Prediction Score Research Articles

Calibration of variant effect predictors on genome-wide data masks heterogeneous performance across genes

In silico variant effect predictions are available for nearly all missense variants but played a minimal role in clinical variant classification because they were deemed to provide only supporting evidence. Recently, the ClinGen Sequence Variant Interpretation (SVI) Working Group updated recommendations for variant effect prediction use. By analyzing control pathogenic and benign variants across all genes, they were able to compute evidence strength for predictor score intervals with some intervals generating moderate, strong, or even very strong evidence. However, this genome-wide approach could obscure heterogeneous predictor performance in different genes. We quantified the gene-by-gene performance of two top predictors, REVEL and BayesDel, by analyzing control variants in each predictor score interval in 3,668 disease-relevant genes. Approximately 10% of intervals had sufficient control variants for analysis, and ∼70% of these intervals exceeded the maximum number of incorrect predictions implied by the SVI recommendations. These trending discordant intervals arose owing to the divergence of the gene-specific distribution of predictions from the genome-wide distribution, suggesting that gene-specific calibration is needed in many cases. Approximately 22% of ClinVar missense variants of uncertain significance in genes we analyzed (REVEL= 100,629, BayesDel= 71,928) had predictions in trending discordant intervals. Thus, genome-wide calibrations could result in many variants receiving inappropriate evidence strength. To facilitate a review of the SVI's calibrations, we developed a web application enabling visualization of gene-specific predictions and trending concordant and discordant intervals.

Higher Circulating Neutrophil Counts Is Associated with Increased Risk of All-Cause Mortality and Cardiovascular Disease in Patients with Diabetic Kidney Disease.

Accumulating evidence has suggested the pathogenic roles of chronic inflammation and neutrophils in diabetic kidney disease (DKD). This study investigated the relationship between neutrophils, all-cause, and cardiovascular disease (CVD) mortality in type 2 diabetes mellitus (T2DM) patients with DKD. We used data from the National Health and Nutrition Examination Surveys (NHANES) from 2005 to 2020 to investigate the relationship between circulating neutrophils counts, kidney function indices, all-cause, and CVD mortality in adult T2DM patients with DKD. Clinical predictive models and risk scores for long-term mortality were constructed. 44,332 patients [8034 with T2DM and 36,323 without T2DM] were included. Two thousand two hundred twenty patients had DKD, and 775 died (31.5% related to CVD) during a follow-up of 6.18 (range: 5.94-6.42) years. Higher neutrophil counts (Quartile 4, Q4) were associated with increased all-cause and CVD mortality [HR 1.73 (95% CI 1.34-2.25) and 1.81 (95% CI 1.14-2.89), respectively, p < 0.0001 and 0.01]. Neutrophil counts in Q4 showed a positive correlation with urine albumin-creatinine ratio (UACR) but a negative association with eGFR (p < 0.01 for all). Clinical predictive models incorporating neutrophil counts showed satisfactory performance in forecasting 5-year and 10-year CVD mortality-free survival (ROC AUC 0.824 and 0.842, respectively), and the nomogram-predicted survival demonstrated good concordance with observed survival. Higher levels of circulating neutrophil counts show a significant correlation with renal abnormalities and higher all-cause and CVD mortality in T2DM patients with DKD. The novel clinical predictive models and risk scores incorporating neutrophil counts may facilitate stratification and, hence, risk factor management in DKD patients.

Development of a prediction score for Barrett's esophagus in Japanese health checkup settings.

The incidence of esophageal adenocarcinoma has recently increased in Asia, including Japan. A system to identify individuals at high risk for Barrett's esophagus (BE), a pre-cancerous condition of esophageal adenocarcinoma, among the general population is needed to perform endoscopic surveillance appropriately. We therefore developed risk prediction scores for BE at health checkups in Japan. 4128 consecutive health checkup examinees were retrospectively enrolled from October 2021 to March 2022. A prediction score for BE was developed based on the linear transformation of β-regression coefficients in a multivariable regression model incorporating BE predictors. Internal validation was performed by evaluating discrimination and calibration of the prediction model. Three prediction scores corresponding to BE based on its length were developed: all lengths, ≥ 1cm, ≥ 2cm. All scores were internally validated, and the model calibration was excellent. The performance of the prediction models was better for longer BE, with a c-statistic of 0.70 for BE ≥ 2cm, than for shorter values. The prediction score for BE ≥ 2cm yielded sensitivity and specificity of 52.9% and 78.6% in high-risk subjects and 91.2% and 29.3% in intermediate- or high-risk subjects, respectively. This prediction score can potentially increase the endoscopic detection of BE by identifying potentially high-risk individuals from the general population. This is the first report on developing a prediction score for BE that may suit the Japanese population.

