High Predictive Value Research Articles

Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio: A valuable predictor of coronary heart disease incidence

Background and aimExisting studies have found that serological markers for predicting coronary heart disease (CHD) have relatively low predictive value for the severity of coronary arteries and the types of CHD. GGT to HDL-C ratio (GHR) has been shown to be associated with T2DM and non-alcoholic fatty liver disease. Therefore, we explore the relationship among GHR, CHD and its subgroups. Methods and resultsThe study retrospectively analyzed 2703 participants from August 2022 to August 2023. The patients were divided into CHD group (N = 1911) and control group (N = 792) according to the diagnostic criteria of CHD. Adjustments for all covariates found that GHR was an independent risk factor for CHD (OR: 1.025, 95 % CI 1.016–1.033) and had the highest AUC of 0.767 (95 % CI 0.744–0.790) in identifying CHD. Additionally, GHR was significantly associated with multi-vessel CHD (OR: 1.018, 95 % CI 1.012–1.023) and showed excellent diagnostic capability for patients with multi-vessel CHD (AUC: 0.638). Moreover, compared with chronic coronary syndromes (CCS) and unstable angina (UA) groups, the level of GHR was significantly increased in acute myocardial infarction (AMI) (ST elevation myocardial infarction and Non-ST elevation myocardial infarction) group (P < 0.05). GHR had the higher AUC in STMETI [0.819 (95 % CI 0.796–0.854)] and NASTEMI [0.792 (95 % CI 0.766–0.816)] than the CCS and UA groups. ConclusionsOur study analyses found that GHR is an independent risk factor for CHD and can predict the severity of coronary artery stenosis. Moreover, GHR has a high predictive value for AMI than CCS and UA in CHD patients.

Study on medical dispute prediction model and its clinical-application effectiveness based on machine learning

BackgroundMedical dispute is a global public health issue, which has been garnering increasing attention. In this study, we used machine learning (ML) method to establish a dispute prediction model and explored the clinical-application efficiency of this model in effectively reducing the occurrence of medical disputes.MethodsRetrospective study of All disputes filed by Gansu Medical Mediation Committee from 2019 to 2021 and patients with the same hospital level as that of the dispute group and hospitalization year were randomly selected as the control group in 1:1 ratio. SPSS software was used for univariate feature selection of the 14 factors that may cause disputes, and factors with statistical differences were selected. The data were divided into training and test sets in a 7:3 ratio. Six ML models were selected, and Python was used to establish a dispute prediction model. The area under the curve (AUC) of the receiver operating characteristic curve (ROC), sensitivity, specificity, accuracy, precision, average precision (AP), and F1 score were used to characterize the fitting and accuracy of the models, while decision curve analysis (DCA) was used to evaluate their clinical utility.ResultsA total of 1189 patients in the dispute and control groups were extracted. Following 11 influencing factors were selected: the inpatient department, doctor title, patient age, patient gender, patient occupation, payment method, hospitalization days, hospitalization times, discharge method, blood transfusion volume, and hospitalization espenses. Compared to other models, the AUC (0.945, 95% CI 0.913–0.981), Sensitivity (0.887), Accuracy (0.887), AP (0.834), and F1 score (0.880) of the random forest model were higher than those of other models, while the DCA curve indicated its high clinical benefits.ConclusionsInpatient department, hospitalization expenses, and discharge type are the primary influencing factors of dispute. Random forest exhibited high dispute prediction and clinical-application value and is expected to be promoted for offline dispute prediction.

Exploring the Impact of Hemoglobin on Cerebral Blood Flow in Arterial Territories and Surgical Outcomes: Potential Implications for Moyamoya Disease Treatment.

Changes in levels of hemoglobin would result in alterations of cerebral blood flow (CBF). However, the impact of hemoglobin on CBF in moyamoya disease (MMD) remains largely unknown. This study sought to determine whether CBF would be influenced by hemoglobin before surgical revascularization and to analyze the relationships between hemoglobin and CBF with clinical outcome after surgery in patients with MMD. We prospectively enrolled adult patients with MMD undergoing surgical revascularization between June 2020 and December 2022. Preoperative CBF was measured in the territories of anterior, middle, and posterior cerebral arteries (ACA, MCA, and PCA, respectively) using 3-dimensional pseudo-continuous arterial spin labeling magnetic resonance imaging. Clinical outcome at 1 year after surgery was evaluated using the modified Rankin Scale. A total of 60 patients with MMD were included, with 25% (n=15) experiencing unfavorable outcomes. Patients with MMD exhibited lower CBF (ACA: P=0.007; MCA: P<0.001; PCA: P=0.014), compared with healthy controls (n=40). Hemoglobin was negatively and significantly associated with CBF (ACA: β=-0.45, P<0.001; MCA: β=-0.38, P<0.001; PCA: β=-0.54, P<0.001). CBF rather than hemoglobin was significantly related with clinical outcome (ACA: P<0.001; MCA: P<0.001; PCA: P=0.001), and CBF showed high discrimination in predicting clinical outcome (ACA: area under the curve, 0.84; MCA: area under the curve, 0.84; PCA: area under the curve, 0.80). Our findings demonstrate that hemoglobin significantly influences CBF, and CBF has a high predictive value for clinical outcome in MMD. The optimal hemoglobin level before surgical revascularization should be further investigated.

