Search Results (13)

Background: Fenestrated stentgrafting has become a first-line treatment for juxtarenal aneurysms, and the incorporation of all renovisceral vessels with fenestrations has become common to increase the proximal sealing zone. This increases the complexity of the repair compared to using fewer fenestrations, and stenting of the celiac artery (CA), in particular, can be technically challenging. Objective: This study evaluates the mid-term outcomes of leaving the celiac artery unstented during quadruple fenestrated stentgrafting for complex aortic aneurysms. Additionally, it explores the clinical and anatomical factors that influence the decision to not stent the celiac artery. Methods: A retrospective review was conducted of patients with complex aortic aneurysms who underwent elective fenestrated endovascular aneurysm repair (FEVAR) between 2018 and 2023. Custom Cook Zenith grafts were used, and all patients underwent preoperative computed tomography angiography (CTA) as well as follow-up CTA to assess the celiac artery. This study evaluated celiac artery anatomic factors, such as proximal and distal diameter; presence of stenosis (<50% or >50%) and patency; length of any CA stenosis; CA takeoff angulation, CA tortuosity, early CA division; calcification; and presence of CA aneurysm or ectasia anatomical abnormalities. Recorded outcomes of CA instability included any stent stenosis, target vessel occlusion, reintervention, or endoleak (types 1C and 3). Results: A total of 101 patients underwent FEVAR, with 72 receiving a stent in the celiac artery and 29 not receiving it. Rates of technical success (96.5% vs. 100%), intervention times (256 min vs. 237 min), and lengths of hospital stay (5.1 vs. 4.7 days) were similar between unstented vs. stented groups. At one year, no significant difference in celiac artery instability was noted (17.2 vs. 5.5%; p = 0.06). Risk factors for CA occlusion on univariate analysis included a steep takeoff angle (≥140°), length of stenosis >6.5 mm, proximal diameter ≤6.5 mm, preoperative stenosis ≥50%, and celiac artery tortuosity. Conclusions: Anatomical features of the CA impact the ability to achieve routine CA stenting during FEVAR. Selectively not stenting the celiac artery during FEVAR might simplify the procedure without compromising patient safety and mid-term outcomes. Full article

Background: Chronic kidney disease (CKD) is a prevalent complication among individuals with type 2 diabetes (T2D), posing significant diagnostic challenges in resource-limited settings due to infrequent testing and missed hospital visits. This study aimed to develop a simple, effective ML model to identify T2D patients at high risk for reduced kidney function. Methods: We retrospectively analyzed data from 3471 T2D patients collected over a ten-year period at a university hospital in Bangkok, Thailand. Two models were developed using readily available clinical features: one including hemoglobin A1c (HbA1c) levels (the “with-HbA1c” model) and one excluding HbA1c levels (the “non–HbA1c” model). Three tree-based ML algorithms—decision tree, random forest, and extreme gradient boosting (XGBoost) algorithms—were employed. The outcome label was CKD, defined as an estimated Glomerular Filtration Rate (eGFR) < 60 mL/min/1.73 m² that persisted for more than 90 days. The model performance was evaluated using the AUROC. The feature importance was assessed using Shapley additive explanations (SHAP). Results: The XGBoost algorithm demonstrated a strong predictive performance. The “with-HbA1c” model achieved an AUROC of 0.824, while the “non–HbA1c” model attained a comparable AUROC of 0.819. Both models were well-calibrated. SHAP analysis identified age, HbA1c, and systolic blood pressure as the most influential predictors. Conclusions: Our simplified, interpretable ML models can effectively stratify the risk of reduced kidney function in patients with T2D using minimal, routine data. These models represent a promising step toward integration into clinical practice, such as through EHR-based alerts or patient-facing mobile applications, to improve early CKD detection, particularly in resource-limited settings. Full article

