Stepwise Multivariate Logistic Regression Research Articles

Trajectory Analysis for Identifying Classes of Attention Deficit Hyperactivity Disorder (ADHD) in Children of the United States.

Attention Deficit Hyperactivity Disorder (ADHD) is a mental health disorder that affects attention and behavior. People with ADHD frequently encounter challenges in social interactions, facing issues, like social rejection and difficulties in interpersonal relationships, due to their inattention, impulsivity, and hyperactivity. A National Longitudinal Survey of Youth (NLSY) database was employed to identify patterns of ADHD symptoms. The children who were born to women in the NLSY study between 1986 and 2014 were included. A total of 1,847 children in the NLSY 1979 cohort whose hyperactivity/inattention score was calculated when they were four years old were eligible for this study. A trajectory modeling method was used to evaluate the trajectory classes. Sex, baseline antisocial score, baseline anxiety score, and baseline depression score were adjusted to build the trajectory model. We used stepwise multivariate logistic regression models to select the risk factors for the identified trajectories. The trajectory analysis identified six classes for ADHD, including (1) no sign class, (2) few signs since preschool being persistent class, (3) few signs in preschool but no signs later class, (4) few signs in preschool that magnified in elementary school class, (5) few signs in preschool that diminished later class, and (6) many signs since preschool being persistent class. The sensitivity analysis resulted in a similar trajectory pattern, except for the few signs since preschool that magnified later class. Children's race, breastfeeding status, headstrong score, immature dependent score, peer conflict score, educational level of the mother, baseline antisocial score, baseline anxious/depressed score, and smoking status 12 months prior to the birth of the child were found to be risk factors in the ADHD trajectory classes. The trajectory classes findings obtained in the current study can (a) assist a researcher in evaluating an intervention (or combination of interventions) that best decreases the long-term impact of ADHD symptoms and (b) allow clinicians to better assess as to which class a child with ADHD belongs so that appropriate intervention can be employed.

Factors associated with increased 30-day re-operation risk in anterior cruciate ligament reconstruction

BackgroundRevision surgery following isolated anterior cruciate ligament reconstruction (ACLR) has often focused on mid- to long-term revisions due to re-rupture, while short-term 30-day revision is a rare, but underappreciated entity. This study aims to characterize incidence and risk factors for reoperations following isolated ACLR. MethodsThis is a retrospective case-control analysis of the American College of Surgeons National Surgical Quality Improvement Program Database (NSQIP) database from 2005 to 2017. Current Procedural Terminology codes were used to identify elective isolated ACLR patients. Patients undergoing reoperations were analyzed using bivariate analysis against their respective perioperative variables. Multivariate stepwise logistic regression was used to identify independent risk factors for reoperations after ACLR. Results12,790 patients were included in the study. 37.0% of patients were female. Mean age was 32.2+/-10.7 years and mean body mass index (BMI) was 27.8+/-6.5 kg/m2, with 28.9% of patients with BMI > 30. The most frequently reported reason for reoperation based on CPT and ICD-9/10 codes was postoperative infection (0.5%). Overall reoperation rate was approximately 0.5%. Multivariate analysis identified operative time >1.5 h (OR 2.6 [95% CI; 1.5–4.4]), dependent functional status (OR 14.0 [1.4–141.6]), and adjunctive anesthesia (OR 2.4 [95% CI; 1.1–5.0]) as independent risk factors for reoperation. Female sex was a protective factor against reoperations (OR 0.6 [0.3–0.98]). ConclusionPrimary, isolated ACLR is associated with extremely low rates of short-term reoperations. Operative time >1.5 h, dependent functional status, and adjunctive anesthesia were independent risk factors for reoperation and female sex was a protective factor against reoperation. Level of EvidenceLevel III. Retrospective cohort study.

Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics

Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent on endoscopists’ experience. We aim to establish a more accurate predictive model for infiltration depth of early gastric cancer including a standardized colorimetric system, which demonstrates promising clinical implication. A retrospective study of 718 EGC cases was performed. Clinical and pathological characteristics were included, and Commission Internationale de l’Eclariage (CIE) standard colorimetric system was used to evaluate the chromaticity of lesions. The predicting models were established in the derivation set using multivariate backward stepwise logistic regression, decision tree model, and random forest model. Logistic regression shows location, macroscopic type, length, marked margin elevation, WLI color difference and histological type are factors significantly independently associated with infiltration depth. In the decision tree model, margin elevation, lesion located in the lower 1/3 part, WLI a*color value, b*color value, and abnormal thickness in enhanced CT were selected, which achieved an AUROC of 0.810. A random forest model was established presenting the importance of each feature with an accuracy of 0.80, and an AUROC of 0.844. Quantified color metrics can improve the diagnostic precision in the invasion depth of EGC. We have developed a nomogram model using logistic regression and machine learning algorithms were also explored, which turned out to be helpful in decision-making progress.

