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Relevant bibliographies by topics / Multicenter validation

Academic literature on the topic 'Multicenter validation'

Author: Grafiati

Published: 1 June 2024

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Contents

Journal articles
Dissertations / Theses
Book chapters
Conference papers

Journal articles on the topic "Multicenter validation":

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Koehler, John J., Stuart A. Malafa, Jeffrey Hillesland, Lawrence J. Baer, Ralph N. Rogers, Nancy R. Navitskas, Deborah Briggs, et al. "A multicenter validation of the prehospital index." Annals of Emergency Medicine 16, no. 4 (April 1987): 380–85. http://dx.doi.org/10.1016/s0196-0644(87)80354-2.

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Pelletier-Galarneau, M., O. O. Sogbein, X. Pham, J. Hao, J. Le, M. D. Strober, M. L. Middleton, J. Kikut, L. M. Freeman, and L. S. Zuckier. "Multicenter Validation of a Shortened Gastric-Emptying Protocol." Journal of Nuclear Medicine 56, no. 6 (April 16, 2015): 873–76. http://dx.doi.org/10.2967/jnumed.115.155366.

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Bergeron, David, Kelsey Flynn, Louis Verret, Stéphane Poulin, Rémi W. Bouchard, Christian Bocti, Tamàs Fülöp, et al. "Multicenter Validation of an MMSE-MoCA Conversion Table." Journal of the American Geriatrics Society 65, no. 5 (February 15, 2017): 1067–72. http://dx.doi.org/10.1111/jgs.14779.

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Staartjes, Victor E., Carlo Serra, Matteo Zoli, Diego Mazzatenta, Fabio Pozzi, Davide Locatelli, Elena D’Avella, Domenico Solari, Luigi Maria Cavallo, and Luca Regli. "Multicenter external validation of the Zurich Pituitary Score." Acta Neurochirurgica 162, no. 6 (March 14, 2020): 1287–95. http://dx.doi.org/10.1007/s00701-020-04286-w.

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Barry, Jeremy A., Rima Ait-Belkacem, William M. Hardesty, Lydia Benakli, Clara Andonian, Hermes Licea-Perez, Jonathan Stauber, and Stephen Castellino. "Multicenter Validation Study of Quantitative Imaging Mass Spectrometry." Analytical Chemistry 91, no. 9 (April 2, 2019): 6266–74. http://dx.doi.org/10.1021/acs.analchem.9b01016.

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Chen, Xiaolin. "313 Development and Validation of a Scoring System for Hemorrhage Risk in Brain Arteriovenous Malformations." Neurosurgery 70, Supplement_1 (April 2024): 91. http://dx.doi.org/10.1227/neu.0000000000002809_313.

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Abstract:

INTRODUCTION: The dilemma between natural rupture risk and adverse outcomes of intervention is of major concern for patients with unruptured arteriovenous malformations (AVMs). The existing risk score for AVM rupture includes factors that are controversial and lacks prospective validation. METHODS: This prognostic study developed a prediction model derived from a single-center cohort (derivation cohort) and validated in a multicenter external validation cohort and a conservative treatment validation cohort. Patients were recruited from a nationwide multicenter prospective collaboration registry in China. A total of 4135 patients were enrolled. 3962 patients were included (3585 in the derivation cohort and 377 in the multicenter external validation cohort); 1028 patients from the derivation cohort who had time-to-event data and prerupture imaging results were included in the conservative treatment validation cohort. RESULTS: Four risk factors were used to develop the scoring system: ventricular system involvement, venous aneurysm, deep location, and exclusively deep drainage (VALE). The VALE scoring system performed well in all 3 cohorts, with areas under the receiver operating characteristic curve of 0.77 (95% CI, 0.75-0.78) in the derivation cohort, 0.85 (95% CI, 0.81-0.89) in the multicenter external validation cohort, and 0.73 (95% CI, 0.65-0.81) in the conservative treatment validation cohort. The 10-year hemorrhage-free rate was 95.5% (95% CI, 87.1%-100%) in the low-risk group, 92.8% (95% CI, 88.8%-97.0%) in the moderate-risk group, and 75.8% (95% CI, 65.1%-88.3%) in the high-risk group; the model discrimination was significant when comparing these rates between the high-risk group and the low- and moderate-risk groups (p < .001 for both comparisons). CONCLUSIONS: In this prognostic study, the VALE scoring system was developed to distinguish rupture risk among patients with AVMs. The stratification of unruptured AVMs may enable patients with low risk of rupture to avoid unnecessary interventions.

