Prospective Test Research Articles

P13.10.A PREDICTING SURVIVAL OF GLIOBLASTOMAAFTER RADIOTHERAPY USING DEEP LEARNING AND NEUROIMAGING IN A MULTI-CENTRE COHORT

Abstract BACKGROUND Glioblastoma is an aggressive brain tumour routinely monitored with MRI. However, the potential to use imaging as a prognostic biomarker predicting survival after treatment starts is unclear. This study aims to predict survival within eight months of completing radiotherapy from MRIs using deep learning. MATERIAL AND METHODS The dataset consists of 206 prospective and retrospective consecutive patients with glioblastoma (WHO 2021) across 11 UK centres (short-term survival: N=64; 31.1%). Models were trained/validated on N=158 (76.7%) retrospective patients (3 centres). Two holdout sets were sampled: retrospective test set (N=19); and external, prospective test set (N=29; 8 separate centres). Dense convolutional neural networks were developed with separate branches for T1c-w and T2-w MR sequences; a third branch concatenates outputs from those branches to predict survival. Dense blocks used pretrained weights for an abnormality detection model. A semi-supervised approach was implemented; patients without known outcomes were added with pseudo-labels during training. Parameter tuning included the number of updated blocks, linear layer sizes, and weighting of pseudo-labels. Imaging models were compared to counterparts that apply non-imaging variables (demographics, MGMT status/%, treatment). Logistic regression, support vector classifier, and decision tree models were fit on non-imaging features alone with feature selection and mean/mode imputation. Combined imaging/non-imaging networks were developed that added a branch for non-imaging inputs. RESULTS The current best-performing imaging model used MR sequences alone (validation weighted-ROC=0.80, 95% CI=0.75-0.84; balanced accuracy=0.70, 95% CI=0.55-0.85). Among non-imaging models, the logistic regression model with feature selection performed best (validation weighted-ROC=0.59, 95% CI=0.56-0.63; balanced accuracy=0.59, 95% CI=0.56-0.63). Combined model development is ongoing. CONCLUSION This is the first known model applying deep learning to MRIs from multiple centres to distinguish patients with failure to respond to chemoradiotherapy, and those who survive the subsequent treatment window. Based on initial results, image-based models performed best at predicting survival. Such models could be used across centres to suggest closer monitoring and trial targeting of patients with expected short-term survival compared to treatment response.

Can Non-Invasive Spectrophotometric Hemoglobin Replace Laboratory Hemoglobin Concentrations for Preoperative Anemia Screening? A Diagnostic Test Accuracy Study.

Preoperative assessment of hemoglobin concentration in blood is important to diagnose anemia. The primary aim of this prospective diagnostic test accuracy study was to monitor non-invasive spectrophotometric hemoglobin (SpHb, g/dL) concentrations among adults prior to elective surgery and to investigate the correlation and agreement of SpHb with laboratory hemoglobin (Hb, g/dl). A secondary aim was to identify the anemia cut-off values for SpHb based on the World Health Organization (WHO) definitions for anemia. This study included 151 consecutive patients (age ≥ 18 year) presenting for preoperative evaluation prior to scheduled elective general or orthopedic surgery. Results identified the mean ± SD of SpHb at 11.43 ± 2.01 g/dL, which underestimated the mean laboratory Hb (12.64 ± 2.29 g/dL, p < 0.001). A bias mean difference (SpHb-Hb) of -1.21 g/dL, with a SD of 1.76, was reported. This bias (SpHb-Hb) was inversely correlated with the mean Hb concentrations. A positive correlation existed between SpHb and Hb, with a good degree of reliability and a significant Intra Class Correlation (ICC). SpHb diagnosed anemia in 32.3% and 60.3% of males and females, respectively. The SpHb cut-off values to identify anemia were 11.3 and 10.2 g/dL for males and females, respectively, with a sensitivity of 83.3% for males and only 62.9% for females. The specificity for males and females were 81% and 91.3%, respectively. SpHb sensitivity allows for anemia diagnosis among males, but not females. However, the specificity allows SpHb to rule out anemia for both.

