Low Probability Group Research Articles

Echocaridographic assessment of pulmonary hypertension: improving the probability

Abstract Introduction Pulmonary hypertension (PH) is a cardio-pulmonary disorder characterised by raised pulmonary artery pressure (mPAP >20mmHg) leading to right ventricular failure, and death if left untreated. Transthoracic echocardiography (TTE) assessment of PH uses a probability-based approach, combining peak tricuspid regurgitant velocity with other supporting signs. We evaluated the latest ESC TTE PH guidelines in a real-world UK dataset and identified markers that may improve the sensitivity of the existing algorithm. Method Retrospective analysis of 447 patients referred for initial PH assessment. This was a select population of patients who underwent both TTE and right heart catheter (RHC) (mean time to RHC = 40±30 days). In addition to current TTE PH probability markers we analysed right ventricular free wall strain (RVFWS). Measurements were made by a single operator using Tomtec Arena 2020. Crosstabulation, ROC curve analysis and T-tests were used to compare variables between PH and no PH. Results Mean sample age was 64±15 yrs (61% female). 6.9% (n=4) of the no PH group had pulmonary mid-systolic notching, which may be due to pseudo-notching attributable to incomplete Doppler envelope. Sensitivity and specificity of current ESC TTE probability guidelines were 83%, and 65% respectively (95% C.I.). However, within the low probability group (i.e. those felt to be less likely to have PH) 62% (n=63) had confirmed PH at RHC (mPAP = 28±9). The addition of RVFWS as an additional marker to the existing supporting signs of PH (Table 1) resulted in an improvement of the sensitivity of the algorithm to 92% with a mild reduction in specificity (63%). The number of false negatives were reduced by 51%. Of these, the majority were in the low TTE probability group (n = 32). Conclusions Using current PH TTE probability algorithms classifies a significant proportion of those with PH as having a low TTE PH probability. The addition of RVFWS improves the sensitivity of the existing algorithm to 92% and reduces false negatives by 51%.

Calibration, Clinical Utility and Specificity of Clinical Decision Support Tools in Inflammatory Bowel Disease

Background and AimsClinical decision support tools (CDSTs) have been developed to predict response to vedolizumab (VDZ) and ustekinumab (UST) in Crohn’s disease (CD) and ulcerative colitis (UC). In addition to assessing their discrimination performance, our study aimed to evaluate their calibration, clinical utility and specificity. MethodsWe included 280 CD and 218 UC patients initiating VDZ, and 194 CD patients initiating UST. We assessed discrimination by comparing rates of effectiveness outcomes between response probability groups forecasted by CDSTs. Calibration curves and decision curve analysis evaluated the calibration and clinical utility of VDZ-CDSTs. Additionally, we examined the agreement between UST-CDST and VDZ-CDST in assigning response probability groups among CD patients starting UST. ResultsIn the overall cohort, CDSTs allocated 7.2%, 50.0% and 42.8% of the patients to the low, intermediate and high response probability groups, respectively. VDZ-CDSTs groups demonstrated significant differences in the rates of clinical and endoscopic response and remission, while UST-CDST groups showed significant discrimination only for clinical remission. Although VDZ-CDSTs overestimated clinical remission rates, they more accurately predicted rates of VDZ persistence without need for surgery or dose escalation. Compared to empirically treating all patients with VDZ, VDZ-CDSTs yielded higher net benefits in selecting patients who would continue VDZ without need for surgery or dose escalation. Finally, the agreement between UST-CDST and VDZ-CDST in predicting response was 73.7%. ConclusionVDZ-CDSTs significantly discriminated response to VDZ and were more beneficial in identifying patients who would continue therapy without requiring surgery or dose escalation, compared to treating all patients empirically.

Clinical Utility of Recently Food and Drug Administration-Approved IntelliSep Test (Sepsis Biomarker) for Early Diagnosis of Sepsis: Comparison with Other Biomarkers.