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Lafage, Virginie, Neil J. Bharucha, Frank Schwab, Robert A. Hart, Douglas Burton, Oheneba Boachie-Adjei, Justin S. Smith, et al. "Multicenter validation of a formula predicting postoperative spinopelvic alignment." Journal of Neurosurgery: Spine 16, no. 1 (January 2012): 15–21. http://dx.doi.org/10.3171/2011.8.spine11272.

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Object Sagittal spinopelvic imbalance is a major contributor to pain and disability for patients with adult spinal deformity (ASD). Preoperative planning is essential for pedicle subtraction osteotomy (PSO) candidates; however, current methods are often inaccurate because no formula to date predicts both postoperative sagittal balance and pelvic alignment. The authors of this study aimed to evaluate the accuracy of 2 novel formulas in predicting postoperative spinopelvic alignment after PSO. Methods This study is a multicenter retrospective consecutive PSO case series. Adults with spinal deformity (> 21 years old) who were treated with a single-level lumbar PSO for sagittal imbalance were evaluated. All patients underwent preoperative and a minimum of 6-month postoperative radiography. Two novel formulas were used to predict the postoperative spinopelvic alignment. The results predicted by the formulas were then compared with the actual postoperative radiographic values, and the formulas' ability to identify successful (sagittal vertical axis [SVA] ≤ 50 mm and pelvic tilt [PT] ≤ 25°) and unsuccessful (SVA > 50 mm or PT > 25°) outcomes was evaluated. Results Ninety-nine patients met inclusion criteria. The median absolute error between the predicted and actual PT was 4.1° (interquartile range 2.0°–6.4°). The median absolute error between the predicted and actual SVA was 27 mm (interquartile range 11–47 mm). Forty-one of 54 patients with a formula that predicted a successful outcome had a successful outcome as shown by radiography (positive predictive value = 0.76). Forty-four of 45 patients with a formula that predicted an unsuccessful outcome had an unsuccessful outcome as shown by radiography (negative predictive value = 0.98). Conclusions The spinopelvic alignment formulas were accurate when predicting unsuccessful outcomes but less reliable when predicting successful outcomes. The preoperative surgical plan should be altered if an unsuccessful result is predicted. However, even after obtaining a predicted successful outcome, surgeons should ensure that the predicted values are not too close to unsuccessful values and should identify other variables that may affect alignment. In the near future, it is anticipated that the use of these formulas will lead to better surgical planning and improved outcomes for patients with complex ASD.

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Stiell, I. G. "Multicenter Prospective Validation of the Canadian CT Head Rule." Academic Emergency Medicine 10, no. 5 (May 1, 2003): 539—a—539. http://dx.doi.org/10.1197/aemj.10.5.539-a.

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Stiell, I. G. "Multicenter Prospective Validation of the Canadian C-Spine Rule." Academic Emergency Medicine 9, no. 5 (May 1, 2002): 359—b—360. http://dx.doi.org/10.1197/aemj.9.5.359-b.

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Domeier, Robert M., Robert A. Swor, Rawden W. Evans, J. Brian Hancock, William Fales, Jon Krohmer, Shirley M. Frederiksen, Edgardo J. Rivera-Rivera, and M. Anthony Schork. "Multicenter Prospective Validation of Prehospital Clinical Spinal Clearance Criteria." Journal of Trauma: Injury, Infection, and Critical Care 53, no. 4 (October 2002): 744–50. http://dx.doi.org/10.1097/00005373-200210000-00021.

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More sources

Dissertations / Theses on the topic "Multicenter validation":

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FALOPPI, LUCA. "MULTICENTER PROSPECTIVE STUDY OF ANGIOGENESIS POLYMORPHISM VALIDATION IN HCC PATIENTS TREATED WITH SORAFENIB: THE INNOVATE STUDY." Doctoral thesis, Università degli Studi di Cagliari, 2019. http://hdl.handle.net/11584/270329.

