Sepsis in obstetric care for the emergency clinician: A review.

Sepsis remains a leading cause of mortality among pregnant and recently pregnant patients, rendering it a subject of vital importance to emergency clinicians in the US. However, death by sepsis has been found to be largely preventable with prompt and appropriate intervention. This narrative review provides a summary of the physiologic, epidemiologic, and systemic factors specific to obstetric sepsis that contribute to delays in diagnosis and treatment. Additionally, it provides a framework for emergency department providers to approach infection identification, antimicrobial selection, and appropriate resuscitation prior to disposition.

Evaluation of outcomes of clinical phenotyping-based treatment for bladder pain syndrome/interstitial cystitis.

Introduction: Bladder pain syndrome/Interstitial cystitis (BPS/IC) is clinically of diverse types because different causes contribute to the development of their symptoms. It is important to classify patients into various groups based on the possible etiopathogenesis of their condition. Treatment may be tailored to each specific group according to the possible cause. Methodology: Twenty-five patients diagnosed with BPS/IC were categorized into four different clinical phenotypes (CP) based on their history of symptoms, allergy, dysfunctional voiding, neuropathic pain, and the presence of Hunner's ulcer. Some patients could be classified into multiple groups. The patients were given oral pentosan polysulfate, and treatment specific to their CP. Patients in CP1, CP2, and CP3 groups received, respectively hydroxyzine, clonazepam, and amitriptyline. Patients with Hunner's lesions (HL) (CP4) underwent hydro distension and ablation of the lesion, followed by intravesical instillation of heparin and hydrocortisone. The patients were evaluated using the Apollo clinical scoring (ACS) system and their clinical scores were recorded at 1, 3, and 6 month(s). Results: Among the 25 patients, 5, 7, 4, and 9 patients were classified into CP 1 - CP4 groups respectively, and were all subjected to ACS assessment. In CP1 group (allergy group), 80% (4/5) of patients responded well to the treatment and 20% (1/5) had unsatisfactory responses. In CP2 group (dysfunctional voiding group), 71.42% (5/7) patients had good, and 28.57% (2/7) had excellent responses. In CP3 group (neuropathic pain group), 28.57% (3/4) patients had excellent, and 75% (1/4) patients had good responses. In CP4 group (HL group), 33.33% (3/9) patients had unsatisfactory, 44.44% (4/9) achieved good, and 22.22% (2/9) had excellent responses. Overall, 16% (4/25) patients had unsatisfactory, 56% (14/25) attained good, and 28% (7/25) had an excellent response at the completion of the study. Conclusion: Using clinical phenotyping-based features indicative of etiology could potentially improve treatment outcomes by targeting the specific pathological processes contributing to the patients' symptoms.

A Simple MRI Score Predicts Pathological General Movements in Very Preterm Infants with Brain Injury-Retrospective Cohort Study.

BACKGROUND/OBJECTIVES: Very preterm infants are at increased risk of brain injury and impaired brain development. The Total Abnormality Score and biometric parameters, such as biparietal width, interhemispheric distance and transcerebellar diameter, are simple measures to evaluate brain injury, development and growth using cerebral magnetic resonance imaging data at term-equivalent age. The aim of this study was to evaluate the association between the Total Abnormality Score and biometric parameters with general movements in very preterm infants with brain injury. METHODS: This single-center retrospective cohort study included 70 very preterm infants (≤32 weeks' gestation and/or <1500 g birth weight) born between January 2017 and June 2021 in a level-three neonatal intensive care unit with brain injury-identified using cerebral magnetic resonance imaging data at term-equivalent age. General movements analysis was carried out at corrected age of 8-16 weeks. Binary logistic regression and Spearman correlation were used to examine the associations between the Total Abnormality Score and biometric parameters with general movements. RESULTS: There was a significant association between the Total Abnormality Score and the absence of fidgety movements [OR: 1.19, 95% CI = 1.38-1.03] as well as a significant association between the transcerebellar diameter and fidgety movements (Spearman ρ = -0.269, p < 0.05). CONCLUSIONS: Among very preterm infants with brain injury, the Total Abnormality Score can be used to predict the absence of fidgety movements and may be an easily accessible tool for identifying high-risk very preterm infants and planning early interventions accordingly.

