Gold Standard Research Articles

Concordance Rate of Pre-Operative Radiological Stage with Postoperative Pathological Stage in Colon Cancer

Aim: This study aimed to assess the concordance rate between pre-operative radiological staging using CT imaging and postoperative pathological staging in patients with colon cancer. Methodology: A prospective observational study was conducted at the Oncology Department of Jinnah Postgraduate Medical Center, Pakistan, with ethical committee approval between February 2023 to July 2023. Inclusion criteria involved patients diagnosed with colon adenocarcinoma aged >18 receiving treatment at the center, while exclusion criteria comprised unconfirmed colon cancer, lack of consent, benign colonic polyps, metastatic cancer, chemotherapy recipients, and incomplete data. Sample size estimation yielded 227 patients. Recruitment used consecutive sampling, and data were collected using a predefined proforma. CT scans were performed, and T-stage was assessed by radiologists and pathologists. Histological analysis followed established guidelines, with final pathology serving as the gold standard. Results: The diagnostic accuracy of CT imaging was evaluated, with statistically significant concordance found between CT scans and histopathological diagnoses (p-value = 0.046). CT scans demonstrated a sensitivity of 57.14% for Stage I tumors and a specificity of 88.18% for Stage II-III tumors. The positive predictive value (PPV) was 13.3%, and the negative predictive value (NPV) was 98.48%, resulting in an overall accuracy of 87.22%. These findings suggest that CT imaging is valuable for identifying Stage II-III tumors, exhibiting good specificity and NPV, although sensitivity and PPV for Stage I tumors were comparatively lower. Chi-square testing confirmed the statistical significance of these results (p-value ≤ 0.05) Conclusion: This study highlights the utility of CT imaging in pre-operative staging of colon cancer, particularly for Stage II-III tumors, where it exhibits notable accuracy. However, improvements may be needed to enhance sensitivity and PPV for Stage I tumors. Keywords: Colon cancer, CT imaging, pathological staging, concordance rate, diagnostic accuracy.

#758 NGAL dipstick for peritonitis: bridging the gap between rapid assessment and clinical efficiency in peritoneal dialysis

Abstract Background and Aims Neutrophil gelatinase-associated lipocalin (NGAL) is a versatile protein known for its multifunctional roles, extending beyond its conventional use as a biomarker. It actively participates in crucial biological processes such as inflammation, proliferation, and migration. This study seeks to evaluate NGALds, a recently developed dipstick test, in comparison to the established laboratory method (NGALlab) for the early detection of peritonitis related to peritoneal dialysis (PD). The focus of the investigation lies in analyzing peritoneal fluid to develop a rapid and effective diagnostic tool, aiming to enhance the management of peritonitis. Method A retrospective analysis was undertaken to validate diagnostic accuracy, utilizing parallel samples obtained from peritoneal effluents. Samples were obtained from both PD stable patients undergoing routine analysis and from PD patients with suspected or confirmed peritonitis. The assessment of NGALds involved a direct comparison with the established NGALlab. Peritoneal NGALlab quantification was conducted using the BioPorto test, employing a particle-enhanced turbidimetric immunoassay. The NGALds, a rapid semi-quantitative assay, utilized colorimetric test strips and an antibody sandwich lateral flow dipstick test. The greatest value of NGAL detected by dipstick is 600 μg/L. Statistical analyses, including Spearman rank correlation coefficients (Rs), were performed with SPSS Statistics 26.0 software. Additionally, ROC analysis was carried out using white cell count and percentage of Neutrophils in peritoneal fluids as the gold standard. Results Among the 301 peritoneal effluent samples analyzed, 156 were diagnosed with suspected peritonitis using NGALlab and ISPD criteria. Each sample underwent analyses with both NGALlab and NGALds. As depicted in Fig. 1, NGALds exhibited a robust correlation with NGALlab categories (Rs = 0.876, P < 0.001), accurately identifying 96% (150 out of 156) of peritonitis cases. Discrepancies between NGALlab and NGALds were most evident when NGAL values exceeded the 600 μg/L threshold. Nevertheless, these variations did not impact clinical significance, as both methods consistently diagnosed elevated NGAL values indicative of peritonitis. After ROC analysis, which yielded an AUC of 0.82 (p < 0.001) (Fig. 2), the Youden Index was employed to identify a threshold value of 100 μg/L for the diagnosis of suspected peritonitis. Importantly, the application of this threshold to NGALds demonstrated a positive predictive value of 0.64 and a negative predictive value of 0.87. Conclusion In conclusion, our study reinforces the significant correlation between NGAL values obtained through the laboratory standard (NGALlab) and the novel NGAL dipstick test (NGALds). Notably, NGALds exhibited high efficacy, accurately identifying 96% of peritonitis cases diagnosed by NGALlab. This robust performance positions the NGAL dipstick as a valuable and accessible alternative for rapid assessment in patients exhibiting symptoms indicative of peritonitis. The user-friendly attributes of NGALds not only make it a practical diagnostic tool but also a patient-centric one. Furthermore, the high negative predictive value provides confidence in considering NGALds as a frontline diagnostic tool for suspected peritonitis. The ease of use and prompt results open a promising avenue for improving clinical workflows, offering an opportunity for expedited and efficient peritonitis diagnosis. For instance, NGALds could find utility in centres where NGAL is unavailable in the laboratory or at the patient's home.

