138 research outputs found

    Validation and comparison of 28 risk prediction models for coronary artery disease

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    Aims Risk prediction models (RPMs) for coronary artery disease (CAD), using variables to calculate CAD risk, are potentially valuable tools in prevention strategies. However, their use in the clinical practice is limited by a lack of poor model description, external validation, and head-to-head comparisons. Methods and results CAD RPMs were identified through Tufts PACE CPM Registry and a systematic PubMed search. Every RPM was externally validated in the three cohorts (the UK Biobank, LifeLines, and PREVEND studies) for the primary endpoint myocardial infarction (MI) and secondary endpoint CAD, consisting of MI, percutaneous coronary intervention, and coronary artery bypass grafting. Model discrimination (C-index), calibration (intercept and regression slope), and accuracy (Brier score) were assessed and compared head-to-head between RPMs. Linear regression analysis was performed to evaluate predictive factors to estimate calibration ability of an RPM. Eleven articles containing 28 CAD RPMs were included. No single best-performing RPM could be identified across all cohorts and outcomes. Most RPMs yielded fair discrimination ability: mean C-index of RPMs was 0.706 +/- 0.049, 0.778 +/- 0.097, and 0.729 +/- 0.074 (P < 0.01) for prediction of MI in UK Biobank, LifeLines, and PREVEND, respectively. Endpoint incidence in the original development cohorts was identified as a significant predictor for external validation performance. Conclusion Performance of CAD RPMs was comparable upon validation in three large cohorts, based on which no specific RPM can be recommended for predicting CAD risk

    A Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis analysis to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy:A systematic review

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    BACKGROUND: Postoperative pancreatic fistula is a frequent and potentially lethal complication after pancreatoduodenectomy. Several models have been developed to predict postoperative pancreatic fistula risk. This study was performed to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist that provides guidelines on reporting prediction models to enhance transparency and to help in the decision-making regarding the implementation of the appropriate risk models into clinical practice.METHODS: Studies that described prediction models to predict postoperative pancreatic fistula after pancreatoduodenectomy were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The TRIPOD checklist was used to evaluate the adherence rate. The area under the curve and other performance measures were extracted if reported. A quadrant matrix chart is created to plot the area under the curve against TRIPOD adherence rate to find models with a combination of above-average TRIPOD adherence and area under the curve.RESULTS: In total, 52 predictive models were included (23 development, 15 external validation, 4 incremental value, and 10 development and external validation). No risk model achieved 100% adherence to the TRIPOD. The mean adherence rate was 65%. Most authors failed to report on missing data and actions to blind assessment of predictors. Thirteen models had an above-average performance for TRIPOD checklist adherence and area under the curve.CONCLUSION: Although the average TRIPOD adherence rate for postoperative pancreatic fistula models after pancreatoduodenectomy was 65%, higher compared to other published models, it does not meet TRIPOD standards for transparency. This study identified 13 models that performed above average in TRIPOD adherence and area under the curve, which could be the appropriate models to be used in clinical practice.</p

    Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements

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    Breast tumors are blindly identified using Principal (PCA) and Independent Component Analysis (ICA) of localized reflectance measurements. No assumption of a particular theoretical model for the reflectance needs to be made, while the resulting features are proven to have discriminative power of breast pathologies. Normal, benign and malignant breast tissue types in lumpectomy specimens were imaged ex vivo and a surgeon-guided calibration of the system is proposed to overcome the limitations of the blind analysis. A simple, fast and linear classifier has been proposed where no training information is required for the diagnosis. A set of 29 breast tissue specimens have been diagnosed with a sensitivity of 96% and specificity of 95% when discriminating benign from malignant pathologies. The proposed hybrid combination PCA-ICA enhanced diagnostic discrimination, providing tumor probability maps, and intermediate PCA parameters reflected tissue optical properties.This work has been supported by the Spanish Government through CYCIT projects DA2TOI (FIS2010-19860), TFS (TEC2010-20224-C02-02) and Alma’s Eguizabal PhD Grant (FPU12/04130) and by Dartmouth College