Characterization of a mouse-adapted strain of bat severe acute respiratory syndrome-related coronavirus.

Bats carry genetically diverse severe acute respiratory syndrome-related coronaviruses (SARSr-CoVs). Some of them utilize human angiotensin-converting enzyme 2 (hACE2) as a receptor and cannot efficiently replicate in wild-type mice. Our previous study demonstrated that the bat SARSr-CoV rRsSHC014S induces respiratory infection and lung damage in hACE2 transgenic mice but not wild-type mice. In this study, we generated a mouse-adapted strain of rRsSHC014S, which we named SMA1901, by serial passaging of wild-type virus in BALB/c mice. SMA1901 showed increased infectivity in mouse lungs and induced interstitial lung pneumonia in both young and aged mice after intranasal inoculation. Genome sequencing revealed mutations in not only the spike protein but the whole genome, which may be responsible for the enhanced pathogenicity of SMA1901 in wild-type BALB/c mice. SMA1901 induced age-related mortality similar to that observed in SARS and COVID-19. Drug testing using antibodies and antiviral molecules indicated that this mouse-adapted virus strain can be used to test prophylactic and therapeutic drug candidates against SARSr-CoVs. IMPORTANCE The genetic diversity of SARSr-CoVs in wildlife and their potential risk of cross-species infection highlights the importance of developing a powerful animal model to evaluate the antibodies and antiviral drugs. We acquired the mouse-adapted strain of a bat-origin coronavirus named SMA1901 by natural serial passaging of rRsSHC014S in BALB/c mice. The SMA1901 infection caused interstitial pneumonia and inflammatory immune responses in both young and aged BALB/c mice after intranasal inoculation. Our model exhibited age-related mortality similar to SARS and COVID-19. Therefore, our model will be of high value for investigating the pathogenesis of bat SARSr-CoVs and could serve as a prospective test platform for prophylactic and therapeutic candidates.

COVID-19 vaccine intention: Prospective and concurrent tests of a disposition-belief-motivation framework.

The present study tested a novel integration of prospective and concurrent associations of demographic factors, traits, political orientation, coping strategies, infection and preventive beliefs, preventive behaviors, coronavirus disease 2019 (COVID-19) symptoms, exposure, and viral testing with COVID-19 vaccine intention. The preregistered study used a stratified online U.S. sample (N = 500). Three assessments were aligned with (a) "15 days to slow the spread" in March 2020, (b) the first mortality surge in April/May 2020, and (c) the vaccine authorization and major case/mortality surge during December 2020 and January 2021. Consistent with contemporaneous polling in December 2020, 66.4% of participants indicated they intended to receive an approved vaccine. Allowing for covarying interrelations, path modeling showed direct associations of greater education (β = .11, p < .01), the absence of child(ren) in the household (β = -.14, p < .001), more liberal political orientation (β = -.17, p < .001), stronger concurrent perceived norms for preventive behaviors (β = .23, p < .001), and more frequent concurrent mask wearing (β = .23, p < .001) with stronger vaccine intention. Prospective and concurrent trait, coping strategy, and sickness experience measures were not associated with intention. The close alignment of assessments with the public health timeline and the prospective and concurrent design provide needed clarity for the effects of stable demographic and dispositional factors (educational, parental, ideological) and more malleable preventive beliefs and behaviors, indicating potentially fruitful pathways to bolster novel vaccine intention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Metacognitive Appraisals of Perseverative Cognition: A Prospective Test Across Thought Types

Metacognitive Appraisals of Perseverative Cognition: A Prospective Test Across Thought Types

Comparison between alarm-based and probability-based earthquake forecasting methods