#1454 Usefulness of the clinical frailty scale in Dutch patients with end-stage kidney disease

Abstract Background and Aims Frailty is common in end-stage kidney disease (ESKD) patients which may benefit from advance care planning. Currently there are multiple frailty screening instruments available, of which the Frailty Index is commonly used to estimate frailty in ESKD patients. The Clinical Frailty Scale is a less time consuming alternative to estimate frailty. We aimed to investigate the performance of the Clinical Frailty Scale as a screening tool for frailty in an ESKD population. Method A cross-sectional observational study was performed at Kidney Centre Apeldoorn. Included patients received haemodialysis, peritoneal dialysis, pre-dialysis care, or conservative treatment. Frailty was assessed with both the Frailty Index and the Clinical Frailty Scale. The Frailty Index consisted of 38 components considering activities of daily living, physical aspects, psychosocial factors, comorbidities, and functional tests. The functional tests included grip strength, walking speed, and cognitive functioning measured by the Mini Mental State Examination. The Frailty Index was calculated by dividing the number of deficits by the total number of components measured. A patient with a Frailty Index ≥0.25 was considered frail. The Clinical Frailty Scale consisted of nine classes varying from very fit to terminally ill. Patients who scored 4 on the Clinical Frailty Scale were considered vulnerable. Patients with a score ≥5 were considered frail. Nephrologists not familiar with the Clinical Frailty Scale were asked to complete the Clinical Frailty Scale after medical consultation. The sensitivity, specificity and area under the curve (AUC) of the Clinical Frailty Scale were determined. The Frailty Index was used as the golden standard. Results In total, 144 patients were included of whom 60 (41.7%) were frail according to the Frailty Index. The mean age was 67.4 years (SD±13.5) and 56 (38.9%) were female. Overall, 72 patients (50.0%) were treated by haemodialysis, 13 (9.0%) by peritoneal dialysis, 6 (4.2%) received conservative treatment, and 53 (36.8%) were pre-dialysis patients. According to the Frailty Index, 55.6% of the haemodialysis patients were frail compared to 20.8% of the pre-dialysis patients. The Clinical Frailty Scale identified 37 (25.7%) patients as frail and 17 (11.8%) patients as vulnerable. The cut-off point of the Clinical Frailty Scale for vulnerable (≥4) had a sensitivity of 63.3%, a specificity of 81.0%, and AUC of 0.72. The cut-off point of the Clinical Frailty Scale for frail (≥5) had a sensitivity of 50.0%, a specificity of 91.7%, and AUC of 0.71. Conclusion Prevalence of frailty was high in patients with ESKD. Although the Clinical Frailty Scale is a quick and easy tool for the identification of frailty in ESKD patients, the sensitivity of the Clinical Frailty Scale was too low to implement it in daily clinical practice. Sensitivity might be increased by training of nephrologists in using the Clinical Frailty Scale.

#2575 GFR in onco-nephrology: the innovative use of measured GFR in the management of oncological solitary kidney