Predictive value of platelet-to-albumin ratio combined with the C2HEST score for New-Onset atrial fibrillation in elderly patients with acute ST-segment elevation myocardial infarction

BackgroundNew-onset atrial fibrillation (NOAF) is a common adverse outcome in acute ST-segment elevation myocardial infarction (STEMI) patients following percutaneous coronary intervention (PCI) and is associated with a worse prognosis. The platelet-to-albumin ratio (PAR) has been utilized to predict the severity and prognosis of cardiovascular diseases. This study aims to investigate the predictive value of PAR combined with the C2HEST score for NOAF in the elderly population with STEMI undergoing PCI.Methods445 elderly STEMI patients without a history of atrial fibrillation (AF) who underwent PCI were consecutively enrolled in this study. Multivariate logistic regression analysis was used to identify independent risk factors for NOAF after PCI.Results50 patients (11.2%) developed NOAF after PCI. Multivariate logistic regression analysis revealed that heart rate (HR), systemic immune-inflammation index (SII), uric acid (UA), PAR, and C2HEST score were independent risk factors for NOAF. The area under the curve (AUC) of the combined PAR and C2HEST score was 0.839, and Delong’s test indicated that the combined model had superior predictive value compared to individual markers (AUC of PAR: 0.738; AUC of C2HEST score: 0.752) (P < 0.05). The addition of PAR and C2HEST score to this model (HR, SII, and UA) significantly improved the reclassification and discrimination ability (IDI 0.175; NRI 0.734, both P < 0.001). During regular follow-up, the incidence of MACE was higher in the NOAF group compared to the non-NOAF group.ConclusionThe combination of PAR and the C2HEST score has a high predictive value for NOAF in elderly STEMI patients following PCI.

Associations between neutrophil-percentage-to-albumin ratio level and all-cause mortality and cardiovascular disease-cause mortality in general population: evidence from NHANES 1999-2010.

Chronic inflammation is a recognized independent risk factor for cardiovascular disease (CVD), highlighting the need for reliable inflammatory indicator to predict CVDs. As an inflammatory indicator which has been proved to have predictive value for prognosis of CVDs, neutrophil percentage-to-albumin ratio (NPAR) has obtained increasing attention, but further research is needed to confirm the relationship with mortality in the general population. This prospective cohort study included 21,317 individuals who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010, where baseline characteristics and NPAR level were extracted. Data for CVD and all-cause mortality were acquired by linking the cohort database with the National Death Index through December 31, 2019. We employed restricted cubic spline analyses to examine the nonlinear association. Weighted Kaplan-Meier curves with log-rank tests were conducted to access cumulative survival differences across different NPAR results. Multivariable Cox proportional hazards regression models were used to compute hazard ratios and 95% CIs. Receiver Operating Characteristic (ROC) curves were used to compare predictive value of NPAR with systemic immune inflammation index (SII) and neutrophils percent. In this cohort study, during 270,014 person-years of follow-up, 4,074 all-cause deaths and 1,116 CVD-cause deaths were documented. NPAR levels exhibited significant nonlinear associations with both CVD-cause (P = 0.018 for nonlinearity) and all-cause mortality (P < 0.001 for nonlinearity). Participants in the highest NPAR tertile had a significantly increased risk of all-cause mortality (HR: 1.46, 95% CI: 1.33-1.61) and CVD-cause mortality (HR: 1.54, 95% CI: 1.32-1.80) compared to those in the lowest tertile in the fully adjusted model, while no association was detected for individuals in the middle tertile. Further ROC analysis confirmed that NPAR had higher predictive value than neutrophil percent segment and SII. Elevated NPAR level was significantly associated with an increased risk of all-cause and CVD-cause mortality in general population. The high predictive value of NPAR, combined with the easy-to-calculate property, suggests that its potential as a novel inflammatory indicator is worthy of further investigation.