SUMMARY In a recent work, we applied the every earthquake a precursor according to scale (EEPAS) probabilistic model to the pseudo-prospective forecasting of shallow earthquakes with magnitude $M\ 5.0$ in the Italian region. We compared the forecasting performance of EEPAS with that of the epidemic type aftershock sequences (ETAS) forecasting model, using the most recent consistency tests developed within the collaboratory for the study of earthquake predictability (CSEP). The application of such models for the forecasting of Italian target earthquakes seems to show peculiar characteristics for each of them. In particular, the ETAS model showed higher performance for short-term forecasting, in contrast, the EEPAS model showed higher forecasting performance for the medium/long-term. In this work, we compare the performance of EEPAS and ETAS models with that obtained by a deterministic model based on the occurrence of strong foreshocks (FORE model) using an alarm-based approach. We apply the two rate-based models (ETAS and EEPAS) estimating the best probability threshold above which we issue an alarm. The model parameters and probability thresholds for issuing the alarms are calibrated on a learning data set from 1990 to 2011 during which 27 target earthquakes have occurred within the analysis region. The pseudo-prospective forecasting performance is assessed on a validation data set from 2012 to 2021, which also comprises 27 target earthquakes. Tests to assess the forecasting capability demonstrate that, even if all models outperform a purely random method, which trivially forecast earthquake proportionally to the space–time occupied by alarms, the EEPAS model exhibits lower forecasting performance than ETAS and FORE models. In addition, the relative performance comparison of the three models demonstrates that the forecasting capability of the FORE model appears slightly better than ETAS, but the difference is not statistically significant as it remains within the uncertainty level. However, truly prospective tests are necessary to validate such results, ideally using new testing procedures allowing the analysis of alarm-based models, not yet available within the CSEP.

Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study

Ultrasonography is the most widely used technique to diagnose echinococcosis; however, challenges in using this technique and the demand on medical resources, especially in low-income or remote areas, can delay diagnosis. We aimed to develop a deep convolutional neural network (DCNN) model based on ultrasonography to identify echinococcosis and its types, especially alveolar echinococcosis. This retrospective, large-scale, multicentre study used ultrasound images from patients assessed at 84 hospitals in China, obtained between Jan 1, 2002, and Dec 31, 2021. Patients with a diagnosis of cystic echinococcosis, alveolar echinococcosis, or seven other types of focal liver lesions were included. We tested ResNet-50, ResNext-50, and VGG-16 as the backbone network architecture for a classification DCNN model and input the perinodular information from the ultrasound images. We trained and validated the DCNN model to diagnose and classify echinococcosis using still greyscale ultrasound images of focal liver lesions in four stages: differentiating between echinococcosis and other focal liver lesions (stage one); differentiating cystic echinococcosis, alveolar echinococcosis, and other focal liver lesions (stage two); differentiating cystic echinococcosis, alveolar echinococcosis, benign other focal liver lesions, and malignant focal liver lesions (stage three); and differentiating between active and transitional cystic echinococcosis and inactive cystic echinococcosis (stage four). We then tested the algorithm on internal, external, and prospective test datasets. The performance of DCNN was also compared with that of 12 radiologists recruited between Jan 15, 2022, and Jan 28, 2022, from Qinghai, Xinjiang, Anhui, Henan, Xizang, and Beijing, China, with different levels of diagnostic experience for echinococcosis and other focal liver lesions in a subset of ultrasound data that were randomly chosen from the prospective test dataset. The study is registered at ClinicalTrials.gov (NCT03871140). The study took place between Jan 1, 2002, and Dec 31, 2021. In total, to train and test the DCNN model, we used 9631 liver ultrasound images from 6784 patients (2819 [41·7%] female patients and 3943 [58·3%] male patients) from 87 Chinese hospitals. The DCNN model was trained with 6328 images, internally validated with 984 images, and tested with 2319 images. The ResNet-50 network architecture outperformed VGG-16 and ResNext-50 and was generalisable, with areas under the receiver operating characteristic curve (AUCs) of 0·982 (95% CI 0·960-0·994), 0·984 (0·972-0·992), and 0·913 (0·886-0·935) in distinguishing echinococcosis from other focal liver lesions; 0·986 (0·966-0·996), 0·962 (0·946-0·975), and 0·900 (0·872-0·924) in distinguishing alveolar echinococcosis from cystic echinococcosis and other focal liver lesions; and 0·974 (0·818-1·000), 0·956 (0·875-0·991), and 0·944 (0·844-0·988) in distinguishing active and transitional cystic echinococcosis from inactive echinococcosis in the three test datasets. Specifically, in patients with the hepatitis B or hepatitis C virus, the model could distinguish alveolar echinococcosis from hepatocellular carcinoma with an AUC of 0·892 (0·812-0·946). In identifying echinococcosis, the model showed significantly better performance compared with senior radiologists from a high-endemicity area (AUC 0·942 [0·904-0·967] vs 0·844 [0·820-0·866]; p=0·027) and improved the diagnostic ability of junior, attending, and senior radiologists before and after assistance with AI with comparison of AUCs of 0·743 (0·714-0·770) versus 0·850 (0·826-0·871); p<0·0001, 0·808 (0·782-0·832) versus 0·886 (0·864-0·905); p<0·0001, and 0·844 (0·820-0·866) versus 0·870 (0·847-0·890); p=0·092, respectively. The DCNN model was shown to be accurate and robust, and could improve the ultrasound diagnostic ability of radiologists for echinococcosis and its types for highly endemic and remote regions. National Natural Science Foundation of China and National Key Research & Development Program of China. For the Chinese translation of the abstract see Supplementary Materials section.