    Head-to-head comparison of 14 prediction models for postoperative delirium in elderly non-ICU patients:an external validation study

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    OBJECTIVES: Delirium is associated with increased morbidity, mortality, prolonged hospitalisation and increased healthcare costs. The number of clinical prediction models (CPM) to predict postoperative delirium has increased exponentially. Our goal is to perform a head-to-head comparison of CPMs predicting postoperative delirium in non-intensive care unit (non-ICU) elderly patients to identify the best performing models. SETTING: Single-site university hospital. DESIGN: Secondary analysis of prospective cohort study. PARTICIPANTS AND INCLUSION: CPMs published within the timeframe of 1 January 1990 to 1 May 2020 were checked for eligibility (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). For the time period of 1 January 1990 to 1 January 2017, included CPMs were identified in systematic reviews based on prespecified inclusion and exclusion criteria. An extended literature search for original studies was performed independently by two authors, including CPMs published between 1 January 2017 and 1 May 2020. External validation was performed using a surgical cohort consisting of 292 elderly non-ICU patients. PRIMARY OUTCOME MEASURES: Discrimination, calibration and clinical usefulness. RESULTS: 14 CPMs were eligible for analysis out of 366 full texts reviewed. External validation was previously published for 8/14 (57%) CPMs. C-indices ranged from 0.52 to 0.74, intercepts from −0.02 to 0.34, slopes from −0.74 to 1.96 and scaled Brier from −1.29 to 0.088. Based on predefined criteria, the two best performing models were those of Dai et al (c-index: 0.739; (95% CI: 0.664 to 0.813); intercept: −0.018; slope: 1.96; scaled Brier: 0.049) and Litaker et al (c-index: 0.706 (95% CI: 0.590 to 0.823); intercept: −0.015; slope: 0.995; scaled Brier: 0.088). For the remaining CPMs, model discrimination was considered poor with corresponding c-indices <0.70. CONCLUSION: Our head-to-head analysis identified 2 out of 14 CPMs as best-performing models with a fair discrimination and acceptable calibration. Based on our findings, these models might assist physicians in postoperative delirium risk estimation and patient selection for preventive measures

    A nomogram to predict the probability of axillary lymph node metastasis in early breast cancer patients with positive axillary ultrasound

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    Among patients with a preoperative positive axillary ultrasound, around 40% of them are pathologically proved to be free from axillary lymph node (ALN) metastasis. We aimed to develop and validate a model to predict the probability of ALN metastasis as a preoperative tool to support clinical decision-making. Clinicopathological features of 322 early breast cancer patients with positive axillary ultrasound findings were analyzed. Multivariate logistic regression analysis was performed to identify independent predictors of ALN metastasis. A model was created from the logistic regression analysis, comprising lymph node transverse diameter, cortex thickness, hilum status, clinical tumour size, histological grade and estrogen receptor, and it was subsequently validated in another 234 patients. Coefficient of determination (R-2) and the area under the ROC curve (AUC) were calculated to be 0.9375 and 0.864, showing good calibration and discrimination of the model, respectively. The false-negative rates of the model were 0% and 5.3% for the predicted probability cut-off points of 7.1% and 13.8%, respectively. This means that omission of axillary surgery may be safe for patients with a predictive probability of less than 13.8%. After further validation in clinical practice, this model may support increasingly limited surgical approaches to the axilla in breast cancer

    Early detection of heterotopic ossification using near‐infrared optical imaging reveals dynamic turnover and progression of mineralization following Achilles tenotomy and burn injury