Background/Objectives: Miscarriage is a common pregnancy complication that significantly impacts individuals’ health due to its physical and psychological effects. This study aimed to investigate the association between periodontal health and hematological parameters in women who experienced miscarriage before the 20th week of gestation, and to assess the potential predictive value of these parameters for miscarriage risk by comparing them with those of women with an uncomplicated pregnancy course. Methods: This study was a prospective case–control and cross-sectional study. It included a total of 82 participants, comprising 41 women with miscarriage and 41 healthy pregnant controls. The periodontal examinations included measurements of the Gingival Index (GI), Plaque Index (PI), Probing Depth (PD), Clinical Attachment Loss (CAL), and Simplified Calculus Index (SCI). Additionally, complete blood counts (CBCs) were obtained from all participants. Appropriate statistical analyses, including non-parametric, correlation, logistic regression, and ROC analyses, were conducted, with the significance level set at p < 0.05. Results: The primary outcome measure was CAL as an indicator of periodontal disease severity and its association with miscarriage risk. Additional outcomes included Plateletcrit (PCT), the Platelet Count (PLT), and the Neutrophil-to-Lymphocyte Ratio (NLR) to evaluate systemic inflammatory responses and their correlations with periodontal parameters. CAL was significantly elevated in the miscarriage group (p < 0.001) and emerged as the strongest predictor of miscarriage risk (OR = 0.0537, p < 0.001, AUC = 0.8691). PCT was significantly higher in the miscarriage group (p = 0.017) and positively correlated with the GI (p = 0.041), suggesting a link between systemic inflammation and periodontal health. Conclusions: Considering this study’s limitations, CAL was the strongest predictor of miscarriage, while PLT and PCT had some discriminative power. Collaboration between obstetricians and dentists can facilitate early diagnosis and intervention by promoting routine oral health check-ups before and during pregnancy. Additionally, integrating oral health assessments into prenatal care and developing public health policies could enhance access to dental services during both preconception and pregnancy periods. Full article

Background: Current severity scoring systems in intensive care units (ICUs) are complex and time-consuming, limiting their utility for rapid clinical decision-making. This study aimed to develop and validate simplified prediction models using readily available biomarkers for assessing in-hospital mortality risk. Methods: We analyzed 19,720 adult ICU patients in this retrospective study. Three prediction models were developed: a basic model using lactate-to-albumin ratio (LAR) and neutrophil percent-to-albumin ratio (NPAR) and two enhanced models incorporating mechanical ventilation and continuous renal replacement therapy. Model performance was evaluated against Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation (APACHE) II score using machine learning approaches and validated through comprehensive subgroup analyses. Results: Among individual biomarkers, SOFA score showed the highest discriminatory power (area under these curves [AUC] 0.931), followed by LAR (AUC 0.830), CAR (AUC 0.749), and NPAR (AUC 0.748). Our enhanced Model 3 demonstrated exceptional predictive performance (AUC 0.929), statistically comparable to SOFA (p = 0.052), and showed a trend toward superiority over APACHE II (AUC 0.900, p = 0.079). Model 2 performed comparably to APACHE II (AUC 0.913, p = 0.430), while Model 1, using only LAR and NPAR, achieved robust performance (AUC 0.898) despite its simplicity. Subgroup analyses across different ICU types demonstrated consistent performance of all three models, supporting their broad clinical applicability. Conclusions: This study introduces novel, simplified prediction models that rival traditional scoring systems in accuracy while offering significantly faster implementation. These findings represent a crucial step toward more efficient and practical risk assessment in critical care, potentially enabling earlier clinical interventions and improved patient outcomes. Full article