A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer.

BACKGROUND/OBJECTIVES: Nuclear pleomorphism, a crucial determinant of breast cancer grading under the Nottingham Histopathology Grading (NHG) system, remains inadequately quantified in the existing literature. Motivated by this gap, our study seeks to investigate and establish correlations among morphological features across various scores of nuclear pleomorphism, as per the NHG system. We aim to quantify nuclear pleomorphism across these scores and validate our proposed measurement method against ground-truth data. METHODS: Initially, we deconstruct the descriptions of nuclear pleomorphism into three core elements: size, shape, and appearance. These elements are subsequently mathematically modeled into equations, termed ESize, EShape, and EAppearance. These equations are then integrated into a unified model termed Harmonic Mean (HM). The HM equation yields a value approaching 1 for nuclei demonstrating characteristics of score-3 nuclear pleomorphism and near 0 for those exhibiting features of score-1 nuclear pleomorphism. RESULTS: The proposed HM model demonstrates promising performance metrics, including Accuracy, Recall, Specificity, Precision, and F1-score, with values of 0.97, 0.96, 0.97, 0.94, and 0.95, respectively. CONCLUSIONS: In summary, this study proposes the HM equation as a novel feature for the precise quantification of nuclear pleomorphism in breast cancer.

Computed Tomography Evaluation of Coronary Atherosclerosis: The Road Travelled, and What Lies Ahead.

Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to support CCTA diagnostic and prognostic value both for stable and acute symptoms. It enables rapid and cost-effective rule-out of CAD, and permits quantification and characterization of coronary plaque and associated significance. In this comprehensive review, we detail the road traveled as CCTA evolved to include quantitative assessment of plaque stenosis and extent, characterization of plaque characteristics including high-risk features, functional assessment including fractional flow reserve-CT (FFR-CT), and CT perfusion techniques. The state of current guideline recommendations and clinical applications are reviewed, as well as future directions in the rapidly advancing field of CT technology, including photon counting and applications of artificial intelligence (AI).

Hypoxic-ischemic brain injury in pig after cardiac arrest - A new histopathological scoring system for non-specialists.

Introduction: After cardiac arrest and successful resuscitation patients often present with hypoxic-ischemic brain injury, which is a major cause of death due to poor neurological outcome. The development of a robust histopathological scoring system for the reliable and easy identification and quantification of hypoxic-ischemic brain injury could lead to a standardization in the evaluation of brain damage. We wanted to establish an easy-to-use neuropathological scoring system to identify and quantify hypoxic-ischemic brain injury. Methods: The criteria for regular neurons, hypoxic-ischemic brain injury neurons and neurons with ischemic neuronal change (ischemic change neurons) were established in collaboration with specialized neuropathologists. Nine non-specialist examiners performed cell counting using the mentioned criteria in brain tissue samples from a porcine cardiac arrest model. The statistical analyses were performed using the interclass correlation coefficient for counting data and reliability testing. Results: The inter-rater reliability for regular neurons (ICC 0.68 (0.42 - 0.84; p < 0.001) and hypoxic-ischemic brain injury neurons (ICC 0.87 (0.81 - 0.92; p < 0.001) showed moderate to excellent correlation while ischemic change neurons showed poor reliability. Excellent results were seen for intra-rater reliability for regular neurons (ICC 0.9 (0.68 - 0.97; p < 0.001) and hypoxic-ischemic brain injury neurons (ICC 0.99 (0.83 - 1; p < 0.001). Conclusion: The scoring system provides a reliable method for the discrimination between regular neurons and neurons affected by hypoxic/ischemic injury. This scoring system allows an easy and reliable identification and quantification of hypoxic-ischemic brain injury for non-specialists and offers a standardization to evaluate hypoxic-ischemic brain injury after cardiac arrest.

A weighted Bayesian integration method for predicting drug combination using heterogeneous data.