Real-Time Dialysis Dose: Ionic Dialysis Versus Classical Urea Kinetic Modeling Indices.

Introduction Worldwide, over 850 million people need renal replacement therapy, and over 80% of them are on hemodialysis. The term "dialysis adequacy" is most often associated with the achievement of minimally acceptable indices - single pool Kt/V (spKt/V) and urea reduction ratio (URR%) and largely does not take into account other clinical indicators in patients. In addition, it should be taken into account that in the conditions of clinical practice, their measurement is carried out according to standards controlled by the regulatory structures and is carried out with a frequency between one and three months, and not during each dialysis procedure. Accordingly, based on the obtained value, we assume that it refers to the urea clearance of the entire dialysis prescription. A new methodology for measuring dialysis adequacy through ionic dialysis allows dose estimation in real time without the need for additional blood testsby recording the difference in sodium ion conductivity at the dialyzer inlet and outlet. The latter corresponds to the dialysis dose delivered and can be measured at each dialysis session, enabling timely therapeutic intervention at minimal cost to the community. The aim of this original article is to present ion dialysis to the community as a reliable and inexpensive alternative to classical urea kinetic modeling (UKM), evaluating the comparability of the two methods and the possible sources of error in the result. Material and methods This was a retrospective study of 32 patients undergoing hemodialysis at the Clinic of Nephrology and Dialysis at the University Hospital St. Marina (Varna, Bulgaria) for the period between January and December 2020.For each of the patients, four measurements (every three months) of the delivered dialysis dose were performed by ion dialysis and classical urea kinetic modeling in order to assess the comparability and reliability of the two methods. Results The analysis of the results proved a high correlation between the validated indicators of dialysis adequacy (spKt/V; URR) and those registered with online monitoring (online clearance monitor) by ionic dialysis - online Kt/V (onKt/V)while at the same time reporting a significant difference in the two methods - primarily based on the anthropometric formulas used to estimate the volume. The established regression models confirmed the high predictive value of ionic dialysis in relation to the actually delivered dose. Discussion Despite the high bond strength, our recorded values ​​for onKt/V are 8% lower compared to results using UKM. Therefore, onKt/V as an assessment metric has the ability to underestimate the dialysis dose received. Various factors as a possible source of error and its cause have been reported by some authors. Several studies have reported differences of 2-5% in instantaneous conductance measurements, which they associate mainly with differences in the diffusion coefficients of urea and sodium, as well as different effects of dialysis membrane charge or inadequate ultrafiltration correction. Conclusions Our study confirms that online clearance monitoring (OCM) is a practical non-invasive tool for daily use that complements the classic performance of OCM by helping to deliver an adequate dialysis dose with increased patient benefit and minimal cost of financial resources.

Clinical values of MRSI, CRP and FABP4 in the diagnosis and prognosis of acute pancreatitis.

To examine the clinical values of C-reactive protein (CRP), fatty acid-binding protein 4 (FABP4) and magnetic resonance severity index (MRSI) in acute pancreatitis (AP) cases. 70 AP patients and another 70 healthy controls were recruited, and the MRSI score was calculated. Receiver operator characteristic (ROC) curve was used for diagnostic performance analysis. FABP4 levels were elevated in AP patients, and significantly correlated with CRP and MRSI score. Serum FABP4 and MRSI score displayed high diagnostic performance for AP. FABP4, MRSI score and CRP levels were positively correlated with disease severity. MRSI score and FABP4 were independently related to patients' survival, and showed high predictive values. FABP4 may serve as a potential marker for the diagnosis of AP, with the advantages of low cost and high simplicity. The levels of FABP4 and MRSI score can predict the poor survival of the patients.

Susceptibility Screening of HIV-1 Viruses to Broadly Neutralizing Antibodies, Teropavimab and Zinlirvimab, in People With HIV-1 Suppressed by Antiretroviral Therapy.

