High-risk Patients Research Articles

Ultrasound, contrast-enhanced ultrasound and pyelonephritis: A narrative review

Acute pyelonephritis (APN) is a bacterial infection resulting in kidney inflammation, typically arising as a complication of an ascending urinary tract infection that ascends from the bladder to the kidneys. Clinical diagnosis is generally based on clinical and laboratory findings. Recent guidelines recommend not performing diagnostic imaging unless a complicated APN is suspected or the infection affects high-risk patients such as the elderly, immunocompromised individuals, or diabetics. Contrast-enhanced ultrasound (CEUS) is a valuable tool in both the diagnosis and follow-up of APN. It aids in distinguishing small simple nephritic involvement from abscess complications and monitoring their evolution over time during antibiotic therapy. Given its lack of ionizing radiation and nephrotoxicity, CEUS is a valid diagnostic modality for approaching and monitoring pyelonephritis, improving early identification and characterization of inflammatory lesions. This review aims to summarize the main evidence on the use of ultrasound and CEUS in the diagnosis of APN and its follow-up.

Abstract A161: Racial and ethnic differences in receipt of guideline-recommended hepatocellular carcinoma surveillance in a high Risk, diverse primary care patient population: A study in two large integrated healthcare systems in California and Hawai‘i

Abstract Guideline-recommended ultrasounds for hepatocellular carcinoma (HCC) surveillance target patients with cirrhosis and certain liver conditions, yet uptake remains low, particularly among racial/ethnic minority groups. Underuse may be attributed to factors at the patient, provider, healthcare system, and neighborhood levels. However, in-depth analyses identifying contributory factors are lacking. We investigated the presence of racial/ethnic disparities in receipt of recommended surveillance among high-risk patients as a retrospective analysis of electronic health record (EHR) data from Kaiser Permanente Hawai‘i (KPHI) and Sutter Health in California, both of which serve numerous Asian American, Hispanic, Native Hawaiian (NH), other Pacific Islander (PI), and multiracial/ethnic patients. We included patients with ≥1 in-person encounter (2000-2017), no history of liver cancer, and a clinical indication of surveillance eligibility (cirrhosis, chronic hepatitis B or C, or a high FIB-4 score ≥2.67) with a minimum EHR follow-up of 18 months post-eligibility. Recommended surveillance is biannual abdominal imaging (ultrasound, CT, MRI) or alpha-1 fetoprotein tests. We categorized eligible patients as 'ever surveilled' if conducted at least once during follow-up and by the proportion of follow-up time they were up-to-date with surveillance (PTUDS). The cohort includes 54,597 patients (9,488 from KPHI; 45,109 from Sutter); current results are for the KPHI subset only. Among N=9,488 patients (median age: 52; 46% female; 26% NHW, 14% NH, 11% Filipino, 10% multiracial/ethnic) median follow-up was 91 months and 82% were surveilled at least once, with a mean PTUDS of 14% (SD=19%) overall and 19% (SD=21%) among the surveilled. We used sex- and age-adjusted log-risk regression for risk ratio (RR) of ‘ever surveilled’ vs. not and linear regression for PTUDS; NHW is the reference group in all models. We found that NH (RR=0.96, 95%CI 0.93-1.00), PI (RR=0.91, 95%CI 0.97-0.95) and multiracial/ethnic (RR=0.95, 95%CI 0.91-0.99) patients were significantly less likely to be ever surveilled, and that PI (beta=-0.02, 95% CI -0.04-0.01) race/ethnicity was significantly associated with lower PTUDS, while Chinese (beta=0.04, 95% CI 0.02-0.06), Korean (beta=0.04, 95%CI 0.01-0.07), Vietnamese (beta=0.05, 95%CI 0.02-0.09), and other Asian (beta=0.03, 95%CI 0.00-0.07) ethnicities were significantly associated with higher PTUDS. Although not statistically significant, surveillance rates were lower for American Indian/Alaska Native and Black groups, and higher for Japanese and Non-Hispanic Other race/ethnicity groups. Continued analyses will incorporate Sutter data, employ fully adjusted models with clustering by health system, and examine patient, provider, and neighborhood drivers of these disparities. Our findings indicate racial/ethnic disparities in HCC surveillance receipt, particularly noting the heterogeneity within Asian populations, and underscore the importance of analyzing disaggregated data for Asian American groups to fully understand and address these disparities. Citation Format: Enyao Y. Zhang, Mindy DeRouen, Alison J. Canchola, Aly M. Cortella, Pushkar Inamdar, Janet N. Chu, Sixiang Nie, Mai Vu, Ma Somsouk, Michele M. Tana, Anna D. Rubinsky, Iona Cheng, Mi-Ok Kim, Mark Segal, Chanda Ho, Yihe G. Daida, Su-Ying Liang, Hashem B. El-Serag, Scarlett L. Gomez, Salma Shariff-Marco, Caroline A. Thompson. Racial and ethnic differences in receipt of guideline-recommended hepatocellular carcinoma surveillance in a high Risk, diverse primary care patient population: A study in two large integrated healthcare systems in California and Hawai‘i [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A161.