Risk Prediction Score for Thermal Mapping of Pharmaceutical Transport Routes in Brazil

Risk Prediction Score for Thermal Mapping of Pharmaceutical Transport Routes in Brazil

Predicting New-Onset Atrial Fibrillation in Patients with Coronary Artery Bypass Graft: the Precise-Dapt Score

&lt;b&gt;Aim:&lt;/b&gt;&amp;nbsp;Postoperative new-onset atrial fibrillation (POAF) after isolated coronary artery bypass graft surgery (CABG) is associated with adverse events. The Predicting bleeding complications in patients undergoing stent implantation and subsequent dual antiplatelet therapy (PRECISE-DAPT) score is used to predict the bleeding risk after dual antiplatelet therapy and has been associated with arrhythmias in recent years. Therefore, the present study sought to investigate the association between the PRECISE-DAPT score and POAF after coronary artery bypass graft surgery.&lt;br /&gt; &lt;b&gt;Materials and Methods:&lt;/b&gt;&amp;nbsp;350 patients who underwent CABG were retrospectively screened. After exclusion criteria, 135 patients were included in the study. A total of 135 patients who underwent on-pump CABG were divided into two groups: patients with POAF and those without POAF. The PRECISE-DAPT score was calculated for each patient, and intergroup comparisons of the calculated scores were performed.&lt;br /&gt; &lt;b&gt;Results:&lt;/b&gt;&amp;nbsp;POAF was detected in 66 patients out of 135. Patients with POAF had longer hospital stays. PRECISE-DAPT score was higher in the patients with POAF compared to the patients without POAF (p&amp;lt;0.001). PRECISE-DAPT score was determined to be a predictor of POAF after CABG (odds ratio [OR]: 1.305; 95% confidence interval [CI]: 1.268–2.030; p&amp;lt;0.001).&amp;nbsp;The PRECISE-DAPT score for POAF risk had a sensitivity of 60% and a specificity of 79% at cut-off values of 14.5 and above.&lt;br /&gt; &lt;b&gt;Conclusion:&lt;/b&gt;&amp;nbsp;An increased PRECISE-DAPT score may be used as a predictive score for POAF that may develop during hospital stay after on-pump CABG.

Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.

CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable for longitude assessment during anti-tumor therapy. This work aims to develop and validate a noninvasive workflow based on contrast-enhanced CT (CECT) images to evaluate the CD8+ T-cell infiltration profiles of GC. GC patients were retrospectively and consecutively enrolled and randomly assigned to the training (validation) or test cohort at a 7:3 ratio. All patients were binary classified into the CD8-high (infiltrated proportion≥20%) or CD8-low group (infiltrated proportion<20%) group. A total of 1170 radiomics features were extracted from each presurgical CECT series. After feature selection, fifteen radiomics features were transmitted to three independent machine-learning models for the computation of predictive radiological scores. Multilayer perceptron (MLP) was applied to merge the radiological scores with clinical factors. The predictive efficacy of the radiological scores and of the combined model was evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis in both the training and test cohorts. A total of 210 patients were enrolled in this study (mean age: 63.22±8.74years, 151 men), and were randomly assigned to the training set (n=147) or the test set (n=63). The merged radiological score was correlated with CD8 infiltration in both the training (p=1.8e-10) and test cohorts (p=0.00026). The combined model integrating the radiological scores and clinical features achieved an area under the curve (AUC) value of 0.916 (95% CI: 0.872-0.960) in the training set and 0.844 (95% CI: 0.742-0.946) in the test set for classifying CD8-high GCs. The model was well-calibrated and exhibited net benefit over "treat-all" and"treat-none" strategies in decision curve analysis. Artificial intelligent systems combining radiological features and clinical factors could accurately predict CD8 infiltration levels of GC, which may benefit personalized treatment of GC in the context of immunotherapy.

Individualized MRI-based stroke PRediction scOre using plaque Vulnerability for symptomatic carotid artEry disease patients (IMPROVE).