Non-Invasive Ventilation Support during Hospitalization for SARS-CoV-2 and the Risk of Venous Thromboembolism.

Background/Objectives: Although SARS-CoV-2 infection is a significant risk factor for venous thromboembolism (VTE), data on the impact of the use of non-invasive ventilation support (NIVS) to mitigate the risk of VTE during hospitalization are scarce. Methods: Data for 1471 SARS-CoV-2 patients, hospitalized in a single hub during the first pandemic wave, were collected from clinical records, including symptom duration and type, information on lung abnormalities on chest computed tomography (CT), laboratory parameters and the use of NIVS. Determining VTE occurrence during hospital stays was the main endpoint. Results: Patients with VTE (1.8%) had an increased prevalence of obesity (26% vs. 11%), diabetes (41% vs. 21%), higher CHA2DS2VASC score (4, IQR 2-5 vs. 3, IQR 1-4, age- and sex-adjusted, p = 0.021) and cough (65% vs. 44%) and experienced significantly higher rates of NIVS (44% vs. 8%). Using a stepwise multivariate logistic regression model, the prevalence of electrocardiogram abnormalities (odds ratio (OR) 2.722, 95% confidence interval (CI) 1.039-7.133, p = 0.042), cough (OR 3.019, 95% CI 1.265-7.202, p = 0.013), CHA2DS2-VASC score > 3 (OR 3.404, 95% CI 1.362-8.513, p = 0.009) and the use of NIVS (OR 15.530, 95% CI 6.244-38.627, p < 0.001) were independently associated with a risk of VTE during hospitalization. NIVS remained an independent risk factor for VTE even after adjustment for the period of admission within the pandemic wave. Conclusions: Our study suggests that NIVS is a risk factor for VTE during hospitalization in SARS-CoV-2 patients. Future studies should assess the optimal prophylactic strategy against VTE in patients with a SARS-CoV-2 infection candidate to non-invasive ventilatory support.

Abstract PO2-10-11: Impact of COVID-19 Pandemic on the Disease Volume, Severity and Clinical Complications at Diagnosis and During First Year of Advanced Breast Cancer: COVID19-ABC Quasi-Experimental Study

Abstract Background: The COVID-19 pandemic affected healthcare systems, tumbling cancer screening programs and increasing fear of infection among medical facilities users. We hypothesized that the pandemic negatively impacted the clinical outcomes of patients (pts) with advanced breast cancer (ABC). The COVID19-ABC study aims to assess the influence of the pandemic on disease volume, severity, and clinical complications at diagnosis and during 1st year of ABC. Methods: Single-center, retrospective, quasi-experimental study with historical control. We included women treated for unresectable/metastatic recurrent or stage IV de novo ABC in a Belgian cancer center. Pts were eligible if ABC was diagnosed between 1/Jun/2020-30/Nov/2021 - pandemic exposure (Exp) cohort - or between 1/Jun/2017-30/Nov/2018 - historical (Hist) cohort. We collected data from medical records for baseline characteristics and study outcomes: proportion of oligometastatic disease (OMD) at ABC diagnosis, and proportion of visceral crisis and disease-related serious clinical events during the 1st month and between 1-12 months after ABC diagnosis. We compared baseline variables between the two cohorts using χ2 test for frequencies and Wilcoxon rank-sum test for continuous variables. We performed a pre-planned subgroup analysis by year of pandemic, immunohistochemistry (IHC) subtype, and recurrent vs de novo ABC. Univariate and multivariate backward stepwise logistic regressions were used to determine the odds ratio (OR) and the 95% confidence interval (CI) of the association of exposure to the pandemic with study outcomes, controlling for confounders. Results: We included 150 pts, 74 in Exp and 76 in Hist cohort. Age and proportion of de novo ABC and triple-negative breast cancer (TNBC) were numerically higher, while comorbidities and Ki67 index were significantly higher among patients in the Exp cohort (Table 1). Pts in the Exp cohort had a significantly higher risk of visceral crisis during the 1st month of ABC (28.4% vs 15.8%; OR 4.24, 95% CI, 1.45-12.39, adjusted for histology grade and recurrent vs de novo), with similar trend between 1-12 months of ABC (19.4% vs 12.7%, OR 1.66, 95% CI, 0.67-4.13). Visceral crisis tended to be more common in patients diagnosed in the 2nd vs 1st year of the pandemic (35.7% vs 26.7%, p=0.50). We observed higher proportions of visceral crisis in the Exp cohort for pts with recurrent ABC (36.5% vs 17.7%, p=0.02), HER2+ (66.7% vs 10.0%, p=0.01), and TNBC (40.0% vs 18.2%, p=0.21) IHC subtypes. The most common indicators of visceral crisis in the Exp cohort were symptomatic brain metastases (33.3%), malignant hypercalcemia (28.6%), and liver metastases with hepatic tests abnormalities (23.8%). OMD at presentation (35.1% vs 36.8%, p=0.83) and disease-related serious clinical events during 1st month (31.1% vs 37.3%, p=0.42) and between 1-12 months (31.9% vs 34.2%, p=0.77) did not differ between cohorts. Conclusion: Our study reports a more clinically severe presentation of ABC during the pandemic compared to historical control. This emerged particularly in recurrences and in more aggressive disease subtypes such as HER2+ and TNBC, suggesting a later diagnosis of ABC during the pandemic. These findings require validation in a larger sample, and longer follow-up is needed to assess survival impact. Table 1. Baseline clinicopathologic characteristics at diagnosis of advanced breast cancer (missing values: 1 for menopausal status, 21 for grade). Citation Format: Diogo Martins-Branco, Véronique Debien, Michel Moreau, Giovanna Pinna, Ottavia Amato, François Cherifi, Guilherme Nader-Marta, Marianne Paesmans, Evandro de Azambuja. Impact of COVID-19 Pandemic on the Disease Volume, Severity and Clinical Complications at Diagnosis and During First Year of Advanced Breast Cancer: COVID19-ABC Quasi-Experimental Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-10-11.