HIV envelope (env) diversity may result in resistance to broadly neutralizing antibodies (bNAbs). Assessment of genotypic or phenotypic susceptibility to antiretroviral treatment is often performed in people with HIV-1 (PWH) and used for clinical trial screening for HIV-1 bNAb susceptibility. Optimal bNAb susceptibility screening methods are not yet clear. Phenotypic and genotypic analyses were conducted on 124 screening samples from a phase 1b study of bNAbs teropavimab (3BNC117-LS) and zinlirvimab (10-1074-LS) administered with lenacapavir in virally suppressed PWH. Phenotypic analysis was conducted on integrated HIV-1 provirus and stimulated outgrowth virus, with susceptibility to bNAbs defined as 90% inhibitory concentration ≤2 μg/mL. The proviral DNA HIV env gene was genotyped using deep sequencing, and bNAb susceptibility predicted using published env amino acid signatures. Proviral phenotypic results were reported for 109 of 124 samples; 75% (82/109) were susceptible to teropavimab, 65% (71/109) to zinlirvimab, and 50% (55/109) to both bNAbs. Phenotypic susceptibility of outgrowth viruses was available for 39 samples; 56% (22/39) were susceptible to teropavimab, and 64% (25/39) to zinlirvimab. Phenotypic susceptibilities correlated between these methods: teropavimab r = 0.82 ( P < 0.0001); zinlirvimab r = 0.77 ( P < 0.0001). Sixty-seven samples had genotypic and phenotypic data. Proviral genotypic signatures predicted proviral phenotypic susceptibility with high positive predictive value (68%-86% teropavimab; 63%-90% zinlirvimab). bNAb susceptibility was correlated among all 3 in vitro assays used to determine teropavimab and zinlirvimab susceptibility in virally suppressed PWH. These findings may help refine PWH selection criteria for eligibility for future studies.

Derivation of a clinical decision rule for termination of resuscitation in non-traumatic pediatric out-of-hospital cardiac arrest

AimPrehospital termination of resuscitation (ToR) rules are used to predict medical futility in adult out-of-hospital cardiac arrest (OHCA), however, the available evidence for pediatric patients is limited. The primary aim of this study is to derive a Pediatric Termination of Resuscitation (PToR) prediction rule for use in pediatric non-traumatic OHCA patients. MethodsWe analyzed a retrospective cohort of pediatric OHCA patients within the CARES database over a 10-year period (2013–2022). We split the dataset into training and test datasets and fit logistic regressions with Least Absolute Shrinkage and Selection Operator (LASSO) to select predictor variables and estimate predictive test characteristics for the primary outcome of death and a secondary composite outcome of death or survival to hospital discharge with unfavorable neurologic status. ResultsWe analyzed a sample of 21,240 children where 2,326 (11.0%) survived to hospital discharge, and 1,894 (8.9%) survived to hospital discharge with favorable neurologic status. We derived a PToR rule for death demonstrating a specificity of 99.1% and a positive predictive value (PPV) of 99.8% and a PToR rule for death or survival with poor neurologic status with a specificity of 99.7% and PPV of 99.9% within the test dataset. ConclusionWe derived a clinical prediction rule with high specificity and positive predictive value in prehospital settings utilizing Advanced Life Support (ALS) providers which may inform termination of resuscitation considerations in pediatric patients. Further prospective and validation studies will be necessary to define the appropriateness and applicability of these PToR criteria for routine use.

Ultrasound-based radiomics nomogram for predicting HER2-low expression breast cancer.

Accurate preoperative identification of Human epidermal growth factor receptor 2 (HER2) low expression breast cancer (BC) is critical for clinical decision-making. Our aim was to use machine learning methods to develop and validate an ultrasound-based radiomics nomogram for predicting HER2-low expression in BC. In this retrospective study, 222 patients (108 HER2-0 expression and 114 HER2-low expression) with BC were included. The enrolled patients were randomly divided into a training cohort and a test cohort with a ratio of 8:2. The tumor region of interest was manually delineated from ultrasound image, and radiomics features were subsequently extracted. The features underwent dimension reduction using the least absolute shrinkage and selection operator (LASSO) algorithm, and rad-score were calculated. Five machine learning algorithms were applied for training, and the algorithm demonstrating the best performance was selected to construct a radiomics (USR) model. Clinical risk factors were integrated with rad-score to construct the prediction model, and a nomogram was plotted. The performance of the nomogram was assessed using receiver operating characteristic curve and decision curve analysis. A total of 480 radiomics features were extracted, out of which 11 were screened out. The majority of the extracted features were wavelet features. Subsequently, the USR model was established, and rad-scores were computed. The nomogram, incorporating rad-score, tumor shape, border, and microcalcification, achieved the best performance in both the training cohort (AUC 0.89; 95%CI 0.836-0.936) and the test cohort (AUC 0.84; 95%CI 0.722-0.958), outperforming both the USR model and clinical model. The calibration curves showed satisfactory consistency, and DCA confirmed the clinical utility of the nomogram. The nomogram model based on ultrasound radiomics exhibited high prediction value for HER2-low BC.

