month program with lifestyle counseling aimed at weight reduction in an overweight working population with a two-year time horizon from a societal perspective.
A randomized controlled trial comparing a program with two modes of intervention delivery against self-help. 1386 Employees from seven companies participated (67% male, mean age 43 (SD 8.6) years, mean BMI 29.6 (SD 3.5) kg/m2). All groups received self-directed lifestyle brochures. The two intervention groups additionally received a workbook-based program with phone counseling (phone; n=462) or a web-based program with e-mail counseling (internet; n=464). Body weight was measured at baseline and 24 months after baseline. Quality of life (EuroQol-5D) was assessed at baseline, 6, 12, 18 and 24 months after baseline. Resource use was measured with six-monthly diaries and valued with Dutch standard costs. Missing data were multiply imputed. Uncertainty around differences in costs and incremental cost-effectiveness ratios was estimated by applying non-parametric bootstrapping techniques and graphically plotting the results in cost-effectiveness planes and cost-effectiveness acceptability curves.
At two years the incremental cost-effectiveness ratio was €1009/kg weight loss in the phone group and €16/kg weight loss in the internet group. The cost-utility analysis resulted in €245,243/quality adjusted life year (QALY) and €1337/QALY, respectively. The results from a complete-case analysis were slightly more favorable. However, there was considerable uncertainty around all outcomes.
Neither intervention mode was proven to be cost-effective compared to self-help.
Body weight; Cost-effectiveness; Cost-utility; Distance counseling; Intervention; Lifestyle; RCT; Workplace health promotion
The additional benefit of lifestyle interventions in patients receiving cardioprotective drug treatment to improve cardiovascular risk profile is not fully established.
The objective was to evaluate the effectiveness of a target-driven multidisciplinary structured lifestyle intervention programme of 6 months duration aimed at maximum reduction of cardiovascular risk factors in patients with cardiovascular disease (CVD) compared with usual care.
A single centre, two arm, parallel group randomised controlled trial was performed. Patients with stable established CVD and at least one lifestyle-related risk factor were recruited from the vascular and cardiology outpatient departments of the university hospital. Blocked randomisation was used to allocate patients to the intervention (n = 71) or control group (n = 75) using an on-site computer system combined with allocations in computer-generated tables of random numbers kept in a locked computer file. The intervention group received the comprehensive lifestyle intervention offered in a specialised outpatient clinic in addition to usual care. The control group continued to receive usual care. Outcome measures were the lifestyle-related cardiovascular risk factors: smoking, physical activity, physical fitness, diet, blood pressure, plasma total/HDL/LDL cholesterol concentrations, BMI, waist circumference, and changes in medication.
The intervention led to increased physical activity/fitness levels and an improved cardiovascular risk factor profile (reduced BMI and waist circumference). In this setting, cardiovascular risk management for blood pressure and lipid levels by prophylactic treatment for CVD in usual care was already close to optimal as reflected in baseline levels. There was no significant improvement in any other risk factor.
Even in CVD patients receiving good clinical care and using cardioprotective drug treatment, a comprehensive lifestyle intervention had a beneficial effect on some cardiovascular risk factors. In the present era of cardiovascular therapy and with the increasing numbers of overweight and physically inactive patients, this study confirms the importance of risk factor control through lifestyle modification as a supplement to more intensified drug treatment in patients with CVD.