Abstract PO4-11-04: Early Discontinuation of Adjuvant Chemotherapy in Older Adults with Early Breast Cancer: Results from the Prospective Multicenter HOPE Study

Abstract Background: Older adults with early breast cancer (EBC) treated with adjuvant chemotherapy frequently experience severe toxicities. As a result of such toxicities, many older adults do not complete all planned chemotherapy cycles (i.e., discontinue chemotherapy early). Early discontinuation may increase the risk of recurrence and decrease survival. However, aging is heterogeneous and identifying which older adult is at risk of early discontinuation before starting chemotherapy remains a key knowledge gap. To fill this gap, we examined the incidence, reasons, and risk factors for early discontinuation of adjuvant chemotherapy in older adults with EBC. Methods: This is a post-hoc analysis of 501 older adults (age&amp;gt;65) with EBC enrolled in the Hurria Older PatiEnts (HOPE) with Breast Cancer Study (NCT01472094, R01AG037037), a prospective multicenter study. All participants were treated with neo/adjuvant chemotherapy. Prior to initiating chemotherapy, participants completed survey measures on sociodemographic, clinical, and geriatric assessment characteristics. The primary outcome was early discontinuation (yes/no; yes, defined as failure to complete all planned chemotherapy cycles). Multivariable logistic regression with stepwise selection was used to evaluate the association between baseline variables (demographic, clinical, geriatric assessment) and early discontinuation. Results: A total of 501 participants (median [range] age, 70 [65-86] years and mean [SD] physician-rated KPS 93 [9.3]) were included. One hundred and thirteen (23%) had early discontinuation. Among participants with early discontinuation, 69% discontinued treatment within the last 3 cycles. In bivariate analysis, early discontinuation was associated with older age (continuous), higher stage (II/III), use of non-TC regimens (anthracycline-based or trastuzumab-based), lower albumin level (continuous), a history of diabetes, ≥1 fall in the last 6 months, and lower activities of daily living (ADL) score (&amp;lt; 85). Multivariable stepwise logistic regression analysis identified that ≥1 fall in the last 6 months, ADL score &amp;lt; 85, and regimen were associated with early discontinuation at p &amp;lt; 0.05. In the final model, after accounting for clinically meaningful variables including age, stage, and regimen, the results for falls (odds ratio [OR] = 2.04, 95% CI: 1.10-3.78, p=0.02) and ADL (OR=2.10, 95% CI: 1.32-3.34, p=0.002) remained highly significant. Compared to participants with no falls and ADL scores &amp;gt;85, participants with who reported both falls and an ADL score &amp;lt; 85 prior to initiation of chemotherapy had more than 4-fold increased odds of early discontinuation (Table). Conclusion: In this cohort of older adults with EBC, nearly 1 in 4 older patients initiated neo/adjuvant chemotherapy but did not complete all planned chemotherapy cycles. Older patients at risk for early discontinuation should be identified and targeted upfront before initiating chemotherapy. Table. Multivariable associations between falls, ADL score, and early discontinuation. *Adjusted for age (continuous), stage (I vs. II/III), and regimen (anthracycline based + no trastuzumab vs. non-anthracycline based + no trastuzumab vs. anthracycline based + trastuzumab vs. platinum/CMF + trastuzumab vs. taxol only + trastuzumab vs. other). ** Five patients missing fall information. Two patients missing ADL score. Citation Format: Jingran Ji, Canlan Sun, Rachel Freedman, Harvey Cohen, Heidi Klepin, William Tew, Beverly Moy, Andrew Chapman, Tanya Wildes, Efrat Dotan, Allison Magnuson, Tracey O'Connor, Mary Anne Fenton, Heeyoung Kim, Vani Katheria, Cary Gross, Hyman Muss, Mina Sedrak. Early Discontinuation of Adjuvant Chemotherapy in Older Adults with Early Breast Cancer: Results from the Prospective Multicenter HOPE Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-11-04.