BACKGROUND: In the management of complex diseases, the strategic adoption of combination therapy has gained considerable prominence. Combination therapy not only holds the potential to enhance treatment efficacy but also to alleviate the side effects caused by excessive use of a single drug. Presently, the exploration of combination therapy encounters significant challenges due to the vast spectrum of potential drug combinations, necessitating the development of efficient screening strategies. METHODS: In this study, we propose a prediction scoring method that integrates heterogeneous data using a weighted Bayesian method for drug combination prediction. Heterogeneous data refers to different types of data related to drugs, such as chemical, pharmacological, and target profiles. By constructing a multiplex drug similarity network, we formulate new features for drug pairs and propose a novel Bayesian-based integration scheme with the introduction of weights to integrate information from various sources. This method yields support strength scores for drug combinations to assess their potential effectiveness. RESULTS: Upon comprehensive comparison with other methods, our method shows superior performance across multiple metrics, including the Area Under the Receiver Operating Characteristic Curve, accuracy, precision, and recall. Furthermore, literature validation shows that many top-ranked drug combinations based on the support strength score, such as goserelin and letrozole, have been experimentally or clinically validated for their effectiveness. CONCLUSIONS: Our findings have significant clinical and practical implications. This new method enhances the performance of drug combination predictions, enabling effective pre-screening for trials and, thereby, benefiting clinical treatments. Future research should focus on developing new methods for application in various scenarios and for integrating diverse data sources.

Preschool musicality is associated with school-age communication abilities through genes related to rhythmicity.

Early-life musical engagement is an understudied but developmentally important and heritable precursor of later (social) communication and language abilities. This study aims to uncover the aetiological mechanisms linking musical to communication abilities. We derived polygenic scores (PGS) for self-reported beat synchronisation abilities (PGSrhythmicity) in children (N≤6,737) from the Avon Longitudinal Study of Parents and Children and tested their association with preschool musical (0.5-5 years) and school-age (social) communication and cognition-related abilities (9-12 years). We further assessed whether relationships between preschool musicality and school-age communication are shared through PGSrhythmicity, using structural equation modelling techniques. PGSrhythmicity were associated with preschool musicality (Nagelkerke-R2=0.70-0.79%), and school-age communication and cognition-related abilities (R2=0.08-0.41%), but not social communication. We identified links between preschool musicality and school-age speech- and syntax-related communication abilities as captured by known genetic influences underlying rhythmicity (shared effect ß=0.0065(SE=0.0021), p=0.0016), above and beyond general cognition, strengthening support for early music intervention programmes.

The preoperative scoring system combining neutrophil/lymphocyte ratio and CA19-9 predicts the long-term prognosis of intrahepatic cholangiocarcinoma patients undergoing curative liver resection.

BACKGROUND: This study aims to investigate preoperative prognostic factors available for intrahepatic cholangiocarcinoma (ICC) patients and propose a new preoperative prognostic scoring system for ICC that combines CA19-9 and neutrophil/lymphocyte ratio (NLR). METHODS: In this retrospective analysis, 1728 patients diagnosed with ICC and undergoing curative liver resections were studied. This study employed univariate and multivariate Cox regression to find factors affecting recurrence and overall survival (OS), and furthermore assessed how preoperative models influenced tumor traits and postoperative recurrence. RESULTS: The results of the multivariate Cox regression analysis indicated that two preoperative variables, NLR and Ca19-9, were independent risk factors affecting postoperative recurrence and OS in ICC patients. Based on this data, assigning a score of 0 (NLR ≤ 2.4 and Ca19-9 ≤ 37U/ml) or 1 (NLR > 2.4 and Ca19-9 > 37U/ml) to these two factors, a preoperative prognostic score was derived. According to the scoring model, patients were divided into three groups: 0 points (low-risk group), 1 point (intermediate-risk group), and 2 points (high-risk group). The 5-year recurrence and OS rates for the three groups were 56.6%, 68.2%, 77.8%, and 56.8%, 40.6%, 27.6%, respectively, with all P values < 0.001. Furthermore, high-risk group patients were more prone to early recurrence (early recurrence rates for high-, intermediate-, and low-risk groups were 56.8%, 51.5%, and 37.1%, respectively, P < 0.001) and extrahepatic metastasis (extrahepatic metastasis rates for high-, intermediate-, and low-risk groups were 31.7%, 26.4%, and 15.4%, respectively, P < 0.001). In terms of tumor characteristics, high-risk group patients had larger tumor diameters and were more likely to experience microvascular invasion, lymph node metastasis, and perineural invasion. CONCLUSIONS: The predictive capacity of postoperative recurrence and OS rates in ICC patients is effectively captured by the preoperative scoring system incorporating NLR and CA19-9 levels.