Abstract Background and Aims A reliable assessment of renal function in onco-nephrology and especially in oncological solitary kidney (SK) is of paramount importance. Nowadays, the use of estimated GFR is predominant in clinical practice because it is fast, easy and cost-effective. However, eGFR harbours a significant error in comparison to gold standards methods using exogenous molecules such as iohexol or iothalamate (mGFR). Aim of this study was to determine the extent of the error of eGFR compared to the mGFR in onco-nephrological patients with a solitary kidney (SK) after nephrectomy (RN). Method A total consecutive cohort of 200 SK who previous underwent RN for renal cancer was enrolled in a single tertiary institution from 2017 to 2023 to compare the most used eGFR formulas (MDRD, CKD-EPI crea 2012, CKD-EPI 2021 crea, CKD-EPI cyst 2012, CKD-EPI Cyst 2021, CKD-EPI cyst/creat, Cockroft-Gault) with a mGFR method using Iohexol Plasma Clearance. Clinical and laboratory data were reported for each patient. True positives (TP) and False positives, (FP) were classified in CKD stages based on eGFR and mGFR. Comparisons between groups were performed using Wilcoxon ranks sum test for numerical variables and Pearson's Chi square test for categorical ones. Results Overall median age was 67 years (IQR: 56.75), median BMI 24.8 (IQR: 22.8; 27.7), Male: 74.9%,F: 25.1% Diabetes: 10.9% Hypertension: 53.8%, CKD stage I: 3.7%, II: 25.5%, IIIA:28,IIIB: 27.5%, IV: 13.4%, V: 1.74%, mean Creatinine:1,46 mg/dl (1.16-1,84), cystatin: 1.23 (0.95-1.56). Surprisingly, SK cohort harboured a non-negligible errors in each CKD class with a huge discrepancy between the eGFR formulas and the gold standard method (Figs 1 and 2), suggesting the great relevance of mGFR in the clinical decision making algorithm. Conclusion The use of mGFR in nephrectomized patients for RC remains fundamental to avoid misleading evaluations and to perform correct personalized pharmacological therapies.

Hallucination Rates and Reference Accuracy of ChatGPT and Bard for Systematic Reviews: Comparative Analysis.

Large language models (LLMs) have raised both interest and concern in the academic community. They offer the potential for automating literature search and synthesis for systematic reviews but raise concerns regarding their reliability, as the tendency to generate unsupported (hallucinated) content persist. The aim of the study is to assess the performance of LLMs such as ChatGPT and Bard (subsequently rebranded Gemini) to produce references in the context of scientific writing. The performance of ChatGPT and Bard in replicating the results of human-conducted systematic reviews was assessed. Using systematic reviews pertaining to shoulder rotator cuff pathology, these LLMs were tested by providing the same inclusion criteria and comparing the results with original systematic review references, serving as gold standards. The study used 3 key performance metrics: recall, precision, and F1-score, alongside the hallucination rate. Papers were considered "hallucinated" if any 2 of the following information were wrong: title, first author, or year of publication. In total, 11 systematic reviews across 4 fields yielded 33 prompts to LLMs (3 LLMs×11 reviews), with 471 references analyzed. Precision rates for GPT-3.5, GPT-4, and Bard were 9.4% (13/139), 13.4% (16/119), and 0% (0/104) respectively (P<.001). Recall rates were 11.9% (13/109) for GPT-3.5 and 13.7% (15/109) for GPT-4, with Bard failing to retrieve any relevant papers (P<.001). Hallucination rates stood at 39.6% (55/139) for GPT-3.5, 28.6% (34/119) for GPT-4, and 91.4% (95/104) for Bard (P<.001). Further analysis of nonhallucinated papers retrieved by GPT models revealed significant differences in identifying various criteria, such as randomized studies, participant criteria, and intervention criteria. The study also noted the geographical and open-access biases in the papers retrieved by the LLMs. Given their current performance, it is not recommended for LLMs to be deployed as the primary or exclusive tool for conducting systematic reviews. Any references generated by such models warrant thorough validation by researchers. The high occurrence of hallucinations in LLMs highlights the necessity for refining their training and functionality before confidently using them for rigorous academic purposes.

A comparison of gelatine surrogates for wound track assessment.

The use of ordnance gelatine has been widespread in the field of ballistics as a simulant for soft tissue when assessing ballistic threats. However, the traditional method of preparing ordnance gelatine is time-consuming and requires precision to ensure that the final mold meets the required specifications. Furthermore, temperature control is necessary post-production, and there are limitations on its usage duration. To address these issues, manufacturers have developed pre-mixed, gelatine-like products that are stable at room temperature and require less preparation time. Nonetheless, it is uncertain whether these new products can perform in the same manner as the gold standard of ordnance gelatine. This study used five types of blocks, including ordnance gelatine (10% and 20%), Clear Ballistics (10% and 20%) and Perma-Gel (10%) and subjected them to 9mm, 0.380 Auto fired from a universal receiver and a 5.56 × 45mm ammunition fired by a certified firearms instructor. Delta-V and total energy dissipation were measured after each test using data collected from ballistic chronographs placed in front of and behind each block. High-speed video was recorded, and a cut-down analysis conducted. The findings revealed variations in energy dissipation and fissure formation within the block, with greater energy based on fissure formation observed in the ordnance gelatine. Additionally, the high-speed video showed the occurrence of secondary combustions occurring in the premixed gelatines.