Mitral Geometry on the Mechanism of Left Ventricular Outflow Tract Obstruction in Hypertrophic Cardiomyopathy

The mechanism of left ventricular outflow tract obstruction (LVOTO) is complex in hypertrophic cardiomyopathy (HCM). We aimed to evaluate the impact of mitral valve geometry on LVOTO by echocardiography. The study population comprised 177 consecutive patients with HCM. Morphological findings of left ventricular hypertrophy and LVOTO-related abnormalities were assessed by comprehensive transthoracic echocardiography. Aortomitral angle, mitral leaflet length, and coaptation height were measured and analyzed at rest. Multivariable stepwise forward logistic regression analysis was performed to identify geometric predictors of LVOTO. One hundred thirty-seven patients had an LVOT gradient ≥30mm Hg. Multivariable logistic regression showed that aortomitral angle (odds ratio [OR], 0.89; 95% CI, 0.83-0.95, P<.001), coaptation height (OR, 1.96; 95% CI, 1.41-2.72, P<.001), and accessory mitral valve chordae tendineae (OR, 13.1; 95% CI, 4.32-39.95; P<.001) were independently associated with LVOTO. Receiver operating characteristic analysis showed that the area under the curve of mitral coaptation height was higher (area under the curve=0.815) than the other 2 indicators (P<.05). Mitral coaptation height, aortomitral angle, and accessory mitral valve chordae tendineae were important predictors of SAM and LVOTO in HCM independent of septal hypertrophy.

Assessing the reliability and accuracy of sex estimation models utilizing sternal morphometry derived from computed tomography in the Ghanaian population

Sex estimation models are specific to populations and cannot be generalized due to genetic and environmental variabilities. This retrospective cross-sectional study, conducted between January and September 2023 at the Tamale Teaching Hospital, included 119 (50.9 %) females and 115 (49.1 %) males aged 23–82 years. Measurements, including manubrium length (M), manubrium width (MW), sternal body length (B), combined manubrium and sternal body lengths (CL), corpus sterni width at first sternebrae (CSWS1), and corpus sterni width at third sternebrae (CSWS3), were obtained from Computerized Tomographic (CT) images of the sternum using DICOM Viewer, accurate to 0.1 cm. Subsequently, sternal area (SA) and sternal index (SI) were calculated. Univariable and stepwise multivariable discriminant function analysis (DFA) and logistic regression (LR) models were developed using a training sample (70 %), and cross-validation was performed on a holdout sample (30 %). Results showed that the linear measurements, excluding M, and sternal area were higher in males than females (P<0.001), while the sternal index was <50 % in males but >50 % in females (P<0.001). Univariable sex estimation accuracies, in cross-validation, ranged from 43.7 % to 92.9 % in DFA and 50.0–92.9 % in LR. For multivariable models, the accuracy ranges were 92.9–94.3 % in DFA and 91.6–93.0 % in LR. The sternal body length was the most accurate at 90.1 % in DFA and 90.2 % in LR, with lower sex bias (male-female) in LR than in DFA (-0.1 vs. 8.7). The sternum proves valuable for sex estimation, with sternal body length as the most accurate linear measurement. However, multivariable models, particularly LR, demonstrate higher accuracy compared to DFA.

A practical nomogram for predicting early death in elderly small cell lung cancer patients: A SEER-based study.

This study aimed to identify risk factors for early death in elderly small cell lung cancer (SCLC) patients and develop nomogram prediction models for all-cause and cancer-specific early death to improve patient management. Data of elderly patients diagnosed with SCLC were extracted from the SEER database, then randomly divided into training and validation cohorts. Univariate and stepwise multivariable Logistic regression analyses were performed on the training cohort to identify independent risk factors for early death in these patients. Nomograms were developed based on these factors to predict the overall risk of early death. The efficacy of the nomograms was validated using various methods, including ROC analysis, calibration curves, DCA, NRI, and IDI. Among 2077 elderly SCLC patients, 773 died within 3 months, 713 due to cancer-specific causes. Older age, higher AJCC staging, brain metastases, and lack of surgery, chemotherapy, or radiotherapy increase the risk of all-cause early death, while higher AJCC staging, brain metastases, lung metastases, and lack of surgery, chemotherapy, or radiotherapy increase the risk of cancer-specific death (P < .05). These identified factors were used to construct 2 nomograms to predict the risk of early death. The ROC indicated that the nomograms performed well in predicting both all-cause early death (AUC = 0.823 in the training cohort and AUC = 0.843 in the validation cohort) and cancer-specific early death (AUC = 0.814 in the training cohort and AUC = 0.841 in the validation cohort). The results of calibration curves, DCAs, NRI and IDI also showed that the 2 sets of nomograms had good predictive power and clinical utility and were superior to the commonly used TNM staging system. The nomogram prediction models constructed in this study can effectively assist clinicians in predicting the risk of early death in elderly SCLC patients, and can also help physicians screen patients at higher risk and develop personalized treatment plans for them.