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Sorafenib represents the standard of care for advanced hepatocellular carcinoma (HCC). However, molecular predictors of sorafenib efficacy have not yet been identified. In retrospective studies, conducted on different HCC patients treated with sorafenib, polymorphisms (SNPs) of major genes involved in the angiogenic process (eNOS, Ang2, VEGF, VEGFR, HIF-1α) showed to be able to predict the clinical outcome in these series. On the basis of these preliminary results, our aim was to validate in a prospective study these data in patients with advanced HCC patients treated with sorafenib (INNOVATE study, NCT02786342). 182 patients were enrolled in the study and they were treated with sorafenib between March 2015 and June 2018, 17 did not fulfil the inclusion criteria and they were considered screening failure. Out of the 165 patients who met the selection criteria, 114 patients were dead and 127 had progressed after a median follow-up time of 25.9 months at the time of database lock in February 2019. We present the results of the first part of the analyses planned, regarding eNOS and Ang2 (SNPs). We analyzed eNOS 786 T>C and Ang2 rs55633437 G>T by Real Time PCR method or by direct sequencing in relation to the primary end point (PFS). Event-time distributions were estimated using the Kaplan-Meier method and survival curves were compared using the log-rank test. The main characteristics of these patients are: Child–Pugh (CP) class-A was the most represented (91.9%), 65.7% had BCLC-C stage disease and 24.1% of patients had α-fetoprotein (AFP) level >400 ng/ml. The most common underlying aetiology was hepatitis infections from C virus (39.3%) and others aetiologies (23.3%). Median PFS was 5.2 months (95% CI 4.5-6.5) and median OS was 13.1 months (95% CI 10.4-15.7). At univariate analysis, we confirmed that eNOS 786 TT genotype was significantly associated with a lower median PFS (2.4 vs 5.9 months, HR 0.43, 95% CI 0.26-0.70 p=0.0007) and OS (8.1 vs 15.7 months, HR 0.38, 95% CI 0.24-0.60 p<0.0001) than the other genotypes. At univariate analysis, we not confirmed that Ang2 rs55633437 TT+GT genotypes were significantly associated with a lower median PFS (2.4 vs 5.7 months, HR 1.93, 95% CI 0.91-4.07 p=0.0833) and OS (15.1 vs 13.0 months, HR 2.68, 95% CI 1.67-4.29 p=0.55) than the other genotype. No significant association was found between the main clinical-pathologic patients characteristics and eNOS polymorphisms. Following adjustment for clinical covariates (Gender, Child Pugh, Portal Vein Thrombosis, LDH, aetiology and eNOS), multivariate analysis confirmed eNOS as only independent prognostic factor predicting survival. Conclusions: Our Italian multicenter, prospective study confirmed that eNOS-786 TT genotype may be capable of identifying a subset of HCC patients who have a lower median OS and PFS than the other genotypes. For the first time in ten years of sorafenib research our study confirms the prognostic role of a biological marker in a prospective study.

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Kim, Eun Young. "Machine-learning based automated segmentation tool development for large-scale multicenter MRI data analysis." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/4998.

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Background: Volumetric analysis of brain structures from structural Mag- netic Resonance (MR) images advances the understanding of the brain by providing means to study brain morphometric changes quantitatively along aging, development, and disease status. Due to the recent increased emphasis on large-scale multicenter brain MR study design, the demand for an automated brain MRI processing tool has increased as well. This dissertation describes an automatic segmentation framework for subcortical structures of brain MRI that is robust for a wide variety of MR data. Method: The proposed segmentation framework, BRAINSCut, is an inte- gration of robust data standardization techniques and machine-learning approaches. First, a robust multi-modal pre-processing tool for automated registration, bias cor- rection, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. The segmentation framework was then constructed to achieve robustness for large-scale data via the following comparative experiments: 1) Find the best machine-learning algorithm among several available approaches in the field. 2) Find an efficient intensity normalization technique for the proposed region-specific localized normalization with a choice of robust statistics. 3) Find high quality features that best characterize the MR brain subcortical structures. Our tool is built upon 32 handpicked multi-modal muticenter MR images with man- ual traces of six subcortical structures (nucleus accumben, caudate nucleus, globus pallidum, putamen, thalamus, and hippocampus) from three experts. A fundamental task associated with brain MR image segmentation for re- search and clinical trials is the validation of segmentation accuracy. This dissertation evaluated the proposed segmentation framework in terms of validity and reliability. Three groups of data were employed for the various evaluation aspects: 1) traveling human phantom data for the multicenter reliability, 2) a set of repeated scans for the measurement stability across various disease statuses, and 3) a large-scale data from Huntington's disease (HD) study for software robustness as well as segmentation accuracy. Result: Segmentation accuracy of six subcortical structures was improved with 1) the bias-corrected inputs, 2) the two region-specific intensity normalization strategies and 3) the random forest machine-learning algorithm with the selected feature-enhanced image. The analysis of traveling human phantom data showed no center-specific bias in volume measurements from BRAINSCut. The repeated mea- sure reliability of the most of structures also displayed no specific association to disease progression except for caudate nucleus from the group of high risk for HD. The constructed segmentation framework was successfully applied on multicenter MR data from PREDICT-HD [133] study ( < 10% failure rate over 3000 scan sessions pro- cessed). Conclusion: Random-forest based segmentation method is effective and robust to large-scale multicenter data variation, especially with a proper choice of the intensity normalization techniques. Benefits of proper normalization approaches are more apparent compared to the custom set of feature-enhanced images for the ccuracy and robustness of the segmentation tool. BRAINSCut effectively produced subcortical volumetric measurements that are robust to center and disease status with validity confirmed by human experts and low failure rate from large-scale multicenter MR data. Sample size estimation, which is crutial for designing efficient clinical and research trials, is provided based on our experiments for six subcortical structures.