Background/Objective: High-risk subsets of patients with acute coronary syndrome (ACS) experience decreased access to optimal care and have poor clinical outcomes, reflecting an inertia to the delivery of guideline-directed and evidence-based therapy and implementation of critical care pathways. We aim to investigate the clinical effectiveness of a simplified implementation checklist to counter treatment inertia in patients with high comorbidity burden. Methods: An ACS critical care pathway was simplified and reduced to a minimalistic checklist including only items on GDMT and invasive strategy. A total of 2005 consecutive patients with ACS were evaluated including 1499 patients receiving standard care and 506 patients managed with the checklist. Patients with STEMI undergoing primary percutaneous coronary interventions and patients receiving upfront cardiovascular intensive care were excluded. Multivariate regression spline models were used to study the relationship between comorbidity, expressed as the Charlson Comorbidity Index (CCI) and a management strategy including guideline-directed medical therapy (GDMT) and an early invasive approach. Inverse probability of treatment weighting (IPTW) was used to address confounding factors. The use of GDMT and early invasive therapy were compared in patients receiving standard care and checklists. The 90-day composite outcome of all-cause mortality, recurrent ACS and stroke were compared between patients receiving standard care and those receiving checklists. Results: High CCI was associated with decreased GDMT, invasive strategy and the utilization of critical care pathway. Checklist utilization was unaffected by high CCI and led to sustained and higher use of GDMT and invasive approach in patients despite high CCI. Checklist managed patients have >10% higher rates of prescription of each class of GDMT (p < 0.0001) and more than twice the rate of early invasive approach (51.0% vs. 20.7%, (p < 0.0001) compared to patients receiving standard care. The 90-day composite outcome was lower in checklist management patients compared to patients receiving standard care, adjusted hazard ratio 0.61 (95% CI 0.46–0.81), log-rank p = 0.0006, especially in patients with high CCI, adjusted hazard ratio 0.60 (95% CI 0.38–0.97), log-rank p = 0.035 for CCI 5–6; adjusted hazard ratio 0.53 (95% CI 0.35–0.84), log-rank p = 0.0057 for CCI 7 or more. Conclusions: The use of a simplified checklist is associated with better implementation of GDMT and invasive strategy as well as better 90-day clinical outcomes in ACS patients with high comorbidity burden Full article

Background/Objectives: Acute ischemic stroke (AIS) is a leading cause of disability and mortality worldwide. Despite advances in interventions such as thrombolysis (TL) and mechanical thrombectomy (MT), current treatment protocols remain largely standardized, focusing on general eligibility rather than individual patient characteristics. To address this gap, we introduce the Stroke-SCORE (Simplified Clinical Outcome Risk Evaluation), a predictive tool designed to personalize AIS management by providing data-driven, individualized recommendations to optimize treatment strategies and improve patient outcomes. Methods: The Stroke-SCORE was derived using retrospective data from 793 AIS patients admitted to the University of Pécs (February 2023–September 2024). Logistic regression analysis identified age, National Institutes of Health Stroke Scale (NIHSS) score at admission, and pre-morbid modified Rankin Scale (pre-mRS) score as key predictors of unfavorable outcomes at 90 days (defined as modified Rankin Scale [mRS] score > 2). Based on these predictors, a simplified risk score was developed to stratify patients into low-, moderate-, and high-risk groups, guiding treatment decisions on TL, MT, combination therapy (TL + MT), or standard care (SC). Internal validation was performed to assess the model’s predictive performance via receiver operating characteristic (ROC) analysis and isotonic regression calibration with bootstrapping. Results: The Stroke-SCORE was moderately positively correlated with a 90-day mRS score > 2 (odds ratio [OR] = 0.70, 95% confidence interval [CI]: 0.58–0.83, p < 0.001), with an area under the curve (AUC) of 0.86, a sensitivity and specificity of 79% and 81%, respectively, and an overall accuracy of 80%. Simulations indicated that personalized treatment guided by the Stroke-SCORE significantly reduced unfavorable outcomes. Conclusions: The Stroke-SCORE demonstrates strong predictive performance as a practical, data-driven approach for personalizing AIS treatment decisions. In the future, external, multicenter prospective validation is needed to confirm its applicability in real-world settings. Full article