Effect of SGLT2-Inhibitors on Polygraphic Parameters in Elderly Patients Affected by Heart Failure, Type 2 Diabetes Mellitus, and Sleep Apnea.

Obstructive sleep apneas (OSAs) and central sleep apneas (CSAs) are the most common comorbidities in Heart Failure (HF) that are strongly associated with all-cause mortality. Several therapeutic approaches have been used to treat CSA and OSA, but none have been shown to significantly improve HF prognosis. Our study evaluated the effects of a 3-months treatment with sodium-glucose cotransporter type 2 inhibitor (SGLT2i) on polygraphic parameters in patients with sleep apnea (SA) and HF, across the spectrum of ejection fraction, not treated with continuous positive air pressure (CPAP). A group of 514 consecutive elderly outpatients with HF, type 2 diabetes mellitus (T2DM) and SA, eligible for treatment with SGLT2i, were included in the investigation before starting any CPAP therapy. The two groups were compared with the t-test and Mann-Whitney test for unpaired data when appropriate. Then, a simple logistic regression model was built using 50% reduction in AHI as the dependent variable and other variables as covariates. A multivariate stepwise logistic regression model was constructed using the variables that linked with the dependent variable to calculate the odds ratio (OR) for the independent predictors associated with the reduction of 50% in AHI. The treated group experienced significant improvements in polygraphic parameters between baseline values and follow-up with reduction in AHI (28.4 ± 12.9 e/h vs. 15.2 ± 6.5 e/h; p < 0.0001), ODI (15.4 ± 3.3 e/h vs. 11.1 ± 2.6 e/h; p < 0.0001), and TC90 (14.1 ± 4.2% vs. 8.2 ± 2.0%; p < 0.0001), while mean SpO2 improved (91. 3 ± 2.3 vs. 93.8 ± 2.5); p < 0.0001. These benefits were not seen in the untreated population. The use of SGLT2i in patients suffering from HF and mixed-type SA not on CPAP therapy significantly contributes to improving polygraphic parameters.

Combined diagnosis for Parkinson's disease via gait and eye movement disorders

Background and objectivesWith the discovery of the potential role of gait and eye movement disorders in Parkinson's disease (PD) recognition, we intend to investigate the combined diagnostic value of gait and eye movement disorders for PD. MethodsWe enrolled some Chinese PD patients and healthy controls and separated them into the training and validation sets based on enrollment time. Performance in five oculomotor paradigms and in one gait paradigm was examined using an infrared eye tracking device and a wearable gait analysis device. We developed and validated a combined model for PD diagnosis via multivariate stepwise logistic regression analysis. Furthermore, subgroup comparisons and multi-model comparison were performed to assess its applicability and advantages. ResultsA total of 145 PD patients and 80 healthy controls in China were recruited. The pro-saccade velocity, the trunk-sway max, and the turn mean angular velocity were finally screened out for the model development. Incorporating age factor, the ternary model demonstrated more satisfactory performance on ROC (AUC of 0.953 in the training set and AUC of 0.972 in the validation set), calibration curve, and decision curve. A nomogram was drawn to visualize the model. The combined model outperforms individual models with a broad application and the unique diagnostic value for early detection of PD patients, especially TD-PD patients. ConclusionWe demonstrated the presence of gait and eye movement disorders, as well as the feasibility, applicability, and superiority of employing them together to diagnose PD.

Immunomodulatory Effect of COVID-19 on HLA-Antibody Profile in Renal Transplant Recipients.

Background/Objectives: The novel coronavirus disease 2019 (COVID-19) has led to significant morbidity and mortality among kidney transplant recipients. SARS-CoV-2 has been hypothesized to cause an unusual immunological dysregulation triggering alloimmunity and leading to graft rejection. Methods: This prospective observational cohort study assessed 321 kidney transplant recipients who had COVID-19 infection. After the infection, patients' sera were tested for the presence of anti-HLA de novo DSA and non-DSA specificities. Logistic regression analysis and a stepwise multivariable logistic regression analysis were used to analyze the independent risk factors associated with the development of antibodies, adjusting for known confounders. The variables evaluated were acute COVID-19 characteristics (i.e., presentation, and need for hospitalization), demographic characteristics (i.e., age, gender, and primary renal disease), clinical characteristics (i.e., various comorbidities), and post-COVID-19 sequelae. Results: Anti-HLA de novo DSA developed in 18.7% of patients, while anti-HLA class I and class II non-DSA antibodies developed de novo in 84 (26.3%) and 83 (25.9%) patients, respectively. The development of DSA, HLA-DQ, and HLA-DR antibodies was predicted by the history of graft rejection. Obesity appeared to be protective against the emergence of de novo DSA. De novo DSA and HLA-DR antibody formation was positively linked with intravenous immunoglobulin use, CMV-hyperimmune globulin use, and decreased doses of immunosuppression during acute infection. Better allograft function during the acute disease was a protective factor against the formation of HLA-DQ and HLA-DR antibodies. Positive predictors of de novo DSA development were graft biopsy and the reactivation of EBV after infection. Conclusions: These findings suggest that the SARS-CoV-2 virus has an immunomodulatory effect and may be associated with an increased mortality in this population.