Development of an online authentic radiology viewing and reporting platform to test the skills of radiology trainees in Low- and Middle-Income Countries.

BACKGROUND: Diagnostic radiology residents in low- and middle-income countries (LMICs) may have to provide significant contributions to the clinical workload before the completion of their residency training. Because of time constraints inherent to the delivery of acute care, some of the most clinically impactful diagnostic radiology errors arise from the use of Computed Tomography (CT) in the management of acutely ill patients. As a result, it is paramount to ensure that radiology trainees reach adequate skill levels prior to assuming independent on-call responsibilities. We partnered with the radiology residency program at the Aga Khan University Hospital in Nairobi (Kenya) to evaluate a novel cloud-based testing method that provides an authentic radiology viewing and interpretation environment. It is based on Lifetrack, a unique Google Chrome-based Picture Archiving and Communication System, that enables a complete viewing environment for any scan, and provides a novel report generation tool based on Active Templates which are a patented structured reporting method. We applied it to evaluate the skills of AKUHN trainees on entire CT scans representing the spectrum of acute non-trauma abdominal pathology encountered in a typical on-call setting. We aimed to demonstrate the feasibility of remotely testing the authentic practice of radiology and to show that important observations can be made from such a Lifetrack-based testing approach regarding the radiology skills of an individual practitioner or of a cohort of trainees. METHODS: A total of 13 anonymized trainees with experience from 12 months to over 4 years took part in the study. Individually accessing the Lifetrack tool they were tested on 37 abdominal CT scans (including one normal scan) over six 2-hour sessions on consecutive days. All cases carried the same clinical history of acute abdominal pain. During each session the trainees accessed the corresponding Lifetrack test set using clinical workstations, reviewed the CT scans, and formulated an opinion for the acute diagnosis, any secondary pathology, and incidental findings on the scan. Their scan interpretations were composed using the Lifetrack report generation system based on active templates in which segments of text can be selected to assemble a detailed report. All reports generated by the trainees were scored on four different interpretive components: (a) acute diagnosis, (b) unrelated secondary diagnosis, (c) number of missed incidental findings, and (d) number of overcalls. A 3-score aggregate was defined from the first three interpretive elements. A cumulative score modified the 3-score aggregate for the negative effect of interpretive overcalls. RESULTS: A total of 436 scan interpretations and scores were available from 13 trainees tested on 37 cases. The acute diagnosis score ranged from 0 to 1 with a mean of 0.68 ± 0.36 and median of 0.78 (IQR: 0.5-1), and there were 436 scores. An unrelated secondary diagnosis was present in 11 cases, resulting in 130 secondary diagnosis scores. The unrelated secondary diagnosis score ranged from 0 to 1, with mean score of 0.48 ± 0.46 and median of 0.5 (IQR: 0-1). There were 32 cases with incidental findings, yielding 390 scores for incidental findings. The number of missed incidental findings ranged from 0 to 5 with a median at 1 (IQR: 1-2). The incidental findings score ranged from 0 to 1 with a mean of 0.4 ± 0.38 and median of 0.33 (IQR: 0- 0.66). The number of overcalls ranged from 0 to 3 with a median at 0 (IQR: 0-1) and a mean of 0.36 ± 0.63. The 3-score aggregate ranged from 0 to 100 with a mean of 65.5 ± 32.5 and median of 77.3 (IQR: 45.0, 92.5). The cumulative score ranged from - 30 to 100 with a mean of 61.9 ± 35.5 and median of 71.4 (IQR: 37.4, 92.0). The mean acute diagnosis scores and SD by training period were 0.62 ± 0.03, 0.80 ± 0.05, 0.71 ± 0.05, 0.58 ± 0.07, and 0.66 ± 0.05 for trainees with ≤ 12 months, 12-24 months, 24-36 months, 36-48 months and > 48 months respectively. The mean acute diagnosis score of 12-24 months training was the only statistically significant greater score when compared to ≤ 12 months by the ANOVA with Tukey testing (p = 0.0002). We found a similar trend with distribution of 3-score aggregates and cumulative scores. There were no significant associations when the training period was categorized as less than and more than 2 years. We looked at the distribution of the 3-score aggregate versus the number of overcalls by trainee, and we found that the 3-score aggregate was inversely related to the number of overcalls. Heatmaps and raincloud plots provided an illustrative means to visualize the relative performance of trainees across cases. CONCLUSION: We demonstrated the feasibility of remotely testing the authentic practice of radiology and showed that important observations can be made from our Lifetrack-based testing approach regarding radiology skills of an individual or a cohort. From observed weaknesses areas for targeted teaching can be implemented, and retesting could reveal their impact. This methodology can be customized to different LMIC environments and expanded to board certification examinations.

