Positive Predictive Value Research Articles

Diagnostic value of the flare sign in predicting extracapsular extension in metastatic axillary lymph nodes and nodal status on breast magnetic resonance imaging.

This study aimed to evaluate the diagnostic performance of breast magnetic resonance imaging (MRI) in predicting extracapsular extension (ECE) and axillary nodal status in the axillary metastatic lymph nodes of patients with breast cancer. The preoperative MRI scans of 92 patients with breast cancer and axillary metastases who did not receive neoadjuvant treatment between January 2018 and January 2024 were retrospectively examined. The presence of an increased signal in the axillary fatty tissue surrounding the lymph node (flare sign) on T2-weighted images, irregular nodal contour (shaggy margin), axillary asymmetry (difference in the number and size of lymph nodes compared with the unaffected axilla), loss of the fatty hilum in the most suspicious lymph node, and morphological features on T1-weighted images were assessed. Each dissected axillary lymph node was examined for ECE, and the histopathological results were recorded. Axillary flare sign was significantly associated with the presence of ECE (P < 0.001), number of lymph nodes with ECE (P < 0.001), the presence of ≥4 axillary metastatic lymph nodes (P < 0.001), size of the primary tumor (P = 0.033), lymphovascular invasion in the primary tumor (P < 0.001), and presence of perineural invasion (P = 0.001). The flare sign exhibited 65.7% sensitivity, 96% specificity, 97.8% positive predictive value, 51.1% negative predictive value, and 73.9% accuracy in predicting ECE. Additionally, the receiver operating characteristic curve analysis revealed an area under the curve of 0.808 (95% confidence interval: 0.719-0.898). The flare sign has high performance in predicting ECE and axillary nodal status and is associated with primary tumor aggressiveness, indicating its potential utility in preoperative evaluation. The flare sign on breast MRI may play a crucial role in preoperative planning, surgical decision-making, and axillary status assessment by accurately predicting ECE.

A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents

Skin sensitization is a significant concern for chemical safety assessments. Traditional animal assays often fail to predict human responses accurately, and ethical constraints limit the collection of human data, necessitating a need for reliable in silico models of skin sensitization prediction. This study introduces HuSSPred, an in silico tool based on the Human Predictive Patch Test (HPPT). HuSSPred aims to enhance the reliability of predicting human skin sensitization effects for chemical agents to support their regulatory assessment. We have curated an extensive HPPT database and performed chemical space analysis and grouping. Binary and multiclass QSAR models were developed with Bayesian hyperparameter optimization. Model performance was evaluated via five-fold cross-validation. We performed model validation with reference data from the Defined Approaches for Skin Sensitization (DASS) app. HuSSPred models demonstrated strong predictive performance with CCR ranging from 55 to 88%, sensitivity between 48 and 89%, and specificity between 37 and 92%. The positive predictive value (PPV) ranged from 84 to 97%, versus negative predictive value (NPV) from 22 to 65%, and coverage was between 75 and 93%. Our models exhibited comparable or improved performance compared to existing tools, and the external validation showed the high accuracy and sensitivity of the developed models. HuSSPred provides a reliable, open-access, and ethical alternative to traditional testing for skin sensitization. Its high accuracy and reasonable coverage make it a valuable resource for regulatory assessments, aligning with the 3Rs principles. The publicly accessible HuSSPred web tool offers a user-friendly interface for predicting skin sensitization based on chemical structure.

Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System–Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study

Background The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment. Objective This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries. Methods A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology. Advanced ML algorithms were harnessed to sculpt predictive models that ascertain resistance to quintessential antibiotics, particularly levofloxacin and ciprofloxacin, by using the amassed spectral data. Results Our ML models revealed remarkable proficiency in forecasting antibiotic resistance, with the random forest classifier emerging as particularly effective in predicting resistance to both levofloxacin and ciprofloxacin, achieving the highest area under the curve of 0.95. Performance metrics across different models, including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score, were detailed, underlining the potential of these algorithms in aiding the development of precision treatment strategies. Conclusions This investigation highlights the synergy between MALDI-TOF MS and ML as a beacon of hope against the escalating threat of antibiotic resistance. The advent of AI-CDSS heralds a new era in clinical diagnostics, promising a future in which rapid and accurate resistance prediction becomes a cornerstone in combating infectious diseases. Through this innovative approach, we answered the challenge posed by KP and other multidrug-resistant pathogens, marking a significant milestone in our journey toward global health security.