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Jaouen, Tristan. "Caractérisation du cancer de la prostate de haut grade à l’IRM multiparamétrique à l’aide d’un système de diagnostic assisté par ordinateur basé sur la radiomique et utilisé comme lecteur autonome ou comme second lecteur." Electronic Thesis or Diss., Lyon, 2022. http://www.theses.fr/2022LYSE1140.

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Abstract:

Nous avons développé un système de diagnostic assisté par ordinateur (CAD) basé sur des régions d'intérêt pour caractériser le cancer de la prostate avec un grade de l'International Society of Urological Pathology (ISUP) ≥2 lors d'une IRM multiparamétrique (IRM-mp). Les paramètres de l'image provenant de 2 jeux de données multi-constructeurs de 265 IRM pré-prostatectomie et 112 IRM pré-biopsie ont été combinés en utilisant la régression logistique. Les meilleurs modèles contenaient le 2e percentile d’ADC (ADC2) et le taux de rehaussement normalisé (WI) dans la zone périphérique (ZP) et le 25e percentile d'ADC (ADC25) dans la zone de transition (ZT). Ils ont été associés dans le système CAD. Le CAD a été évalué rétrospectivement sur 2 jeux de données multi-constructeurs contenant respectivement 158 et 105 IRM pré-biopsie de notre institution (test interne) et d'une autre institution (test externe). Deux radiologues ont indépendamment décrit les lésions ciblées par la biopsie. Le score PI-RADSv2 (Prostate Imaging-Reporting and Data System version 2) attribué prospectivement lors de la biopsie et le score CAD ont été comparés aux résultats de la biopsie. A l’échelle des patients, les aires sous la courbe Receiver Operating Characteristic (AUC) du score PI-RADSv2 étaient de 82% (IC 95% : 74-87) et 85% (IC 95% : 79-91) dans les jeux de données de test interne et externe respectivement. Pour les deux radiologues, le score CAD avait des AUC similaires dans les jeux de données interne (82%, IC 95% : 76-89, p=1 ; 84%, IC 95% : 78-91, p=1) et externe (82%, IC 95% : 76-89, p=0.82 ; 86%, IC 95% : 79-93, p=1). La combinaison du PI-RADSv2 et du CAD aurait pu éviter 41 à 52% des biopsies tout en manquant 6 à 10% des cancers ISUP≥2. Le système CAD a confirmé sa robustesse dans une étude multicentrique impliquant 22 scanners et des protocoles d'imagerie très hétérogènes. Dans l'analyse par patient, le CAD et le PI-RADSv2 avaient des performances similaires en termes d’AUC (76%, IC 95% : 70-82 contre 79%, IC 95% : 73-86 ; p=0.34) et de sensibilité (86%, IC 95% : 76-96 contre 89%, IC 95% : 79-98 pour le PI-RADSv2≥4). La spécificité du CAD (62%, IC 95% : 53-70 contre 49% ; IC 95% : 39-59 pour le PI-RADSv2≥4) permettait une complémentarité avec le score PI-RADSv2 pour potentiellement éviter 50% des biopsies, tout en manquant 13% des cancers ISUP≥2. Ces résultats étaient similaires à ceux rapportés dans les cohortes de test issues d’un unique centre et ont ouvert la voie à de nouvelles applications du CAD. Le CAD a d’abord permis une bonne discrimination des cancers ISUP≥2 chez des patients placés en surveillance active. Son AUC (80% ; IC 95% : 74-86) était similaire à celle du score PI-RADSv2 attribué prospectivement par des uro-radiologues spécialisés (81%, IC 95% : 74-87 ; p=0.96). Le CAD était plus spécifique que les scores PI-RADS≥3 (p<0.001) et PI-RADS≥4 (p<0.001). Il pourrait offrir une solution pour sélectionner les patients pouvant éviter sans risque une biopsie de confirmation ou de suivi dans le cadre de leur surveillance active (25%). Il manquerait alors 5% des cancers ISUP≥2. Le CAD a enfin été confronté aux IRM-mp pré-prostatectomie de 56 patients japonais, issus d’une population qui est géographiquement éloignée de sa population d’entraînement et qui intéresse de par ses faibles taux d’incidence et de mortalité du cancer de la prostate. Son AUC était alors similaire au score PI-RADSv2 attribué par un radiologue expérimenté dans la ZP (80%, IC 95% : 71-90 contre 80%, IC 95% : 71-89 ; p=0.886) et dans la ZT (79%, IC 95% : 66-90 contre 93%, 95%CI : 82-96 ; p=0.051). Ces résultats prometteurs et robustes sur des jeux de données hétérogènes suggèrent que le CAD pourrait être utilisée dans la routine clinique quotidienne comme un second lecteur pour aider à sélectionner les patients pouvant éviter la biopsie en toute sécurité. Ce CAD pourrait aider les lecteurs moins expérimentés à caractériser les lésions de la prostate
