Multivariate Stepwise Logistic Regression Analysis Research Articles

Abstract 9495: Prognostic Value of Machine Learning on Clinical Parameters for Cardiac Prognosis in Patinets with Acute Congestive Heart Failure

Introduction: Congestive heart failure (CHF) in acute phase, many clinical fundamental parameters including vital sign, laboratory data, or initial treatment were investigated, and we can roughly estimate the prognosis with the parameters. However, machine learning method for prediction of the prognosis is still challenging. Hypothesis: Machine learning methods have higher performance for predicting cardiac prognosis in patients with CHF than conventional statistical model. Methods: We enrolled consecutive 300 patients with CHF (79.5±12.1 years, 158 Males). Patients with acute coronary syndrome, mechanical circulatory support cases, and cardio-pulmonary arrest cases were excluded. Objective variable was set as cardiac death in one year. First, multivariate stepwise logistic regression analysis with Akaike’s information criterion (AIC) was performed, and extracted parameters which had the most versatile predictive value. Propensity score (PS) was calculated with the extracted parameters, and the prediction model constructed by cut-off value of ROC curve analysis of PS. Next, machine learning (random forest method and deep learning) to build predictive model was performed with the predictors. Finally, accuracy of each predictive model was compared. Results: Thirty cases showed cardiac death in one year. Logistic regression with AIC extracted 8 predictors, and the cut off-value of propensity score with the 8 parameters was 0.110. The accuracy was 0.714 and area under ROC (AUROC) was 0.836. Conversely, random forest method demonstrated the accuracy as 0.927, AUROC 0.860. On deep learning, the accuracy was 0.937 and AUROC 0.901.The top 4 high feature importance of random forest were Cl/red blood cell count/pH/Anion Gap. However, accuracy of those predictors was lower than that of machine learning. Conclusions: Machine learning was a powerful tool to predict cardiac prognosis of CHF, comparing with conventional statistical model.

Clinical factors predictive of appropriate treatment in COPD: a community hospital setting

Background: Chronic obstructive pulmonary disease (COPD) is a common respiratory disease. The appropriate treatment according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guideline was 19-60%. However, there are limited data on predictors of appropriate treatment in patients with COPD. This study aimed to evaluate risk factors of appropriate treatment in patients with COPD according to the GOLD guideline in a real-world community setting. Methods: This is a retrospective study conducted at a community hospital. Inclusion criteria were adult patients diagnosed as COPD treated at a COPD clinic. The primary outcome was the appropriate treatment, defined by correct pharmacological treatment by the GOLD guideline according to the ABCD severity assessment. Clinical predictors of appropriate treatment were executed by stepwise multivariate logistic regression analysis. Results: 136 patients with COPD met the study criteria. Of those, 100 patients had inappropriate treatment according to the GOLD guideline. Three factors were independently associated with the appropriate treatment including number of admissions, modified Medical Research Council (mMRC) score, and CAT score. These factors had adjusted odds ratio of 3.11, 2.86, and 1.26, respectively. Causes of inappropriate treatment were unavailability of long-acting muscarinic antagonist (LAMA) (51 patients; 79.69%), treated by inhaled corticosteroid (ICS) alone (12 patients; 18.75%), and treated with only bronchodilator (1 patient; 1.56%). Conclusions: Appropriate COPD patients’ treatment according to the GOLD guideline was 26.47% in community setting. Factors associated with severity of COPD were associated with prescribing appropriate treatments.

Predictors of Comorbid Anxiety Symptoms After a New Diagnosis of Epilepsy: A Prospective 12-Month Follow-Up Observation.

Objectives: We aimed to identify the factors contributing to comorbid anxiety symptoms over a 12-month follow-up period in Chinese adults with newly diagnosed epilepsy.Methods: Adult patients with newly diagnosed epilepsy (PWNDE) were recruited from First Hospital, Jilin University. Anxiety symptoms were assessed using the Generalized Anxiety Disorder-7 questionnaire (GAD-7; Chinese version) at 12 months. Multivariate stepwise logistic regression analysis was employed to identify the predictors for anxiety symptoms at 12 months.Results: A total of 157 PWNDE completed the study and were included in the final analysis. The percentage of participants with anxiety symptoms significantly decreased from 31.2% at baseline to 23.6% at 12 months (p = 0.027). Multivariate stepwise logistic regression analysis indicated that depressive symptoms at baseline [odds ratio (OR) 3.877 (95% confidence interval (CI) 1.683–8.933); P = 0.001] and the number of antiseizure medications (ASMs) during the follow-up period [OR 2.814 (95% CI 1.365–5.803); P = 0.005] were independent factors contributing to comorbid anxiety symptoms at 12 months.Conclusion: Depressive symptoms at baseline and the number of ASMs during the follow-up period were significant predictors of comorbid anxiety symptoms 12 months after a diagnosis of epilepsy.