Background: The effectiveness and cost-effectiveness of genetic testing for hereditary breast and ovarian cancer largely rely on the identification and clinical management of individuals with a pathogenic variant prior to developing cancer. Simulation modelling is commonly utilised to evaluate genetic testing strategies due to its ability to synthesise collections of data and extrapolate over long time periods and large populations. Existing genetic testing simulation models use simplifying assumptions for predictive genetic testing and risk management uptake, which could impact the reliability of their estimates. Our objective was to develop a microsimulation model that accurately reflects current genetic testing and subsequent care in Australia, directly incorporating the dynamic nature of predictive genetic testing within families and adherence to cancer risk management recommendations. Methods: The populatioN gEnEtic testing MOdel (NEEMO) is a population-level microsimulation that incorporates a detailed simulation of individuals linked within five-generation family units. The genetic component includes heritable high- and moderate-risk monogenic gene variants, as well as polygenic risk. Interventions include clinical genetic services, breast screening, and risk-reducing surgery. Model validation is described, and then to illustrate a practical application, NEEMO was used to compare clinical outcomes for four genetic testing scenarios in patients newly diagnosed with breast cancer (BC) and their relatives: (1) no genetic testing, (2) current practice, (3) optimised referral for genetic testing, and (4) genetic testing for all BC. Results: NEEMO accurately estimated genetic testing utilisation according to current practice and associated cancer incidence, pathology, and survival. Predictive testing uptake in first- and second-degree relatives was consistent with known prospective genetic testing data. Optimised genetic referral and expanded testing prevented up to 9.3% of BC and 4.1% of ovarian cancers in relatives of patients with BC. Expanding genetic testing eligibility to all BC patients did not lead to improvement in life-years saved in at-risk relatives compared to optimised referral of patients eligible for testing under current criteria. Conclusions: NEEMO is an adaptable and validated microsimulation model for evaluating genetic testing strategies. It captures the real-world uptake of clinical and predictive genetic testing and recommended cancer risk management, which are important considerations when considering real-world clinical and cost-effectiveness. Full article

Background: A subarachnoid hemorrhage due to an aneurysmal rupture (aSAH) is a serious condition with severe neurological consequences. The World Federation of Neurosurgical Societies (WFNS) classification is a reliable predictor of death and long-term disability in patients with aSAH. Poor-grade neurological conditions on admission in aSAH (PG-aSAH) are often linked to high mortality rates and unfavorable outcomes. However, more than one-third of patients with PG-aSAH may recover and have good functional outcomes if aggressive treatment is provided. We developed a risk model called Identifying POor GRade Outcomes (IPOGRO) to predict 6-month mRS outcomes in PG-aSAH patients as a secondary analysis of a previously published study. Methods: All consecutive patients in poor-grade neurological conditions (WFNS IV-V) admitted to our institute from 2010 to 2020 due to aSAH were considered. Clinical and neuroradiological parameters were employed in the univariable analysis to evaluate the relationship with a 6-month modified Rankin Scale (mRS). Then, a multivariable multinomial regression model was performed to predict 6-month outcomes. Results: 149 patients with PG-aSAH were included. Most patients were surgically treated, with only 33.6% being endovascularly treated. The 6-month mRS score was significantly associated with clinical parameters on admission, such as lowered Glasgow Coma Scale (GCS), leukocytosis, hyperglycemia, raised Systolic Blood Pressure (SBP), greater Simplified Acute Physiology Score (SAPS II score), increased initial serum Lactic Acid (LA) levels, and the need for Norepinephrine (NE) administration. Neuroradiological parameters on the initial CT scan showed a significant association with a worsening 6-month mRS. The IPOGRO risk model analysis showed an association between a WFNS V on admission and a poor outcome (mRS 4-5), while raised SBP was associated with mortality. Conclusions: Our IPOGRO risk model indicates that PG-aSAH patients with higher SBP at admission had an increased risk of death at 6-month follow-up, whereas patients with WFNS grade V at admission had an increased risk of poor outcome but not mortality. Full article