MME and PTPRC: key renal biomarkers in lupus nephritis

Background Lupus nephritis (LN) is an autoimmune-related kidney disease with a poor prognosis, however the potential pathogenic mechanism remains unclear and there is a lack of precise biomarkers. Therefore, a thorough screening and identification of renal markers in LN are immensely beneficial to the research on its pathogenic mechanisms and treatment strategies. Methods We utilized bioinformatics to analyze the differentially expressed genes (DEGs) at the transcriptome level of three clusters: total renal, glomeruli, and renal tubulointerstitium in the GEO database to discover potential renal biomarkers of LN. We utilized NephroSeq datasets and measured mRNA and protein levels in the kidneys of MRL/lpr mice to confirm the expression of key DEGs. Results Seven significantly differential genes (EGR1, MME, PTPRC, RORC, MX1, ZBTB16, FKBP5) were revealed from the transcriptome database of GSE200306, which were mostly enriched in the pathway of the hematopoietic cell lineage and T cell differentiation respectively by KEGG and GO analysis. The seven hot differential genes were verified to have consistent change trends using three datasets from NephroSeq database. The receiver operating characteristic (ROC) curve indicated that five DEGs (PTPRC, MX1, EGR1, MME and RORC) exhibited a higher diagnostic ROC value in both the glomerulus and tubulointerstitium group. Validation of core genes using MRL/lpr mice showed that MME and PTPRC exhibit significantly differential mRNA and protein expression patterns in mouse kidneys like the datasets. Conclusions This study identified seven key renal biomarkers through bioinformatics analysis using the GEO and NephroSeq databases. It was identified that MME and PTPRC may have a high predictive value as renal biomarkers in the pathogenesis of LN, as confirmed by animal validation.

Liver segmental volumes and their relationship with 5-year prognostication.

This study aimed to analyze the predictive value of caudate to right lobe ratio (CRL-R) and liver segmental volume ratio (LSVR) for chronic liver disease (CLD) on routine abdominal CT scans and their association with 5-year decompensation- and transplant-free survival. This retrospective study included 108 patients without CLD and 98 patients with biopsy-proven CLD. All patients underwent abdominal CT scans between 03/2015 and 08/2017. Patients with CLD were divided into three groups: early CLD (F0-F2; eCLD; n = 40), advanced CLD (F3-F4; aCLD; n = 20), and aCLD with clinically significant portal hypertension (aCLDPH; n = 38). CRL-R and LSVR were compared between groups using Kruskal-Wallis test and ROC analysis to determine cutoff-values. 5-year decompensation- and transplant-free survival were assessed by Kaplan-Meier curve analysis. CRL-R and LSVR were significantly different between all groups (p < 0.001). A CRL-R cutoff-value of > 0.99 predicted aCLD with a sensitivity of 69% and a specificity of 80% (AUC = 0.75, p < 0.001), while LSVR > 0.37 had a sensitivity of 67% and a specificity of 84% (AUC = 0.80, p < 0.001). CLD-patients with both CRL-R > 0.99 and LSVR > 0.37 had a significantly lower probability of 5-year decompensation-free survival (31%) as well as lower probability of 5-year transplant-free survival (41%) than those with a CRL-R < 0.99 and/or LSVR < 0.37 (70%, 62%, p = 0.006, p = 0.038). CRL-R and LSVR showed a high predictive value for CLD on routine abdominal CT scans. In patients with CLD, both CRL-R and LSVR may be combined and are associated with 5-year decompensation-free and transplant-free survival.

Prognostic value of serum total IgE and FeNO levels in children with atopic constitution bronchiolitis