Context: IntelliSep by Cytovale has received United States (U.S.) Food and Drug Administration (FDA) approval as a sepsis biomarker test. However, the clinical utility of this new test is not assessed in emergency departments. Objective: We investigated the clinical utility of this test using 44 patients visiting the emergency department at The University of Kansas Medical Center by comparing it with the monocyte distribution width (MDW) and other biomarkers including the von Willebrand factor (vWF) and ADAMTS13. Design and Methods: IntelliSep assesses the cellular host response via deformability cytometry of biophysical leukocyte properties and produces a score (IntelliSep Index; ISI: from 0.1 (lowest risk) to 10 (highest risk). We measured the ISI in 44 patients (19 high probability and 25 low probability of sepsis groups) using EDTA-anticoagulated blood. Left over plasma was used for measuring the plasma von Willebrand factor (vWF) and ADAMTS13 antigen by ELISA assays. The MDW was obtained during routine CBC analysis using a Beckman hematology analyzer. The lactate and high-sensitivity troponin I levels were measured using a Beckman analyzer. Procalcitonin was measured using a Cobas e801 analyzer. Results: The median ISI was twofold higher in the high-probability group than in the low-probability group (p < 0.01) while the median MDW was 34.5% higher in the high-probability group than in the low-probability group (p < 0.01). However, the correlation between the ISI and MDW was only modest (r = 0.66). In addition, significantly higher levels of plasma vWF antigen but lower levels of plasma ADAMTS13 antigen in the high-probability group were found, resulting in significantly higher vWF/ADAMTS13 ratios in the high-probability group than in the low-probability group. Conclusions: The new IntelliSep test along with vWF/ADAMTS13 ratios may be useful for the early diagnosis of sepsis in patients visiting the emergency department, which appears to be superior to the traditional marker, MDW.

Stepwise algorithm using computed tomography and magnetic resonance imaging for differential diagnosis of fat-poor angiomyolipoma in small renal masses: A prospective validation study.

To validate the diagnostic accuracy of a stepwise algorithm to differentiate fat-poor angiomyolipoma (fp-AML) from renal cancer in small renal masses (SRMs). We prospectively enrolled 223 patients with solid renal masses <4 cm and no visible fat on unenhanced computed tomography (CT). Patients were assessed using an algorithm that utilized the dynamic CT and MRI findings in a stepwise manner. The diagnostic accuracy of the algorithm was evaluated in patients whose histology was confirmed through surgery or biopsy. The clinical course of the patients was further analyzed. The algorithm classified 151 (68%)/42 (19%)/30 (13%) patients into low/intermediate/high AML probability groups, respectively. Pathological diagnosis was made for 183 patients, including 10 (5.5%) with fp-AML. Of these, 135 (74%)/36 (20%)/12 (6.6%) were classified into the low/intermediate/high AML probability groups, and each group included 1 (0.7%)/3 (8.3%)/6 (50%) fp-AMLs, respectively, leading to the area under the curve for predicting AML of 0.889. Surgery was commonly opted in the low and intermediate AML probability groups (84% and 64%, respectively) for initial management, while surveillance was selected in the high AML probability group (63%). During the 56-month follow-up, 36 (82%) of 44 patients initially surveyed, including 13 of 18 (72%), 6 of 7 (86%), and 17 of 19 (89%) in the low/intermediate/high AML probability groups, respectively, continued surveillance without any progression. This study confirmed the high diagnostic accuracy for differentiating fp-AMLs. These findings may help in the management of patients with SRMs.

Machine learning-based detection of sleep-disordered breathing in hypertrophic cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) is often concomitant with sleep-disordered breathing (SDB), which can cause adverse cardiovascular events. Although an appropriate approach to SDB prevents cardiac remodelling, detection of concomitant SDB in...

Development of a diagnostic prediction model for giant cell arteritis by sequential application of Southend Giant Cell Arteritis Probability Score and ultrasonography: a prospective multicentre study

Giant cell arteritis is a critically ischaemic disease with protean manifestations that require urgent diagnosis and treatment. European Alliance of Associations for Rheumatology (EULAR) recommendations advocate ultrasonography as the first investigation for suspected giant cell arteritis. We developed a prediction tool that sequentially combines clinical assessment, as determined by the Southend Giant Cell Arteritis Probability Score (SGCAPS), with results of quantitative ultrasonography. This prospective, multicentre, inception cohort study included consecutive patients with suspected new onset giant cell arteritis referred to fast-track clinics (seven centres in Italy, the Netherlands, Spain, and UK). Final clinical diagnosis was established at 6 months. SGCAPS and quantitative ultrasonography of temporal and axillary arteries with three scores (ie, halo count, halo score, and OMERACT GCA Score [OGUS]) were performed at diagnosis. We developed prediction models for diagnosis of giant cell arteritis by multivariable logistic regression analysis with SGCAPS and each of the three ultrasonographic scores as predicting variables. We obtained intraclass correlation coefficient for inter-rater and intra-rater reliability in a separate patient-based reliability exercise with five patients and five observers. Between Oct 1, 2019, and June 30, 2022, we recruited and followed up 229 patients (150 [66%] women and 79 [34%] men; mean age 71 years [SD 10]), of whom 84 were diagnosed with giant cell arteritis and 145 with giant cell arteritis mimics (controls) at 6 months. SGCAPS and all three ultrasonographic scores discriminated well between patients with and without giant cell arteritis. A reliability exercise showed that the inter-rater and intra-rater reliability was high for all three ultrasonographic scores. The prediction model combining SGCAPS with the halo count, which was termed HAS-GCA score, was the most accurate model, with an optimism-adjusted C statistic of 0·969 (95% CI 0·952 to 0·990). The HAS-GCA score could classify 169 (74%) of 229 patients into either the low or high probability groups, with misclassification observed in two (2%) of 105 patients in the low probability group and two (3%) of 64 of patients in the high probability group. A nomogram for easy application of the score in daily practice was created. A prediction tool for giant cell arteritis (the HAS-GCA score), combining SGCAPS and the halo count, reliably confirms and excludes giant cell arteritis from giant cell arteritis mimics in fast-track clinics. These findings require confirmation in an independent, multicentre study. Royal College of Physicians of Ireland, FOREUM.