Diagnostic Accuracy of Automated Diabetic Retinopathy Image Assessment Software: IDx-DR and RetCAD.

Automated diabetic retinopathy (DR) screening using artificial intelligence has the potential to improve access to eye care by enabling large-scale screening. However, little is known about differences in real-world performance between available algorithms. This study compares the diagnostic accuracy of two AI screening platforms, IDx-DR and RetCAD, for detecting referable diabetic retinopathy (RDR). Retinal images from 758 patients with diabetes were collected during screening from various clinics in Poland. Each patient was graded by three graders with 320 patients graded by Polish and 438 patients graded by Indian graders, with the majority decision serving as the reference standard. The images were evaluated independently by the IDx-DR and RetCAD algorithms. Sensitivity, specificity, positive and negative predictive values, and agreement between algorithms and human graders were calculated and statistically compared. IDx-DR demonstrated higher sensitivity of 99.3% but lower specificity of 68.9% for RDR detection compared to RetCAD which had 89.4% sensitivity and 94.8% specificity. The positive predictive value was higher for RetCAD (96.4% vs 48.1% for IDx-DR) while the negative predictive value was higher for IDx-DR (99.5% vs 83.1% for RetCAD). Both algorithms achieved high sensitivity (> 95%) for sight-threatening diabetic retinopathy detection. In this direct comparison using the same patient cohort, the two algorithms showed differences in their operating parameters for RDR screening. IDx-DR prioritized avoiding false negatives over false positives while RetCAD maintained a more balanced trade-off. These results highlight the variable performance of current artificial intelligence screening solutions and suggest the importance of considering algorithm performance metrics when deploying automated diabetic retinopathy screening programs, based on available healthcare resources.

Diagnostic performance of multishot echo-planar imaging (RESOLVE) and non-echo-planar imaging (HASTE) diffusion-weighted imaging in cholesteatoma with an emphasis on signal intensity ratio measurement

To evaluate the diagnostic efficacy of multishot echo-planar imaging (EPI) [RESOLVE (RS)] and non-EPI (HASTE) diffusion-weighted imaging (DWI) in detecting cholesteatoma (CHO), and to explore the role of signal intensity (SI) ratio measurements in addressing diagnostic challenges. We analyzed RS-EPI and non-EPI DWI images from 154 patients who had undergone microscopic middle ear surgery, with pathological confirmation of their diagnoses. Two radiologists, referred to as Reader A and Reader B, independently reviewed the images without prior knowledge of the outcomes. Their evaluation focused on lesion location, T1-weighted (T1W) signal characteristics, and contrast enhancement in temporal bone magnetic resonance imaging. Key parameters included lesion hyperintensity, size, SI, SI ratio, and susceptibility artifact scores across both imaging modalities. Of the patients, 62.3% (96/154) were diagnosed with CHO, whereas 37.7% (58/154) were found to have non-CHO conditions. In RS-EPI DWI, Reader A achieved 89.6% sensitivity, 79.3% specificity, 87.8% positive predictive value (PPV), and 82.1% negative predictive value (NPV). Non-EPI DWI presented similar results with sensitivities of 89.6%, specificities of 86.2%, PPVs of 91.5%, and NPVs of 83.3%. Reader B’s results for RS-EPI DWI were 82.3% sensitivity, 84.5% specificity, 89.8% PPV, and 74.2% NPV, whereas, for non-EPI DWI, they were 86.5% sensitivity, 89.7% specificity, 93.3% PPV, and 80% NPV. The interobserver agreement was excellent (RS-EPI, κ: 0.84; non-EPI, κ: 0.91). The SI ratio measurements were consistently higher in non-EPI DWI (Reader A: 2.51, Reader B: 2.46) for the CHO group compared with RS-EPI. The SI ratio cut-off (>1.98) effectively differentiated hyperintense lesions between CHO and non-CHO groups, demonstrating 82.9% sensitivity and 100% specificity, with an area under the curve of 0.901 (95% confidence interval: 0.815–0.956; P < 0.001). Susceptibility artifact scores averaged 1.18 ± 0.7 (Reader A) and 1.04 ± 0.41 (Reader B) in RS-EPI, with non-EPI DWI recording a mean score of 0. Both RS-EPI and non-EPI DWI exhibited high diagnostic accuracy for CHO. While RS-EPI DWI cannot replace non-EPI DWI, their combined use improves sensitivity. SI ratio measurement in non-EPI DWI was particularly beneficial in complex diagnostic scenarios. This study refines CHO diagnostic protocols by showcasing the diagnostic capabilities of both RS-EPI and non-EPI DWI and highlighting the utility of SI measurements as a diagnostic tool. These findings may reduce false positives and aid in more accurate treatment planning, offering substantial insights for clinicians in managing CHO.