Drugs causing prostate-specific antigen changes: the food and drug administration adverse event reporting system combined with Mendelian randomization analysis

ABSTRACT Background Prostate cancer is one of the most common malignancies in men worldwide, and prostate-specific antigen (PSA) screening is widely used for its early detection. Drug use may affect PSA levels, but the effect for most drugs is currently unknown. Methods This study first investigated drugs related to PSA changes through the Food and Drug Administration Adverse Event Reporting System (FAERs) database, and then used a Mendelian randomization (MR) method to explore the causal relationship between specific drugs and PSA changes using a genome-wide association study (GWAS) data. The statistical analysis software SAS and R were used in the study. Results Through analysis of the FAERs database, 22 drugs were found to be associated with an increase in PSA, and 14 drugs were associated with a decrease in PSA. MR analysis showed that the use of tamsulosin may lead to an increase in PSA. Heterogeneity test, horizontal pleiotropy test and leave-one-out Analysis verified the stability of the results. MR analyses for other drugs did not show statistical significance. Conclusion This study provided a basis for better understanding the impact of medications on prostate health, helping to avoid overdiagnosis or underdiagnosis of high-risk patients. However, research still requires larger-scale validation and in-depth exploration.

Long-term outcomes of Allium ureteral stent as a treatment for ureteral obstruction

Ureteral obstruction is a prevalent urological condition associated with significant complications. The purpose of our study was to assess the safety and efficacy of a novel self-expanding, large caliber, biocompatible polymer-coated ureteral stent (Allium) for the treatment of ureteral obstructions. We conducted a retrospective analysis of data from patients who underwent Allium ureteral stent placement at our institute between November 2018 and May 2023. Demographic, clinical, and perioperative parameters were collected and analyzed. Logistic regression analyses were performed to identify preoperative factors predicting Allium stent migration. The study cohort comprised 30 patients who received a total of 40 successfully implanted Allium stents. No significant adverse events related to the insertion procedure were observed. During a median follow-up period of 29 months (range: 1–60 months), migration occurred in 11 (27.5%) stents while encrustation was noted in 8 (20%) stents. The median functional duration of the Allium stents was found to be 22 months (range:1–60 months), with an overall functioning rate at last follow-up being recorded as 59.5%. Multivariate analysis revealed that the glomerular filtration rate of the ipsilateral kidney was the sole risk factor predictive of Allium stent migration. With its minimal invasiveness and good tolerability, the Allium stent represents a safe and viable management option for treating ureteric obstructions; however, it should not be considered as definitive treatment but rather as an alternative option for patients unwilling or unsuitable for definitive treatment, particularly high-risk individuals or elderly patients exhibiting decreased ipsilateral glomerular filtration rates.

Performance of D-dimer, cardiac troponin T, C-reactive protein and NT-proBNP in prediction of long-term mortality in patients with suspected pulmonary embolism

Abstract Background Pulmonary embolism (PE) is a common and potentially life-threatening condition requiring emergent diagnostic work-up. Despite wide use of biomarkers, little is known how they predict long-term prognosis of patients evaluated for suspected PE. Methods We sought to assess the predictive performance of NT-proBNP, C-reactive protein (CRP), D-dimer (FIDD) and cardiac troponin T (cTnT) in patients who underwent computed tomography pulmonary angiography (CTPA) for clinical suspicion of PE. The analysis involved 1001 patients, with 222 (22.2%) receiving a PE diagnosis at index imaging. Mean age of patients with and without PE were 65.0 ± 17.1 and 64.5 ± 17.7 years, respectively. Median follow-up time was 3.9 years [IQR 2.9-4.9]. Results Mortality was relatively high both among patients with and without documented PE (24.8% vs. 31.7%, p=0.047). In patients with PE, only elevated NT-proBNP>1000 ng/L and CRP>50 mg/L levels at hospital admission were associated with higher mortality in an adjusted Cox regression model, but ROC analysis showed no improved prediction compared to clinical variables. Among patients without PE, elevated NT-proBNP>1000 ng/L, CRP>10 mg/L, cTnT>50 ng/L and FIDD>1.0 mg/L all predicted mortality. In an ROC analysis among patients without PE, models including NT-proBNP, cTnT or CRP provided improved predictive performance. Conclusions Patients evaluated for clinical suspicion of PE have high long-term mortality. Commonly used biomarkers provide long-term prognostic value in patients without PE. Given the relatively young age, it is vital to identify these high-risk patients, and perform differential diagnosis work-up for alternative life-threatening conditions, and manage them as appropriate.