X-ray polarization measurement of the gold standard of radio-quiet active galactic nuclei: NGC 1068

NGC 1068 is the most observed radio-quiet active galactic nucleus (AGN) in polarimetry, yet its high-energy polarization has never been probed before due to a lack of dedicated polarimeters. Using the first X-ray polarimeter sensitive enough to measure the polarization of AGNs, we want to probe the orientation and geometric arrangement of (sub)parsec-scale matter around the X-ray source. We used the Imaging X-ray Polarimetry Explorer (IXPE) satellite to measure, for the first time, the 2-8 keV polarization of NGC 1068. We pointed IXPE at the target for a net exposure time of 1.15 Ms, in addition to using two Chandra snapshots of sim 10 ks each in order to account for the potential impact of several ultraluminous X-ray sources (ULXs) within IXPE's field of view. We measured a 2 -- 8 keV polarization degree of 12.4&lt;!PCT!&gt; pm 3.6&lt;!PCT!&gt; and an electric vector polarization angle of 101$^ pm 8$^ at a 68&lt;!PCT!&gt; confidence level. If we exclude the spectral region containing bright Fe K lines and other soft X-ray lines where depolarization occurs, the polarization fraction rises to 21.3&lt;!PCT!&gt; pm 6.7&lt;!PCT!&gt; in the 3.5 -- 6.0 keV band, with a similar polarization angle. The observed polarization angle is found to be perpendicular to the parsec-scale radio jet. Using a combined Chandra and IXPE analysis plus multiwavelength constraints, we estimated that the circumnuclear “torus” may sustain a half-opening angle of 50 -- 55$^ (from the vertical axis of the system). Thanks to IXPE, we have measured the X-ray polarization of NGC 1068 and found comparable results, both in terms of the polarization angle orientation with respect to the radio jet and the torus half-opening angle, to the X-ray polarimetric measurement achieved for the other archetypal Compton-thick AGN: the Circinus galaxy. Probing the geometric arrangement of parsec-scale matter in extragalactic objects is now feasible thanks to X-ray polarimetry.

Inflammatory fibroid polyp– a rare aetiology for adult ileocolic intussusception

We report a case of an adult ileocolic intussusception secondary to an inflammatory fibroid polyp (IFP), a rare and unexpected association between a surgical condition, and an underlying histopathological process. Intussusception is an uncommon surgical diagnosis in adults, and an IFP is rare mesenchymal tumour. Surgical intervention of the intussusception in an adult patient, given the uncertain aetiology of the lead point, is recommended as gold standard.

Large language model based framework for automated extraction of genetic interactions from unstructured data.

Extracting biological interactions from published literature helps us understand complex biological systems, accelerate research, and support decision-making in drug or treatment development. Despite efforts to automate the extraction of biological relations using text mining tools and machine learning pipelines, manual curation continues to serve as the gold standard. However, the rapidly increasing volume of literature pertaining to biological relations poses challenges in its manual curation and refinement. These challenges are further compounded because only a small fraction of the published literature is relevant to biological relation extraction, and the embedded sentences of relevant sections have complex structures, which can lead to incorrect inference of relationships. To overcome these challenges, we propose GIX, an automated and robust Gene Interaction Extraction framework, based on pre-trained Large Language models fine-tuned through extensive evaluations on various gene/protein interaction corpora including LLL and RegulonDB. GIX identifies relevant publications with minimal keywords, optimises sentence selection to reduce computational overhead, simplifies sentence structure while preserving meaning, and provides a confidence factor indicating the reliability of extracted relations. GIX's Stage-2 relation extraction method performed well on benchmark protein/gene interaction datasets, assessed using 10-fold cross-validation, surpassing state-of-the-art approaches. We demonstrated that the proposed method, although fully automated, performs as well as manual relation extraction, with enhanced robustness. We also observed GIX's capability to augment existing datasets with new sentences, incorporating newly discovered biological terms and processes. Further, we demonstrated GIX's real-world applicability in inferring E. coli gene circuits.

Meaning of ACR-TIRADS recommendation in favor of follow-up rather than FNAC in thyroid nodules.