Sweat conductivity diagnostic accuracy for cystic fibrosis: a systematic review and meta-analysis

ObjectiveWe conducted a systematic review and meta‐analysis of diagnostic test accuracy studies to summarise the properties of sweat conductivity (SC) to rule in/out cystic fibrosis (CF).Data sourceWe searched PubMed, Embase,...

Development of the Virtual Kitchen Protocol for Prospective Memory: a virtual reality-based measure of everyday prospective memory abilities

ABSTRACT Introduction Prospective memory is the ability to remember to accomplish a task at a specified point in the future. While this cognitive ability has a large impact on daily functioning, it is rarely assessed during neuropsychological evaluations. Furthermore, existing clinical prospective memory measures are few in number and have significant limitations, including applicability to everyday functioning and appropriate norming for older adulthood. There are also many gaps in the literature on prospective memory, such as how environmental factors affect performance across the lifespan. Method In the current study, we develop and establish a new virtual reality-based measure of prospective memory, the Virtual Kitchen Protocol for Prospective Memory. Young adults (ages 18–29; n = 56), healthy older adults (ages 60–90; n = 94), and clinical older adults (ages 62–90; n = 30) were compared on their performances on both the developed virtual reality prospective memory test and a parallel paper-and-pencil prospective memory test to investigate the impact of test environment across participant group. Results The Virtual Kitchen Protocol for Prospective Memory was found to adequately differentiate between young adult, healthy older adult, and clinical older adult populations – suggesting baseline ability for prospective memory assessment in clinical settings with older adults and potential for future improvement of neuropsychological evaluations. Additionally, the developed virtual prospective memory task appeared to mimic environmental factors in everyday life but did not replicate the benefit previously measured in healthy older adults’ prospective memory ability in naturalistic settings. Conclusions Overall, the current study built upon extant knowledge of prospective memory in both normal and abnormal aging, suggesting future directions in replicating familiar home environments. Findings provided additional evidence toward future validation of virtual reality assessment tools in clinical neuropsychological evaluations of cognitive abilities, such as prospective memory, with both healthy and clinical older adult populations.

Diagnostic Accuracy of Frailty Screening Instruments Validated for Use among Older Adults Attending Emergency Departments: A Systematic Review and Meta-Analysis.