Validation of the European Society of Cardiology pretest probability models for obstructive coronary artery disease in high-risk population

ObjectiveThe pre-test probability (PTP) model for obstructive coronary artery disease (CAD) was updated in 2019 by the European Society of Cardiology (ESC). To our knowledge, this model was never externally validated in a population with a high incidence of CAD. The aim of this study is to validate the new PTP ESC model in our population, which has a high CAD incidence, and to compare it with the previous PTP ESC model from 2013. MethodsWe retrospectively analysed 1294 symptomatic patients with suspected CAD referred to our centre between 2015 and 2019. In all patients, the PTP score was calculated based on age, gender, and symptoms according to the ESC model from 2013 (2013-ESC-PTP) and 2019 (2019-ESC-PTP). All patients underwent invasive coronary angiography (ICA). ResultsOf the 1294 patients, obstructive CAD was diagnosed in 533 patients (41.2%). The 2019-ESC-PTP model categorised significantly more patients into the low probability group (PTP < 15%) than the 2013-ESC-PTP model (39.8% vs. 5.6%, p < 0.001). Obstructive CAD prevalence was underestimated using 2019-ESC-PTP at all PTP levels (calibration intercept 1.15, calibration slope 0.96). The 2013-ESC-PTP overestimated obstructive CAD prevalence (calibration intercept −0.24, calibration slope 0.73). The discrimination measured with an area under the curve was similar for both models, indicating moderate accuracy of the models. ConclusionIn high-risk Serbian population, both the 2013 and 2019 ESC-PTP models had moderate accuracy in diagnosing CAD, with the 2019-ESC-PTP underestimating the prevalence of CAD and the 2013-ESC-PTP overestimating it. Further studies are warranted to establish PTP models for high-risk countries.

Acute prevention of aheart attack : Early identification of prodromal symptoms as the Rosetta Stone in decoding the heart attack problem.

Chest discomfort before severe chest pain represents amarker of clinical ischemia and indicates live myocardium in jeopardy and often precedes cardiac arrest or acute myocardial infarction (MI). The intermittent or "stuttering" symptoms that precede MI are referred to as "prodromal symptoms." These symptoms have been shown to correlate with cyclic ST changes and repeated episodes of spontaneous reperfusion and occlusion, occurring during aperiod of hours or days before the acute ischemia proceeds to death or heart damage. These symptoms of premonitory angina have been associated with improved outcomes due to ischemic pre-conditioning or opening of collateral vascular channels around the area of ischemia. Acute prevention of an MI through recognition of prodromal symptoms represents an opportunity to significantly reduce heart attack deaths. The Early Heart Attack Care (EHAC) program puts emphasis on prodromal symptom recognition and allows for ashift in time backward to prevent the ischemic process from proceeding to MI. This strategy has been shown to detect the 15% of patients with ischemia in the low-probability group and to reduce inappropriate admissions to hospital as well as to reduce the number of patients with missed MI being sent home from the emergency department.

Intraoperative in vivo confocal laser endomicroscopy imaging at glioma margins: can we detect tumor infiltration?

