Search Filters for Finding Prognostic and Diagnostic Prediction Studies in Medline to Enhance Systematic Reviews

Background: The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter. Methodology/Principal Findings: Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next -using word frequency methods - we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85. Conclusions/Significance: Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studie

A methodological framework to distinguish spectrum effects from spectrum biases and to assess diagnostic and screening test accuracy for patient populations: Application to the Papanicolaou cervical cancer smear test

<p>Abstract</p> <p>Background</p> <p>A spectrum effect was defined as differences in the sensitivity or specificity of a diagnostic test according to the patient's characteristics or disease features. A spectrum effect can lead to a spectrum bias when subgroup variations in sensitivity or specificity also affect the likelihood ratios and thus post-test probabilities. We propose and illustrate a methodological framework to distinguish spectrum effects from spectrum biases.</p> <p>Methods</p> <p>Data were collected for 1781 women having had a cervical smear test and colposcopy followed by biopsy if abnormalities were detected (the reference standard). Logistic models were constructed to evaluate both the sensitivity and specificity, and the likelihood ratios, of the test and to identify factors independently affecting the test's characteristics.</p> <p>Results</p> <p>For both tests, human papillomavirus test, study setting and age affected sensitivity or specificity of the smear test (spectrum effect), but only human papillomavirus test and study setting modified the likelihood ratios (spectrum bias) for clinical reading, whereas only human papillomavirus test and age modified the likelihood ratios (spectrum bias) for "optimized" interpretation.</p> <p>Conclusion</p> <p>Fitting sensitivity, specificity and likelihood ratios simultaneously allows the identification of covariates that independently affect diagnostic or screening test results and distinguishes spectrum effect from spectrum bias. We recommend this approach for the development of new tests, and for reporting test accuracy for different patient populations.</p

Predicting the outcome of conservative treatment with physiotherapy in adults with shoulder pain associated with partial-thickness rotator cuff tears – a prognostic model development study

Model coefficient statistics (DOCX 21 kb

Fertility, pregnancy and delivery in women after biventricular repair for double outlet right ventricle

Objectives: To investigate outcome of pregnancy and fertility in women with double outlet right ventricle (DORV). Methods: Using 2 congenital heart disease registries, 21 female patients with DORV (aged 18-39 years) were retrospectively identified. Detailed recordings of each patient and their completed (>20 weeks gestation) pregnancies were recorded. Results: Overall, 10 patients had 19 pregnancies, including 3 spontaneous miscarriages (16%). During the 16 live birth pregnancies, primarily (serious) noncardiac complications were observed, e.g. premature labor/delivery (n = 7 and n = 3, respectively), small for gestational age (n = 4), preeclampsia (n = 2) and recurrence of congenital heart disease (n = 2). Except for postpartum endocarditis and deterioration of subpulmonary obstruction, only mild cardiac complication pregnancies were recorded. Two women with children reported secondary female infertility. Several menstrual cycle disorders were reported: secondary amenorrhea (n = 4), primary amenorrhea (n = 3) and oligomenorrhea (n = 2). Conclusion: Successful pregnancy in women with DORV is possible. Primarily noncardiac complications were observed and only few (minor) cardiac complications. Infertility and menstrual cycle disorders appear to be more prevalent. Copyrigh

Patient-reported outcomes in the aging population of adults with congenital heart disease: results from APPROACH-IS.

The congenital heart disease (CHD) population now comprises an increasing number of older persons in their 6th decade of life and beyond. We cross-sectionally evaluated patient-reported outcomes (PROs) in persons with CHD aged 60 years or older, and contrasted these with PROs of younger patients aged 40-59 years and 18-39 years. Adjusted for demographic and medical characteristics, patients ≥60 years had a lower Physical Component Summary, higher Mental Component Summary, and lower anxiety (Hospital Anxiety and Depression Scale-Anxiety) scores than patients in the two younger categories. For satisfaction with life, older persons had a higher score than patients aged 40-59 years. Registration: ClinicalTrials.gov NCT02150603

Independent Validation of an Existing Model Enables Prediction of Hearing Loss after Childhood Bacterial Meningitis

Objective: 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. Study design: 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. Results: 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. Conclusions: 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

The Serret-Andoyer Formalism in Rigid-Body Dynamics: I. Symmetries and Perturbations

This paper reviews the Serret-Andoyer (SA) canonical formalism in rigid-body dynamics and presents some new results. As is well known, the problem of unsupported and unperturbed rigid rotator can be reduced. The availability of this reduction is offered by the underlying symmetry, which stems from conservation of the angular momentum and rotational kinetic energy. When a perturbation is turned on, these quantities are no longer preserved. Nonetheless, the language of reduced description remains extremely instrumental even in the perturbed case. We describe the canonical reduction performed by the Serret-Andoyer (SA) method, and discuss its applications to attitude dynamics and to the theory of planetary rotation. Specifically, we consider the case of angular-velocity-dependent torques, and discuss the variation-of-parameters-inherent antinomy between canonicity and osculation. Finally, we address the transformation of the Andoyer variables into the action-angle ones, using the method of Sadov

Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule

AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Prospective Complications Study (n = 1115) were used to develop the prediction rule (development set). Multivariable logistic regression analysis was used to assess the association between potential predictors and progression to microalbuminuria within 7 years. The performance of the prediction rule was assessed with calibration and discrimination (concordance statistic [c-statistic]) measures. The rule was validated in three other diabetes studies (Pittsburgh Epidemiology of Diabetes Complications [EDC] study, Finnish Diabetic Nephropathy [FinnDiane] study and Coronary Artery Calcification in Type 1 Diabetes [CACTI] study). RESULTS: Of patients in the development set, 13% were microalbuminuric after 7 years. Glycosylated haemoglobin, AER, WHR, BMI and ever smoking were found to be the most important predictors. A high-risk group (n = 87 [8%]) was identified with a risk of progression to microalbuminuria of 32%. Predictions showed reasonable discriminative ability, with c-statistic of 0.71. The rule showed good calibration and discrimination in EDC, FinnDiane and CACTI (c-statistic 0.71, 0.79 and 0.79, respectively). CONCLUSIONS/INTERPRETATION: We developed and validated a clinical prediction rule that uses relatively easily obtainable patient characteristics to predict microalbuminuria in patients with type 1 diabetes. This rule can help clinicians to decide on more frequent check-ups for patients at high risk of microalbuminuria in order to prevent long-term chronic complication