Role of cfDNA and ctDNA to improve the risk stratification and the disease follow-up in patients with endometrial cancer: towards the clinical application

BackgroundThere has been a rise in endometrial cancer (EC) incidence leading to increased mortality. To counter this trend, improving the stratification of post-surgery recurrence risk and anticipating disease relapse and treatment resistance is essential. Liquid biopsy analyses offer a promising tool for these clinical challenges, though the best strategy for applying them in EC must be defined. This study was designed to determine the value of cfDNA/ctDNA monitoring in improving the clinical management of patients with localized and recurrent disease.MethodsPlasma samples and uterine aspirates (UA) from 198 EC patients were collected at surgery and over time. The genetic landscape of UAs was characterized using targeted sequencing. Total cfDNA was analyzed for ctDNA presence based on the UA mutational profile.ResultsHigh cfDNA levels and detectable ctDNA at baseline correlated with poor prognosis for DFS (p-value < 0.0001; HR = 9.25) and DSS (p-value < 0.0001; HR = 11.20). This remained clinically significant when stratifying tumors by histopathological risk factors. Of note, cfDNA/ctDNA analyses discriminated patients with early post-surgery relapse and the ctDNA kinetics served to identify patients undergoing relapse before any clinical evidence emerged.ConclusionsThis is the most comprehensive study on cfDNA/ctDNA characterization in EC, demonstrating its value in improving risk stratification and anticipating disease relapse in patients with localized disease. CtDNA kinetics assessment complements current strategies to monitor the disease evolution and the treatment response. Therefore, implementing cfDNA/ctDNA monitoring in clinical routines offers a unique opportunity to improve EC management.Translational relevanceThe study demonstrates that high levels of cfDNA and detectable ctDNA at baseline are strong indicators of poor prognosis. This enables more accurate risk stratification beyond traditional histopathological factors, allowing clinicians to identify high-risk patients who may benefit from more aggressive treatment and closer monitoring. Moreover, longitudinal analysis of cfDNA/ctDNA can detect disease recurrence months before clinical symptoms or imaging evidence appear. This early warning system offers a significant advantage in clinical practice, providing a window of opportunity for early intervention and potentially improving patient outcomes.

Identification of prognostic biomarkers in neuroblastoma using WGCNA and multi-omics analysis

BackgroundNeuroblastoma (NB) is one of the most frequent parenchymal tumors among children, with a high degree of heterogeneity and wide variation in clinical presentation. Despite significant therapeutic advances in recent years, long-term survival in high-risk patients remains low, emphasizing the urgent need to find new biomarkers and construct reliable prognostic models.MethodsIn this study, data from neuroblastoma samples in the ArrayExpress database were utilized to identify key gene modules and pivotal genes associated with NB prognosis by weighted gene co-expression network analysis (WGCNA). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis was performed using the DAVID database. Based on these hub genes, survival prognosis models were constructed and validated on an independent validation set in the Gene Expression Omnibus (GEO) database. Differences in biological functions and immune microenvironments and the sensitivity to pharmacological and immunotherapeutic treatments of patients in the high- and low-risk groups were examined by gene set enrichment analysis (GSEA) and immune infiltration analysis.ResultsWGCNA identified 14 gene modules and screened the module with the highest relevance to the International Neuroblastoma Staging System (INSS), containing 60 pivotal genes. GO and KEGG analyses demonstrated that these pivotal genes were mainly implicated in biological processes and signaling pathways including DNA replication, cell division, mitotic cell cycle, and cell cycle. Based on Lasso regression and COX regression analysis, a prognostic model containing DHFR, GMPS and E2F3 was constructed, and the RiskScore was significantly correlated with the 1-, 3- and 5-year survival of the patients. GSEA and immune infiltration analyses revealed significant differences in the levels of cell cycle-related pathways and immune cell infiltration between the high and low RiskScore groups. In particular, patients in the high-risk group are less likely to benefit from immunotherapy and may be better suited for treatment with drugs such as Oxaliplatin and Alpelisib.ConclusionThis research systematically identified biomarkers related to NB prognosis and developed a reliable prognostic model applying WGCNA and multiple bioinformatics methods. The model has important application value in predicting patients’ prognosis, evaluating drug sensitivity and immunotherapy effect, and provides new ideas and directions for precise treatment of neuroblastoma.

Prevention and management of allergic-like reactions to iodine contrast media: a best practice implementation project.