Evaluation of the Vaginal Panel Realtime PCR kit (Vircell, SL) for diagnosing vaginitis: A comparative study with routinely used diagnostics.

Vaginitis is a prevalent clinical disorder associated with several adverse health consequences, prompting women to seek medical care. In this study we evaluate the Vaginal Panel Real-Time PCR kit (qPCR test) against routinely used diagnostics for detection of bacterial vaginosis (BV), vulvovaginal candidiasis (VVC), and trichomoniasis. A total of 1011 vaginal swab specimens were analyzed. The routinely diagnostic methods for BV was Gram stain-based Nugent score. VVC presence was detected by culture, and Candida species were identified using MALDI-TOF MS. Trichomonas vaginalis was identified by culture in a selective medium. Molecular analyses were conducted on the MagXtract® 3200 System and analyzed using the CFX96™ Real-Time PCR Detection System. The sensitivity, specificity, positive predictive value, and negative predictive value of the qPCR test compared to the reference method for BV diagnosis was 93.1%, 88.8%, 90.1% and 92.2%, respectively, with a Kappa value of 0.82. For Candida species, sensitivity, specificity, positive predictive value, and negative predictive value were 96.0%, 98.4%, 95.3%, and 98.7%, respectively. The qPCR test detected 32 additional positive samples for Candida not reported by the routinely used diagnostics. For trichomoniasis, the qPCR test identified T. vaginalis in fifteen specimens, despite no microscopic detection in cultured specimens. Our results demonstrate that the Vaginal Panel Real-Time PCR kit shows optimal concordance with routinely used diagnostics for diagnosing vaginitis. Furthermore, enhancing detection of T. vaginalis. However, further validation studies are necessary to confirm its full diagnostic accuracy. The use of nucleic acid amplification tests (NAATs) provides rapid and accurate diagnosis, crucial for early detection and treatment of vaginitis.

Pre-transplant Screening for MMP-9 in Allogeneic HSCT Candidates

Purpose: InflammaDry® (Quidel Eye Health, San Diego, California), an FDA-approved point-of-care commercial test, measures matrix metalloproteinase-9 (MMP-9) levels in the tear film. MMP-9 is an inflammatory biomarker that is elevated in response to ocular surface stress, particularly observed in ocular graft-versus-host disease (oGVHD). The purpose of this study is to assess the prevalence of MMP-9 positivity and a score &gt;4 on the OSDI-6 questionnaire in patients before allogeneic hematopoietic stem cell transplant (HSCT). Methods: A prospective, observational, cross-sectional single center pilot study was conducted among 23 patients (46 eyes) undergoing planned allogenic HSCT. InflammaDry® results, OSDI-6 questionnaire results, and development of oGVHD were collected. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and chi-square test were calculated. Results: InflammaDry® demonstrated high sensitivity (1.0) but low specificity (0.1429) for oGVHD development. The PPV was 0.25, while the NPV was 1.0. No statistical significance was found between InflammaDry® result and development of oGVHD (p-value&gt; 0.05). Conclusion: InflammaDry® is not an effective tool for detecting the onset or predicting the risk of developing oGVHD. A significant percentage of patients exhibited ocular inflammation before allogeneic HSCT, suggesting that initiating prophylactic treatment could be valuable in reducing oGVHD development.