Thyroid Imaging Reporting and Data Systems (TIRADSs) have been largely diffused for their high accuracy in risk stratification of thyroid nodules (TNs) and their selection for fine-needle aspiration cytology (FNAC). The most popular TIRADSs are ACR-, EU-, and K-TIRADS, with some discrepancies each other. One major difference is that ACR-TIRADS includes a recommendation in favor of follow-up in TNs having a major diameter insufficient to indicate FNAC. The present study aimed to explore prevalence and significance of this recommendation. EU- and K-TIRADS were used as comparator. A retrospective series of thyroidectomies was searched according to a pre-defined protocol. The study period was 2019-2023. Preoperative ultrasound images were reviewed by radiologists blinded of clinical data. Matching of TIRADS and histology was performed later. Histology was the gold standard. The study series included 39 TNs classified as category 3, 4, or 5 and assessed for follow-up according to ACR-TIRADS. The overall cancer frequency was 25.6%, being 13% in category 3, 20% in category 4, and 83.3% in category 5. The category assessment according to ACR-, EU-, and K-TIRADS was not significantly different. EU-TIRADS indicated FNAC in 10 TNs of which two cancers and eight benign lesions. K-TIRADS recommended FNAC in 32 TNs of which seven cancers and 25 benign lesions. TNs assessed for follow-up according to ACR-TIRADS are cancer in one-fourth of cases. EU- and, especially, K-TIRADS allow us to select for FNAC cancers, with the burden of non-negligible frequency of unnecessary FNACs.

New sagittal abdominal diameter and transverse abdominal diameter based equations to estimate visceral fat area in type 2 diabetes patients

ObjectiveComputed Tomography (CT) or Magnetic Resonance Imaging (MRI) are considered gold standards for measuring visceral fat area (VFA). However, their relatively high prices and potential radiation exposure limit their widespread use in clinical practice and everyday life. Therefore, our study aims to develop a VFA estimated equation based on sagittal abdominal diameter (SAD) and transverse abdominal diameter (TAD) using anthropometric indexes. To the best of our knowledge, there have been limited studies investigating this aspect thus far.MethodsThis study was designed as a cross-sectional, retrospective cohort survey. A total of 288 patients (167 males and 121 females) aged 18–80 with type 2 diabetes (T2D) were consecutively collected from a multicenter hospital, and VFA was measured by CT. Subsequently, variables highly correlated with VFA were screened through general linear correlation analysis. A stepwise regression analysis was then conducted to develop a VFA estimated equation. Discrepancies between the estimated and actual VFA values were assessed using the Bland-Altman method to validate the accuracy of the equation.ResultsIn the female T2D population, triglyceride (TG), SAD, TAD were found to be independently correlated with VFA; in the male T2D population, BMI, TG, SAD and TAD showed independent correlations with VFA. Among these variables, SAD exhibited the strongest correlation with VFA (r = 0.83 for females, r = 0.88 for males), followed by TAD (r = 0.69 for females, r = 0.79 for males). Based on these findings, a VFA estimated equation was developed for the T2D population: VFA (male) =-364.16 + 15.36*SAD + 0.77*TG + 9.41*TAD − 5.00*BMI (R2 = 0.75, adjusted R2 = 0.74); VFA(female)=-170.87 + 9.72*SAD-24.29*(TG^-1) + 3.93*TAD (R2 = 0.69, adjusted R2 = 0.68). Both models demonstrated a good fit. The Bland-Altman plot indicated a strong agreement between the actual VFA values and the estimated values, the mean differences were close to 0, and the majority of differences fell within the 95% confidence interval.ConclusionsIn the T2D population, a VFA estimated equation is developed by incorporating SAD and TAD along with other measurement indices. This equation demonstrates a favorable estimated performance, suggesting to the development of novel and practical VFA estimation models in the future study.

A Proposal of a New Tool for the Assessment of Damage in Behçet Syndrome Uveitis: Cerrahpasa Ocular Damage Grading System

ABSTRACT Introduction/Objective There is currently no tool available to assess the severity of damage in uveitis due to Behçet’s syndrome (BS). In this preliminary study, we developed a new grading system to evaluate ocular damage and assessed it in a prospective cohort. Methods A specialist in BS uveitis (YO) developed a grading system for ocular damage with five grades based on the extent of damage in the posterior segment. YO trained a senior and general ophthalmologist with sample fundus images. BS patients who had undergone color fundus photography during their routine visits in attack-free periods were included in the study. The color fundus photos of this prospective cohort were evaluated blindly by YO and his trainees using the new grading tool. Inter and intra-observer agreement between the graders were assessed by Cohen’s kappa analysis. The evaluation of YO was considered as the gold standard. Results One hundred eighty-five eyes of 108 (29 F/79 M) patients with BS uveitis were graded for damage by two investigators. Their mean age was 38,58 years and their median ocular disease duration was 13 years. The gold standard and the two investigators exhibited substantial concordance with the ocular damage grading system. The inter- and intra-observer agreement were also almost perfect. Conclusion The newly developed ocular damage grading system enables the standardization of damage severity in BS uveitis. It is imperative to conduct internal and external validations across diverse cohorts. Furthermore, future studies should investigate its correlation with other multimodal imaging methods such as fluorescein angiography and optical coherence tomography.