With the wide application of iodine contrast media (ICM), the occurrence of allergic-like reactions to iodine contrast media (ALR-ICM) has increased. Strategies for the prevention and management of ALR-ICM need to be identified to provide quality care to patients undergoing enhanced computed tomography. The overarching aim of this project was to improve the prevention and management of ALR-ICM at a medical imaging center of a nearly 5,000-bed tertiary hospital in China. This project was guided by the JBI Evidence Implementation Framework, which is grounded in an audit, feedback, and re-audit strategy. A baseline audit was conducted to measure current practices against recommended best practices. Feedback from the audit was used to identify barriers and design strategies to improve practice. A follow-up audit was conducted to measure changes in compliance with best practices. The results revealed a positive change in compliance with best practices. More than 60% compliance with the four audit criteria was observed. The overall ALR-ICM rate decreased from 0.56% to 0.19%, while emergency equipment management dramatically increased from 37.50% to 100%. The smallest improvement was observed for pre-procedure prophylactic treatment of high-risk patients (27.66%). Most audit criteria showed moderate improvements in compliance with best practices. Further testing of this program in more hospitals is needed. http://links.lww.com/IJEBH/A269.

Risk of recurrent venous thromboembolism in patients with cancer: an individual patient data meta-analysis and development of a prediction model

Background About 7% of patients with cancer-associated venous thromboembolism (CAT) develop a recurrence during anticoagulant treatment. Identification of high-risk patients may help guide treatment decisions. Aim To identify clinical predictors and develop a prediction model for on-treatment recurrent CAT. Methods For this individual patient data (IPD) meta-analysis, we used data from four randomized controlled trials evaluating low-molecular-weight heparin (LMWH) or direct oral anticoagulants (DOACs) for CAT (Hokusai VTE Cancer, SELECT-D, CLOT, and CATCH). The primary outcome was adjudicated on-treatment recurrent CAT during 6-month follow-up. A clinical prediction model was developed using multivariable logistic regression analysis with backward selection. This model was validated using internal-external cross validation. Performance was assessed by the c-statistic and a calibration plot. Results After excluding patients using vitamin K antagonists, the combined dataset comprised 2,245 patients with cancer and acute CAT who were treated with edoxaban (23%), rivaroxaban (9%), dalteparin (47%), or tinzaparin (20%). Recurrent on-treatment CAT during 6-month follow-up occurred in 150 (6.7%) patients. Predictors included in the final model were age (restricted cubic spline), breast cancer (OR 0.42; 95%-CI 0.20-0.87), metastatic disease (OR 1.44; 95%-CI 1.01-2.05), treatment with DOAC (OR 0.66; 95%-CI 0.44-0.98), and deep vein thrombosis only as index event (OR 1.72; 95%-CI 1.31-2.27). The c-statistic of the model was 0.63 (95%-CI 0.54-0.72) after internal-external cross validation. Calibration varied across studies. Conclusions The prediction model for recurrent CAT included five clinical predictors and has only modest discrimination. Prediction of recurrent CAT at the initiation of anticoagulation remains challenging.

Machine Learning-Based Predictions of Mortality and Readmission in Type 2 Diabetes Patients in the ICU

Prognostic outcomes for patients with type 2 diabetes in the intensive care unit (ICU), including mortality and readmission rates, are critical for informed clinical decision-making. Although existing research has established a link between type 2 diabetes and adverse outcomes in the ICU, the potential of machine learning techniques for enhancing predictive accuracy has not been fully realized. This study seeks to develop and validate predictive models employing machine learning algorithms to forecast mortality and 30-day post-discharge readmission rates among ICU type 2 diabetes patients, thereby enhancing predictive accuracy and supporting clinical decision-making. Data were extracted and preprocessed from the MIMIC-III database, focusing on 14,222 patients with type 2 diabetes and their corresponding ICU admission records. Comprehensive information, including vital signs, laboratory results, and demographic characteristics, was utilized. Six machine learning algorithms—bagging, AdaBoost, GaussianNB, logistic regression, MLP, and SVC—were developed and evaluated using 10-fold cross-validation to predict mortality at 3 days, 30 days, and 365 days, as well as 30-day post-discharge readmission rates. The machine learning models demonstrated strong predictive performance for both mortality and readmission rates. Notably, the bagging and AdaBoost models showed superior performance in predicting mortality across various time intervals, achieving AUC values up to 0.8112 and an accuracy of 0.8832. In predicting 30-day readmission rates, the MLP and AdaBoost models yielded the highest performance, with AUC values reaching 0.8487 and accuracy rates of 0.9249. The integration of electronic health record data with advanced machine learning techniques significantly enhances the accuracy of mortality and readmission predictions in ICU type 2 diabetes patients. These models facilitate the identification of high-risk patients, enabling timely interventions, improving patient outcomes, and demonstrating the significant potential of machine learning in clinical prediction and decision support.