Bronchiolitis is a significant factor contributing to bronchial asthma in infants and young children. After treatment, recurrent wheezing symptoms often occur, especially in children with atopic constitution, who tend to have more severe conditions and poorer prognosis. Therefore, exploring the prognostic value of total serum immunoglobulin E (tIgE) and fractional exhaled nitric oxide (FeNO) levels in children with atopic constitution who suffer from bronchiolitis is of great significance. A total of 260 children with bronchiolitis admitted to our hospital from October 2020 to June 2022 were regarded as the research subjects with prospective study, according to whether the children had atopic constitution, they were grouped into non atopic constitution group (n = 156) and atopic constitution group (n = 104); after 6 months of treatment, children with atopic constitution were grouped into a good prognosis group (n = 58) and a poor prognosis group (n = 46) based on their prognosis; in addition, 260 healthy children who underwent physical examination and had clinical data consistent with those of children with bronchiolitis were regarded as the reference group. The serum tIgE and FeNO levels of each group were compared; multivariate Logistic regression was applied to analyze the prognostic factors of children with atopic constitution bronchiolitis; ROC curve was applied to analyze the predictive value of tIgE and FeNO levels after treatment for the prognosis of children with atopic constitution bronchiolitis. The tIgE levels in the control group, non-atopic group, and atopic group [(123.54 ± 29.62) IU/mL, (245.71 ± 30.59) IU/mL, (316.46 ± 31.78) IU/mL, respectively] increased sequentially, with statistically significant differences (F = 1766.954, P = 0.000). The FeNO levels in the control group, non-atopic group, and atopic group [(8.36 ± 3.57) ppb, (15.28 ± 3.69) ppb, (19.84 ± 3.58) ppb, respectively] also increased sequentially, with statistically significant differences (F = 765.622, P = 0.000). The tIgE, FeNO, proportion of patients with asthma family history, and proportion of patients with allergic family history in the poor prognosis group were obviously higher than those in the good prognosis group (P < 0.05). Multivariate Logistic regression analysis showed that family history of asthma, family history of allergies, tIgE, and FeNO were influencing factors for the prognosis of children with atopic bronchiolitis (P < 0.05). The AUC of the combination of tIgE and FeNO in predicting the prognosis of children with atopic constitutional bronchiolitis was 0.910, with a sensitivity of 78.26% and a specificity of 93.10%, which was superior to the independent prediction of tIgE and FeNO (Zcombined detection−tIgE = 2.442, Zcombined detection−FeNO = 3.080, P = 0.015, 0.002). The levels of tIgE and FeNO in children with atopic constitution bronchiolitis are obviously increased, and the combination of the two has high predictive value for the prognosis of atopic constitution bronchiolitis.

Study of Variables Related to Cerebrovascular Accident in Patients with COVID-19: A Literature Review

The objective of this article is to provide a bibliographic survey on the relationship between COVID-19 and stroke through a systematic review conducted in national and international journals without temporal delimitation, using articles indexed in multidisciplinary and health databases. The databases investigated were: BVS, PubMed, ERIC, SciELO, Web of Science, and Sociological Abstracts. Among the studies found, 43 articles were selected. Some of these were then used to produce the "literature review" section. Since stroke and COVID-19 can present similar symptoms, diagnosing stroke can be more challenging in some cases, highlighting the need for further research on the subject. The studies show a relationship between the severity of the condition and the occurrence of vascular events, with a higher incidence observed in patients hospitalized in intensive care units (ICUs). Additionally, it is important to mention the significance of d-dimer levels in the patient, as it is a factor with high predictive value for thrombotic events. The challenges in improving diagnosis and treatment are primarily due to the difficulty in understanding the pathophysiology, triggering events, and research on the topic.

Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening

ObjectiveTo assess the feasibility of using non-mydriatic fundus photography in conjunction with an artificial intelligence (AI) reading platform for large-scale screening of diabetic retinopathy (DR). MethodsIn this study, we selected 120 patients with diabetes hospitalized in our institution from December 2019 to April 2021. Retinal imaging of 240 eyes was obtained using non-mydriatic fundus photography. The fundus images of these patients were divided into two groups based on different interpretation methods. In Experiment Group 1, the images were analyzed and graded for DR diagnosis using an AI reading platform. In Experiment Group 2, the images were analyzed and graded for DR diagnosis by an associate chief physician in ophthalmology, specializing in fundus diseases. Concurrently, all patients underwent the gold standard for DR diagnosis and grading—fundus fluorescein angiography (FFA)—with the outcomes serving as the Control Group. The diagnostic value of the two methods was assessed by comparing the results of Experiment Groups 1 and 2 with those of the Control Group. ResultsKeeping the control group (FFA results) as the gold standard, no significant differences were observed between the two experimental groups regarding diagnostic sensitivity, specificity, false positive rate, false negative rate, positive predictive value, negative predictive value, Youden's index, Kappa value, and diagnostic accuracy (X2 = 0.371, P > 0.05). ConclusionCompared with the manual reading group, the AI reading group revealed no significant differences across all diagnostic indicators, exhibiting high sensitivity and specificity, as well as a relatively high positive predictive value. Additionally, it demonstrated a high level of diagnostic consistency with the gold standard. This technology holds potential for suitability in large-scale screening of DR.

Predicting survival in sepsis: The prognostic value of NLR and BAR ratios.