We developed a region of interest-based (ROIs) computer-aided diagnosis system (CAD) to characterize International Society of Urological Pathology grade (ISUP) ≥2 prostate cancers at multiparametric MRI (mp-MRI). Image parameters from two multi-vendor datasets of 265 pre-prostatectomy and 112 pre-biopsy MRIs were combined using logistic regression. The best models used the ADC 2nd percentile (ADC2) and normalized wash-in rate (WI) in the peripheral zone (PZ) and the ADC 25th percentile (ADC25) in the transition zone (TZ). They were combined in the CAD system. The CAD was retrospectively assessed on two multi-vendor datasets containing respectively 158 and 105 pre-biopsy MRIs from our institution (internal test dataset) and another institution (external test dataset). Two radiologists independently outlined lesions targeted at biopsy. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) score prospectively assigned at biopsy and the CAD score were compared to biopsy findings. At patient level, the areas under the Receiver Operating Characteristic curve (AUC) of the PI-RADSv2 score were 82% (95% CI: 74-87) and 85% (95% CI: 79-91) in the internal and external test datasets respectively. For both radiologists, the CAD score had similar AUC results in the internal (82%, 95% CI: 76-89, p=1; 84%, 95% CI: 78-91, p=1) and external (82%, 95% CI: 76-89, p=0.82; 86%, 95% CI: 79-93, p=1) test datasets. Combining PI-RADSv2 and CAD findings could have avoided 41-52% of biopsies while missing 6-10% of ISUP≥2 cancers. The CAD system confirmed its robustness showing good discrimination of ISUP ≥2 cancers in a multicentric study involving 22 different scanners with highly heterogeneous image protocols. In per patient analysis, the CAD and the PI-RADSv2 had similar AUC values (76%, 95% CI: 70-82 vs 79%, 95% CI: 73-86; p=0.34) and sensitivities (86%, 95% CI: 76-96 vs 89%, 95% CI: 79-98 for PI-RADSv2 ≥4). The specificity of the CAD (62%, 95% CI: 53-70 vs 49%, 95% CI: 39-59 for PI-RADSv2 ≥4) could be used to complement the PI-RADSv2 score and potentially avoid 50% of biopsies, while missing 13% of ISUP ≥2 cancers. These findings were very similar to those reported in the single center test cohorts. Given its robustness, the CAD could then be exploited in more specific applications. The CAD first provided good discrimination of ISUP ≥2 cancers in patients under Active Surveillance. Its AUC (80%, 95% CI: 74-86) was similar to that of the PI-RADS score prospectively assigned by specialized uro-radiologists at the time of biopsy (81%, 95% CI: 74-87; p=0.96). After dichotomization, the CAD was more specific than the PI-RADS ≥3 (p<0.001) and the PI-RADS ≥4 scores (p<0.001). It could offer a solution to select patients who could safely avoid confirmatory or follow-up biopsy during Active Surveillance (25%), while missing 5% of ISUP≥2 cancers. Finally, the CAD was tested with the pre-prostatectomy mp-MRIs of 56 Japanese patients, from a population which is geographically distant from its training population and which is of interest because of its low prostate cancer incidence and mortality. The CAD obtained an AUC similar to the PI-RADSv2 score assigned by an experience radiologist in the PZ (80%, 95% CI: 71-90 vs 80%, 95% CI: 71-89; p=0.886) and in the TZ (79%, 95% CI: 66-90 vs 93%, 95%CI: 82-96; p=0.051). These promising and robust results across heterogeneous datasets suggest that the CAD could be used in clinical routine as a second opinion reader to help select the patients who could safely avoid biopsy. This CAD may assist less experience readers in the characterization of prostate lesions

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O'Gorman, Neil Matthew. "Development of a first trimester prediction model for preeclampsia and prospective validation in a multicentre setting." Thesis, King's College London (University of London), 2018. https://kclpure.kcl.ac.uk/portal/en/theses/development-of-a-first-trimester-prediction-model-for-preeclampsia-and-prospective-validation-in-a-multicentre-setting(6dfb8db3-cd42-4847-839e-59a7ab597864).html.