Immune biomarkers and secondary hemophagocytic lymphohistiocytosis: a scoping review protocol.

To identify immunological pathways and markers of severity of illness associated with clinical outcomes that may represent potential therapeutic targets in the management of secondary hemophagocytic lymphohistiocytosis. A broad range of immunomodulatory therapies is used to manage hemophagocytic lymphohistiocytosis, however the supporting evidence for these therapies is scarce. Identifying patients likely to experience more severe disease, or die, is currently extremely difficult, if not impossible. The identification of implicated cytokines in secondary disease can provide further support for the identification of high-risk patients and the development of targeted therapies. Studies reporting immune biomarker and cytokine measurement in adult patients (age >18 years) with secondary hemophagocytic lymphohistiocytosis. The proposed review will be conducted in line with the JBI methodology for scoping reviews. The MEDLINE (Ovid) and Embase (Ovid) databases will be searched, without date limitations. Data will be extracted using a data extraction tool developed by the reviewers. Relevant sources will be retrieved, and their citation details imported into the JBI System for the Unified Management, Assessment and Review of Information.

Anoikis-related genes in breast cancer patients: reliable biomarker of prognosis

BackgroundBreast cancer (BC) is the most common cancer in women, and its progression is closely related to the phenomenon of anoikis. Anoikis, the specific programmed death resulting from a lack of contact between cells and the extracellular matrix, has recently been recognized as playing a critical role in tumor initiation, maintenance, and treatment. The ability of cancer cells to resist anoikis leads to cancer progression and metastatic colonization. However, the impact of anoikis on the prognosis of BC patients remains unclear.MethodThis study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect transcriptome and clinical data of BC patients. Anoikis-related genes (ARGs) were classified into subtypes A and B through consensus clustering. Subsequently, survival prognosis analysis, immune cell infiltration analysis, and functional enrichment analysis were performed for both subtypes. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a set of 10 ARGs related to prognosis was identified. Immune cell infiltration and tumor microenvironment analyses were conducted on these 10 ARGs to develop a prognostic model. Furthermore, single-cell data analysis and real-time polymerase chain reaction (RT-PCR) analysis were employed to study the expression of the 10 identified prognostic ARGs in BC cells.ResultsOne hundred thirty-five ARGs were identified as differentially expressed genes in the TCGA and GEO databases, with 42 of them associated with the survival prognosis of BC patients. Analyses involving Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) revealed distinct expression patterns of ARGs between types A and B. Patients in type A exhibited worse survival prognosis and lower immune cell infiltration compared to type B. Subsequent analyses identified 10 key ARGs (YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, LAMB3, CD24, SLC2A1, CDC25C, and SLC39A6) relevant to BC prognosis. Kaplan–Meier analysis indicated that high-risk patients based on these ARGs had a poorer BC prognosis. Additionally, Cox regression analysis established gender, age, T (tumor), N (nodes), and risk score as predictive factors in a nomogram model for BC. The model demonstrated diagnostic value for BC patients at 1, 3, and 5 years. Decision curve analysis (DCA) verified the risk score as a reliable predictor of BC patient survival rates. Moreover, RT-PCR results confirmed differential expressions of YAP1, PIK3R1, BAK1, PHLDA2, CD24, SLC2A1, and CDC25C in BC cells, with SLC39A6, EDA2R, and LAMB3 showing low expression levels.ConclusionARGs markers can be used as BC biomarkers for risk stratification and survival prediction in BC patients. Besides, ARGs can be used as stratification factors for individualized and precise treatment of BC patients.

Effectiveness of Risk Analysis Index Frailty Scores as a Predictor of Adverse Outcomes in Lower Extremity Reconstruction.

The rising clinical importance of assessing frailty is driven by its predictive capability for postoperative outcomes. This study assesses RAI-rev (Risk Analysis Index) effectiveness in predicting adverse outcomes in lower extremity (LE) flap reconstruction. Analyzing NSQIP data from 2015-2020, we compared demographics, perioperative factors, and 30-day outcomes in all locoregional and free flap cases. Frailty scores, calculated using RAI-rev, were categorized with <15 as non-frail and >35 as the most frail. Adjusted odds-ratios (aOR) for specific complications were calculated using non-frail as the reference group. Frailty scores in locoregional flaps were compared to those in free flaps. We identified 270 locoregional and 107 free flap cases. Higher RAI-rev scores in locoregional flaps correlated with increased complications, such as deep surgical site infection (1% non-frail vs. 20% RAI 31-35), stroke (0% non-frail vs. 17% most-frail), and mortality (0% non-frail vs. 17% most-frail). Locoregional flap cases with RAI-rev scores in the most-frail group had a significantly elevated aOR for stroke (51.0, 95% CI: 1.8-1402.5, p=0.02), mortality (43.1, 95% CI: 1.6-1167.6, p=0.03), and any complication (6.8, 95% CI: 1.2-37.4, p=0.03). In free flap cases, higher RAI-rev scores were associated with increased complications, with only sepsis showing a statistically significant difference (6% non-frail vs. 100% most-frail; aOR 42.3, CI: 1.45 - 1245.3, p=0.03). Free flap cases had a significantly lower RAI-rev score compared to locoregional flap cases (14.91 vs. 17.64, p=0.01). Elevated RAI-rev scores (>35) correlated with more complications in locoregional flaps, while free flap reconstruction patients had generally low RAI-rev scores. This suggests that free flaps are less commonly recommended for presumed higher-risk patients. The study demonstrates that RAI-rev may be able to serve as a risk calculator in lower extremity reconstruction, aiding in the assessment of candidates for limb salvage versus amputation.