Due to the high-risk nature of sepsis, emergency departments urgently need a simple evaluation method to assess the degree of inflammation and prognosis in sepsis patients, providing a reference for diagnosis and treatment. To investigate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) combined with the blood urea nitrogen-to-serum albumin ratio (BAR) in sepsis. A total of 377 sepsis patients admitted to Lishui People's Hospital from June 2022 to June 2023 were selected as the study subjects. Based on their prognosis, they were divided into a survival group (255 cases) and a death group (82 cases). The clinical data of the two groups were compared. Multivariate logistic analysis was used to identify factors influencing sepsis prognosis, and ROC curve analysis was used to assess the predictive efficacy of NLR, BAR, and their combination. Compared with survivors, non-survivors had higher NLR and BAR, with statistically significant differences (p< 0.05). After adjusting for confounding factors, NLR (OR = 1.052) and BAR (OR = 1.095) were found to be independent prognostic factors for sepsis patients (both p< 0.05). The AUC of NLR combined with BAR was 0.798 (95% CI 0.745-0.850, p< 0.05), higher than the AUC of NLR alone (0.776) and BAR alone (0.701). The combination of NLR and BAR has a high predictive value for the prognosis of sepsis patients. Its simple calculation makes it particularly suitable for use in emergency departments.

Prognostic Significance of Tumor and Inflammatory Markers in Disease-Free and Overall Survival Duration in Colonic Adenocarcinoma Patients.

Introduction Colorectal carcinoma (CRC) continues to be a major global health concern, contributing substantially to cancer incidence and mortality. Colonic adenocarcinoma, a common subtype of CRC, is influenced by various prognostic factors, including tumor stage, histopathological characteristics, and tumor markers. Despite their routine use in clinical settings, the prognostic value of traditional tumor markers, such as carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA 19-9), and others, is still under debate. In this study, we aim to analyze the tumor markers' prognostic significance in our CRC patients in terms of disease-free survival and overall survival. Methods A retrospective study was conducted on 71 patients who underwent surgery for colonic adenocarcinoma between January 1, 2018, and January 1, 2024. Data on patient demographics, recurrence rates, survival times, and tumor marker levels (CEA, CA 19-9, CA 125, AFP, and CRP to albumin ratio (CAR)), disease-free survival duration (DFS), and overall survival durations (OS) were collected and analyzed. Statistical analyses included Pearson and Spearman correlation coefficients, the Mann-Whitney U test, ROC curve analysis, and Kaplan-Meier survival analysis. Results The study found that elevated CAR and CA 125 levels were significantly associated with higher mortality and recurrence rates, whereas elevated CEA levels were strongly predictive of recurrence. Receiver operating characteristic (ROC) analysis identified optimal cutoff values for these markers, with CEA ≥ 47.145, CA 125 ≥ 15.85, and CAR ≥ 6.796 demonstrating high specificity and predictive value for recurrence. Kaplan-Meier analysis revealed that patients with CEA < 47.145 had a significantly longer DFS (67.7 months) compared to those with CEA ≥ 47.145 (24 months, p < 0.001). Similarly, patients with CA 125 < 15.85 and CAR < 6.796 showed longer DFS compared to those with higher values. Overall survival analysis also highlighted that patients with CA 125 < 21.71 and CAR < 4.09 had better survival outcomes, with significant differences of 26 and 10 months, respectively (p < 0.001 and p = 0.001). Conclusion Tumor markers, such as CEA, CA 125, and CAR, hold significant prognostic value in colonic adenocarcinoma, with higher levels correlating with poorer outcomes. These findings underscore the importance of integrating tumor markers into clinical decision-making to optimize treatment strategies and improve patient survival. Future research should focus on standardizing the use of these markers and exploring novel biomarkers for enhanced prognostication.

Positive predictive value of administrative diagnosis codes, for all patient encounters in the electronic health record, to detect postoperative infections: Retrospective cohort study after cesarean delivery