Evaluating the precision of an online visual acuity test tool.

The aim of this study was to assess the precision of a web-based tool in measuring visual acuity (VA) in ophthalmic patients, comparing it to the traditional in-clinic evaluation using a Snellen chart, considered the gold standard. We conducted a prospective and in-clinic validation comparing the Eyecare Visual Acuity Test® to the standard Snellen chart, with patients undergoing both tests sequentially. Patients wore their standard spectacles as needed for both tests. Inclusion criteria involved individuals above 18 years with VA equal to or better than +1 logMar (20/200) in each eye. VA measurements were converted from Snellen to logMAR, and statistical analyses included Bland-Altman and descriptive statistics. The study, encompassing 322 patients and 644 eyes, compared Eyecare Visual Acuity Test® to conventional methods, revealing a statistically insignificant mean difference (0.01 logMAR, P = 0.1517). Bland-Altman analysis showed a narrow 95% limit of agreement (0.22 to -0.23 logMAR), indicating concordance, supported by a significant Pearson correlation (r = 0.61, P < 0.001) between the two assessments. The Eyecare Visual Acuity Test® demonstrates accuracy and reliability, with the potential to facilitate home monitoring, triage, and remote consultation. In future research, it is important to validate the Eyecare Visual Acuity Test® accuracy across varied age cohorts, including pediatric and geriatric populations, as well as among individuals presenting with specific comorbidities like cataract, uveitis, keratoconus, age-related macular disease, and amblyopia.

Design of a bi-directional methodology for automated assessment of compliance to continuous application of clinical guidelines, and its evaluation in the type 2 diabetes domain.

We introduce a new approach for automated guideline-based-care quality assessment, the bidirectional knowledge-based assessment of compliance (BiKBAC) method, and the DiscovErr system, which implements it. Our methodology compares the guideline's Asbru-based formal representation, including its intentions, with the longitudinal medical record, using a top-down and bottom-up approach. Partial matches are resolved using fuzzy temporal logic. The system was evaluated in the type 2 Diabetes management domain, comparing it to three expert clinicians, including two diabetes experts. The system and the experts commented on the management of 10 patients, randomly selected from 2,000 diabetes patients. On average, each record spanned 5.23 years; the data included 1,584 medical transactions. The system provided 279 comments. The experts made 181 different unique comments. The completeness (recall) of the system was 91% when the gold standard was comments made by at least two of the three experts, and 98%, compared to comments made by all three experts. The experts also assessed all of the 114 medication-therapy-related comments, and a random 35% of the 165 tests-and-monitoring-related comments. The system's correctness (precision) was 81%, compared to comments judged as correct by both diabetes experts, and 91%, compared to comments judged as correct by one diabetes expert and at least as partially correct by the other. 89% of the comments were judged as important by both diabetes experts, 8% were judged as important by one expert, and 3% were judged as less important by both experts. Adding the validated system comments to the experts' comments, the completeness scores of the experts were 75%, 60%, and 55%; the expert correctness scores were respectively 99%, 91%, and 88%. Thus, the system could be ranked first in completeness and second in correctness. We conclude that systems such as DiscovErr can effectively assess the quality of continuous guideline-based care.

A prospective observational comparative study to compare the diagnostic efficacy of the Fenyo Lindberg scoring system and Yash scoring system in patients of acute appendicitis in tertiary care hospitals in central India

Background Acute appendicitis is a typical surgical emergency requiring prompt and accurate diagnosis for timely intervention. This prospective observational comparative study aims to assess the diagnostic efficacy of two scoring systems, the Yash scoring system and the Fenyo-Lindberg scoring system, compared to the gold standard of histopathological diagnosis. The study is conducted at A.V.B.R.H., a tertiary care hospital in Central India, focusing on providing valuable insights into the comparative performance of these scoring systems in the local patient population. Methods The study adopts a prospective observational comparative design, enrolling clinically diagnosed cases of acute appendicitis from the outpatient and inpatient departments of the Surgery department at A.V.B.R.H. Patients willing to undergo surgery are included. At the same time, those with complicating factors or contraindications are excluded. Data collection involves thorough clinical evaluations, scoring system assessments, and comprehensive investigations, with histopathology as the reference standard. Statistical analyses include descriptive statistics, comparative analyses, primary outcome assessments, and regression analyses, ensuring a robust evaluation of the diagnostic efficacy of the scoring systems. Expected Outcome Anticipated outcomes include a comprehensive understanding of the diagnostic efficacy of the Yash and Fenyo-Lindberg scoring systems in acute appendicitis. The study aims to identify which scoring system demonstrates superior accuracy, sensitivity, and specificity, providing valuable information for clinical decision-making. The results will contribute to optimizing diagnostic protocols for acute appendicitis, potentially influencing patient management and surgical interventions. This study’s findings are expected to be relevant to the local setting and broader contexts, enhancing the knowledge surrounding acute appendicitis diagnosis.