Tracing HIV Infection among high-risk Tuberculosis Patients in Hodiedah Referral Center, Yemen

Background: HIV and tuberculosis [TB] are major public health concerns in Yemen. However, in this population, there is limited information on the prevalence of HIV infection among TB patients. This study aims to trace and describe cases of HIV infection among high-risk tuberculosis patients attending the Hodiedah referral center in Yemen. Methods: A cross-sectional study design was employed, and a convenience sampling method was used to select 40 high-risk tuberculosis patients out of 164 confirmed cases. Data was collected through a questionnaire regarding sociodemographic features and clinical signs. Results: Of 40 high-risk TB patients, only 4 tested positive for HIV, indicating a 10% prevalence. More than half [55.0%] were aged between 18 and 40 years, with the majority [57.5%] being male. Over half [57.5%] resided in urban areas, and approximately two-thirds [62.5%] had no formal education. Most participants [87.5%] belonged to a low socioeconomic status, with a monthly income of less than 50,000 Yemeni Riyals. The age group of 18–40 years had the highest frequency of HIV-positive cases [50.0%]. All HIV-positive cases occurred in males. Younger age and travel history showed higher odds of HIV positivity. Diarrhea, bone pain, and abdominal pain were associated with HIV-TB co-infection. Conclusion: A relatively high HIV prevalence points to an urgent need to scale up integrated screening, testing, and treatment programs within existing TB clinics to address this unmet HIV/TB burden. Males, younger ages, and travel outside the country emerged as potential high-risk groups that could be prioritized for screening; incorporating symptom-based algorithms into clinical protocols may help front-line workers recognize and refer to suspected co-infection cases for testing. Larger studies are warranted to validate the findings and better inform control programs.

Effects of Dexmedetomidine in Improving Oxygenation and Reducing Pulmonary Shunt in High-Risk Pediatric Patients Undergoing One-Lung Ventilation for Thoracic Surgery: A Double-Blind Randomized Controlled Trial.

Background and objectives Pediatric thoracic surgery has unique considerations due to the immaturity of the respiratory system anatomically and physiologically, which presents technical and pharmacological considerations, including the very common technique of one-lung ventilation (OLV), which causes serious complications in children. Therefore, we investigated the effects of dexmedetomidine on oxygenation and pulmonary shunt fraction (Qs/Qt) in high-risk pediatric patients undergoing OLV for thoracic surgery. This randomized controlled trial aimed to investigate dexmedetomidine's effect on the partial pressure of arterial oxygen (PaO2) and pulmonary shunt fraction (Qs/Qt). Methods A total of 63 children underwent thoracic surgery with OLV and were divided into two groups. The dexmedetomidine group (group Dex, n = 32) received dexmedetomidine (0.4 μg/kg/hour), and the placebo group (group placebo, n = 31) received normal saline. Two arterial and central venous blood samples were taken for arterial and venous blood gas analysis at four time points: T1 (10 minutes after mechanical ventilation of total lung ventilation), T2 (10 minutes after OLV), T3 (60 minutes after OLV), and T4 (20 minutes after the end of OLV). At these intervals, the following parameters were measured: PaO2, Qs/Qt, mean arterial pressure (MAP), heart rate (HR), and peak inspiratory pressure (PIP). Results The two groups had no significant differences in FEV1/FVC and baseline pulmonary shunt fraction (Qs/Qt). Dexmedetomidine significantly improved PaO2 compared with placebo during OLV (T2 and T3). There was a significant decrease in Qs/Qt compared with placebo during OLV (T2, T3, and T4). There was a decrease in PIP compared with placebo during OLV (T2 and T3). No statistically significant differences in MAP or HR were observed between the groups. Conclusion Infusion of dexmedetomidine during OLV in high-risk pediatric thoracic surgery reduces shunt and pulmonary shunt fraction Qs/Qt, improves PaO2 and body oxygenation, reduces PIP and pressure load, and maintains hemodynamic stability (MAP, HR).