In TIA and stroke patients with carotid stenosis, estimations of future ipsilateral ischemic stroke risk and treatment decisions are currently primarily based on the degree of stenosis. Intraplaque hemorrhage (IPH), which can be readily visualized on carotid MRI, is increasingly established as an easy to assess and a very strong and independent predictor for ipsilateral stroke risk, stronger than any clinical risk factor. We developed a clinical prediction model (IMPROVE) incorporating IPH, degree of stenosis, and clinical risk factors to select patients with symptomatic carotid stenosis at high risk for stroke. IMPROVE was developed on pooled clinical and MRI data from five cohort studies of 760 recent TIA or minor stroke patients with carotid plaque who received optimal medical treatment. We used Cox proportional hazards models to determine the coefficients of IMPROVE. IMPROVE was internally validated using bootstrapping and converted to one- and three-year ipsilateral ischemic stroke risk. The development dataset contained 65 ipsilateral incident ischemic strokes that occurred during a median follow-up of 1.2 years (IQR: 0.5-4.1). The IMPROVE model includes five predictors, which are in order of importance: degree of stenosis, presence of IPH on MRI, classification of last event (cerebral vs ocular), sex, and age. Internal validation revealed a good accuracy (C-statistic: 0.82; 95% CI: 0.77-0.87) and no evidence for miscalibration (calibration slope: 0.93). Using presence of IPH on MRI and only four conventional parameters, the IMPROVE model provides accurate individual stroke risk estimates, which may facilitate stratification for revascularization.

Risk factors and development of a predictive score model for tumor lysis syndrome in childhood leukemia: a 10-year experience from a single tertiary hospital in Thailand

Tumor lysis syndrome (TLS) in childhood leukemia was assessed retrospectively in 252 patients in a single tertiary center in Thailand during 2009–2019. Fifty-one (20.2%) developed TLS during their induction chemotherapy; 60.7% (31/51) were spontaneous TLS and 47% (24/51) developed clinical TLS. The predictive score model consisted of white blood cell (WBC) count more than 50,000 cells/mm3, glomerular filtration rate less than 90, and aspartate transaminase more than 44 units/L. The TLS development rates were 11.1%, 46.2%, and 78.5% in the low, intermediate, and high-risk groups, respectively. Death during the first induction phase in patients with TLS was significantly higher than in the patients without TLS. However, the 5-year overall survival rates for the children with and without TLS were not significantly different.

Novel “Ex-PRO” score for the cardiovascular complications prediction in extrasystolic arrhythmia

Novel “Ex-PRO” score for the cardiovascular complications prediction in extrasystolic arrhythmia

Hanc score is a replicable clinical risk score for outcome prediction of Taiwanese clopidogrel non-responders after percutaneous coronary intervention

Hanc score is a replicable clinical risk score for outcome prediction of Taiwanese clopidogrel non-responders after percutaneous coronary intervention

Escalating Surgical Treatment for Left Ventricular Assist Device Infection and Expected Mortality: Clinical Risk Prediction Score.

Left ventricular assist devices (LVAD) improve survival for patients with cardiac failure, but LVAD-specific infection (VSI) remains a challenge with poorly understood predictive risk factors. The indications and use of escalating medical treatment to surgical debridement and potential flap reconstruction are not well characterized. A retrospective review of consecutive patients undergoing primary LVAD implantation at a tertiary academic center was performed. The primary outcome measures were 90-day and overall mortality after VSI. Cox proportional hazards regression was used to generate a risk prediction score for mortality. Of the 760 patients undergoing primary LVAD implantation, 255 (34%) developed VSI; of these patients, 91 (36%) were managed medically, 134 (52%) with surgical debridement, and 30 (12%) with surgical debridement and flap reconstruction. One-year survival after infection was 85% with median survival of 2.40 years. Factors independently associated with increased mortality were diabetes (hazard ratio [HR] 1.44, p = 0.04), MRSA infection (HR 1.64, p = 0.03), deep space (pump pocket or outflow cannula) involvement (HR 2.26, p < 0.001), and extracorporeal membrane oxygenation after LVAD (HR 2.52, p < 0.01). Factors independently associated with decreased mortality were flap reconstruction (HR 0.49, p = 0.02) and methicillin-sensitive Staphylococcus aureus infection (HR 0.63, p = 0.03). A clinical risk prediction score was developed using these factors and showed significant differences in median survival, which was 5.67 years for low-risk (score 0 to 1), 3.62 years for intermediate-risk (score 2), and 1.48 years for high-risk (score ≥3; p < 0.001) patients. We developed a clinical risk prediction score to stratify patients with VSI. In selected cases, escalating surgical treatment was associated with increased survival. Future work is needed to determine whether early surgical debridement and flap reconstruction can alter outcomes in select cases of VSI.