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Preeclampsia affects 2-3% of all pregnancies and is a major cause of maternal and perinatal morbidity and mortality. In the last ten years, extensive research has been devoted to screening for preeclampsia with the aim of reducing the prevalence of the disease through pharmacologic intervention in the high-risk group and to minimize perinatal morbidity and mortality by tailoring antenatal care accordingly to determine the appropriate time and place for delivery. The purpose of this study was to develop a first trimester screening model for preeclampsia combining a variety of elements from the maternal demographic characteristics and medical history with biophysical and biochemical markers. This model was subsequently prospectively validated on a new dataset. The efficacy of the developed screening model was then compared to the first trimester approaches to screening recommended by the National Institute for Health and Care Excellence and the American College of Obstetricians and Gynecologists. The material covered in this thesis was published in three papers in peer reviewed journals. The first publication involved using data from 35,948 singleton pregnancies that included 1,058 preeclamptic pregnancies (2.9%). Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of uterine artery pulsatility index, mean arterial pressure, serum pregnancy-associated plasma protein-A, and placental growth factor multiple of the median values. Five-fold cross validation was used to assess the performance of screening for preeclampsia in pregnant women that delivered at < 37 weeks’ gestation and ≥37 weeks’ gestation by models that combined maternal factors with individual biomarkers and their combination with screening by maternal factors alone In pregnancies that experienced preeclampsia, the values of uterine artery PI and mean arterial pressure were increased, and the values of serum pregnancy-associated plasma protein-A and placental growth factor were decreased. For all biomarkers, the deviation from normal was greater for early than late preeclampsia; therefore, the performance of screening was related inversely to the gestational age at which delivery became necessary for maternal and/or fetal indications. Combined screening by maternal factors, uterine artery PI, mean arterial pressure, and placental growth factor predicted 75%, of preeclampsia < 37 weeks and 47% preeclampsia ≥37 weeks’ gestation, at a false positive rate of 10%. The second study examined the diagnostic accuracy of the above model in a prospective first-trimester multicentre study of screening for preeclampsia in 8775 singleton pregnancies. The detection rates (DRs) and false-positive rates (FPRs) for delivery with preeclampsia < 32, < 37 and ≥37 weeks’ gestation were estimated and compared with those for the dataset used for development of the algorithm. In this study population, 239 (2.7%) cases developed PE, of which 17 (0.2%), 59 (0.7%) and 180 (2.1%) developed preeclampsia < 32, < 37 and ≥37 weeks’ gestation, respectively. With combined screening using the above model, the DR was 100% for preeclampsia < 32 weeks, 75% for preeclampsia < 37 weeks and 43% for PE ≥37 weeks, at a 10% FPR. These DRs were similar to the estimated rates for the dataset used for development of the model: 89% for preeclampsia < 32 weeks, 75% for PE < 37 weeks and 47% for PE ≥37 weeks. The third component of this thesis was to compare the performance of screening for preeclampsia based on risk factors from the medical history, as recommended by NICE and ACOG, with our model developed in the first study. Screening with use of NICE guidelines detected 41% of preeclampsia at < 32 weeks, 39% of PE at < 37 weeks and 34% of PE at ≥37 weeks, at 10.2% FPR. Screening with use of ACOG recommendations detected 94% of PE at < 32 weeks, 90% of PE at < 37 weeks and 89% ≥37 weeks, at 64.2% FPR. Screening based on the ACOG recommendations for use of aspirin only detected 6% of PE at < 32 weeks, 5% of PE at < 37 weeks and 2% of PE at ≥37 weeks, at a 0.2% FPR. The findings of these studies demonstrate that a combination of maternal factors, biophysical and biochemical markers can effectively identify women at high-risk of developing early preeclampsia and that the model developed in this study performs better than the screening approaches recommended by NICE and ACOG.

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Biesenberger, Simon [Verfasser]. "Prospektive, kontrollierte Multicenter-Studie zur Validation des Sentinel-Node-Konzeptes beim Mammakarzinom / Simon Biesenberger." 2005. http://d-nb.info/995009252/34.

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Linhares, Daniela Vilas Boas Rosa. "Validation of Control of Allergic Rhinitis and Asthma Test for Children (CARATKids) - a prospective multicenter study." Master's thesis, 2014. https://repositorio-aberto.up.pt/handle/10216/72911.

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Linhares, Daniela Vilas Boas Rosa. "Validation of Control of Allergic Rhinitis and Asthma Test for Children (CARATKids) - a prospective multicenter study." Dissertação, 2014. https://repositorio-aberto.up.pt/handle/10216/72911.