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    Heterotopic ossification (HO) is the abnormal formation of bone in soft tissue. Current diagnostics have low sensitivity or specificity to incremental progression of mineralization, especially at early time points. Without accurate and reliable early diagnosis and intervention, HO progression often results in incapacitating conditions of limited range of motion, nerve entrapment, and pain. We hypothesized that non‐invasive near‐infrared (NIR) optical imaging can detect HO at early time points and monitor heterotopic bone turnover longitudinally. C57BL6 mice received an Achilles tenotomy on their left hind limb in combination with a dorsal burn or sham procedure. A calcium‐chelating tetracycline derivative (IRDye 680RD BoneTag) was injected bi‐weekly and imaged via NIR to measure accumulative fluorescence for 11 wk and compared to in vivo microCT images. Percent retention of fluorescence was calculated longitudinally to assess temporal bone resorption. NIR detected HO as early as five days and revealed a temporal response in HO formation and turnover. MicroCT could not detect HO until 5 wk. Confocal microscopy confirmed fluorophore localization to areas of HO. These findings demonstrate the ability of a near‐infrared optical imaging strategy to accurately and reliably detect and monitor HO in a murine model. © 2014 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 32:1416–1423, 2014.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108601/1/jor22697.pd

    Oncoplastic Surgical Techniques for Personalized Breast Conserving Surgery in Breast Cancer Patient with Small to Moderate Sized Breast

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    Oncoplastic surgery has revolutionized the field of breast conserving surgery (BCS). The final aims of this technique are to obtain an adequate resection margin that will reduce the rate of local recurrence while simultaneously improving cosmetic outcomes. To obtain successful results after oncoplastic surgery, it is imperative that patients be risk-stratified based on risk factors associated with positive margins, that relevant imaging studies be reviewed, and that the confirmation of negative margins be confirmed during the initial operation. Patients who had small- to moderate-sized breasts are the most likely to be dissatisfied with the cosmetic outcome of surgery, even if the defect is small; therefore, oncoplastic surgery in this population is warranted. Reconstruction of the remaining breast tissue is divided into volume displacement and volume replacement techniques. The use of the various oncoplastic surgeries is based on tumor location and excised breast volume. If the excised volume is less than 100 g, the tumor location is used to determine which technique should be used, with the most commonly used technique being volume displacement. However, if the excised volume is greater than 100 g, the volume replacement method is generally used, and in cases where more than 150 g is excised, the latissimus dorsi myocutaneous flap may be used to obtain a pleasing cosmetic result. The local recurrence rate after oncoplastic surgery was lower than that of conventional BCS, as oncoplastic surgery reduced the rate of positive resection margins by resecting a wider section of glandular tissue. If the surgeon understands the advantages and disadvantages of oncoplastic surgery, and the multidisciplinary breast team is able to successfully collaborate, then the success rate of BCS with partial breast reconstruction can be increased while also yielding a cosmetically appealing outcome

    Intraoperative Multispectral Fluorescence Imaging for the Detection of the Sentinel Lymph Node in Cervical Cancer: A Novel Concept

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    PURPOSE: Real-time intraoperative near-infrared fluorescence (NIRF) imaging is a promising technique for lymphatic mapping and sentinel lymph node (SLN) detection. The purpose of this technical feasibility pilot study was to evaluate the applicability of NIRF imaging with indocyanin green (ICG) for the detection of the SLN in cervical cancer. PROCEDURES: In ten patients with early stage cervical cancer, a mixture of patent blue and ICG was injected into the cervix uteri during surgery. Real-time color and fluorescence videos and images were acquired using a custom-made multispectral fluorescence camera system. RESULTS: Real-time fluorescence lymphatic mapping was observed in vivo in six patients; a total of nine SLNs were detected, of which one (11%) contained metastases. Ex vivo fluorescence imaging revealed the remaining fluorescent signal in 11 of 197 non-sentinel LNs (5%), of which one contained metastatic tumor tissue. None of the non-fluorescent LNs contained metastases. CONCLUSIONS: We conclude that lymphatic mapping and detection of the SLN in cervical cancer using intraoperative NIRF imaging is technically feasible. However, the technique needs to be refined for full applicability in cervical cancer in terms of sensitivity and specificity
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