CAPS: a simple clinical tool for β-amyloid positivity prediction in clinical Alzheimer syndrome.

With the advent of anti-β-amyloid therapies, clinical distinction between Aβ + and Aβ- in cognitive impairment is becoming increasingly important for stratifying referral and better utilization of biomarker assays. Cognitive profile, rate of decline, neuropsychiatric inventory questionnaire (NPI-Q), and imaging characteristics were collected from 52 subjects with possible/probable AD. Participants with Aβ+ status had lower baseline MMSE scores (24.50 vs. 26.85, p = 0.009) and higher total NPI-Q scores (2.73 vs. 1.18, p < 0.001). NPI-Q score was found to be the only independent predictor for β-amyloid positivity (p = 0.008). A simple scoring system, namely Clinical β-Amyloid Positivity Prediction Score (CAPS), was developed by using the following parameters: NPI-Q, rapidity of cognitive decline, and white matter microangiopathy. Data from 48 participants were included in the analysis of accuracy of CAPS. CAP Score of 3 or 4 successfully classified Aβ + individuals in 86.7% cases. Clinical β-Amyloid Positivity Prediction Score is a simple clinical tool for use in primary care and memory clinic settings to predict β-amyloid positivity in individuals with clinical Alzheimer Syndrome can potentially facilitate referral for Anti Aβ therapies.

A novel surgical risk predictor combining frailty and hypoalbuminemia - A cohort study of 9.8m patients from the ACS-NSQIP database.

The functional decline seen in frail patients is associated with significant morbidity and mortality. The modified frailty index 5 (mFI-5) score is an accepted risk predictor score in surgery. Hypoalbuminemia has been correlated with poor postoperative outcomes.There exists, however, a gap in the literature regarding the combined assessment of frailty and hypoalbuminemia and the predictive power of this combined assessment. This retrospective cohort study aimed to investigate the association of preoperative albumin and frailty, as assessed with the mFI-5 score, and its ability to predict surgical outcomes. We queried the ACS-NSQIP database (2008-2021) to identify all surgical patients. Perioperative data, including demographics and preoperative laboratory values, including albumin, were collected. The predictive power of the mFI-5 and hypoalbuminemia (Alb) independently, and in combination (mFI-5+Alb), was assessed using multivariable linear and logistic regression models 30-day outcomes were assessed including mortality, length of hospital stay, reoperation, medical and surgical complications, and discharge destination. A total of 9,782,973 patients were identified of whom 4,927,520 (50.4%) were non-frail (mFI=0), 3,266,636 had a frailty score of 1 (33.4%), 1,373,968 a score of 2 (14.0%), 188,821 a score of 3 (1.9%) and 26,006 a score greater or equal to 4 (0.3%). Albumin levels were available for 4,570,473 patients (46.7%), of whom 848,315 (18.6%) had hypoalbuminemia. The combined assessment (mFI-5+Alb) was found to be a more accurate risk predictor than each factor independently for all outcomes. A weak negative correlation between serum albumin levels and mFI scores was established (Spearman R: -0.2; <0.0001). Combined assessment of frailty and albumin was the strongest risk predictor. Therefore, for patients undergoing surgery, we recommend consideration of both serum albumin and frailty in order to optimally determine perioperative planning, including multi-disciplinary care mobilization and pre- and posthabilitation.

Prognostic Clinical and Biological Markers for Amyotrophic Lateral Sclerosis Disease Progression: Validation and Implications for Clinical Trial Design and Analysis.