Background and Objectives: The Taiwan Triage and Acuity Scale (TTAS) is reliable for triaging patients in emergency departments in Taiwan; however, most triage decisions are still based on chief complaints. The reverse-shock index (SI) multiplied by the simplified motor score (rSI-sMS) is a more comprehensive approach to triage that combines the SI and a modified consciousness assessment. We investigated the combination of the TTAS and rSI-sMS for triage compared with either parameter alone as well as the SI and modified SI. Materials and Methods: We analyzed 13,144 patients with trauma from the Taipei Tzu Chi Trauma Database. We investigated the prioritization performance of the TTAS, rSI-sMS, and their combination. A subgroup analysis was performed to evaluate the trends in all clinical outcomes for different rSI-sMS values. The sensitivity and specificity of rSI-sMS were investigated at a cutoff value of 4 (based on previous study and the highest score of the Youden Index) in predicting injury severity clinical outcomes under the TTAS system were also investigated. Results: Compared with patients in triage level III, those in triage levels I and II had higher odds ratios for major injury (as indicated by revised trauma score < 7 and injury severity score [ISS] ≥ 16), intensive care unit (ICU) admission, prolonged ICU stay (≥14 days), prolonged hospital stay (≥30 days), and mortality. In all three triage levels, the rSI-sMS < 4 group had severe injury and worse outcomes than the rSI-sMS ≥ 4 group. The TTAS and rSI-sMS had higher area under the receiver operating characteristic curves (AUROCs) for mortality, ICU admission, prolonged ICU stay, and prolonged hospital stay than the SI and modified SI. The combination of the TTAS and rSI-sMS had the highest AUROC for all clinical outcomes. The prediction performance of rSI-sMS < 4 for major injury (ISS ≥ 16) exhibited 81.49% specificity in triage levels I and II and 87.6% specificity in triage level III. The specificity for mortality was 79.2% in triage levels I and II and 87.4% in triage level III. Conclusions: The combination of rSI-sMS and the TTAS yielded superior prioritization performance to TTAS alone. The integration of rSI-sMS and TTAS effectively enhances the efficiency and accuracy of identifying trauma patients at a high risk of mortality. Full article

Background: Caustic ingestion has gained increasing attention worldwide. However, the insight into whether to use esophagogastroduodenoscopy (EGD) or computed tomography (CT) for first-line investigation remains controversial. This study aimed to evaluate a diagnostic and management algorithm that combines EGD and CT for rapid triage. Methods: We established an algorithm for our hospital in 2013, aiming to maximize the benefits and minimize the limitations of EGD and CT. Then, we retrospectively analyzed the 163 enrolled patients treated between 2014 and 2019 and categorized them into 4 groups: A = 3 (1.8%): with perforation signs and directly confirmed by CT, B = 10 (6.1%): clinically suspected perforation but not initially proven by CT, C = 91 (55.8%): initial perforation less favored but with EGD grade ≥ 2b or GI/systemic complications, and D = 59 (36.2%): clinically stable with EGD grade ≤ 2a, according to initial signs/symptoms and EGD/CT grading. The morbidity and mortality of each group were analyzed. The predictive values of EGD and CT were examined by logistic regression analyses and receiver operating characteristic (ROC) curves. Results: The outcomes of such algorithm were reported. CT was imperative for patients with toxic signs and suspected perforation. For non-emergent operations, additional EGD was safe and helpful in identifying surgical necessity. For patients with an initially low perforation risk, EGD alone sufficiently determined admission necessity. Among inpatients, EGD provided excellent discrimination for predicting the risk for signs/symptoms’ deterioration. Routine additional CT was only beneficial for those with deteriorating signs/symptoms. Conclusions: According to the analyses, initial signs/symptoms help to choose EGD or CT as the first-line investigative tool in caustic patients. CT is necessary for seriously injured patients, but it cannot replace EGD for moderate/mild injuries. The severity stratification and patient categorization help to simplify complex scenarios, accelerate decision-making, and prevent unnecessary intervention/therapy. External validation in a larger sample size is further indicated for this algorithm. Full article