Confocal laser endomicroscopy (CLE) is a US Food and Drug Administration-cleared intraoperative real-time fluorescence-based cellular resolution imaging technology that has been shown to image brain tumor histoarchitecture rapidly in vivo during neuro-oncological surgical procedures. An important goal for successful intraoperative implementation is in vivo use at the margins of infiltrating gliomas. However, CLE use at glioma margins has not been well studied. Matching in vivo CLE images and tissue biopsies acquired at glioma margin regions of interest (ROIs) were collected from 2 institutions. All images were reviewed by 4 neuropathologists experienced in CLE. A scoring system based on the pathological features was implemented to score CLE and H&E images from each ROI on a scale from 0 to 5. Based on the H&E scores, all ROIs were divided into a low tumor probability (LTP) group (scores 0-2) and a high tumor probability (HTP) group (scores 3-5). The concordance between CLE and H&E scores regarding tumor probability was determined. The intraclass correlation coefficient (ICC) and diagnostic performance were calculated. Fifty-six glioma margin ROIs were included for analysis. Interrater reliability of the scoring system was excellent when used for H&E images (ICC [95% CI] 0.91 [0.86-0.94]) and moderate when used for CLE images (ICC [95% CI] 0.69 [0.40-0.83]). The ICCs (95% CIs) of the LTP group (0.68 [0.40-0.83]) and HTP group (0.68 [0.39-0.83]) did not differ significantly. The concordance between CLE and H&E scores was 61.6%. The sensitivity and specificity values of the scoring system were 79% and 37%. The positive predictive value (PPV) and negative predictive value were 65% and 53%, respectively. Concordance, sensitivity, and PPV were greater in the HTP group than in the LTP group. Specificity was higher in the newly diagnosed group than in the recurrent group. CLE may detect tumor infiltration at glioma margins. However, it is not currently dependable, especially in scenarios where low probability of tumor infiltration is expected. The proposed scoring system has excellent intrinsic interrater reliability, but its interrater reliability is only moderate when used with CLE images. These results suggest that this technology requires further exploration as a method for consistent actionable intraoperative guidance with high dependability across the range of tumor margin scenarios. Specific-binding and/or tumor-specific fluorophores, a CLE image atlas, and a consensus guideline for image interpretation may help with the translational utility of CLE.

Multimorbidity patterns and associated factors in a megacity: a cross-sectional study.

To identify empirical patterns of multimorbidity and quantify their associations with socioeconomic, behavioral characteristics, and health outcomes in the megacity of São Paulo. This was a cross-sectional study conducted through household interviews with residents aged 20 years or older in urban areas (n = 3,184). Latent class analysis was used to identify patterns among the co-existence of 22 health conditions. Age-adjusted prevalence ratios were estimated using Poisson regression. The analysis of latent classes showed 4 patterns of multimorbidity, whereas 58.6% of individuals were classified in the low disease probability group, followed by participants presenting cardiovascular conditions (15.9%), respiratory conditions (12.8%), and rheumatic, musculoskeletal, and emotional conditions (12.8%). Older individuals, with lower schooling and lower household income, presented higher multimorbidity prevalence in cardiovascular, respiratory, rheumatic, musculoskeletal, and emotional conditions patterns compared with the low disease probability pattern. The results showed four distinct patterns of multimorbidity in the megacity population, and these patterns are clinically recognizable and theoretically plausible. The identification of trends between patterns would make it feasible to estimate the magnitude of the challenge for the organization of health care policies.

Simple Signs for Complex Problem

Objectives: To find simple clinical signs for diagnosing pulmonary embolism on bedside.&#x0D; Methodology: This was a hospital based cross sectional observational study conducted in cardiology department Saidu teaching hospital from July 2019 to December 2020. 89 patients of either sex and all age groups with suspected pulmonary embolism (PE) were included. Clinical data and basic tests of all these patients were obtained, then according to ESC diagnostic algorithm patients were divided into low, intermediate and high probability groups. 74 patients with intermediate and high probability went for CTPA, while 15 patients with low probability were exclude from study. In 67 patients pulmonary embolism was confirmed on CTPA. Clinical data of these 67 patients was analyzed for most common presenting symptoms and signs.&#x0D; Results: Data was available on 67 patients with confirmed PE, 58.2% were male and 41.8% were female. Mean age of study population was 53.15+/-16.29. Patients from different parts of Malakand division were included. 95.5 % patient presented with new onset dyspnea, 1.5 % presented with isolated chest pain, while 3% presented with other symptoms. 62.7 % patient had provoked and 37.3% had unprovoked PE. Mean heart rate of study population was 99.63. 95% patients had oxygen saturation of less than 96%. Other common findings included normal chest examination, sinus tachycardia on ECG, normal chest X-ray, and some form of right ventricular abnormality on Echo.&#x0D; Conclusion: Patient with new onset Dyspnea, resting Tachycardia, oxygen saturation below 95% at rest or mild exertion, and no other explanation for these findings should be evaluated for pulmonary embolism with CTPA.