Development and validation of a prognostic scoring system for 1-year mortality in older patients with hip fractures.

BACKGROUND: Hip fractures in older people result in increased mortality. OBJECTIVE: We developed and validated an accurate and simple prognostic scoring system for hip fractures that can be used preoperatively. DESIGN: Retrospective study. SETTING: Multicenter. PARTICIPANTS: Patients aged ≥65 years with hip fractures who underwent surgery between 2011 and 2021 were enrolled. METHODS: The significant factors were determined with logistic regression analysis, and a scoring system was developed. The patients were classified into three groups, and a log-rank test was performed to evaluate 1-year survival rates. The model was internally and externally validated using the 5-fold cross-validation and data from another hospital, respectively. RESULTS: We included 1026 patients. The analysis revealed eight significant prognostic factors: sex, body mass index, history of chronic heart failure and malignancy, activities of daily living (ADLs) before injury, hemoglobin and the prognostic nutritional index (PNI) at injury, and the American Society of Anesthesiologists Physical Status. The area under the receiver operating characteristic curve (AUC) after internal validation was 0.853. The external validation data consisted of 110 patients. The AUC of the model for the validation data was 0.905, showing outstanding discrimination. Sensitivity and specificity were 88.7% vs. 100% and 93.3% vs. 95.2% for the development and validation data, respectively. CONCLUSIONS: We developed and validated an accurate and simple prognostic scoring system for hip fractures using only preoperative factors. Our findings highlight PNI as an important predictor of prognosis in hip fracture patients.

Development of a Nutrient Profiling Model for Processed Foods in Japan.

Numerous nutrient profiling models (NPMs) exist worldwide, but Japan lacks an official NPM. Using the Australian and New Zealand Health Star Rating (HSR) as a reference, "Processed Foods in Japan version 1.0" (NPM-PFJ (1.0)) was developed to fit Japanese food culture and policies. In total, 668 processed foods from the Standard Tables of Food Composition in Japan were analyzed, excluding seasonings/spices, fats/oils, alcoholic beverages, and infant food. The NPM-PFJ (1.0) scoring algorithm was adapted from HSR, with revised reference values for energy, saturated fat, total sugars, sodium, protein, and dietary fiber in alignment with Japanese standards. Reference values for fruits, vegetables, nuts, and legumes (fvnl) remained unchanged. Median scores were 4.5 for HSR and 5.0 for NPM-PFJ (1.0), showing high correlation (r = 0.939, p < 0.01). Thereafter, food categories familiar and meaningful in Japan were defined based on a hierarchical cluster analysis of scoring patterns, creating six categories with distinct characteristics. Finally, the rating algorithm for NPM-PFJ (1.0) was created using each group's score distribution (10th percentile). The NPM-PFJ (1.0) was developed through a fully transparent and evidence-based process and is expected to facilitate the reformulation of food products by food industries and help consumers easily access healthier processed foods. This model marks a significant step forward in developing an NPM tailored to Japanese food culture and health policies, with the potential to enhance public health.

"Application of CT radiomics in brain metastasis of lung cancer: A systematic review and meta-analysis".