With increasing recognition of the value of incorporating prognostic markers into amyotrophic lateral sclerosis (ALS) trial design and analysis plans, there is a pressing need to understand which among the prevailing clinical and biochemical markers have real value, and how they can be optimally used. A subset of patients with ALS recruited through the multi-center Phenotype-Genotype-Biomarker study (clinicaltrials.gov: NCT02327845) was identified as "trial-like" based on meeting common trial eligibility criteria. Clinical phenotyping was performed by evaluators trained in relevant assessments. Serum neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH), urinary p75ECD, plasma microRNA-181, and an array of biochemical and clinical measures were evaluated for their prognostic value. Associations with functional progression were estimated by random-slopes mixed models of ALS functional rating scale-revised (ALSFRS-R) score. Associations with survival were estimated by log-rank test and Cox proportional hazards regression. Potential sample size savings from adjusting for given biomarkers in a hypothetical trial were estimated. Baseline serum NfL is a powerful prognostic biomarker, predicting survival and ALSFRS-R rate of decline. Serum NfL <40pg/ml and >100pg/ml correspond to future ALSFRS-R slopes of ~0.5 and 1.5 points/month, respectively. Serum NfL also adds value to the best available clinical predictors, encapsulated by the European Network to Cure ALS (ENCALS) predictor score. In models of functional decline, the addition of NfL yields ~25% sample size saving above those achieved by inclusion of either clinical predictors or ENCALS score alone. The prognostic value of serum pNfH, urinary p75ECD, and plasma miR-181ab is more limited. Among the multitude of biomarkers considered, only blood NfL adds value to the ENCALS prediction model and should be incorporated into analysis plans for all ongoing and future ALS trials. Defined thresholds of NfL might also be used in trial design, for enrichment or stratified randomisation, to improve trial efficiency. NIH (U01-NS107027, U54-NS092091). ALSA (16-TACL-242).

Evaluation of risk prediction scores for adults hospitalized with COVID-19 in a highly-vaccinated population, Aotearoa New Zealand 2022

ObjectivesCOVID-19 severity prediction scores need further validation due to evolving COVID-19 illness. We evaluated existing COVID-19 risk prediction scores in Aotearoa New Zealand, including for Māori and Pacific peoples who have been inequitably affected by COVID-19. MethodsWe conducted a multicenter retrospective cohort study in adults hospitalized with COVID-19 from January to May 2022, including all Māori and Pacific patients, and every second non-Māori, non-Pacific (NMNP) patient to achieve equal analytic power by ethnic grouping. We assessed the accuracy of existing severity scores (4C Mortality, CURB-65, PRIEST, and VACO) to predict death in the hospital or within 28 days. ResultsOf 2319 patients, 582 (25.1%) identified as Māori, 914 (39.4%) as Pacific, and 862 (37.2%) as NMNP. There were 146 (6.3%, 95% confidence interval 5.4-7.4%) deaths, with a predicted probability of death higher than observed mortality for VACO (10.4%), modified PRIEST (15.1%) and 4C mortality (15.5%) scores, but lower for CURB-65 (4.5%). C-statistics (95% CI) of severity scores were: 4C mortality: Māori 0.82 (0.75, 0.88), Pacific 0.87 (0.83, 0.90), NMNP 0.90 (0.86, 0.93); CURB-65: Māori 0.83 (0.69, 0.92), Pacific 0.87 (0.82, 0.91), NMNP 0.86 (0.80, 0.91); modified PRIEST: Māori 0.85 (0.79, 0.90), Pacific 0.81 (0.76, 0.86), NMNP 0.83 (0.78, 0.87); and VACO: Māori 0.79 (0.75, 0.83), Pacific 0.71 (0.58, 0.82), NMNP 0.78 (0.73, 0.83). ConclusionsFollowing re-calibration, existing risk prediction scores accurately predicted mortality.

Simultaneous prognostic score validation in patients with out-of-hospital cardiac arrest by a post-hoc analysis based on national multicenter registry

Using a nationwide multicenter prospective registry in Japan’s data, we calculated prognostic and predictive scores, including the Out-of-Hospital Cardiac Arrest (OHCA); Cardiac Arrest Hospital Prognosis (CAHP); Nonshockable rhythm, Unwitnessed arrest, Long no-flow or Long low-flow period, blood PH < 7.2, Lactate > 7.0 mmol/L, End-stage chronic kidney disease on dialysis, Age ≥ 85 years, Still resuscitation, and Extracardiac cause (NULL-PLEASE); revised post-Cardiac Arrest Syndrome for Therapeutic hypothermia (rCAST); and MIRACLE2 scores, for adult patients with cardiac arrest. The MIRACLE2 score was validated with the modified MIRACLE2 score, which excludes information of pupillary reflexes. Each score was calculated only for the cases with no missing data for the variables used. These scores’ accuracies were compared using neurological outcomes 30 days after out-of-hospital cardiac arrest (OOHCA). Patients with a cerebral performance category scale of 1 or 2 were designated as having favorable neurological outcomes. Each score’s discrimination ability was evaluated by the receiver operating characteristic curve’s area under the curve (AUC). To assess in detail in areas of high specificity and high sensitivity, which are areas of interest to clinicians, partial AUCs were also used. The analysis included 11,924 hospitalized adult patients. The AUCs of the OHCA, MIRACLE2, CAHP, rCAST, and NULL-PLEASE scores for favorable neurological outcomes were 0.713, 0.727, 0.785, 0.761, and 0.831, respectively. The CAHP and NULL-PLEASE scores were significantly more accurate than the rest. Accuracies did not differ significantly between the CAHP and NULL-PLEASE scores. The NULL-PLEASE score was significantly better at discriminating favorable neurological prognoses at 30 days in patients with OOHCA compared to other scoring systems.