BackgroundPrioritization of anesthetizing locations for infection prevention depends on having a high positive predictive value for the detection of postoperative infection (PPV). Our study goal was to estimate the PPV after cesarean birth using hospital's International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes. Because earlier studies had low PPV for infection from antibiotic medication administration records, if each prescription had a corresponding diagnosis code, infections must have been listed for presumptive diagnoses (e.g., redness), not literally infection. Our cohort of obstetrical patients was unique for scientific investigation in that the vast majority developing postoperative infection were evaluated postoperatively by the same (surgical) department. MethodsThe population studied were all patients undergoing cesarean delivery from October 2015 through March 2022 at the University of Iowa. The ICD-10-CM codes were obtained from any type of encounter in the health record (e.g., clinic visit or emergency room). The hospital's quality improvement daily surveillance program followed National Healthcare Safety Network (NHSN) definitions. ResultsThe 147 cases studied were 2.9 % of the 5006 cesarean deliveries performed. Every postoperative infection from the daily surveillance program was included among the 147 cases. There were 144 of these patients evaluated by an obstetrician on the date of the ICD-10 diagnosis code(s) detecting postoperative infection. The estimated positive predictive value was 99.3 % (143/144), lower 95 % confidence limit 96.8 %. ConclusionsTo optimize patient benefit and hospital return on investment, infection preventive measures should include operating room/specialty combinations with the most postoperative infections. Automated health record review is needed. Every ICD-10-CM code is based on a clinician's note and thus the clinician's specialty (department) is known from the hospital's diagnosis tables. Using diagnosis codes for 90-day postoperative infection from surgeons' notes, high positive predictive value can be obtained (e.g., for use by anesthesia departments).

Imaging findings in suspected penile fracture: alternative diagnoses and surgical correlation.

The primary objective is to compare the imaging and surgical findings in a cohort of patients with suspected penile fracture (PF). Retrospective cohort study of all patients with suspected PF over an 11-year period at a tertiary referral andrology centre. All dedicated presurgical imaging with ultrasound (US) and MRI was analysed and correlated with intraoperative findings; alternative diagnoses were recorded. One hundred and ninety-three patients were included. One hundred and four (54%) had alternative diagnoses to PF including dorsal vein rupture and haematoma. Ninety-nine (51%) underwent surgical exploration of which 89 (46%) had PF. US correctly confirmed the presence and marked the site of fracture in 92% of cases. MRI was primarily used as a problem-solving tool (13 cases) and demonstrated a more extensive injury than US (12 cases). The reported size of tunical defect on imaging was a median of 7 mm (IQR 4-10) significantly smaller than on exploration (median 20 mm, IQR 10-30; P < .0001). US has a high positive predictive value in the confirmation of PF. MRI improves the detection and characterizing the extent of injury. Imaging marking informs surgical incision but defect size is under appreciated on all imaging modalities. Penile imaging has a high positive predictive value to not only confirm the diagnosis of PF but to stage the extent of injury and mark the skin, which impacts the surgical technique. Alternative diagnoses to fracture are common and imaging could prevent unnecessary surgical exploration.

Role of ultrasound and magnetic resonance neurography in the detection of median nerve abnormalities in carpal tunnel syndrome

BackgroundThe most prevalent cause of peripheral nerve entrapment is carpal tunnel syndrome, which is characterized by compression of the median nerve at the wrist as a result of nearby or localized microvascular interference as well as structural alterations to the median nerve or adjacent tissues. However, no special information regarding the median nerve or its surroundings is provided by clinical examination or electrophysiological testing. The purpose of this study is to evaluate the effectiveness of magnetic resonance neurography (MRN) and ultrasound in identifying changes and abnormalities of the median nerve in carpal tunnel syndrome.MethodsThe twenty-five patients in this study ranged in age from 27 to 63 years old, with a mean age of 47. There were 18 female patients and seven male patients. All patients were sent to the radiology department from the orthopedics, neurology, outpatient clinic, and neurology department, at Ain Shams Hospital, Faculty of Medicine, Ain Shams University. All of the patients had clinically manifested pain along the median nerve distribution, each of the sixteen patients had hand paresthesia, and four had thenar muscle atrophy.ResultsIn the current study, Ultrasound exhibits low negative predictive value of 67% and specificity of 67%, but high positive predictive value of 95%, sensitivity of 95%, and overall accuracy of 92%. On the other hand, (MRN) exhibits a low negative predictive value of 60% and a high specificity of 75% in the diagnosis of nerve entrapment, but it also displays a high positive predictive value of 95%, sensitivity of 90%, and overall accuracy of 88%. Regarding the assessment of the recurrence cause and post-surgical evaluation is more reliable by Magnetic Resonance Neurography examination.ConclusionsMagnetic resonance neurography and high-resolution ultrasonography can be utilized to diagnose patients with median nerve entrapment and patients who cannot be diagnosed electrophysiologically.MRN is a more accurate method for detecting the exact location of nerve entrapment and evaluating nerve recovery after surgical intervention than nerve conduction studies and electromyography. Additionally, MRN can be used to identify causes that were not previously recognized based on physical examination and electrophysiological tests.