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Book chapters on the topic "Multicenter validation":

1

Calderon-Ortiz, Mauricio, Matthew D. Rifkin, Daniel H. O’Leary, James F. Toole, M. Gene Bond, Fred A. Bryan, Tarle Holen, et al. "Multicenter Validation Study of Real Time (B Mode) Ultrasound, Arteriography, and Pathology: I. Methods and Materials." In Pathobiology of the Human Atherosclerotic Plaque, 733–49. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3326-8_49.

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O’Leary, Daniel H., Fred A. Bryan, Marta W. Goodison, Barry B. Goldberg, Raymond Gramiak, Marshall Ball, M. Gene Bond, et al. "Multicenter Validation Study of Real Time (B Mode) Ultrasound, Arteriography, and Pathology: II. Repeatability/Variability Assessment." In Pathobiology of the Human Atherosclerotic Plaque, 751–66. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3326-8_50.

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Ricotta, John J., Fred A. Bryan, M. Gene Bond, Alfred Kurtz, Daniel H. O’Leary, Jeffery K. Raines, Alan S. Berson, et al. "Multicenter Validation Study of Real Time (B Mode) Ultrasound, Arteriography, and Pathology: III. Sensitivity and Specificity Assessment." In Pathobiology of the Human Atherosclerotic Plaque, 767–83. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3326-8_51.

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Schenk, Eric A., John Ricotta, M. Gene Bond, Thomas Aretz, Jean Angelo, Hong Y. Choi, Thomas Rinalski, et al. "Multicenter Validation Study of Real Time (B Mode) Ultrasound, Arteriography, and Pathology: V. Pathologic Evaluation of Endarteroctomy Specimens and of Perfusion Fixed Carotid Arteries." In Pathobiology of the Human Atherosclerotic Plaque, 799–809. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3326-8_53.

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Smullens, S. N., J. K. Raines, D. H. O’Leary, M. Ball, J. J. Ricotta, N. F. Gustafson, M. G. Bond, et al. "Multicenter Validation Study of Real Time (B Mode) Ultrasound, Arteriography, and Pathology: IV. Comparison of B Mode Ultrasonic Imaging with Arteriography in Lower Extremity Arteries." In Pathobiology of the Human Atherosclerotic Plaque, 785–97. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3326-8_52.

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"The Saline vs. Albumin Fluid Evaluation (SAFE) Study." In 50 Studies Every Anesthesiologist Should Know, edited by Anita Gupta, Elena N. Gutman, Michael E. Hochman, Anita Gupta, Elena N. Gutman, and Michael E. Hochman, 125–30. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190237691.003.0024.

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Abstract:

This case focuses on studying the effects of albumin and saline fluid evaluations by asking the question: What is the effect of fluid resuscitation with albumin or saline on outcomes in the intensive care unit (ICU)? This large, multicenter, prospective, randomized, double-blind trial failed to demonstrate a benefit of albumin vs. crystalloid solution for resuscitation in the ICU. These findings are consistent with other studies. Post hoc analyses from the SAFE Study have, however, suggested certain patient subgroups that may benefit from receiving saline over albumin (severe brain injury patients) and albumin over saline (severe sepsis patients). These findings require further validation, however.

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Di Meco, Gabriele, Sara Mora, Daniele Roberto Giacobbe, Silvia Dettori, Ilias Karaiskos, Matteo Bassetti, and Mauro Giacomini. "A Wide Database for a Multicenter Study on Pneumocystis jirovecii Pneumonia in Intensive Care Units." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220521.

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Abstract:

Pneumocystis jirovecii pneumonia (PJP) is an opportunistic fungal infection that may affect patients with immunosuppression. In order to improve the diagnosis accuracy for PJP, facilitating the collection of data across Europe to reliably assess the performance of diagnostic tests for PJP is essential to improve the care of critically ill patients developing this severe condition. Such large data can be collected thanks to the contribution of several European hospitals in the compilation of a dedicated electronic Case Report Form (eCRF). The main focus of this work is to create an interface with high ergonomics both in the compilation and in the subsequent validation of the records.

Conference papers on the topic "Multicenter validation":

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Kobylarz Ribeiro, Jhonatan, Henrique D. P. dos Santos, Felipe Barletta, Mateus Cichelero da Silva, Renata Vieira, Hugo M. P. Morales, and Cristian da Costa Rocha. "A Machine Learning Early Warning System: Multicenter Validation in Brazilian Hospitals." In 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2020. http://dx.doi.org/10.1109/cbms49503.2020.00067.