Clinical prediction model for MODY type diabetes mellitus in children

BACKGROUND: MODY (maturity-onset diabetes of the young) is a rare monogenic form of diabetes mellitus, the gold standard of diagnosis is mutations detection in the genes responsible for the development of this form diabetes. Genetic test is expensive and takes a lot of time. The diagnostic criteria for MODY are well known. The development of clinical decision support system (CDSS) which allows physicians based on clinical data to determine who should have molecular genetic testing is relevant.AIM: Provided a retrospective analysis of clinical data of the patients with T1DM and MODY, from 0 to 18 years old, regardless of the duration of the disease to develop the model. Based on clinical data, a feedforward neural network (NN) was implemented - a multilayer perceptron.MATERIALS AND METHODS: Development of the most effective algorithm for predicting MODY in children based on available clinical indicators of 1710 patients with diabetes under the age of 18 years using a multilayer feedforward neural network.RESULTS: The sample consisted of 1710 children under the age of 18 years with T1DM (78%) and MODY (22%) diabetes. For the final configuration of NS the following predictors were selected: gender, age at passport age, age at the diagnosis with DM, HbA1c, BMI SDS, family history of DM, treatment. The performance (quality) assessment of the NN was carried out on a test sample (the area under the ROC (receiver operating characteristics) curve reached 0.97). The positive predictive value of PCPR was achieved at a cut-off value of 0.40 (predicted probability of MODY diabetes 40%). At which the sensitivity was 98%, specificity 93%, PCR with prevalence correction was 78%, and PCR with prevalence correction was 99%, the overall accuracy of the model was 94%.Based on the NN model, a CDSS was developed to determine whether a patient has MODY diabetes, implemented as an application.CONCLUSION: The clinical prediction model MODY developed in this work based on the NN, uses the clinical characteristic available for each patient to determine the probability of the patient having MODY. The use of the developed model in clinical practice will assist in the selection of patients for diagnostic genetic testing for MODY, which will allow for the efficient allocation of healthcare resources, the selection of personalized treatment and patient monitoring.

Performance of artificial intelligence versus clinicians on the detection of contact between mandibular third molar and inferior alveolar nerve

AbstractPurposeThis study aimed to assess the performance of the ResNet‐50 deep learning algorithm in classifying panoramic images to determine contact between mandibular third molars and inferior alveolar nerve (IAN), comparing its performance with newly graduated dentists and oral and maxillofacial surgery specialists.MethodsPanoramic radiographs of mandibular third molars were retrieved from the Radiology Department, School of Dentistry, Kashan University of Medical Sciences. The images were independently classified as “contact” or “none‐contact” by the ResNet‐50 model, three newly graduated dentists, and three oral and maxillofacial surgery specialists. A maxillofacial radiologist sets the gold standard using cone beam‐CT. The accuracy, precision, recall, specificity, and dice coefficient were calculated for each group, with inter‐rater reliability assessed using Cohen's kappa value.ResultsOf the 548 images retrieved, 15% were allocated as the testing dataset, amounting to 82 images. The deep learning model showed the highest performance metrics, with an accuracy of 87.80%, precision of 78.57%, recall of 84.61%, specificity of 89.28%, and dice coefficient of 81.48%. Conversely, novice dentists had the lowest performance metrics (accuracy: 74.39% ± 2.99%, precision: 57.75% ± 4.33%, recall: 74.36% ± 1.81%, specificity: 74.4% ± 4.46%, and dice coefficient: 64.87% ± 2.69%). Specialists demonstrated accuracy of 84.96% ± 1.52%, precision of 72.65% ± 2.78%, recall of 84.61% ± 3.14%, specificity of 85.12% ± 2.23%, and dice coefficient of 78.11% ± 1.99%.ConclusionDeep learning algorithms can achieve comparable outcomes with oral and maxillofacial specialists and may outperform novice clinicians in diagnosing contact between third molars and IAN.