Echocardiographic probability of pulmonary hypertension: a real world audit comparing 2015 and 2022 ESC guidelines

Abstract Introduction Transthoracic echocardiography (TTE) is an established screening tool used in the assessment of suspected Pulmonary Hypertension (PH). ESC guidelines released in 2015 recommend the use of specific echocardiographic parameters for the assessment of PH. Here, the tricuspid regurgitation velocity (TRV) together with echocardiographic markers of PH from three categories (the ventricles, the pulmonary artery, and the IVC/RA) are used to define the echocardiographic probability of PH being present (as either, low, intermediate or high). In 2022, the ESC updated this algorithm to include a revised haemodynamic definition of PH and also additional parameters for estimating the echocardiographic probability of PH(1). New parameters include the TAPSE/sPAP ratio as well as the combined assessment of the pulmonary artery (PA) and aortic root diameter. This retrospective audit evaluates the impact of the most recent 2022 ESC TTE PH algorithm in detecting PH in a real world cohort referred to a shared care PH centre. Method Between 2010 and 2020, a total of 306 patients referred for initial assessment of PH underwent TTE followed by RHC (mean interval 31±29 days). PH TTE probabilities were calculated using both 2015 and 2022 ESC guidance. The 2022 haemodynamic definition of PH was applied to both cohorts. The sensitivity and specificity of both 2015 and 2022 were calculated. Results The mean sample age is 67±14years (62% female). A summary of the TTE PH probability parameters is shown in Table 1. Using the 2015 ESC algorithm, the cohort comprised 24% (n=75), 23% (n=70) and 53% (161) for low, intermediate, and high TTE PH probability respectively. Within the low TTE probability group, 33% (n=25) had PH confirmed at RHC (see Figure 1). Sensitivity and specificity for the cohort is 88% and 65% respectively. The same dataset analysed using the 2022 algorithm demonstrates that 23% (n=71) has a low TTE PH probability, 19% (n=58) intermediate and 58% (n=177) a high TTE PH probability. Within the low TTE group the percentage of patients with PH at RHC was 35% (n=25) (Figure 1). Sensitivity and specificity for the 2022 TTE PH probability algorithm was 89% and 62% respectively. The introduction of the TAPSE/sPAP ratio (&amp;lt;0.55 mm/mmHg) contributed to 16 patients changing from intermediate to high TTE PH probability. Two patients with a low TTE probability demonstrated a ratio &amp;lt;0.55 mm/mmHg, of which one moved from low to intermediate probability. The PA/AR diameter led to 3 patients changing from low to intermediate TTE PH probability. Conclusion The sensitivity and specificity for the 2015 and new 2022 PH TTE probability algorithm are similar. Further developments in TTE algorithms are needed to improve the detection of PH in those thought to have a low TTE probability of PH.Table 1.0Figure 1.0

A clinician's guide to gallstones and common bile duct (CBD): A study protocol for a systematic review and evidence-based recommendations.

Gallstones are one of the most common and costly diseases of the gastrointestinal tract and occur when a combination of deposits consisting of fat or minerals accumulate in the gallbladder or common bile duct (CBD). This paper provides a comprehensive review of gallstone epidemiology, diagnosis, and management, focusing on current clinical guidelines and evidence-based approaches. A systematic literature review gathered information from various sources, including PubMed, Trip, Google Scholar, Clinical Key, and reputable medical association websites. Keywords related to gallstones, CBD stones, cholelithiasis, choledocholithiasis, and guidelines were used to extract relevant recommendations. Expert consultations and consensus meetings localized the recommendations based on the target population and available resources. The paper discusses demographic factors, dietary habits, and lifestyle influences contributing to gallstone formation. Gallstones are categorized into cholesterol and pigment types, with varying prevalences across regions. Many individuals with gallstones remain asymptomatic, but complications can lead to serious and potentially life-threatening conditions. Diagnosis relies on history, physical examination, laboratory tests, and transabdominal ultrasound. Specific predictive factors help categorize patients into high, moderate, or low probability groups for CBD stones. Evidence-based recommendations for gallstone diagnosis and management are presented, emphasizing individualized treatment plans. Surgical interventions, nonsurgical treatments like oral litholysis with UDCA, and stenting are discussed. The management of gallstones in pregnant women is also addressed, considering the potential risks and appropriate treatment options during pregnancy.