Nutraceuticals and pharmacological to balance the transitional microbiome to extend immunity during COVID-19 and other viral infections

Abstract Scope The underlying medical conditions and gut dysbiosis is known to influence COVID-19 severity in high-risk patients. The current review proposed the optimal usage of nutraceuticals &amp; pharmacological interventions can help regulate the protective immune response and balance the regulatory functionality of gut microbiota. Summary Many studies have revealed that the probiotic interventions viz., Lactobacillus rhamnosus, L. plantarum &amp; other bacterial spp. reduce IFNγ &amp; TNF-α and increase IL-4 &amp; IL-10 secretions to control the immunostimulatory effects in upper respiratory tract infection. Dietary fibres utilized by beneficial microbiota and microbial metabolites can control the NF-kB regulation. Vitamin C halts the propagation of pathogens and vitamin D and A modulate the GM. Selenium and Flavonoids also control the redox regulations. Interferon therapy can antagonize the viral replications, while corticosteroids may reduce the death rates. BCG vaccine reprograms the monocytes to build trained immunity. Bifidobacterium and related microbes were found to increase the vaccine efficacy. Vaccines against COVID-19 and season flu also boost the immunity profile for robust protection. Over all, the collective effects of these therapeutics could help increase the opportunities for faster recovery from infectious diseases. Conclusion The nutraceutical supplements and pharmacological medicines mediate the modulatory functionalities among beneficial microbes of gut, which in turn eliminate pathogens, harmonize the activity of immune cells to secrete essential regulatory molecular receptors and adaptor proteins establishing the homeostasis in the body organs through essential microbiome. Therefore, the implementation of this methodology could control the severity events during clinical sickness and reduce the mortalities.

Total versus Partial Pancreatectomy in Patients with Pancreatic Cancer Arising from Multifocal or Diffuse Intraductal Papillary Mucinous Neoplasia - A Multicenter Observational Study.

To investigate the impact of total pancreatectomy (TP) on oncological outcomes for patients at high-risk of local recurrence or secondary progression in the remnant gland after partial pancreatectomy (PP) for IPMN-associated cancer. Major risk factors for invasive progression in the remnant gland include multifocality, diffuse main duct dilation, and the presence of invasive cancer. In these high-risk patients, a TP may be oncologically beneficial. However, current guidelines discourage TP, especially in elderly patients. This international multicenter study compares TP versus PP in patients with adenocarcinoma arising from multifocal or diffuse IPMN (2002-2022). Log-rank test and multivariable Cox-analysis with interaction analysis was performed to assess overall survival (OS), disease-free survival (DFS), and local-DFS. Of 359 included patients, 162 (45%) were treated with TP, whereas 197 (55%) underwent PP. Despite TP and PP having similar R0-rates (59% vs. 58%, P=0.866), patients undergoing a TP had significantly longer local-DFS compared to PP (P=0.039). However, no difference in OS was observed between the two surgical approaches (P=0.487). In a multivariable analysis, young age (optimal cut-off ≤63.6yrs) was associated with an OS benefit derived from TP (HR:0.44, 95%CI:0.22-0.89), whereas no significant difference was observed in elderly patients (HR:1.24, 95%CI:0.92-1.67, Pinteraction=0.007). Since overall, patients with diffuse or multifocal IPMN with an invasive component do not benefit from TP in terms of OS, the indication for TP may be individualized to young patients who have sufficient life expectancy to benefit from the prevention of secondary progression or local recurrence.

A comparative retrospective study of pre-fibrotic primary myelofibrosis versus overtly fibrotic stage in Qatar: clinicopathological, genetic landscape, risk stratification and survival data (2008–2021) – a single center experience

ABSTRACT Background In MENA region, there is a lack of evidence on Primary Myelofibrosis (PMF), leading to its underrepresentation in medical literature. This study marks the first comprehensive report on PMF data in Qatar, presenting findings from a single-center study spanning 13 years (2008-2021). Methods Clinicopathological data, genetic features, and disease progression parameters of pre-PMF and overt PMF subgroups were collected. Overall survival (OS), progression-free survival (PFS), DIPSS plus four categories and merged low and high-risk DIPSS scoring groups were assessed. Results Pre-PMF patients showed higher hemoglobin (P < 0.001), and platelet counts (P < 0.05) but lower blast counts, LDH levels, constitutional symptoms (P < 0.0001), and splenomegaly (P < 0.010) than overt PMF patients. JAK2 V617F mutation was more common in pre-PMF (P = 0.059), while unfavorable karyotypes were exclusive to overt PMF (P = 0.028). Median overall survival was significantly longer at 276.9 months (IQR: 315.9, 276.9 months) to what was previously reported. Overt PMF patients predominantly fell into the higher DIPSS risk category (P < 0.001) and showed greater disease progression than pre-PMF (P < 0.0001). Complications including refractory anaemia (P < 0.001) and leukemic transformation (P = 0.043), increased notably in the high-risk group. Furthermore, 86.2% of high-risk patients required treatment versus 59.4% of the lower-risk group (P = 0.020). Conclusions To the best of our knowledge our research represents the first and largest published dataset on PMF in MENA region to be published. Merged DIPSS plus scoring came to be a pragmatic tool for defining high-risk patients who significantly differ in mortality, progression, need for treatment and leukemic transformation.