Revalidation of Proactive Gastrostomy Tube Placement Guidelines for Head and Neck Cancer Patients Receiving Helical Intensity-Modulated Radiotherapy

The Royal Brisbane and Women’s Hospital (RBWH) Swallowing and Nutrition Management Guidelines for Patients with Head and Neck Cancer were developed to enable evidence-based decision-making by the Head and Neck Multidisciplinary Team (H&amp;N MDT) regarding enteral nutrition support options. The purpose of this study was to revalidate these guidelines in a cohort of patients receiving helical intensity-modulated radiotherapy (H-IMRT) compared to a historical cohort who received primarily 3D-conformal radiotherapy. Eligible patients attending the RBWH H&amp;N MDT between 2013 and 2014 (n = 315) were assessed by the guidelines, with high-risk patients being recommended proactive gastrostomy tube placement. Data were collected on guideline adherence, gastrostomy tube insertions, the duration of enteral tube use and weight change. Sensitivity, specificity and positive predictive and negative predictive values were calculated and compared with the historical cohort. Overall guideline adherence was 84%, with 60% and 96% adherence to the high-risk and low-risk pathways, respectively. Seventy patients underwent proactive gastrostomy tube placement (n = 62 high-risk; n = 8 low-risk). Validation outcomes were sensitivity 73% (compared to 72%) and specificity 86% (compared to 96%). The guidelines yielded a high sensitivity and specificity, remaining valid in a cohort of patients treated with H-IMRT. Further studies are recommended to improve the sensitivity and understand the decrease in specificity in order to make ongoing guideline improvements.

Evaluation of Fungitell (1,3)-β-D-glucan assay in tear samples for rapid diagnosis of fungal keratitis.

Fungal keratitis (FK) is a serious suppurative and ulcerative corneal infection leading to blindness and vision loss. Rapid diagnosis of FK can contribute to prompt clinical management with early recovery. The study aimed to standardize the detection of (1,3)-β-D-glucan (BDG) and establish the diagnostic cut-off concentration in tears of suspected FK patients along with non-infected controls. This prospective multicentric study was conducted between the period of August 2022 and April 2024. Samples were collected from three tertiary eye-care facilities across India. All suspected FK patients were enrolled in the study. Prior to tear collection, the eye and eyelid were gently cleansed using sterile normal saline (NS) and lint-free tissue paper. Subsequently, 50 µL of sterile NS was instilled into the eye, followed by tear sample collection after 60 s using sterile fine microtips. Tear samples were collected from the contralateral eyes of the FK patients, and those from healthy volunteers served as controls. The concentration of BDG in tears in varying dilutions was quantitatively measured using the Fungitell Assay Kit (Associates of Cape Cod, East Falmouth, Massachusetts). A total of 53 tear samples were analyzed at 1:10 and 1:20 dilutions. The receiver operating curve revealed an area under the curve (AUC) of 0.919 for the 1:10 dilution, with a cut-off value of 123 pg/mL, yielding a sensitivity of 100% and specificity of 84.85%. The corresponding Youden Index was 0.798. At the 1:20 dilution, the AUC was 0.898 with a cut-off of 84 pg/mL, achieving a sensitivity of 70% and specificity of 96.88% with a Youden Index of 0.670. Given the higher specificity at the 1:20 dilution, it was further validated in 145 tear samples. The validation cohort demonstrated a sensitivity of 95.56%, specificity of 83%, positive predictive value (PPV) of 71.67%, negative predictive value (NPV) of 97.65%, and diagnostic odds ratio of 112.4. Notably, a significantly higher BDG concentration (P < 0.0001) was observed in infected tear samples compared to controls (270.6 ± 128.5 vs 37.31 ± 31.32). Detection of BDG in tear samples is a new, non-invasive, and rapid technique showing excellent performance and can be effectively implemented for diagnosing FK in laboratories.

Prognostic value of CURB-65 and pneumonia severity index (PSI) in COVID-19 pneumonia: A retrospective cohort study