PURPOSE: This study aimed to systematically assess the quality and performance of computed tomography (CT) radiomics studies in predicting brain metastasis (BM) among patients with lung cancer. METHODS: The PubMed, Embase and Web of Science were searched for studies predicting BM in patients with lung cancer using CT-based radiomics features. Information regarding patients, imaging, and radiomics analysis was extracted from eligible studies. We assessed the quality of included studies using the Radiomics Quality Scoring (RQS) tool and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A meta-analysis of studies regarding the prediction of BM in patients with lung cancer was performed. RESULTS: Thirteen studies were identified, with sample sizes ranging from 75 to 602. The mean RQS of the studies was 12 (range 9-16), and the corresponding percentage of the score was 33.55 % (range 25.00-44.44 %). Four studies (30.8 %) were considered as low risk of bias, while the remaining nine studies (69.2 %) were considered to have unclear risks. The meta-analysis included twelve studies. The pooled sensitivity, specificity and Area Under the Curve (AUC) value with 95 % confidence intervals were 0.75 [0.69, 0.80], 0.76 [0.68, 0.82], and 0.81 [0.77-0.84], respectively. CONCLUSION: CT radiomics-based models show promising results as a non-invasive method to predict BM in lung cancer patients. However, multicenter and prospective studies are warranted to enhance the stability and acceptance of radiomics.

A scoring-based clinical grading model for xanthelasma palpebrarum: predicting treatment frequency and prognosis.

Xanthelasma palpebrarum is one of the most common cutaneous xanthomas in humans. Currently, there are various methods available for treating xanthelasma palpebrarum, but the high treatment frequency and recurrence rate remain significant challenges for patients. Therefore, it is necessary to establish a reasonable and effective clinical grading system to guide the diagnosis and treatment of xanthelasma palpebrarum. We developed a clinical scoring system related to local injection of pingyangmycin for the treatment of xanthelasma palpebrarum, which can be used to predict early prognosis and treatment outcomes in patients. We collected and retrospectively studied 246 outpatient cases of xanthelasma palpebrarum treated with local injection of pingyangmycin in the Department of Plastic Surgery at Shanghai East Hospital from February 2020 to August 2022. Potential independent risk factors for adverse outcomes (recurrence or non-recurrence) were considered in univariate and multivariate logistic regression models. Predictive factors were determined based on the multivariate logistic regression model and Cox model, and a scoring grading system was established. External validation was conducted on an independent cohort of 110 patients. Based on logistic regression analysis, the number, area, and color of lesions were identified as significant predictive indicators (P < 0.05), with respective AUCs of 0.710, 0.799, and 0.755. The Cox model established hazard ratios for four new severity indicators of xanthelasma palpebrarum: hyperlipidemia, number of lesions, lesion area, and lesion grayscale value. Based on these findings, a new clinical grading model was developed, which was validated to be effective in the external cohort. The new scoring-based clinical predictive model can effectively predict the number of pingyangmycin injection treatments and prognosis in patients with xanthelasma palpebrarum. It holds promise for broader application in clinical practice.

Comparison of different intensive care scoring systems and Glasgow Aneurysm score for aortic aneurysm in predicting 28-day mortality: a retrospective cohort study from MIMIC-IV database.

OBJECTIVE: This study aims to assess the performance of various scoring systems in predicting the 28-day mortality of patients with aortic aneurysms (AA) admitted to the intensive care unit (ICU). METHODS: We utilized data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) to perform a comparative analysis of various predictive systems, including the Glasgow Aneurysm Score (GAS), Simplified Acute Physiology Score (SAPS) III, SAPS II, Logical Organ Dysfunction System (LODS), Sequential Organ Failure Assessment (SOFA), Systemic Inflammatory Response Syndrome (SIRS), and The Oxford Acute Illness Severity Score (OASIS). The discrimination abilities of these systems were compared using the area under the receiver operating characteristic curve (AUROC). Additionally, a 4-knotted restricted cubic spline regression was employed to evaluate the association between the different scoring systems and the risk of 28-day mortality. Finally, we conducted a subgroup analysis focusing on patients with abdominal aortic aneurysms (AAA). RESULTS: This study enrolled 586 patients with AA (68.39% male). Among them, 26 patients (4.4%) died within 28 days. Comparative analysis revealed higher SAPS II, SAPS III, SOFA, LODS, OASIS, and SIRS scores in the deceased group, while no statistically significant difference was observed in GAS scores between the survivor and deceased groups (P = 0.148). The SAPS III system exhibited superior predictive value for the 28-day mortality rate (AUROC 0.805) compared to the LODS system (AUROC 0.771), SOFA (AUROC 0.757), SAPS II (AUROC 0.759), OASIS (AUROC 0.742), SIRS (AUROC 0.638), and GAS (AUROC 0.586) systems. The results of the univariate and multivariate logistic analyses showed that SAPS III was statistically significant for both 28-day and 1-year mortality. Subgroup analyses yielded results consistent with the overall findings. No nonlinear relationship was identified between these scoring systems and 28-day all-cause mortality (P for nonlinear > 0.05). CONCLUSION: The SAPS III system demonstrated superior discriminatory ability for both 28-day and 1-year mortality compared to the GAS, SAPS II SIRS, SOFA, and OASIS systems among patients with AA.