ISRCTN69776211 at http://www.controlled-trials.com
Cardiovascular diseases; Lifestyle intervention; Smoking; Physical activity; Diet; Health behaviour; Randomised controlled trial; Cardiology; Therapy; Cardiovascular risk management
The growing prevalence rate of pediatric obesity, which is frequently accompanied by several cardiometabolic risk factors, has become a serious global health issue. To date, little is known regarding differences for cardiometabolic risk factors (prevalence and means) in children from different countries. In the present review, we aimed to provide a review for the available evidence regarding cardiometabolic risk factors in overweight pediatric populations. We therefore provided information with respect to the prevalence of impaired fasting glucose/impaired glucose tolerance, high triglycerides, low HDL-cholesterol and hypertension (components of the metabolic syndrome) among cohorts from different countries. Moreover, we aimed to compare the means of glucose and lipid levels (triglycerides and HDL-cholesterol) and systolic/diastolic blood pressure values. After careful selection of articles describing cohorts with comparable age and sex, it was shown that both prevalence rates and mean values of cardiometabolic risk factors varied largely among cohorts of overweight children. After ranking for high/low means for each cardiometabolic risk parameter, Dutch-Turkish children and children from Turkey, Hungary, Greece, Germany and Poland were in the tertile with the most unfavorable risk factor profile overall. In contrast, cohorts from Norway, Japan, Belgium, France and the Dominican Republic were in the tertile with most favorable risk profile. These results should be taken with caution, given the heterogeneity of the relatively small, mostly clinical cohorts and the lack of information concerning the influence of the values of risk parameters on true cardiometabolic outcome measures in comparable cohorts. The results of our review present a fair estimation of the true differences between cardiometabolic risk profiles among pediatric cohorts worldwide, based on available literature.
In the present article, we aimed to compare the cardiometabolic risk between overweight children with and without type 1 diabetes (T1DM). Therefore, data with regard to cardiometabolic risk parameters of 44 overweight Caucasian children (3–18 years) with T1DM were matched with 44 overweight peers without T1DM for sex, ethnicity, age and standard deviation score of BMI (Z-BMI). Detailed history was taken, information regarding anthropometrics and family history were collected and blood pressure was measured. Blood samples were collected for evaluation of lipid profiles (fasting in controls, non-fasting in T1DM children), alanine aminotransferase and HbA1c (in children with T1DM). It was found that overweight children with T1DM had lower median standard deviation score of waist circumference (Z-WC) as compared to the overweight control group [median, 2.0 (interquartile range, IQR, 1.5–2.3) vs. 2.6 (IQR, 2.0–2.9), P < 0.001]. After adjustment for Z-WC, in children with T1DM, median high-density lipoprotein cholesterol levels were significantly higher and median low-density lipoprotein cholesterol lower in T1DM children, as compared to their peers without T1DM [1.40 (IQR, 1.2–1.5) vs. 1.2 (IQR, 1.0–1.3) and 2.7 (IQR, 2.5–3.2) vs. 3.0 (IQR, 2.5–3.4), respectively, all P < 0.01]. When dividing children according to glycaemic status, children with suboptimal glycaemic control had higher values of triglycerides as compared to well-controlled children [1.3 (IQR, 1.0–1.8) vs. 0.96 (IQR, 0.80–1.2), P = 0.036]. In conclusion, overweight children with T1DM have a more favourable lipid profile, as compared to non-diabetic overweight controls, in spite of a higher frequency of a positive family history of CVD, T2DM and hypertension. Still, paediatricians should give extra attention to cardiometabolic risk factors within this vulnerable group, taking into account the already high cardiometabolic risk.
Paediatric; Obesity; Overweight; Risk factors for cardiovascular disease; Type 1 diabetes
Osteoprotegerin (OPG), a soluble member of the tumor necrosis factor receptor superfamily, is linked to cardiovascular disease. Negative associations exist between circulating OPG and cardiac function. The adipocytokine adiponectin (ADPN) is downregulated in type 2 diabetes mellitus (T2DM) and coronary artery disease and shows an inverse correlation with insulin sensitivity and cardiovascular disease risk. We assessed the relationship of plasma OPG and ADPN and arterial function, cardiac function and myocardial glucose metabolism in T2DM.
We included 78 asymptomatic men with uncomplicated, well-controlled T2DM, without inducible ischemia, assessed by dobutamine-stress echocardiography, and 14 age-matched controls. Cardiac function was measured by magnetic resonance imaging, myocardial glucose metabolism (MMRglu) by 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography. OPG and ADPN levels were measured in plasma.