Objective: To validate a better scoring system between CURB-65 and the pneumonia severity index (PSI) to predict the need for intensive care unit admission and 30-day mortality in patients with COVID-19 pneumonia. Methods: A retrospective cohort study was conducted on patients in a tertiary care hospital in Kota, Rajasthan. Relevant data about history, and general and systemic examination with laboratory investigations was collected. Patients were categorized into different risk groups for ICU admission and 30-day mortality according to CURB-65 and PSI. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were calculated. Continuous variables, means and percentages were compared using the t-test for numerical data and the Chi-square test for nominal data. Results: 100 patients who tested positive for SARS-CoV-2 by RT-PCR were included; 67 were male and 33 were female. 58 patients had severe disease (SpO2≤90%) and 30 patients died. CURB-65 had an area under the curve (AUC) of 0.81 for predicting ICU admission, with a sensitivity of 92% and a specificity of 54% for high risk patients. Meanwhile, PSI had an AUC of 0.88, with a sensitivity of 83% and a specificity of 73% in high risk patients. In addition, CURB-65 had an AUC of 0.79 for predicting 30-day mortality, with a sensitivity of 60% and a specificity of 89% in high risk patients. PSI had an AUC of 0.71 for predicting 30-day mortality, with a sensitivity of 90% and a specificity of 46% in high risk patients. Conclusions: This single-centre retrospective study involving a cohort of COVID-19 patients demonstrates that CURB-65 and PSI are powerful tools for predicting mortality. However, PSI appears to be slightly better at predicting the need for intensive care unit admission in high-risk patients.

External Validation of the PeRSonal Gestational Diabetes Model for Predicting Adverse Pregnancy Outcomes in Women with Gestational Diabetes: A Retrospective Cohort Study in a Tertiary Hospital in Thailand

Objective: This study aimed to validate the PeRSonal Gestational Diabetes (GDM) model with two-step glucose tolerance diagnostic criteria.Material and Methods: A retrospective cohort study was conducted on participants having delivered with GDM diagnosis in a tertiary hospital; from October 1, 2020, until September 30, 2022. The main outcome was a composite of maternal and perinatal adverse pregnancy complications. Model validation evaluated the predictors and calculated risk by using a two-step glucose tolerance test in the PeRSonal model formula. Model performance was analyzed for discrimination, calibration, and overall performance. Results: This study analyzed 685 from the initial 764 participants with GDM, with 218 (31.8%) developing adverse pregnancy outcomes. The most frequent adverse outcomes were hypertensive disorders in pregnancy 132 (19.3%) and neonatal hypoglycemia 91 (13.3%). This validation achieved an area under the curve (AUC) of 0.70 (95% confidence interval (CI) 0.65 to 0.74), calibration-in-the-large of 0.17, a calibration slope of 1.34, and a Brier score of 0.20, respectively. The cut-off clinical risk probability of 27.5% can predict adverse outcomes with a sensitivity of 67.3%, specificity of 63.8%, a positive predictive value (PPV) of 46.7%, and a negative predictive value (NPV) of 80.5%. Conclusion: The PeRSonal model maintains its predictive effectiveness in two-step glucose tolerance diagnostic criteria.

Prediction of malnutrition using combined index of different nutritional parameters in elderly home care patients

&lt;b&gt;Aim: &lt;/b&gt;This descriptive and cross-sectional study was conducted to assess nutritional status in elderly home care patients using a combined index.&lt;br /&gt; &lt;b&gt;Methods: &lt;/b&gt;The combined index was calculated as a reference tool based on the results of five nutritional parameters (Mini Nutritional Assessment-Short Form [MNA-SF], Short Nutritional Assessment Questionnaire [SNAQ], body mass index, dietary energy, and dietary protein). If a patient was assessed as malnourished or undernourished in at least three of these five parameters, he/she was considered as “any stage of malnutrition” according to the combined index.&lt;br /&gt; &lt;b&gt;Results: &lt;/b&gt;The prevalence of malnutrition was 48.6%, 28.3%, and 47.4% according to the MNA-SF, SNAQ, and combined index, respectively. Dietary energy had the best sensitivity (92.7%) and negative predictive value (91.3%), while SNAQ had the highest specificity (100.0%) and positive predictive value (100.0%) according to the combined index. MNA-SF had the highest inter-rater agreement (kappa [κ]) with the combined index (κ =0.792).&lt;br /&gt; &lt;b&gt;Conclusions:&lt;/b&gt; The use of combined index based on both screening tools and other nutritional parameters could be effective in the diagnosis of malnutrition in elderly home care patients.