Association of coagulation function with the risk of in-hospital mortality in patients with severe acute respiratory distress syndrome

BackgroundTo evaluate the association of coagulation disorder score with the risk of in-hospital mortality in acute respiratory distress syndrome (ARDS) patients. MethodsIn this cohort study, 7,001 adult patients with ARDS were identified from the Medical Information Mart for Intensive Care Database-IV (MIMIC-IV). Univariate and multivariate Logistic stepwise regression models were used to explore the associations of coagulation-associated biomarkers with the risk of in-hospital mortality in patients with ADRS. Restricted cubic spline (RCS) was plotted to explore the association between coagulation disorder score and in-hospital mortality of ARDS patients. ResultsThe follow-up time for in-hospital death was 7.15 (4.62, 13.88) days. There were 1,187 patients died and 5,814 people survived in hospital. After adjusting for confounding factors, increased risk of in-hospital mortality in ARDS patients was observed in those with median coagulation disorder score [odds ratio (OR) = 1.22, 95% confidence interval (CI): 1.01–1.47) and high coagulation disorder score (OR = 1.38, 95% CI: 1.06–1.80). The results of RCS indicated that when the coagulation disorder score >2, the trend of in-hospital mortality rose gradually, and OR was >1. ConclusionsPoor coagulation function was associated with increased risk of in-hospital mortality in ARDS patients. The findings implied that clinicians should regularly detect the levels of coagulation-associated biomarkers for the management of ARDS patients.

Association between Blood Parameters of Nutritional Status and Functional Status in Extreme Longevity.

The relationship between functional and nutritional status in the geriatric population remains an issue of debate and there is a gap in the knowledge regarding this field in long-lived individuals. The main aim of this study was to assess the association between selected blood parameters of nutritional status and functional status in extreme longevity. The inclusion criteria were centenarians above 100 years of age who were examined at their homes, and blood samples were collected. The study group consisted of 170 individuals (25 men and 145 women, median age 100.75 years [100.29-101.58]). Total protein and albumin serum concentration was significantly lower in long-lived individuals with severe functional decline compared to individuals with preserved functional status, p = 0.000001 and p = 0.0000, respectively. Iron serum level was significantly higher in the group with preserved functional status, p = 0.04. Preserved functional status was positively correlated with total protein serum concentration (p = 0.000), albumin concentration (p = 0.000), and iron serum level (p = 0.029). A negative correlation was stated between c-reactive protein (CRP) and functional status (p = 0.032). Univariable logistic regression analysis showed that the functional status of long-lived individuals depends on total protein (OR 2.89, CI 95% [1.67-5.0]) and albumin concentrations (OR 2.34, CI 95% [1.39-3.92]). Multivariable backward stepwise logistic regression analysis showed that a total protein concentration was the only variable independently related to the preserved functional status (OR 3.2, 95% Cl [1.8-5.67]). In long-lived individuals, the total serum protein and albumin levels are lower in centenarians with severe functional decline, and they correlate with functional status. Total protein serum concentration is the only factor independently related to the preserved functional status in extreme longevity.

Rising Cardiovascular Mortality Despite Increased Resource Utilization: Insights From the Nationwide Inpatient Sample Database.