T2DM patients vs. controls showed lower aortic distensibility, left ventricular (LV) volumes, impaired LV diastolic function and MMRglu (all P < 0.05). In T2DM men vs. controls, OPG levels were higher (P = 0.02), whereas ADPN concentrations were decreased (P = 0.04). OPG correlated inversely with aortic distensibility, LV volumes and E/A ratio (diastolic function), and positively with LV mass/volume ratio (all P < 0.05). Regression analyses showed the associations with aortic distensibility and LV mass/volume ratio to be independent of age-, blood pressure- and glycated hemoglobin (HbA1c). However, the associations with LV volumes and E/A ratio were dependent of these parameters. ADPN correlated positively with MMRglu (P < 0.05), which, in multiple regression analysis, was dependent of whole-body insulin sensitivity, HbA1c and waist.
OPG was inversely associated with aortic distensibility, LV volumes and LV diastolic function, while ADPN was positively associated with MMRglu. These findings indicate that in asymptomatic men with uncomplicated T2DM, OPG and ADPN may be markers of underlying mechanisms linking the diabetic state to cardiac abnormalities.
Current Controlled Trials ISRCTN53177482
osteoprotegerin; adiponectin; type 2 diabetes mellitus; arterial function; cardiac function; myocardial metabolism
To critically appraise and compare the measurement properties of the original versions of neck-specific questionnaires.
Bibliographic databases were searched for articles concerning the development or evaluation of the measurement properties of an original version of a self-reported questionnaire, evaluating pain and/or disability, which was specifically developed or adapted for patients with neck pain. The methodological quality of the selected studies and the results of the measurement properties were critically appraised and rated using a checklist, specifically designed for evaluating studies on measurement properties.
The search strategy resulted in a total of 3,641 unique hits, of which 25 articles, evaluating 8 different questionnaires, were included in our study. The Neck Disability Index is the most frequently evaluated questionnaire and shows positive results for internal consistency, content validity, structural validity, hypothesis testing, and responsiveness, but a negative result for reliability. The other questionnaires show positive results, but the evidence for each measurement property is mostly limited, and at least 50% of the information on measurement properties per questionnaire is lacking.
Our findings imply that studies of high methodological quality are needed to properly assess the measurement properties of the currently available questionnaires. Until high quality studies are available, we recommend using these questionnaires with caution. There is no need for the development of new neck-specific questionnaires until the current questionnaires have been adequately assessed.
Neck pain; Neck disability; Questionnaire; Pain measurement; Validation studies; Reproducibility of results; Psychometrics; Systematic review
In prognostic research, prediction rules are generally statistically derived. However the composition and performance of these statistical models may strongly depend on the characteristics of the derivation sample. The purpose of this study was to establish consensus among clinicians and experts on key predictors for persistent shoulder pain three months after initial consultation in primary care and assess the predictive performance of a model based on clinical expertise compared to a statistically derived model.
A Delphi poll involving 3 rounds of data collection was used to reach consensus among health care professionals involved in the assessment and management of shoulder pain.
Predictors selected by the expert panel were: symptom duration, pain catastrophizing, symptom history, fear-avoidance beliefs, coexisting neck pain, severity of shoulder disability, multisite pain, age, shoulder pain intensity and illness perceptions. When tested in a sample of 587 primary care patients consulting with shoulder pain the predictive performance of the two prognostic models based on clinical expertise were lower compared to that of a statistically derived model (Area Under the Curve, AUC, expert-based dichotomous predictors 0.656, expert-based continuous predictors 0.679 vs. 0.702 statistical model).
The three models were different in terms of composition, but all confirmed the prognostic importance of symptom duration, baseline level of shoulder disability and multisite pain. External validation in other populations of shoulder pain patients should confirm whether statistically derived models indeed perform better compared to models based on clinical expertise.