Novel Gene Biomarkers Specific to Human Mesenchymal Stem Cells Isolated from Bone Marrow

In this paper, we present a comparative analysis of the transcriptomic profile of three different human cell types: hematopoietic stem cells (HSCs), bone marrow-derived mesenchymal stem cells (MSCs) and fibroblasts (FIBs). The work aims to identify unique genes that are differentially expressed as specific markers of bone marrow-derived MSCs, and to achieve this undertakes a detailed analysis of three independent datasets that include quantification of the global gene expression profiles of three primary cell types: HSCs, MSCs and FIBs. A robust bioinformatics method, called GlobalTest, is used to assess the specific association between one or more genes expressed in a sample and the outcome variable, that is, the ‘cell type’ provided as a single univariate response. This outcome variable is predicted for each sample tested, based on the expression profile of the specific genes that are used as input to the test. The precision of the tests is calculated along with the statistical sensitivity and specificity for each gene in each dataset, yielding four genes that mark MSCs with high accuracy. Among these, the best performer is the protein-coding gene Transgelin (TAGLN, Gene ID: 6876) (with a Positive Predictive Value &gt; 0.96 and FDR &lt; 0.001), which identifies MSCs better than any of the currently used standard markers: ENG (CD105), THY1 (CD90) or NT5E (CD73). The results are validated by RT-qPCR, providing novel gene biomarkers specific for human MSCs.

Evaluation of the clinical utility of NIPT-plus and analysis of adverse pregnancy outcomes.

To evaluate the performance of NIPT-plus in detecting fetal aneuploidies and CNVs and analyze the factors influencing adverse pregnancy outcomes. The retrospectively analyzed 8726 pregnant women who underwent NIPT-plus for fetal screening were classified into low- (who tested voluntarily) and high-risk (women with advanced age, abnormal ultrasound, abnormal serological screening, or a combination of indications) groups. Basic maternal information, prenatal findings, and pregnancy outcomes were recorded. NIPT-plus performance was assessed for various chromosomal abnormalities and the association between the fetal fraction and adverse pregnancy outcomes. Thirty-six (0.4%) patients had failed tests; 144 (1.65%) positive cases were detected, of which, 107 (74.31%) opted for invasive testing, and 51 were verified as true positives. The total positive predictive value was 45.45% and 48.65% in the low- and high-risk groups, respectively, and the difference was not significant. Among the subsequent cases with abnormal ultrasound monitoring, two false-negative cases were identified, and pathogenic CNV diagnosis was confirmed through amniocentesis, resulting in pregnancy termination. Fetal fraction was not associated with an increased adverse pregnancy outcome risk; however, ethnic differences may affect pregnancy outcomes. NIPT-plus technology use is no longer restricted to high-risk pregnant women, and it may produce false-positive results. The stakeholders should be aware of this limitation. The uncertainties and potential risks of the test results should be explained to the test takers to enable informed decision making and to minimize unnecessary anxiety and concerns. Ethnicity may influence adverse pregnancy outcomes in local multiracial settings.

Diffusion weighted MRI and neutrophil lymphocyte ratio non-invasively predict infection in pancreatic necrosis: a pilot study.

Infected pancreatic necrosis (IPN) is a major determinant of mortality in acute pancreatitis (AP). Non-invasive diagnosis of IPN could guide the intervention in AP. We aimed to investigate the role of non-invasive methods like diffusion weighted magnetic resonance imaging (DW-MRI) and clinico-laboratory parameters as predictors of IPN. Prospective evaluation for predictors of IPN by diffusion restriction (DR) on DW-MRI and clinico-laboratory parameters was performed. Out of 39 patients included, 31 were analysed after exclusion. Twenty-six (83.8%) patients had moderately severe AP, and the rest had severe disease. They were categorized into Group A: patients with documented infection after intervention (n = 17) and Group B: successfully managed without intervention or negative culture after intervention (n = 14). On univariate analysis, Group A had significantly more incidence of fever (P = 0.020), persistent unwellness (P = 0.003), elevated neutrophil count (P = 0.007), lymphocyte count (P = 0.007), neutrophil lymphocyte ratio (NLR) (P = 0.028), DR on DW-MRI (P = 0.001) and low apparent diffusion coefficient (ADC) (P = 0.086). Multivariate analysis revealed DR on DW-MRI (P = 0.004) and NLR (P = 0.035) as significant predictors of IPN, among other factors. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DW-MRI were 94.1%, 78.6%, 91.66%, and 84.21%, respectively. The area under curve of NLR on the ROC plot was 0.85 and the best cutoff was >3.5, with sensitivity, specificity, PPV, and NPV of 70.6%, 78.6%, 80%, and 68.7% respectively. DW-MRI and NLR are promising non-invasive tools for accurate prediction of IPN and hence can guide the need for intervention in acute pancreatitis.