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Cardenas, Diego, José Ferreira Junior, Ramon Moreno, Marina Rebelo, José Krieger, and Marco Gutierrez. "Multicenter Validation of Convolutional Neural Networks for Automated Detection of Cardiomegaly on Chest Radiographs." In Anais Principais do Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/sbcas.2020.11512.

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This work focused on validating five convolutional neural network models to detect automatically cardiomegaly, a health complication that causes heart enlargement, which may lead to cardiac arrest. To do that, we trained the models with a customized multilayer perceptron. Radiographs from two public datasets were used in experiments, one of them only for external validation. Images were pre-processed to contain just the chest cavity. The EfficientNet model yielded the highest area under the curve (AUC) of 0.91 on the test set. However, the Inception-based model obtained the best generalization performance with AUC of 0.88 on the independent multicentric dataset. Therefore, this work accurately validated radiographic models to identify patients with cardiomegaly.

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Fernandez, Rafael, Jose Manuel Serrano, Isabel Umaran, Ricard Abizanda, Andres Carrillo, Maria Jesus Lopez-Pueyo, Pedro Rascado, Begoña Balerdi, Borja Suberviola, and Gonzalo Hernandez. "Ward Mortality After ICU discharge: a Multicenter validation Of The Sabadell Score." In American Thoracic Society 2010 International Conference, May 14-19, 2010 • New Orleans. American Thoracic Society, 2010. http://dx.doi.org/10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a4091.

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Ceccato, Adrian, Raul Mendez, Maria-Carmen De La Torre, Albert Gabarrus, Elena Prina, Otavio Ranzani, Cristina Dominedò, et al. "PES Score validation in a multicenter Cohort of patients with community-acquired pneumonia." In ERS International Congress 2019 abstracts. European Respiratory Society, 2019. http://dx.doi.org/10.1183/13993003.congress-2019.oa3305.

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Garbe, A., Mahajan UM, T. Kohlmann, E. Goni, C. Budde, F. Gorelick, T. Muniraj, et al. "Chronic Pancreatitis Prognosis Score (COPPS): results from an international prospective multicenter validation study." In Viszeralmedizin 2021 Gemeinsame Jahrestagung Deutsche Gesellschaft für Gastroenterologie, Verdauungs- und Stoffwechselkrankheiten (DGVS), Sektion Endoskopie der DGVS, Deutsche Gesellschaft für Allgemein und Viszeralchirurgie (DGAV). Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1733581.

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Garbe, A., Mahajan UM, T. Kohlmann, E. Goni, C. Budde, F. Gorelick, T. Muniraj, et al. "Chronic Pancreatitis Prognosis Score (COPPS): results from an international prospective multicenter validation study." In Viszeralmedizin 2021 Gemeinsame Jahrestagung Deutsche Gesellschaft für Gastroenterologie, Verdauungs- und Stoffwechselkrankheiten (DGVS), Sektion Endoskopie der DGVS, Deutsche Gesellschaft für Allgemein und Viszeralchirurgie (DGAV). Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1733581.

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Frazzoni, L., L. Laterza, C. Fabbri, M. Di Marco, H. Bertani, R. Conigliaro, A. Mussetto, et al. "Clinical validation of priority criteria for indication to colonoscopy: a multicenter prospective study." In ESGE Days 2024. Georg Thieme Verlag KG, 2024. http://dx.doi.org/10.1055/s-0044-1782795.

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Garbe, A., UM Mahajan, T. Kohlmann, E. Goni, C. Budde, E. Martinez-Moneo, T. Shimosegawa, et al. "Chronic Pancreatitis Prognosis Score (COPPS): preliminary results from a prospective multicenter, international validation study." In Viszeralmedizin 2019. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1695211.

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Morand, Eric, Vera Golder, Rangi Kandane-Rathnayake, Molla Huq, Hieu Nim, Worawit Louthrenoo, Shue Fen Luo, et al. "25 Prospective multicenter validation of the lupus low disease activity state (LLDAS) treatment target." In 13th International Congress on Systemic Lupus Erythematosus (LUPUS 2019), San Francisco, California, USA, April 5–8, 2019, Abstract Presentations. Lupus Foundation of America, 2019. http://dx.doi.org/10.1136/lupus-2019-lsm.25.

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Peivandi, A., G. Santarpino, G. Nasso, M. Avolio, M. Tanzariello, L. Giuliano, G. Speziale, and A. Dell 'Aquila. "Multicenter Validation of ACEF II Risk Score: A Reliable Predictive Instrument for CABG Patients." In 51st Annual Meeting of the German Society for Thoracic and Cardiovascular Surgery (DGTHG). Georg Thieme Verlag KG, 2022. http://dx.doi.org/10.1055/s-0042-1742796.

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