Several disease-specific questionnaires to measure pain and disability in patients with neck pain have been translated. However, a simple translation of the original version doesn't guarantee similar measurement properties. The objective of this study is to critically appraise the quality of the translation process, cross-cultural validation and the measurement properties of translated versions of neck-specific questionnaires.
Bibliographic databases were searched for articles concerning the translation or evaluation of the measurement properties of a translated version of a neck-specific questionnaire. The methodological quality of the selected studies and the results of the measurement properties were critically appraised and rated using the COSMIN checklist and criteria for measurement properties.
The search strategy resulted in a total of 3641 unique hits, of which 27 articles, evaluating 6 different questionnaires in 15 different languages, were included in this study. Generally the methodological quality of the translation process is poor and none of the included studies performed a cross-cultural adaptation. A substantial amount of information regarding the measurement properties of translated versions of the different neck-specific questionnaires is lacking. Moreover, the evidence for the quality of measurement properties of the translated versions is mostly limited or assessed in studies of poor methodological quality.
Until results from high quality studies are available, we advise to use the Catalan, Dutch, English, Iranian, Korean, Spanish and Turkish version of the NDI, the Chinese version of the NPQ, and the Finnish, German and Italian version of the NPDS. The Greek NDI needs cross-cultural validation and there is no methodologically sound information for the Swedish NDI. For all other languages we advise to translate the original version of the NDI.
Eddy current induced velocity offsets are of concern for accuracy in cardiovascular magnetic resonance (CMR) volume flow quantification. However, currently known theoretical aspects of eddy current behavior have not led to effective guidelines for the optimization of flow quantification sequences. This study is aimed at identifying correlations between protocol parameters and the resulting velocity error in clinical CMR flow measurements in a multi-vendor study.
Nine 1.5T scanners of three different types/vendors were studied. Measurements were performed on a large stationary phantom. Starting from a clinical breath-hold flow protocol, several protocol parameters were varied. Acquisitions were made in three clinically relevant orientations. Additionally, a time delay between the bipolar gradient and read-out, asymmetric versus symmetric velocity encoding, and gradient amplitude and slew rate were studied in adapted sequences as exploratory measurements beyond the protocol. Image analysis determined the worst-case offset for a typical great-vessel flow measurement.
The results showed a great variation in offset behavior among scanners (standard deviation among samples of 0.3, 0.4, and 0.9 cm/s for the three different scanner types), even for small changes in the protocol. Considering the absolute values, none of the tested protocol settings consistently reduced the velocity offsets below the critical level of 0.6 cm/s neither for all three orientations nor for all three scanner types. Using multilevel linear model analysis, oblique aortic and pulmonary slices showed systematic higher offsets than the transverse aortic slices (oblique aortic 0.6 cm/s, and pulmonary 1.8 cm/s higher than transverse aortic). The exploratory measurements beyond the protocol yielded some new leads for further sequence development towards reduction of velocity offsets; however those protocols were not always compatible with the time-constraints of breath-hold imaging and flow-related artefacts.
This study showed that with current systems there was no generic protocol which resulted into acceptable flow offset values. Protocol optimization would have to be performed on a per scanner and per protocol basis. Proper optimization might make accurate (transverse) aortic flow quantification possible for most scanners. Pulmonary flow quantification would still need further (offline) correction.
In prognostic studies model instability and missing data can be troubling factors. Proposed methods for handling these situations are bootstrapping (B) and Multiple imputation (MI). The authors examined the influence of these methods on model composition.
Models were constructed using a cohort of 587 patients consulting between January 2001 and January 2003 with a shoulder problem in general practice in the Netherlands (the Dutch Shoulder Study). Outcome measures were persistent shoulder disability and persistent shoulder pain. Potential predictors included socio-demographic variables, characteristics of the pain problem, physical activity and psychosocial factors. Model composition and performance (calibration and discrimination) were assessed for models using a complete case analysis, MI, bootstrapping or both MI and bootstrapping.