The Predictive Value of Amplitude-Integrated Electroencephalography for the Neurodevelopmental Outcomes of Preterm Newborns at 12 Months Corrected Age.

In clinical practice, it is crucial to identify diagnostic methods that can forecast the neurodevelopmental outcomes of very preterm neonates. Our study aimed to assess the predictive significance of amplitude-integrated electroencephalography (aEEG) for the neurodevelopmental outcomes of preterm infants at 12 months corrected age and to establish the cut-off score that could indicate potential neurodevelopmental impairments. Preterm neonates born before 32 weeks of gestational age between June 2020 and July 2022 were included in a prospective manner. Amplitude-integrated electroencephalography recordings were conducted at five age intervals (days 1-3; first, second, third and fourth weeks). Recordings were analyzed using the Burdjalov scoring system. The neurodevelopment assessment with Bayley Scales of Infant Development-Second Edition was carried out at 12 months corrected age. A total of 140 newborns were included in the study. Neurodevelopment was assessed in 108 infants at 12 months corrected age. Higher total aEEG Burdjalov scores were observed in groups with normal cognitive and motor development. The most sensitive and specific score for prediction of cognitive impairment in 12 months corrected age was an aEEG evaluation of 5.5 according to Burdjalov score within the first three days. The most sensitive and specific score for prediction of motor impairment was 8.5 within the first week. According to our research there is currently not enough data to accurately foresee the development of newborns at 12 months corrected age according to early aEEG test results. However, conducting a research with bigger sample size and repeated evaluations at a later age might increase the prognostic value of aEEG. In this study cut-off scores of aEEG performed early in life to predict later neurodevelopment outcomes were determined.

Exploring the prognostic landscape of oral squamous cell carcinoma through mitochondrial damage-related genes

Oral squamous cell carcinoma (OSCC), the most prevalent form of oral cancer, poses significant challenges to the medical community due to its high recurrence rate and low survival rate. Mitochondrial Damage-Related Genes (MDGs) have been closely associated with the occurrence, metastasis, and progression of OSCC. Consequently, we constructed a prognostic model for OSCC based on MDGs and identified potential mitochondrial damage-related biomarkers. Gene expression profiles and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Differential analysis was conducted to identify MDGs associated with OSCC. COX analysis was employed to screen seven prognosis-related MDGs and build a prognostic prediction model for OSCC. Cases were categorized into low-risk or high-risk groups based on the optimal risk score threshold. Kaplan-Meier (KM) analysis revealed significant survival differences (P < 0.05). Additionally, the area under the ROC curve (AUC) for patient survival at 1 year, 3 years, and 5 years were 0.687, 0.704, and 0.70, respectively, indicating a high long-term predictive accuracy of the prognostic model. To enhance predictive accuracy, age, gender, risk score, and TN staging were incorporated into a nomogram and verified using calibration curves. Risk scoring based on MDGs was identified as a potential independent prognostic biomarker. Furthermore, BID and SLC25A20 were identified as two potential independent mitochondrial damage-related prognostic biomarkers, offering new therapeutic targets for OSCC.

Hemodynamic characteristics in ruptured and unruptured intracranial aneurysms: a prospective cohort study utilizing the AneurysmFlow™ tool.