Development of a predictive scoring system for vitamin D deficiency 'Vitamin D Deficiency Predicting Scoring (ViDDPreS)' based on the vitamin D status in young Japanese women: a nationwide cross-sectional study.

OBJECTIVE: Vitamin D deficiency (VDD) is common among young women and causes various health problems, including those that occur during pregnancy and childbirth. Thus, we investigated the risk factors for VDD in young Japanese women and developed a simple risk scoring system called Vitamin D Deficiency Predicting Scoring (ViDDPreS). DESIGN: A cross-sectional study, using the following factors for multivariate logistic regression analysis to create the ViDDPreS score: residential area, season, cumulative ambient ultraviolet-B irradiation, BMI, vitamin D supplement use, sun exposure habits, frequency of habitual food intake and eating habits. The subjects were randomly divided into development and test sets for analysis. Serum 25-hydroxivitamin D concentration of less than 20 ng/ml was defined as VDD. SETTING: Four regions (Hokkaido/Tohoku, Kanto, Chubu/Kinki/Shikoku and Kyushu/Okinawa) in Japan. PARTICIPANTS: Five hundred and eighty-three healthy women aged 18-40 years. RESULTS: In the development set, the VDD group (68·4 %) had higher proportions of the following variables than the non-VDD group: residential area outside the Kanto region; blood samples obtained in winter; low BMI (<18·5 kg/m2); vitamin D supplement non-users; short time regularly spent outside on weekdays; intake of fish, vitamin D-abundant fish, dried fish and redfish less than once a week. VDD risk was classified as low, medium or high according to the ViDDPreS scores including these contributing factors, with a test set C-index of 0·671. CONCLUSION: We identified the risk factors for VDD in young Japanese women and developed a simple risk scoring system that enables us to assess VDD risk and aid in the development of appropriate prevention and treatment strategies for this population.

Development of a machine learning-based target-specific scoring function for structure-based binding affinity prediction for human dihydroorotate dehydrogenase inhibitors.

Human dihydroorotate dehydrogenase (hDHODH) is a flavin mononucleotide-dependent enzyme that can limit de novo pyrimidine synthesis, making it a therapeutic target for diseases such as autoimmune disorders and cancer. In this study, using the docking structures of complexes generated by AutoDock Vina, we integrate interaction features and ligand features, and employ support vector regression to develop a target-specific scoring function for hDHODH (TSSF-hDHODH). The Pearson correlation coefficient values of TSSF-hDHODH in the cross-validation and external validation are 0.86 and 0.74, respectively, both of which are far superior to those of classic scoring function AutoDock Vina and random forest (RF) based generic scoring function RF-Score. TSSF-hDHODH is further used for the virtual screening of potential inhibitors in the FDA-Approved & Pharmacopeia Drug Library. In conjunction with the results from molecular dynamics simulations, crizotinib is identified as a candidate for subsequent structural optimization. This study can be useful for the discovery of hDHODH inhibitors and the development of scoring functions for additional targets.

Establishing a novel score system and using it to assess and compare the quality of ChatGPT-4 consultation with physician consultation for obstetrics and gynecology: A pilot study.