Results showed that model composition varied between models as a result of how missing data was handled and that bootstrapping provided additional information on the stability of the selected prognostic model.
In prognostic modeling missing data needs to be handled by MI and bootstrap model selection is advised in order to provide information on model stability.
Low body mass index is a general measure of thinness. However, its measurement can be cumbersome in older persons and other simple anthropometric measures may be more strongly associated with mortality. Therefore, associations of low mid-upper arm circumference, calf circumference, and body mass index with mortality were examined in older persons.
Data of the Longitudinal Aging Study Amsterdam, a population-based cohort study in the Netherlands, were used. The present study included community-dwelling persons 65 years and older in 1992–1993 (n = 1,667), who were followed until 2007 for their vital status. Associations between anthropometric measures and 15-year mortality were examined by spline regression models and, below the nadir, Cox regression models, transforming all measures to sex-specific Z scores.
Mortality rates were 599 of 826 (73%) in men and 479 of 841 (57%) in women. Below the nadir, the hazard ratio of mortality per 1 standard deviation lower mid-upper arm circumference was 1.79 (95% confidence interval, 1.48–2.16) in men and 2.26 (1.71–3.00) in women. For calf circumference, the hazard ratio was 1.45 (1.22–1.71) in men and 1.30 (1.15–1.48) in women and for body mass index 1.38 (1.17–1.61) in men and 1.56 (1.10–2.21) in women. Excluding deaths within the first 3 years after baseline did not change these associations. Excluding those with a smoking history, obstructive lung disease, or cancer attenuated the associations of calf circumference (men) and body mass index (women).
Based on the stronger association with mortality and given a more easy assessment in older persons, mid-upper arm circumference seems a more feasible and valid anthropometric measure of thinness than body mass index in older men and women.
Aged; Anthropometry; Body mass index; Mortality; Thinness
The objective of this study was to report on secondary analyses of a merged trial dataset aimed at exploring the potential importance of patient factors associated with clinically relevant improvements in non-acute, non-specific low back pain (LBP). From 273 predominantly male army workers (mean age 39 ± 10.5 years, range 20–56 years, 4 women) with LBP who were recruited in three randomized clinical trials, baseline individual patient factors, pain-related factors, work-related psychosocial factors, and psychological factors were evaluated as potential prognostic variables in a short-term (post-treatment) and a long-term logistic regression model (6 months after treatment). We found one dominant prognostic factor for improvement directly after treatment as well as 6 months later: baseline functional disability, expressed in Roland–Morris Disability Questionnaire scores. Baseline fear of movement, expressed in Tampa Scale for Kinesiophobia scores, had also significant prognostic value for long-term improvement. Less strongly associated with the outcome, but also included in our final models, were supervisor social support and duration of complaints (short-term model), and co-worker social support and pain radiation (long-term model). Information about initial levels of functional disability and fear-avoidance behaviour can be of value in the treatment of patient populations with characteristics comparable to the current army study population (e.g., predominantly male, physically active, working, moderate but chronic back problems). Individuals at risk for poor long-term LBP recovery, i.e., individuals with high initial level of disability and prominent fear-avoidance behaviour, can be distinguished that may need additional cognitive-behavioural treatment.
Low back pain; Prognostic factors; Secondary analyses; Logistic regression; Multiple imputation
Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection.
In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels.
We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found.
We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values.
This study aimed external validation of a formerly developed prediction model identifying children at risk for hearing loss after bacterial meningitis (BM). Independent risk factors included in the model are: duration of symptoms prior to admission, petechiae, cerebral spinal fluid (CSF) glucose level, Streptococcus pneumoniae and ataxia. Validation helps to evaluate whether the model has potential in clinical practice.
116 Dutch school-age BM survivors were included in the validation cohort and screened for sensorineural hearing loss (>25 dB). Risk factors were obtained from medical records. The model was applied to the validation cohort and its performance was compared with the development cohort. Validation was performed by application of the model on the validation cohort and by assessment of discrimination and goodness of fit. Calibration was evaluated by testing deviations in intercept and slope. Multiple imputation techniques were used to deal with missing values.