Predicting of intestinal ischemia in patients with adhesive small bowel obstruction

Aim. To detect intestinal ischemia promptly in patients with acute adhesive small bowel obstruction.Methods. A total of 124 patients with acute adhesive small bowel obstruction were studied. Logistic regression analysis was performed to determine the most significant prognostic factors for intestinal ischemia. The derived regression coefficient indicators were utilized in a scoring system.Results. Six independent prognostic factors of intestinal ischemia were identified: age, duration of pain, body temperature, white blood cell count, reduced intestinal wall contrast, and localized mesenteric edema visible on a CT scan. Regression coefficient scores were attributed to each variable associated with intestinal ischemia. The predicted occurrence of bowel ischemia was computed as a sum of scores ranging from 0 to 24. A threshold of 6 points was used to define the low-probability group (risk of bowel ischemia was 1.13%). A score between 7 and 15 determined the intermediate-probability group (the risk of intestinal ischemia was 44%). A score of ≥16 defined the high-probability group (all patients in this group had intestinal ischemia).Conclusions. The risk prediction assessment of bowel ischemia was performed with high accuracy (above 90%). This evaluation is reliable and reproducible, hence it may aid the surgeon to differentiate patients with intestinal ischemia for surgical intervention. Since ischemic disorders may be reversible, this could prevent the development of intestinal necrosis.

P055 Giant Cell Arteritis Diagnosis: Metadiagnosis by robust Bayesian estimate of strength of belief

Abstract Background/Aims Metadiagnosis expresses diagnostic belief as: (i) a numeric probability, (ii) degree of confidence in the probability estimate and (iii) defines the derived information as decision thresholds. We use this approach to stratify suspected GCA patients, by disease probability, into three classes. (a) Likely to have GCA, (b) Unlikely to have GCA, and (c) Uncertain GCA status. Methods We developed a Bayesian algorithm that computes a patient’s disease probability based on their signs, symptoms and reference-standard tests. This algorithm forms the computational engine of the first iteration of an online APP. The computational engine incorporated statistical weights (likelihood ratios) from a meta-analysis of 68 unique studies (14 037 unique patients with suspected GCA). The algorithm requires the specification of a disease prevalence. This is the “prior” probability any patient has GCA. We then update this probability incrementally with each additional item of information elicited from the questionnaire proforma (e.g. female? headache? visual abnormality? …) by incremental evidence aggregation. Finally, the outcome of the patient's reference standard test is incorporated (e.g. positive, negative, indeterminate) and a final posterior GCA probability is computed for each patient. Results Quantitative GCA risk estimate for each individual patient, and how that was altered by the result of reference standard test, produces three distinct groups: a) Low probability group - estimated risk of GCA is significantly lower than the prevalence in the cohort. The reference standard test in this group was uniformly negative.b) intermediate probability group - estimated risk of GCA is around the same as the prevalence in the cohort. The reference standard test (TAB) is almost always negative in this group, but not exclusively.c) high probability group - estimated risk of GCA far exceeds the base or population risk level, and the reference standard test (TAB) is typically confirmatory in this group. Conclusion Applying Bayesian algorithmic metadiagnosis, based on established values of how indicators of disease impact on diagnosis, allows numerical disease prediction and non-mathematically communicating the precision of diagnosis may enhance informed patient choice leading to personalised, targeted intervention. An inbuilt artificial neural network (a deep learning method feedback-loop) trains the algorithm to identify the value of all relevant indicators and so improves predictive accuracy. We plan further studies to establish how this approach could impact on patient well-being and resource utilisation. Disclosure L. Clearkin: None.

Retrospective Analysis of the Predictive Value of 18F-FDG PET/CT Metabolic Parameters for PD-L1 Expression in Cervical Cancer

Immunotherapy targeting PD-1/PD-L1 has been proven to be effective for cervical cancer treatment. To explore non-invasive examinations for assessing the PD-L1 status in cervical cancer, we performed a retrospective study to investigate the predictive value of 18F-FDG PET/CT. The correlations between PD-L1 expression, clinicopathological characteristics and 18F-FDG PET/CT metabolic parameters were evaluated in 74 cervical cancer patients. The clinicopathological characteristics included age, histologic type, tumor differentiation, FIGO stage and tumor size. The metabolic parameters included maximum standard uptake (SUVmax), mean standard uptake (SUVmean), total lesion glycolysis (TLG) and tumor metabolic volume (MTV). In univariate analysis, SUVmax, SUVmean, TLG, tumor size and tumor differentiation were obviously associated with PD-L1 status. SUVmax (rs = 0.42) and SUVmean (rs = 0.40) were moderately positively correlated with the combined positive score (CPS) for PD-L1 in Spearman correlation analysis. The results of multivariable analysis showed that the higher SUVmax (odds ratio = 2.849) and the lower degree of differentiation (Odds Ratio = 0.168), the greater probability of being PD-L1 positive. The ROC curve analysis demonstrated that when the cut-off values of SUVmax, SUVmean and TLG were 10.45, 6.75 and 143.4, respectively, the highest accuracy for predicting PD-L1 expression was 77.0%, 71.6% and 62.2%, respectively. The comprehensive predictive ability of PD-L1 expression, assessed by combining SUVmax with tumor differentiation, showed that the PD-L1-negative rate was 100% in the low probability group, whereas the PD-L1-positive rate was 84.6% in the high probability group. In addition, we also found that the H-score of HIF-1α was moderately positively correlated with PD-L1 CPS (rs = 0.51). The SUVmax and differentiation of the primary lesion were the optimum predictors for PD-L1 expression in cervical cancer. There was a great potential for 18F-FDG PET/CT in predicting PD-L1 status and selecting cervical cancer candidates for PD1/PD-L1 immune checkpoint therapy.