Introduction The global burden of cardiovascular disease (CVD) has risen over the past decade, potentially escalating resource utilization, morbidity, and mortality. We analyzed trends in hospitalization for CVDs, outcomes of hospitalizations, and the impact of the COVID-19 pandemic on CVDhospitalizations between 2016 and 2020. Methods Adult CVD hospitalizations recorded in the2016-2020 nationwide inpatient sample (NIS) were identified using major diagnostic categories (MDC- class 5). The NIS is the largest all-payer repository of all hospitalizations in the USA within a calendar year. We compared sociodemographic factors andoutcomes (mortality, length of stay, and hospital charges) of CVD hospitalization before and during the pandemic using Pearson's χ2 tests.We used Stata ranking commands and ICD-10 (10th revision of the International Statistical Classification of Diseases and Related Health Problems) codes to identify the most recurring diagnoses associated with CVD mortality during the study period.Trends in mortality and resource use were assessed using theJonckheere-Terpstra trend test. Hospital charges wereadjusted for inflationusing the Medical Expenditure Panel Survey index. We used stepwise multivariate logistic regression analyses(P ≤ 0.05 for entry; P > 0.10 for removal) to identify covariates associated with cardiovascular mortality during the study period. Results Hospitalizations for CVDs rose from 4,283,502 in 2016 to 4,635,246 in 2019 (Ptrend< 0.001) and declined to 3,865,399 in 2020. 452,930 mortalities were recorded during the study period. In-hospital mortality rose from 111,090 (2.6%) in 2016 to 118,825 (2.8%) in 2020 (Ptrend< 0.001). Compared with the prepandemic years, mortality rates were higher during the pandemic (108,231 [2.8%] vs. 445,373 [2.5%]; P<0.001), and increased in hospitalizations for hypertensive heart disease with chronic kidney disease (CKD) (15,585[14.4%] vs. 45,873 [10.3%]; P<0.001), hypertensive heart disease with heart failure (7,468 [6.9%] vs. 21,378 [4.8%]), ventricular tachycardia (2,056 [1.9%] vs. 7,571 [1.7%]; P=0.022), and peripheral angiopathy with gangrene (1,191 [1.1%] vs. 3,118 [0.7%]; P<0.001). CVD hospitalizations totaled 80.3 million hospital days and 39.7 million hospital procedures during the period. The mean number of procedures (3 vs. 2) and mean length of hospital stay (5.6 vs. 4.5 days) increased during the pandemic (P<0.001). The mean hospital cost for CVD increased from US$ 69,394 in 2016 to US$ 89,728 in 2020 (Ptrend< 0.001). Conclusion CVD mortality increased despite increased resource use over the study period. Hospitalizations during the pandemic had poorer mortality and resource use outcomes than those in the preceding years.

Prediction of false-positive PI-RADS 5 lesions on prostate multiparametric MRI: development and internal validation of a clinical-radiological characteristics based nomogram

BackgroundTo develop a risk model including clinical and radiological characteristics to predict false-positive The Prostate Imaging Reporting and Data System (PI-RADS) 5 lesions.MethodsData of 612 biopsy-naïve patients who had undergone multiparametric magnetic resonance imaging (mpMRI) before prostate biopsy were collected. Clinical variables and radiological variables on mpMRI were adopted. Lesions were divided into the training and validation cohort randomly. Stepwise multivariate logistic regression analysis with backward elimination was performed to screen out variables with significant difference. A diagnostic nomogram was developed in the training cohort and further validated in the validation cohort. Calibration curve and receiver operating characteristic (ROC) analysis were also performed.Results296 PI-RADS 5 lesions in 294 patients were randomly divided into the training and validation cohort (208 : 88). 132 and 56 lesions were confirmed to be clinically significant prostate cancer in the training and validation cohort respectively. The diagnostic nomogram was developed based on prostate specific antigen density, the maximum diameter of lesion, zonality of lesion, apparent diffusion coefficient minimum value and apparent diffusion coefficient minimum value ratio. The C-index of the model was 0.821 in the training cohort and 0.871 in the validation cohort. The calibration curve showed good agreement between the estimation and observation in the two cohorts. When the optimal cutoff values of ROC were 0.288 in the validation cohort, the sensitivity, specificity, PPV, and NPV were 90.6%, 67.9%, 61.7%, and 92.7% in the validation cohort, potentially avoiding 9.7% unnecessary prostate biopsies.ConclusionsWe developed and validated a diagnostic nomogram by including 5 factors. False positive PI-RADS 5 lesions could be distinguished from clinically significant ones, thus avoiding unnecessary prostate biopsy.

18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging of pediatric neuroblastoma: a multi-omics parameters method to predict MYCN copy number category.

The MYCN copy number category is closely related to the prognosis of neuroblastoma (NB). Therefore, this study aimed to assess the predictive ability of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomic features for MYCN copy number in NB. A retrospective analysis was performed on 104 pediatric patients with NB that had been confirmed by pathology. To develop the Bio-omics model (B-model), which incorporated clinical and biological aspects, PET/CT radiographic features, PET quantitative parameters, and significant features with multivariable stepwise logistic regression were preserved. Important radiomics features were identified through least absolute shrinkage and selection operator (LASSO) and univariable analysis. On the basis of radiomics features obtained from PET and CT scans, the radiomics model (R-model) was developed. The significant bio-omics and radiomics features were combined to establish a Multi-omics model (M-model). The above 3 models were established to differentiate MYCN wild from MYCN gain and MYCN amplification (MNA). The calibration curve and receiver operating characteristic (ROC) curve analyses were performed to verify the prediction performance. Post hoc analysis was conducted to compare whether the constructed M-model can distinguish MYCN gain from MNA. The M-model showed excellent predictive performance in differentiating MYCN wild from MYCN gain and MNA, which was better than that of the B-model and R-model [area under the curve (AUC) 0.83, 95% confidence interval (CI): 0.74-0.92 vs. 0.81, 95% CI: 0.72-0.90 and 0.79, 95% CI: 0.69-0.89]. The calibration curve showed that the M-model had the highest reliability. Post hoc analysis revealed the great potential of the M-model in differentiating MYCN gain from MNA (AUC 0.95, 95% CI: 0.89-1). The M-model model based on bio-omics and radiomics features is an effective tool to distinguish MYCN copy number category in pediatric patients with NB.