Using Indocyanine Green Fluorescence Angiography to Evaluate the Impact of Surgical and Patient Factors on Posterior Septal Artery Perfusion in Endoscopic Skull Base Surgery

Abstract Background Nasoseptal flaps (NSF), perfused by the posterior septal artery (PSA), are heavily utilized in endonasal skull base surgery (ESBS). We use indocyanine green (ICG) fluorescence angiography to assess PSA perfusion. Methods A prospective study of adult ESBS patients assessed PSA perfusion using intraoperative ICG. PSA ICG fluorescence intensities (FIs) were quantified. Factors analyzed included demographics, comorbidities, prior sinonasal surgery, surgical approach, concurrent septoplasty, NSF harvest timing, and flap-related complications. t-Tests compared significant ICG baseline differences and changes from baseline. ICG enhancement was compared with postoperative magnetic resonance imaging (MRI). Results A total of 54 patients were studied. Of these, 35 NSFs were harvested, while the remaining 19 underwent cuts for rescue flaps. Mean PSA FI changed from baseline 118.1 ± 28.6 to 114.4 ± 32.3 following reconstruction. Tobacco users had lower baseline FI compared with non-tobacco users (78.3 ± 62.8 vs. 118.4 ± 29.1, p = 0.003). Transpterygoid approaches showed greater decrease from baseline (−25.8 ± 58.9 vs. −3.8 ± 32.1, p = 0.035) than transsphenoidal. No other studied factors, including revision case, timing of flap harvest, flap side, division of palatosphenoidal artery, or concurrent septoplasty, had a significant influence on ICG intensity. In total, 34 of 35 NSFs were viable. ICG fluorescence had a 100% sensitivity, 0% specificity, and 96.6% positive predictive value (PPV) for NSF viability, while MRI enhancement had a 100% sensitivity, 100% specificity, and 100% PPV for NSF viability. Conclusion ICG angiography may provide an intraoperative assessment of flap viability with comparable PPV as postoperative MRI. Tobacco use and transpterygoid approaches may be associated with decreased PSA perfusion.

Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial

Background and Objectives: Lung nodules detected by chest computed tomography (CT) often require invasive biopsies for definitive diagnosis, leading to unnecessary procedures for benign lesions. A blood-based biomarker test that predicts lung cancer risk in CT-detected nodules could help stratify patients and direct invasive diagnostics toward high-risk individuals. Methods: In this multicenter, single-blinded clinical trial, we evaluated a test measuring plasma levels of p53, anti-p53 autoantibodies, CYFRA 21-1, and anti-CYFRA 21-1 autoantibodies in patients with CT-detected lung nodules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated, and subgroup analyses by gender, age, and smoking status were performed. A total of 1132 patients who had CT-detected lung nodules, including 885 lung cancer cases and 247 benign lesions, were enrolled from two academic hospitals in South Korea. Results: The test demonstrated a sensitivity of 78.4% (95% CI: 75.7–81.1) and specificity of 93.1% (95% CI: 90.0–96.3) in predicting lung cancer in CT-detected nodules. The PPV was 97.6%, and the NPV was 54.6%. Performance was consistent across gender (sensitivity 79.3% in men and 76.8% in women) and age groups, with a specificity of 93.4% in men and 92.7% in women. Stage I lung cancer was detected with a sensitivity of 80.6%. Conclusions: The Lung Cancer test based on 9G technology presented here offers a non-invasive method for stratifying lung cancer risk in patients with CT-detected nodules. Its integration into clinical practice could reduce unnecessary interventions and foster earlier detection.

Prevalence of vaginal and cervical HPV infection among 35-year age cohort ever-married women in Kalutara district of Sri Lanka and the validity of vaginal HPV/DNA specimen as a cervical cancer screening tool: a cross-sectional study.