Hemodynamic factors significantly influence the onset, progression, and rupture of intracranial aneurysms (IAs). Current rupture risk prediction scores focus primarily on the clinical, anatomical and morphological aspects. This study aimed to investigate the hemodynamic characteristics differences between ruptured and unruptured IAs. Conducted from July 2021 to July 2022, this prospective cohort study involved patients with ruptured and unruptured IAs undergoing digital subtraction angiography (DSA). Hemodynamic characteristics were assessed using the AneurysmFlow™ tool. Hemodynamic, clinical, anatomical and morphological parameters were compared between ruptured and unruptured IA groups. The study included 127 patients with 135 aneurysms (67 ruptured, 68 unruptured). Complex flow patterns (type 3 and 4) were observed more frequently in ruptured aneurysms compared to unruptured aneurysms (odds ratio [OR], 5.57; 95% confidence interval [CI], 2.49-12.45; P < 0.001) in univariate analysis, and were also more common in unruptured aneurysms associated with daughter sacs features (P = 0.015). The mean aneurysm flow amplitude (MAFA) was lower in ruptured aneurysms, and associated with lower flow velocity in the parent artery related to vasospasm. MAFA in the aneurysmal dome or any additional daughter sacs was lowest compared to other regions inside the aneurysms. The technical failure rate of AneurysmFlow™ measurements was 8.5% (12 out of 139 patients). Additionally, hypertension (OR, 0.42; 95% CI, 0.30-0.54; P < 0.001), bifurcation location (AcomA/ACA/MCA/PcomA/posterior circulation) (OR, 0.17; 95% CI, 0.05-0.29; P = 0.005), and irregular shape (OR, 0.19; 95% CI, 0.05-0.35; P = 0.012) were identified as independently associated with rupture. Complex flow patterns identified on the AneurysmFlow™ tool are significantly more common in ruptured and unruptured aneurysms associated with daughter sac features. The lowest MAFA in the aneurysmal dome and daughter sacs likely indicates specific pathophysiological changes within the aneurysm wall associated with rupture incidence. Hypertension, bifurcation location, and an irregular shape are independently associated with the risk of rupture. Further multicenter studies with larger sample sizes are needed to validate these findings. ACA = anterior cerebral artery; AcomA = anterior communicating artery; IAs = intracranial aneurysms; ICA = internal carotid artery; MAFA = mean aneurysm flow amplitude; MCA = middle cerebral artery; PcomA = posterior communicating artery; RIAs = ruptured intracranial aneurysms; SAH = subarachnoid hemorrhage; UIAs = unruptured intracranial aneurysms.

Developing a risk score to inform the use of rhBMP-2 in adult spinal deformity surgery.

Recombinant human bone morphogenetic protein-2 (rhBMP-2) has not shown superior benefit overall in cost-effectiveness during adult spinal deformity (ASD) surgery. Retrospective PURPOSE: Generate a risk score for pseudarthrosis to inform the utilization of rhBMP-2, balancing costs against quality of life and complications. ASD patients with 3-year data were included. Quality of life gained was calculated from ODI to SF-6D and translated to quality-adjusted life years (QALYs). Cost was calculated using the PearlDiver database and CMS definitions for complications and comorbidities. Established weights were generated for predictive variables via logistic regression to yield a predictive risk score for pseudarthrosis that accounted for frailty, diabetes, depression, ASA grade, thoracolumbar kyphosis and three-column osteotomy use. Risk score categories, established via conditional inference tree (CIT)-derived thresholds were tested for cost-utility of rhBMP-2 usage, controlling for age, prior fusion, and baseline deformity and disability. 64% of ASD patients received rhBMP-2 (308/481). There were 17 (3.5%) patients that developed pseudarthrosis. rhBMP-2 use overall did not lower pseudarthrosis rates (OR: 0.5, [0.2-1.3]). Pseudarthrosis rates for each risk category were: No Risk (NoR) 0%; Low-Risk (LowR) 1.6%; Moderate Risk (ModR) 9.3%; High-Risk (HighR) 24.3%. Patients receiving rhBMP-2 had similar QALYs overall to those that did not (0.163 vs. 0.171, p = .65). rhBMP-2 usage had worse cost-utility in the LowR cohort (p < .001). In ModR patients, rhBMP-2 usage had equivocal cost-utility ($53,398 vs. $61,581, p = .232). In the HighR cohort, the cost-utility was reduced via rhBMP-2 usage ($98,328 vs. $211,091, p < .001). Our study shows rhBMP-2 demonstrates effective cost-utility for individuals at high risk for developing pseudarthrosis. The generated score can aid spine surgeons in the assessment of risk and enhance justification for the strategic use of rhBMP-2 in the appropriate clinical contexts. III.