Early identification of frailty can prevent functional decline. Although multiple frailty screens exist for use in Emergency Departments (EDs), few are validated against diagnostic standards such as comprehensive geriatric assessment. To examine the diagnostic accuracy of ED screens for frailty, scientific databases were searched for prospective diagnostic accuracy test studies from January 2000 to September 2022. Studies were assessed for risk of bias using QUADAS-C. Psychometric properties were extracted and analysed using R. Six studies involving 1,663 participants describing seven frailty screening instruments (PRISMA-7, CFS, VIP, FRESH, BPQ, TRST, and ISAR), representing 13 unique data points, were included. The mean age of participants ranged from 76 to 86 years. The proportion that was female ranged from 45 to 60%. The pooled prevalence rate of frailty was high at 59%. The pooled estimate for sensitivity was 0.85 (95% CI: 0.76-0.91) versus 0.77 (95% CI: 0.62-0.88) for specificity. Pooled accuracy based on area under the ROC curve was 0.89 (95% CI: 0.86-0.90). Although few studies were found, limiting the ability to conduct a meta-analysis of individual instruments, available frailty screens can accurately diagnose frailty in older adults attending the ED. As specificity was comparatively low, additional assessment may be required to identify those requiring inpatient management or onward community referral. Further study is therefore required.

Prospective memory in patients with Mild Cogntive Impairment

Prospective memory is the ability to remember to carry out intended actions and to evoke delayed intentions. It constitutes a crucial skill for the daily functioning of the elderly. It might also be prematurely compromised in neurodegenerative diseases. In the Latin American region, objective measures are not available for its assessment. The aim of this study is to explore prospective memory in patients diagnosed with Mild Cognitive Impairment. As specific aims, we intend to discriminate the performance on prospective memory between patients and healthy subjects and to study the internal consistency and inter-examiner reliability of the Mini Cóndor Test (a simplified version of a prospective memory test developed in Argentina). We carried out a comparative study including a group of 20 patients with Mild Cognitive Impairment and a group of 20 healthy subjects as control group. Results indicated significant statistically differences between groups in prospective memory performance in favor of the control group. The Mini Cóndor Test met adequate scores for internal consistency and inter-rater reliability. These preliminary results suggest that the Mini Cóndor Test has the potential to early detect cognitive impairment associated to neurodegenerative pathology.

IMPROVING HEALTH LITERACY ABILITY FROM DIGITAL POP UP BOOK MEDIA FOR EARLY CHILDREN

Early childhood education level requires readiness from various elements, one of which is through a literacy program health that aims to help children understand the importance of behavior clean and healthy living (PHBS). The PHBS referred to is in the form bring supplies and do not share food as an effort to prevent Covid-19 at school. This research was carried out using the development method refers to research and development steps according to Borg &amp; Gall (1983). The research objective is to develop pop up book media digital-based to improve health literacy skills in children aged 4-6 years. Product trial results consisting of media expert trials, substance experts trials, prospective users trials and tests field. The media expert test results obtained 85.83%, the substance expert test obtained the average 88.94%, and the test results for prospective product users obtained an average of 86.98%. it can be concluded that ABBA's pop up book media is very good and unnecessary revised. The results of the product effectiveness test obtained an average pre-test score (XB) of 1682 and the average post test score (XA) is 1811 when compared to the t table value at a significance level of 5% then 0.004 &lt;0.05 so it can be concluded that pop up book media can improve health literacy skills in children aged 4-6 years.

Validation of a Salivary miRNA Signature of Endometriosis — Interim Data

BackgroundThe discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early and noninvasive diagnosis of the disease. The 109-miRNA saliva signature is the product of miRNA biomarkers and artificial intelligence (AI) modeling. We designed a multicenter study to provide external validation of its diagnostic accuracy. We present here an interim analysis.MethodsThe first 200 patients included in the multicenter prospective ENDOmiRNA Saliva Test study (NCT05244668) were included for interim analysis. The study population comprised women from 18 to 43 years of age with a formal diagnosis of endometriosis or with suspected endometriosis. Epidemiologic, clinical, and saliva sequencing data were collected between November 2021 and March 2022. Genomewide miRNA expression profiling by small RNA sequencing using next-generation sequencing (NGS) was performed, and a random forest algorithm was used to assess the diagnostic accuracy.ResultsIn this interim analysis of the external validation cohort, with a population prevalence of 79.5%, the 109-miRNA saliva diagnostic signature for endometriosis had a sensitivity of 96.2% (95% confidence interval [CI], 93.7 to 97.3%), specificity of 95.1% (95% CI, 85.2 to 99.1%), positive predictive value of 95.1% (95% CI, 85.2 to 99.1%), negative predictive value of 86.7% (95% CI, 77.6 to 90.3%), positive likelihood ratio of 19.7 (95% CI, 6.3 to 108.8), negative likelihood ratio of 0.04 (95% CI, 0.03 to 0.07), and area under the receiver operating characteristic curve of 0.96 (95% CI, 0.92 to 0.98).ConclusionsThe use of NGS and AI in the sequencing and analysis of miRNA provided a saliva-based miRNA signature for endometriosis. Our interim analysis of a prospective multicenter external validation study provides support for its ongoing investigation as a diagnostic tool. (Funded by Ziwig and the Conseil Régional d’Ile de France [Grant EX024087]; ClinicalTrials.gov number, NCT05244668.)