OBJECTIVES: In the current study, we aimed to establish a quantified scoring system for evaluating consultation quality. Subsequently, using the score system to assess the quality of ChatGPT-4 consultations, we compared them with physician consultations when presented with the same clinical cases from obstetrics and gynecology. METHODS: This study was conducted in the Women and Children's Hospital of Chongqing Medical University, a tertiary-care hospital with approximately 16 000-20 000 deliveries and 8500-12 000 gynecologic surgeries per year. The detailed data from obstetric and gynecologic medical records were analyzed by ChatGPT-4 and physicians; the consultation opinions were then generated respectively. All consultation opinions were graded by eight junior doctors using the novel score system; subsequently, the correlation, agreement, and comparison between the two types of consultation opinions were then evaluated. RESULTS: A total of 100 medical records from obstetrics and 100 medical records from gynecology were randomly selected. Pearson correlation analysis suggested a noncorrelation or weak correlation between consultations from ChatGPT-4 and physicians. Bland-Altman plot showed an unacceptable agreement between the two types of consultation opinions. Paired t tests showed that the scores of physician consultations were significantly higher than those generated by ChatGPT-4 in both obstetric and gynecologic patients. CONCLUSION: At present, ChatGPT-4 may not be a substitute for physicians in consultations for obstetric and gynecologic patients. Therefore, it is crucial to pay careful attention and conduct ongoing evaluations to ensure the quality of consultation opinions generated by ChatGPT-4.

External validation of the DIAFORA system to predict lower-extremity amputations in a prospective Danish cohort.

AIM: A diabetes-related foot ulcer (DFU) is a major risk factor for lower-extremity amputation (LEA). To help clinicians predict the risk of LEA in people with DFU, the Diabetic Foot Risk Assessment (DIAFORA) system was developed but has never been externally validated. METHODS: In this study, 317 people presenting with a new DFU were included. At baseline, participants were grouped into three groups based on their DIAFORA score: low-risk (<15), medium-risk (15-25), and high-risk (>25). Participants were followed until healing, LEA, death, or at least 3 months. Discriminative accuracy was evaluated using sensitivity, specificity, likelihood ratios (LRs) and the area under the curve (AUC). RESULTS: All 317 participants completed at least 3 months of follow-up for a median duration of 146 days, during which 12.6% underwent minor amputation and 2.5% major amputation. People in the low- and medium-risk categories had major amputation rates of 0.9% and 2.1%, respectively, and negative LR of major LEA of 0.10 and 0.38, respectively, while the people in the high-risk category had an amputation rate of 25.0% and a positive LR of 12.9. The DIAFORA risk groups had a sensitivity of 75.0% and a specificity of 65.7%, with a corresponding AUC of 0.78 (95% CI 0.68-0.87) for the prediction of major LEA. CONCLUSION: The DIAFORA score is a useful tool for risk stratification of people presenting with a newly occurred DFU, with the external validation presenting results similar to those presented in the original study. The DIAFORA score may guide clinicians towards more individualized DFU treatment regimens.

American Gastroenterological Association Clinical Practice Update on Endoscopic Scoring Systems in Inflammatory Bowel Disease: Commentary.

DESCRIPTION: Endoscopic scoring systems evaluate the severity of inflammation and provide objectivity, uniformity, and standardization of reporting of mucosal appearances in patients with inflammatory bowel disease; thus, they have been advised for assessing the efficacy of medical treatment and prognosis. This American Gastroenterological Association (AGA) Clinical Practice Update Expert Commentary aims to review the utilized endoscopic scoring systems and their role in assessing mucosal healing in inflammatory bowel disease and the practical challenges in their applications, as well as to discuss the future of endoscopic scoring systems. METHODS: This expert commentary was commissioned and approved by the AGA Institute Clinical Practice Updates Committee and the AGA Governing Board to provide timely guidance on a topic of high clinical importance to the AGA membership and underwent internal peer review by the Clinical Practice Updates Committee and external peer review through standard procedures of Clinical Gastroenterology and Hepatology. RESULTS/CONCLUSION: This expert commentary incorporates essential studies in this field and reflects the authors' expertise in the endoscopic evaluation of inflammatory bowel disease.