Background: Early identification of AMD can lead to prompt and more effective treatment, better outcomes, and better final visual acuity; several risk scores have been devised to determine the individual level of risk for developing AMD. Herein, the Delphi method was used to provide recommendations for daily practice regarding preventive measures and follow-up required for subjects at low, moderate, and high risk of AMD evaluated with the Simplified Test AMD Risk-assessment Scale (STARS^®) questionnaire. Methods: A steering committee of three experts drafted and refined 25 statements on the approach to be recommended in different clinical situations [general recommendations (n = 2), use of evaluation tools (n = 4), general lifestyle advice (n = 3), and AREDS-based nutritional supplementation (n = 5)] with the help of a group of international experts, all co-authors of this paper. Thirty retinal specialists from Europe and the US were chosen based on relevant publications, clinical expertise, and experience in AMD, who then provided their level of agreement with the statements. Statements for which consensus was not reached were modified and voted upon again. Results: In the first round of voting, consensus was reached for 24 statements. After modification, consensus was then reached for the remaining statement. Conclusion: An interprofessional guideline to support preventive measures in patients at risk of AMD based on STARS^® scoring has been developed to aid clinicians in daily practice, which will help to optimize preventive care of patients at risk of AMD. Full article

Introduction: Simplified ultrasound-based infertility protocols that appear to provide enough information to plan effective management have been described. Thus, the objective of this study is to compare the diagnostic accuracy of the hysterosalpingo-foam sonography (HyFoSy) in tubal patency testing with the traditional hysterosalpngography (HSG) for establishing a new diagnostic strategy in infertility. Material and Methods: Prospective observational diagnostic accuracy was performed in a private fertility clinic in which 106 women undergoing a preconceptionally visit were recruited. All of them had low risk for tubal disease, had performed an HSG and were negative for Chlamydia trachomatis antibody. Main outcome measures were tubal patency and pain grade. Results: Evaluation of tubal patency by HyFoSy showed a total concordance with the results of the previous HSG in 72.6% (n = 77), and a total discordance for 4.7% (n = 6), with the inter-test agreement Kappa equal to 0.57, which means moderate concordance. Among the patients, 59.1% did not report pain during the procedure, while the remaining 48.1% indicated pain in different degrees; patients usually report less pain and only 6.6% described more pain with HyFoSy than with HSG (OR 6.57 (CI 95% 3.11–13.89)). Clinical outcomes after performing HyFoSy were not affected. Conclusions: HyFoSy is in concordance with HSG regarding tubal patency results and it is a less painful technique than HSG. HyFoSy is more economical and can be performed in an exam room only equipped with an ultrasound scanner. Based on these results, HyFoSy could be the first-choice diagnostic option to assess tubal patency in patients with low risk of tubal disease. Full article

The Sustained Attention to Response Task (SART) has been used to measure neurocognitive functions in older adults. However, simplified average features of this complex dataset may result in loss of primary information and fail to express associations between test performance and clinically meaningful outcomes. Here, we describe a new method to visualise individual trial (raw) information obtained from the SART test, vis-à-vis age, and groups based on mobility status in a large population-based study of ageing in Ireland. A thresholding method, based on the individual trial number of mistakes, was employed to better visualise poorer SART performances, and was statistically validated with binary logistic regression models to predict mobility and cognitive decline after 4 years. Raw SART data were available for 4864 participants aged 50 years and over at baseline. The novel visualisation-derived feature bad performance, indicating the number of SART trials with at least 4 mistakes, was the most significant predictor of mobility decline expressed by the transition from Timed Up-and-Go (TUG) < 12 to TUG ≥ 12 s (OR = 1.29; 95% CI 1.14–1.46; p < 0.001), and the only significant predictor of new falls (OR = 1.11; 95% CI 1.03–1.21; p = 0.011), in models adjusted for multiple covariates. However, no SART-related variables resulted significant for the risk of cognitive decline, expressed by a decrease of ≥2 points in the Mini-Mental State Examination (MMSE) score. This novel multimodal visualisation could help clinicians easily develop clinical hypotheses. A threshold approach to the evaluation of SART performance in older adults may better identify subjects at higher risk of future mobility decline. Full article