P354 Application of the clinical decision support tool to predict treatment outcomes in Crohn’s Disease patients treated with vedolizumab subcutaneous formulation

Abstract Background There is a need to identify Crohn’s Disease (CD) patients who will obtain most clinical benefit from treatment with vedolizumab (VDZ), an anti-α4β7 integrin inhibitor for the treatment of ulcerative colitis and Crohn’s Disease (CD). Previously, a clinical decision support tool (CDST) has been developed and validated to guide treatment decisions in CD patients (pts) treated with intravenous VDZ.1 In this study, we aimed to test the ability of the CDST to predict clinical outcomes in CD pts receiving maintenance treatment with the subcutaneous (SC) formulation of VDZ. Methods Pts with moderate to severe CD receiving maintenance treatment with VDZ SC in the VISIBLE 2 study were categorized using the CDST into low (≤13 points), intermediate (&amp;gt;13 and ≤19 points) and high response probability groups (&amp;gt;19 points) based on the scoring system detailed in Table 1. Clinical outcomes evaluated included clinical remission: CD Activity Index (CDAI) ≤ 150 at Week 6, 14, 30, and 52, and enhanced clinical response: decrease from baseline in CDAI score ≥ 100 points at Week 52. All outcomes were evaluated as observed. Results There were 275 pts who completed induction treatment with VDZ 300 mg IV and continued into maintenance treatment with VDZ 108 mg SC until Week 52. Using the CDST, at baseline, 14 pts (5.1%) had a low, 98 (35.6%) had an intermediate, and 163 (59.3%) had a high probability of treatment response with VDZ. Due to the low number of pts in the low probability group, the low and intermediate groups were combined. At Week 6, 99 pts (61.1%) in the high probability group had achieved clinical remission vs 38 pts (33.9%) in the low/intermediate probability group (Fig 1). Rates of clinical remission in the high probability group continued to exceed those of the low/intermediate group through until Week 52 when 89 pts (86.4%) in the high probability group were in clinical remission vs 43 pts (79.6%) in the low/intermediate probability group (Fig 1). In the high probability group, 97 pts (94.2%) had an enhanced clinical response at Week 52 compared with 46 pts (85.2%) in the low/intermediate group. Conclusion Compared with the low/intermediate group, pts categorized by the CDST as having the highest probability of treatment response to VDZ achieved clinical remission sooner, as early as Week 6. These findings provide further confirmation of the CDST as a means of identifying pts with CD likely to benefit from treatment with VDZ in either IV or SC formulations.

The impact of donor consent mechanism on organ procurement organization performance in the United States

Lack of donor organ availability represents a major limitation to the success of solid organ transplantation. The Scientific Registry of Transplant Recipients (SRTR) publishes performance reports of organ procurement organizations (OPO) in the United States, but does not stratify by the mechanism of donor consent, namely first-person authorization (organ donor registry) and next-of-kin authorization. This study aimed to report the trends in deceased organ donation in the United States and assess the regional differences in OPO performance after accounting for the different mechanisms of donor consent. The SRTR database was queried for all eligible deaths (2008-2019) which were then stratified based on the mechanism of donor authorization. Multivariable logistic regression was performed to assess the probability of organ donation across OPOs based on specific donor consent mechanisms. Eligible deaths were divided into 3 cohorts based on the probability to donate. Consent rates at the OPO level were calculated for each cohort. Organ donor registration among adult eligible deaths in the U.S. increased over time (2008: 10% vs 2019: 39%, p < 0.001), coincident with a decline in next-of-kin authorization rates (2008: 70% vs 2019: 64%, p < 0.001). At the OPO level, the increased organ donor registration was associated with lower next-of-kin authorization rates. Among eligible deaths with medium- and low-probability of donation, recruitment was highly variable across OPO's, ranging from 36% to 75% in the medium-probability group (median 54%, IQR 50%-59%) and 8% and 73% in the low-probability group (median 30%, IQR 17%-38%). Significant variability exists across OPOs in the consent of potentially persuadable donors after adjusting for population demographic differences and the mechanism of consent. Current metrics may not truly reflect OPO performance as they do not account for consent mechanism. There is further opportunity for improvement in deceased organ donation through targeted initiatives across OPOs, modeled after regions with the best performance.