Use of circulating tumor DNA (ctDNA) to complement tumor tissue homologous recombination repair (HRR) gene alteration testing in TALAPRO-2, a phase 3 study of talazoparib (TALA) + enzalutamide (ENZA) versus placebo (PBO) + ENZA as first-line (1L) treatment in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC).

5056 Background: In TALAPRO-2 (NCT03395197), pts unselected for tumor genetic alterations in DNA damage repair pathways, directly or indirectly involved with HRR, received TALA + ENZA (n=402) or PBO + ENZA (n=403) as 1L treatment for mCRPC. HRR status was informed by tumor tissue for 804 pts (99.9%), by tumor tissue and ctDNA for 114 (14.2%), and by ctDNA only for 1 (0.1%). TALA + ENZA demonstrated statistically significant and clinically meaningful improvements in imaging-based progression-free survival over standard of care PBO + ENZA regardless of HRR gene alteration status (presented by Agarwal N at ASCO-GU 2023). Here we assessed the overall agreement of solid tissue vs ctDNA-based testing in assessing tumor HRR gene alteration status. Methods: HRR status for pts randomized in TALAPRO-2 was determined prospectively by testing for the presence of HRR gene alterations using FoundationOne CDx and/or FoundationOne Liquid CDx. Pts were considered HRR-deficient if they had ≥1 alteration in ≥1 of 12 HRR genes by either test. Plasma samples collected at screening were retrospectively tested using FoundationOne Liquid CDx to examine retrospective test performance and to support exploratory resolution of pts with unknown prospective HRR status. Results were reported as HRR-deficient, non-HRR-deficient, or unknown. Results: In prospective testing, high concordance in HRR status was observed between ctDNA and tumor tissue sample results: 95% agreement (90/95) between tests was observed in pts evaluable as either HRR-deficient or non-HRR-deficient by both tests. Retrospective ctDNA test results were reported for 739 pts (207 [28%] with a status of HRR-deficient, 480 [65%] non-HRR-deficient, and 52 [7%] unknown; 66 pts had samples not collected or reported). There was high concordance in pt-level alteration status between prospective molecular profiling (mainly based on solid tumor tissue per above) and retrospective ctDNA testing: the agreement was 84% (438/519) between tests for pts evaluable as HRR-deficient or non-HRR-deficient both prospectively and retrospectively (421/501 [84%] for prospective tumor tissue only vs retrospective ctDNA). Conclusions: Results show 95% agreement between prospective tissue and ctDNA-based HRR status using FoundationOne, consistent with tumor vs ctDNA results recently reported (Tukachinsky. Clin Cancer Res. 2021;27:3094–3105). The high agreement between prospective test results based primarily on tumor tissue and retrospectively assessed ctDNA collected at screening is supportive of exploratory retrospective testing of ctDNA to inform the HRR status of pts whose alteration status is unknown based on prospective testing. Clinical trial information: NCT03395197 .

Radiomics for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Prospective Observational Trial.