Centrally Distributed Adiposity as a Modifiable Risk Factor for Fecal Incontinence: United States Population-based Analysis

Fecal incontinence (FI) is highly prevalent with substantial impacts on quality of life and health care utilization. The impact of obesity on FI remains unclear, with differing conclusions using body mass index (BMI) as a risk factor. We aimed to determine the association between obesity and FI, and whether this relationship is dependent on the distribution of adiposity (waist circumference-to-height ratio [WHtR]). This was a population-based analysis of the National Health and Nutrition Examination Survey, including participants who responded to the bowel health survey in 2005 to 2010. FI was defined by the accidental bowel leakage of solid stool, liquid, or mucus at least once in the past month. Stepwise multivariable logistic regression models were constructed to assess risk factors for FI. A total of 7606 participants were included, with an overall FI prevalence of 9.2%. When stratified by quartiles of body measurements, FI was increasingly prevalent from the 1st to the 4th quartile for both WHtR (range, 5.3%-12.5%) and BMI (range, 7.1%-10.5%). WHtR was associated with FI and was a stronger predictor than BMI in all quartiles of body measurement. On multivariable analysis, WHtR remained a significant predictor of FI comparing the 4th with the 1st quartile of body measurements (odds ratio [OR], 1.77; 95% confidence interval [CI], 1.11-2.80; P= .017), whereas BMI was not. A WHtR cutoff of >0.592 optimized the Youden index in prediction of FI in the overall sample. WHtR was independently associated with increased odds of FI in this nationally representative sample of United States adults, whereas BMI was not consistently correlated. This suggests bowel continence may depend more on how body mass is distributed.

Predictive factors of thoracic aortic calcification in patients candidate for cardiac surgery

BackgroundThe presence of the severe thoracic aortic calcification (TAC) in cardiac surgery patients is associated with adverse post-operative outcome. However, the relationship between cardiovascular risk factors and aortic plaque burden remains unknown. The objective of this study was to determine the predictive factors of TAC in patients candidate for cardiac surgery.MethodsPatients who underwent thoracic CT scan prior to cardiac surgery between August 2020 to April 2021 were included. Of 556 patients, 209 (36.7%) had a thoracic aortic calcium score (TACS) ≥ 400 mm [3] and were compare with the remaining patients. Predictors of severe TAC were assessed through stepwise multivariable logistic regression analysis.ResultsThe patients with TACS ≥ 400 had a higher mean age (67.3 ± 7.1 vs. 55.7 ± 10.6; p < 0.001) with a higher frequency of diabetes mellitus (40.7% vs. 30.8%; p = 0.018), dyslipidemia (49.8% vs. 38.6%; p = 0.010), hypertension (60.8% vs. 44.7%; p < 0.001), opium addiction (18.2% vs. 11.2%; p = 0.023), peripheral vascular disease (PVD) (7.7% vs. 2.3%; p = 0.005) as compared with TACS < 400. The multiple determinants of TAC were PVD (OR = 2.86) followed by opium addiction, diabetes and age.ConclusionsThoracic CT scan prior to cardiac surgery for patients with older age, diabetes, opium addiction and PVD is recommended. Our study could serve as a foundation for future research endeavors aimed at establishing a risk score for TAC.

Development of hypertension models for lung cancer screening cohorts using clinical and thoracic aorta imaging factors

This study aims to develop and validate nomogram models utilizing clinical and thoracic aorta imaging factors to assess the risk of hypertension for lung cancer screening cohorts. We included 804 patients and collected baseline clinical data, biochemical indicators, coexisting conditions, and thoracic aorta factors. Patients were randomly divided into a training set (70%) and a validation set (30%). In the training set, variance, t-test/Mann–Whitney U-test and standard least absolute shrinkage and selection operator were used to select thoracic aorta imaging features for constructing the AIScore. Multivariate logistic backward stepwise regression was utilized to analyze the influencing factors of hypertension. Five prediction models (named AIMeasure model, BasicClinical model, TotalClinical model, AIBasicClinical model, AITotalClinical model) were constructed for practical clinical use, tailored to different data scenarios. Additionally, the performance of the models was evaluated using receiver operating characteristic (ROC) curves, calibration curves and decision curve analyses (DCA). The areas under the ROC curve for the five models were 0.73, 0.77, 0.83, 0.78, 0.84 in the training set, and 0.77, 0.78, 0.81, 0.78, 0.82 in the validation set, respectively. Furthermore, the calibration curves and DCAs of both sets performed well on accuracy and clinical practicality. The nomogram models for hypertension risk prediction demonstrate good predictive capability and clinical utility. These models can serve as effective tools for assessing hypertension risk, enabling timely non-pharmacological interventions to preempt or delay the future onset of hypertension.