Risk factors were distributed equally between both cohorts. Discriminative ability (Area Under the Curve, AUC) of the model was 0.84 in the development and 0.78 in the validation cohort. Hosmer-Lemeshow test for goodness of fit was not significant in the validation cohort, implying good fit concerning the similarity of expected and observed cases. There were no significant differences in calibration slope and intercept. Sensitivity and negative predicted value were high, while specificity and positive predicted value were low which is comparable with findings in the development cohort.
Performance of the model remained good in the validation cohort. This prediction model might be used as a screening tool and can help to identify those children that need special attention and a long follow-up period or more frequent auditory testing.
Two models including age, self-rated health (SRH) and prior sickness absence (SA) were found to predict high SA in health care workers. The present study externally validated these prediction models in a population of office workers and investigated the effect of adding gender as a predictor.
SRH was assessed at baseline in a convenience sample of office workers. Age, gender and prior SA were retrieved from an occupational health service register. Two pre-defined prediction models were externally validated: a model identifying employees with high (i.e. ≥30) SA days and a model identifying employees with high (i.e. ≥3) SA episodes during 1-year follow-up. Calibration was investigated by plotting the predicted and observed probabilities and calculating the calibration slope. Discrimination was examined by receiver operating characteristic (ROC) analysis and the area under the ROC-curve (AUC).
A total of 593 office workers had complete data and were eligible for analysis. Although the SA days model showed acceptable calibration (slope = 0.89), it poorly discriminated office workers with high SA days from those without high SA days (AUC = 0.65; 95% CI 0.58–0.71). The SA episodes model showed acceptable discrimination (AUC = 0.76, 95% CI 0.70–0.82) and calibration (slope = 0.96). The prognostic performance of the prediction models did not improve in the population of office workers after adding gender.
The SA episodes model accurately predicted the risk of high SA episodes in office workers, but needs further multisite validation and requires a simpler presentation format before it can be used to select high-risk employees for interventions to prevent or reduce SA.
Absenteeism; Forecasting; Generalization; Office workers; Regression prognostics; Sick leave; Transportability
Working women of childbearing age are a vital part of the population. Following childbirth, this group of women can experience a myriad of physical and mental health problems that can interfere with their ability to work. Currently, there is little known about cost-effective post-partum interventions to prevent work disability. The purpose of the study was to evaluate whether supervisor telephone contact (STC) during maternity leave is cost-effective from a societal perspective in reducing sick leave and improving quality-adjusted life years (QALYs) compared to common practice (CP).
We conducted an economic evaluation alongside a randomized controlled trial. QALYs were measured by the EuroQol 5-D, and sick leave and presenteeism by the Health and work Performance Questionnaire. Resource use was collected by questionnaires. Data were analysed according to intention-to-treat. Missing data were imputed via multiple imputation. Uncertainty was estimated by 95% confidence intervals, cost-utility planes and curves, and sensitivity analyses.
541 working women from 15 companies participated. Response rates were above 85% at each measurement moment. At the end of the follow-up, no statistically significant between-group differences in QALYs, mean hours of sick leave or presenteeism or costs were observed. STC was found to be less effective and more costly. For willingness-to-pay levels from €0 through €50,000, the probability that STC was cost-effective compared to CP was 0.2. Overall resource use was low. Mean total costs were €3678 (95% CI: 3386; 3951). Productivity loss costs represented 37% of the total costs and of these costs, 48% was attributable to sick leave and 52% to work presenteeism. The cost analysis from a company's perspective indicated that there was a net cost associated with the STC intervention.
STC was not cost-effective compared to common practice for a healthy population of working mothers; therefore, implementation is not indicated. The cost-utility of STC for working mothers with more severe post-partum health problems, however, needs to be investigated. Work presenteeism accounted for half of the total productivity loss and warrants attention in future studies.
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