(1) Background: An increasing amount of research has supported the role of radiomics for predicting pathological complete response (pCR) to neoadjuvant chemoradiation treatment (nCRT) in order to provide better management of locally advanced rectal cancer (LARC) patients. However, the lack of validation from prospective trials has hindered the clinical adoption of such studies. The purpose of this study is to validate a radiomics model for pCR assessment in a prospective trial to provide informative insight into radiomics validation. (2) Methods: This study involved a retrospective cohort of 147 consecutive patients for the development/validation of a radiomics model, and a prospective cohort of 77 patients from two institutions to test its generalization. The model was constructed using T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI to understand the associations with pCR. The consistency of physicians' evaluations and agreement on pathological complete response prediction were also evaluated, with and without the aid of the radiomics model. (3) Results: The radiomics model outperformed both physicians' visual assessments in the prospective test cohort, with an area under the curve (AUC) of 0.84 (95% confidence interval of 0.70-0.94). With the aid of the radiomics model, a junior physician could achieve comparable performance as a senior oncologist. (4) Conclusion: We have built and validated a radiomics model with pretreatment MRI for pCR prediction of LARC patients undergoing nCRT.

Efficiency Index for Binary Classifiers: Concept, Extension, and Application

Many metrics exist for the evaluation of binary classifiers, all with their particular advantages and shortcomings. Recently, an “Efficiency Index” (EI) for the evaluation of classifiers has been proposed, based on the consistency (or matching) and contradiction (or mismatching) of outcomes. This metric and its confidence intervals are easy to calculate from the base data in a 2 × 2 contingency table, and their values can be qualitatively and semi-quantitatively categorised. For medical tests, in which context the Efficiency Index was originally proposed, it facilitates the communication of risk (of the correct diagnosis versus misdiagnosis) to both clinicians and patients. Variants of the Efficiency Index (balanced, unbiased) which take into account disease prevalence and test cut-offs have also been described. The objectives of the current paper were firstly to extend the EI construct to other formulations (balanced level, quality), and secondly to explore the utility of the EI and all four of its variants when applied to the dataset of a large prospective test accuracy study of a cognitive screening instrument. This showed that the balanced level, quality, and unbiased formulations of the EI are more stringent measures.

Significant others and students’ leisure-time physical activity intention: A prospective test of the social influence in sport model

Background/ObjectivesThis two-wave prospective study applied the Social Influence in Sport Model to investigate whether the social influences of parents, physical education (PE) teachers, and peers were predictive of students' intention to engage in leisure-time physical activity (PA). MethodsParticipants were 2,484 secondary school students (11–18 years old) who completed a questionnaire assessing positive influence, punishment, and dysfunction from the three social agents (parents, PE teachers, and peers) at baseline, and PA intention at a 1-month follow-up. Structural equation modelling (SEM) yielded excellent goodness-of-fit and consistent pathways between the three social agents. ResultsStudents' leisure-time PA intention (R2 = .103 to 0.112) was positively associated with positive influence (β = .223 to 0.236, p < .001) and punishment (β = .214 to 0.256, p < .01), and negatively associated with dysfunction (β = - 0.281 to -.335, p < .001). Multi-group SEM showed that the predictions were invariant between parents, PE teachers, and peers. Furthermore, no significant differences in students' gender were found between perceived social influence and PA intention. ConclusionThe findings supported the application of the Social Influence in Sport Model in explaining the role of significant others on students’ intention to take part in leisure-time PA.

CT Radiomics-Based Nomogram for Predicting the Lateral Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma: A Prospective Multicenter Study