In Silico Analysis of MicroRNA Expression Data in Liver Cancer.

Abnormal miRNA expression has been evidenced to be directly linked to HCC initiation and progression. This study was designed to detect possible prognostic, diagnostic, and/or therapeutic miRNAs for HCC using computational analysis of miRNAs expression. Methods: miRNA expression datasets meta-analysis was performed using the YM500v2 server to compare miRNA expression in normal and cancerous liver tissues. The most significant differentially regulated miRNAs in our study undergone target gene analysis using the mirWalk tool to obtain their validated and predicted targets. The combinatorial target prediction tool; miRror Suite was used to obtain the commonly regulated target genes. Functional enrichment analysis was performed on the resulting targets using the DAVID tool. A network was constructed based on interactions among microRNAs, their targets, and transcription factors. Hub nodes and gatekeepers were identified using network topological analysis. Further, we performed patient data survival analysis based on low and high expression of identified hubs and gatekeeper nodes, patients were stratified into low and high survival probability groups. Results: Using the meta-analysis option in the YM500v2 server, 34 miRNAs were found to be significantly differentially regulated (P-value ⩽ .05); 5 miRNAs were down-regulated while 29 were up-regulated. The validated and predicted target genes for each miRNA, as well as the combinatorially predicted targets, were obtained. DAVID enrichment analysis resulted in several important cellular functions that are directly related to the main cancer hallmarks. Among these functions are focal adhesion, cell cycle, PI3K-Akt signaling, insulin signaling, Ras and MAPK signaling pathways. Several hub genes and gatekeepers were found that could serve as potential drug targets for hepatocellular carcinoma. POU2F1 and PPARA showed a significant difference between low and high survival probabilities (P-value ⩽ .05) in HCC patients. Our study sheds light on important biomarker miRNAs for hepatocellular carcinoma along with their target genes and their regulated functions.

IMproving PULmonary hypertension Screening by Echocardiography: IMPULSE

BackgroundThe world symposium on pulmonary hypertension (PH) has proposed that PH be defined as a mean pulmonary artery pressure (mPAP) > 20 mmHg as assessed by right heart catheterisation (RHC). Transthoracic echocardiography (TTE) is an established screening tool used for suspected PH. International guidelines recommend a multi-parameter assessment of the TTE PH probability although effectiveness has not been established using real world data.Study aimsTo determine accuracy of the European Society of Cardiology (ESC) and British Society of Echocardiography (BSE) TTE probability algorithm in detecting PH in patients attending a UK PH centre. To identify echocardiographic markers and revised algorithms to improve the detection of PH in those with low/intermediate BSE/ESC TTE PH probability.MethodsTTE followed by RHC (within 4 months after) was undertaken in patients for suspected but previously unconfirmed PH. BSE/ESC PH TTE probabilities were calculated alongside additional markers of right ventricular (RV) longitudinal and radial function, and RV diastolic function. A refined IMPULSE algorithm was devised and evaluated in patients with low and/or intermediate ESC/BSE TTE PH probability.ResultsOf 310 patients assessed, 236 (76%) had RHC-confirmed PH (average mPAP 42.8 ± 11.7). Sensitivity and specificity for detecting PH using the BSE/ESC recommendations was 89% and 68%, respectively. 36% of those with low BSE/ESC TTE probability had RHC-confirmed PH and BSE/ESC PH probability parameters did not differ amongst those with and without PH in the low probability group. Conversely, RV free wall longitudinal strain (RVFWLS) was lower in patients with vs. without PH in low BSE/ESC probability group (− 20.6 ± 4.1% vs − 23.8 ± 3.9%) (P < 0.02). Incorporating RVFWLS and TTE features of RV radial and diastolic function (RVFAC and IVRT) within the IMPULSE algorithm reduced false negatives in patients with low BSE/ESC PH probability by 29%. The IMPULSE algorithm had excellent specificity and positive predictive value in those with low (93%/80%, respectively) or intermediate (82%/86%, respectively) PH probability.ConclusionExisting TTE PH probability guidelines lack sensitivity to detect patients with milder haemodynamic forms of PH. Combining additional TTE makers assessing RV radial, longitudinal and diastolic function enhance identification of milder forms of PH, particularly in those who have a low BSE/ESC TTE PH probability.