Construction and validation of a dynamic nomogram using Lasso-logistic regression for predicting the severity of severe fever with thrombocytopenia syndrome patients at admission

BackgroundSevere fever with thrombocytopenia syndrome (SFTS) is a highly fatal infectious disease caused by the SFTS virus (SFTSV), posing a significant public health threat. This study aimed to construct a dynamic model for the early identification of SFTS patients at high risk of disease progression.MethodsAll eligible patients enrolled between April 2014 and July 2023 were divided into training and validation sets. Thirty-four clinical variables in the training set underwent analysis using least absolute shrinkage and selection operator (LASSO) logistic regression. Selected variables were then input into the multivariate logistic regression model to construct a dynamic nomogram. The model’s performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) in both training and validation sets. Kaplan-Meier survival analysis was utilized to evaluate prognostic performance.Results299 SFTS patients entered the final investigation, with 208 patients in the training set and 90 patients in the validation set. LASSO and the multivariate logistic regression identified six significant prediction factors: age (OR, 1.060; 95% CI, 1.017–1.109; P = 0.007), CREA (OR, 1.017; 95% CI, 1.003–1.031; P = 0.019), PT (OR, 1.765; 95% CI, 1.175–2.752; P = 0.008), D-dimer (OR, 1.039; 95% CI, 1.005–1.078; P = 0.032), nervous system symptoms (OR, 8.244; 95% CI, 3.035–26.858; P < 0.001) and hemorrhage symptoms (OR, 3.414; 95% CI, 1.096–10.974; P = 0.035). The AUC-ROC, C-index, calibration plots, and DCA demonstrated the robust performance of the nomogram in predicting severity at admission, and Kaplan-Meier survival analysis indicated its utility in predicting 28-day mortality among SFTS patients. The dynamic nomogram is accessible at https://sfts.shinyapps.io/SFTS_severity_nomogram/.ConclusionThis study provided a practical and readily applicable tool for the early identification of high-risk SFTS patients, enabling the timely initiation of intensified treatments and protocol adjustments to mitigate disease progression.

Predicting post-lung transplant survival in systemic sclerosis using CT-derived features from preoperative chest CT scans.

The current understanding of survival prediction of lung transplant (LTx) patients with systemic sclerosis (SSc) is limited. This study aims to identify novel image features from preoperative chest CT scans associated with post-LTx survival in SSc patients and integrate them into comprehensive prediction models. We conducted a retrospective study based on a cohort of SSc patients with demographic information, clinical data, and preoperative chest CT scans who underwent LTx between 2004 and 2020. This cohort consists of 102 patients (mean age, 50 years ± 10, 61% (62/102) females). Five CT-derived body composition features (bone, skeletal muscle, visceral, subcutaneous, and intramuscular adipose tissues) and three CT-derived cardiopulmonary features (heart, arteries, and veins) were automatically computed using 3-D convolutional neural networks. Cox regression was used to identify post-LTx survival factors, generate composite prediction models, and stratify patients based on mortality risk. Model performance was assessed using the area under the receiver operating characteristics curve (ROC-AUC). Muscle mass ratio, bone density, artery-vein volume ratio, muscle volume, and heart volume ratio computed from CT images were significantly associated with post-LTx survival. Models using only CT-derived features outperformed all state-of-the-art clinical models in predicting post-LTx survival. The addition of CT-derived features improved the performance of traditional models at 1-year, 3-year, and 5-year survival prediction with maximum AUC scores of 0.77 (0.67-0.86), 0.85 (0.77-0.93), and 0.90 (95% CI: 0.83-0.97), respectively. The integration of CT-derived features with demographic and clinical features can significantly improve t post-LTx survival prediction and identify high-risk SSc patients. Question What CT features can predict post-lung-transplant survival for SSc patients? Finding CT body composition features such as muscle mass, bone density, and cardiopulmonary volumes significantly predict survival. Clinical relevance Our individualized risk assessment tool can better guide clinicians in choosing and managing patients requiring lung transplant for systemic sclerosis.