Cervical cancer is the 2nd most common female cancer among Sri Lankan females and is almost associated with sexually transmitted cervicovaginal human papillomavirus (HPV) infection. The study objectives were to determine the prevalence of vaginal and cervical HPV infection among 35year old ever-married women and assess the validity of primary healthcare provider-collected vaginal HPV/DNA specimens as a cervical cancer screening tool to improve the coverage of the programme. A descriptive cross-sectional study was carried out from the 1st of September 2018 to the 31st of January 2019. Ever-married women 35 years of age in Kalutara district were the study population. Two women from each Public Health Midwife area (n = 413) were selected randomly from the relevant area eligible families register/s. HPV/DNA cervical specimen and vaginal specimen collection (n = 621) were carried out. Specimens were screened by the Cobas 4800 HPV/DNA automated Polymerase Chain Reaction (PCR) machine. Participants' profiles were recorded by the research assistants using an interviewer-administered questionnaire. The overall prevalence of vaginal and cervical HPV infection was 7.08% (95% CI; 5.2-9.4%) and 6.12% (95% CI; 4.26-8.3%) respectively. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and the kappa coefficient of the vaginal HPV/DNA screening method vs. cervical HPV/DNA screening method were 100%, 98.9%, 86.4%, 100%, 99% and 0.92 respectively. Vaginal HPV/DNA specimen screening method can be used as a cervical cancer screening tool due to its high validity. Pilots of the feasibility should be set up before the regional or national rollout of vaginal sampling strategies.

Comprehensive newborn screening for severe combined immunodeficiency, X-linked agammaglobulinemia, and spinal muscular atrophy: the Chinese experience.

Newborn screening (NBS) for severe combined immunodeficiency (SCID), X-linked agammaglobulinemia (XLA), and spinal muscular atrophy (SMA) enables early diagnosis and intervention, significantly improving patient outcomes. Advances in real-time polymerase chain reaction (PCR) technology have been instrumental in facilitating their inclusion in NBS programs. We employed multiplex real-time PCR to simultaneously detect T-cell receptor excision circles (TRECs), kappa-deleting recombination excision circles (KRECs), and the absence of the survival motor neuron (SMN) 1 gene in dried blood spots from 103,240 newborns in Zhejiang Province, China, between July 2021 and December 2022. Of all the samples, 122 were requested further evaluation. After flow cytometry evaluation and/or genetic diagnostics, we identified one patient with SCID, two patients with XLA, nine patients with SMA [one of whom also had Wiskott-Aldrich Syndrome (WAS)], and eight patients with other medical conditions. The positive predictive values (PPVs) of NBS for SCID, XLA, and SMA were 2.44%, 2.78%, and 100%, respectively. The estimated prevalence rates in the Chinese population were 1 in 103,240 for SCID, 1 in 51,620 for XLA, and 1 in 11,471 for SMA. This study represents the first large-scale screening in mainland China using a TREC/KREC/SMN1 multiplex assay, providing valuable epidemiological data. Our findings suggest that this multiplex assay is an effective screening method for SCID, XLA, and SMA, potentially supporting the universal implementation of NBS programs across China.

A Simple Test Ratio APRI (AST to Platelet Ratio Index) as a Useful Tool for Cirrhosis: A Study from Bir Hospital, Nepal

Background Liver cirrhosis is a leading cause of morbidity and mortality worldwide, including Nepal. Liver biopsy, the gold standard for fibrosis assessment, is invasive and carries risks. The Aspartate Aminotransferase to Platelet Ratio Index (APRI) offers a non-invasive, cost-effective alternative. However, data on its utility in Nepalese populations are limited.  Objective To evaluate the diagnostic performance of APRI as a non-invasive marker of cirrhosis in Nepalese patients, determining its sensitivity, specificity, and predictive values.  Methods This cross-sectional study enrolled 58 cirrhotic patients and 58 healthy controls at Bir Hospital from April 2019 to January 2020. Clinical examinations, laboratory tests, and ultrasonography were performed. APRI with a cut-off of 0.5 was evaluated using SPSS version 23, applying chi-square and ANOVA tests.  Results Among 116 participants, APRI at a 0.5 cut-off demonstrated 88.3% sensitivity, 82.5% specificity, 90.1% positive predictive value, and 70.2% negative predictive value (p = 0.002, 95% CI).  Conclusion APRI is a reliable non-invasive tool for diagnosing liver fibrosis in cirrhotic patients, offering high sensitivity and specificity. It is practical for bedside use, especially in resource-limited settings.