This study is based on multicenter cohorts and aims to utilize computed tomography (CT) images to construct a radiomics nomogram for predicting the lateral neck lymph node (LNLN) metastasis in the papillary thyroid carcinoma (PTC) and further explore the biological basis under its prediction. In the multicenter study, 1213 lymph nodes from 409 patients with PTC who underwent CT examinations and received open surgery and lateral neck dissection were included. A prospective test cohort was used in validating the model. Radiomics features were extracted from the CT images of each patient's LNLNs. Selectkbest, maximum relevance and minimum redundancy and the least absolute shrinkage and selection operator (LASSO) algorithm were used in reducing the dimensionality of radiomics features in the training cohort. Then, a radiomics signature (Rad-score) was calculated as the sum of each feature multiplied by the nonzero coefficient from LASSO. A nomogram was generated using the clinical risk factors of the patients and Rad-score. The nomograms' performance was analyzed in terms of accuracy, sensitivity, specificity, confusion matrix, receiver operating characteristic curves, and areas under the receiver operating characteristic curve (AUCs). The clinical usefulness of the nomogram was evaluated by decision curve analysis. Moreover, three radiologists with different working experiences and nomogram were compared to one another. Whole transcriptomics sequencing was performed in 14 tumor samples; the correlation of biological functions and high and low LNLN samples predicted by the nomogram was further investigated. A total of 29 radiomics features were used in constructing the Rad-score. Rad-score and clinical risk factors (age, tumor diameter, location and number of suspected tumors) compose the nomogram. The nomogram exhibited good discrimination performance of the nomogram for predicting LNLN metastasis in the training cohort (AUC, 0.866), internal test cohort (0.845), external test cohort (0.725), and prospective test cohort (0.808) and showed diagnostic capability comparable to senior radiologists, significantly outperforming junior radiologists (p<0.05). Functional enrichment analysis suggested that the nomogram can reflect the ribosome-related structures of cytoplasmic translation in patients with PTC. Our radiomics nomogram provides a noninvasive method that incorporates radiomics features and clinical risk factors for predicting LNLN metastasis in patients with PTC.

The Impact of Interprofessional Education on Health Profession Students’ Professional Identity

Establishing interprofessional identity is critical in preparing health care teams to work in collaborative environments and enhance efficacy of patient care. Accreditation standards for health profession programs have been implemented to include interprofessional education (IPE), yet there remains obfuscation regarding occupational therapy’s (OT) professional identity. The purpose of this prospective pre-post test study was to assess an experiential IPE event for health profession students (n = 170 from ten health profession programs) to: (1) determine the effectiveness of role playing and team-based case discussions on students’ knowledge and perceptions toward each other’s professions, and (2) specifically assess the impact of the IPE event on students’ perceptions toward OT roles and responsibilities. Health profession students were asked to complete a survey prior to and at the conclusion of the IPE event, which included the validated Interdisciplinary Education Perception Scale (IEPS) and non-standardized closed and open-ended questions. Quantitative analysis of responses showed a significant improvement in interdisciplinary perceptions after the experience as evidenced by higher IEPS scores. Post-test open-ended responses confirmed this finding. Health profession programs were stratified, revealing positive significant differences regarding OT. These findings suggest role-playing and team-based case discussions for IPE can have a positive impact on students’ interprofessional perceptions and understanding of OT.

Shoe-Integrated Sensor System for Diagnosis of the Concomitant Syndesmotic Injury in Chronic Lateral Ankle Instability: A Prospective Double-Blind Diagnostic Test.

Chronic lateral ankle instability (CLAI) is commonly secondary to prior lateral ankle ligament injury, and the concomitant latent syndesmosis injury would prolong recovery time and increase the risk of substantial traumatic arthritis. However, differentiating syndesmotic injury from isolated lateral ankle ligament injury in CLAI cases is difficult by conventional physical and radiological examinations. To improve the accuracy of syndesmotic injury diagnosis, a shoe-integrated sensor system (SISS) is proposed. This system measures plantar pressure during walking to detect the presence of syndesmotic injury. The study included 27 participants who had ankle sprains and underwent an examination. Plantar pressure in eight regions of interest was measured for both limbs, and syndesmotic injuries were examined using arthroscopy. The width of the syndesmosis was measured to evaluate its severity. The characteristics of plantar pressure were compared between patients with normal and injured syndesmosis. The results indicated that peak plantar pressure ratios with logistic regression predicted value > 0.51 accurately distinguished concomitant syndesmotic injury during walking, with high sensitivity (80%) and specificity (75%). The post-test probability of having a syndesmotic injury was positively 80% and negatively 25%. These findings demonstrate the effectiveness of cost-effective wearable sensors in objectively diagnosing concomitant syndesmotic injuries in cases of CLAI.