Extracting Pulmonary Nodules and Nodule Characteristics from Radiology Reports of Lung Cancer Screening Patients Using Transformer Models

Abstract Pulmonary nodules and nodule characteristics are important indicators of lung nodule malignancy. However, nodule information is often documented as free text in clinical narratives such as radiology reports in electronic health record systems. Natural language processing (NLP) is the key technology to extract and standardize patient information from radiology reports into structured data elements. This study aimed to develop an NLP system using state-of-the-art transformer models to extract pulmonary nodules and associated nodule characteristics from radiology reports. We identified a cohort of 3080 patients who underwent LDCT at the University of Florida health system and collected their radiology reports. We manually annotated 394 reports as the gold standard. We explored eight pretrained transformer models from three transformer architectures including bidirectional encoder representations from transformers (BERT), robustly optimized BERT approach (RoBERTa), and A Lite BERT (ALBERT), for clinical concept extraction, relation identification, and negation detection. We examined general transformer models pretrained using general English corpora, transformer models fine-tuned using a clinical corpus, and a large clinical transformer model, GatorTron, which was trained from scratch using 90 billion words of clinical text. We compared transformer models with two baseline models including a recurrent neural network implemented using bidirectional long short-term memory with a conditional random fields layer and support vector machines. RoBERTa-mimic achieved the best F1-score of 0.9279 for nodule concept and nodule characteristics extraction. ALBERT-base and GatorTron achieved the best F1-score of 0.9737 in linking nodule characteristics to pulmonary nodules. Seven out of eight transformers achieved the best F1-score of 1.0000 for negation detection. Our end-to-end system achieved an overall F1-score of 0.8869. This study demonstrated the advantage of state-of-the-art transformer models for pulmonary nodule information extraction from radiology reports.

Lateral Posterior Method for Depth Correction while Using the Gates Protocol for GFR Estimation: Is it Comparable to the Gold Standard GFR Estimation by Plasma Sampling?

Abstract Background Glomerular filtration rate (GFR) estimation by Gates protocol using the gamma camera for diethylenetriaminepentaacetic acid (DTPA) dynamic renography has not compared well with the gold standard GFR by plasma sampling method. This is because depth of the kidneys is generally not considered. Our aim was to study whether manual depth correction using the skin to middle of kidney distance in lateral view and posterior aspect-lateral posterior method would reduce the bias in the Gates GFR as compared with the gold standard. Materials and Methods Retrospective study of 27 adult prospective renal donors who underwent GFR by plasma sampling and DTPA dynamic renography at Inlaks and Budhrani Hospital, Pune, Maharashtra, India between January 2022 and April 2023. The entire data was statistically analyzed using Statistical Package for Social Sciences (SPSS ver 21.0, IBM Corporation, United States) for MS Windows. Results There is no significant agreement between plasma sampling versus gamma camera method and plasma sampling versus lateral posterior method for depth correction for GFR measurements; however, the evidence of systemic bias is lower for the gamma camera method compared with the lateral posterior method for depth correction as against the plasma sampling method. Conclusion The lateral posterior method for depth correction while using the gamma camera-based Gates protocol is not a reliable method for depth correction in the western Indian adult population with preserved renal function.

How framing bias impacts preferences for innovation in bone tissue engineering.

It is currently unknown if surgeons and biomaterial scientists &or tissue engineers (BS&orTE) process and evaluate information in similar or different (un)biased ways. For the gold standard of surgery to move "from bench to bedside", there must naturally be synergies between these key stakeholders' perspectives. Because only a small number of biomaterials & tissue engineering innovations have been translated into the clinic today, we hypothesised this lack of translation is rooted in the psychology of surgeons and BS&orTE. Presently, both clinicians and researchers doubt the compatibility of surgery and research in their daily routines. This has led to the use of a metaphorical expression "squaring of the circle," which implies an unsolvable challenge. As bone tissue engineering belongs to the top 5 research areas in tissue engineering we choose the field of bone defect treatment options for our bias study. Our study uses an online survey instrument for data capture: incorporating a behavioural economics cognitive framing experiment methodology. Our study sample consisted of surgeons (n=208) and BS&orTE (n=59). And we employed a convenience sampling method, with participants (conference attendants) being approached both in person and via email - 22 October 2022-13 March 2023. We find no distinct positive-negative cognitive framing differences by occupation. That is, any framing bias present in this surgical decision-making setting does not appear to differ significantly between surgeon and BS&orTE specialisation. When we explored within group differences by frames, we see statistically significant (p<0.05) results for surgeons in the positive frame ranking autologous bone graft transplantation lower compared to surgeons in the negative frame. Further, surgeons in the positive frame rank Ilizarov bone transport method higher compared to surgeons in the negative frame (p<0.05).