Risk Factors for Ischaemic Stroke in an Omani Community: A case-control study.

ObjectivesStroke is recognised as the third most common cause of mortality and it has an increasing incidence in developing countries. Recognition and control of risk factors are of prime importance in the prevention of stroke. This study aimed to examine the characteristics of ischaemic stroke (IS) patients in Oman and quantify its various risk factors using a case-control model.MethodsThis case-control study was conducted from January 2012 to March 2013 at Sultan Qaboos University Hospital and Royal Hospital, Muscat. Adult Omani patients with IS who were admitted to either hospital were compared to age- and gender-matched controls. Demographic factors and frequency of various conventional risk factors were documented. Univariate and stepwise multivariate logistic regression analyses were performed to evaluate the risk factors associated with IS.ResultsA total of 255 patients and age-and gender-matched controls were included in this study. The mean age was 62.2 ± 13.2 years and 63.14% were male. Most cases (89.02%) were above 45 years of age. Cardio-embolism (31.76%) was the commonest mechanism of IS. Stepwise multiple logistic regression model revealed that family history of stroke was the strongest independent risk factor, followed by hypertension and high-density lipoprotein levels (odds ratio: 10.10, 5.17 and 3.34, respectively; P <0.01 each).ConclusionCardio-embolism was the predominant mechanism of IS in this study. Family history of stroke, hypertension and reduced high-density lipoprotein were the leading independent risk factors. Strong emphasis on screening for risk factors, control of hypertension and lifestyle modification for those with a family history of stroke would be expected to emerge as the major stroke-preventive measures in Oman.

Cohort study on the prognosis of acute cerebral infarction in different circulatory systems at 1-year follow-up

BackgroundTo evaluate the prognosis of acute cerebral infarction at 1-year follow-up in different circulation infarctions.MethodsClinical data of 858 consecutive patients with acute cerebral infarction were collected. Of the 858 cases, 21 (2.45%) were lost to follow-up and 837 completed follow-up and thus were enrolled in this study. At 1-year follow-up, death or moderate-to-severe dysfunction (modified Rankin Scale (mRS) ≥ 3 points) was regarded as the poor prognostic endpoint. Univariate analysis and multivariate logistic stepwise regression analysis were performed to assess the prognosis. The prediction probability of indicators was obtained for the multivariate model, and the receiver operating characteristic curve was delineated to calculate the area under the curve (AUC) to predict the fitness of the model.ResultsThe older the age, the greater the probability of a poor prognosis. Patients with previous diabetes and cerebral infarction had a poor prognosis. The higher the National Institutes of Health Stroke Scale and mRS scores and the lower the Barthel index at admission, the worse the prognosis of the patients. The longer the hospital stay, the worse the prognosis of the patients. The prognosis of different circulation infarctions was different. The AUC of the multivariate model was AUC = 0.893, and the 95% confidence interval was 0.870–0.913, indicating a good fit. The prognosis of anterior circulation infarction (ACI) was worse than that of posterior circulation infarction (PCI) (P < 0.05). The prognosis of patients with ACI and PCI was not significantly different from that of patients with ACI or PCI alone (P > 0.05).ConclusionsDiabetes, the Barthel index at admission and previous cerebral infarction are poor prognostic factors of acute cerebral infarction. The prognosis of ACI is worse than that of PCI. Different factors affect the prognosis of different circulatory system infarctions.

Predictors of long-term clinical response in patients with non-radiographic axial spondyloarthritis receiving certolizumab pegol

BackgroundIdentification of predictive clinical factors of long-term treatment response may contribute to improved management of non-radiographic axSpA (nr-axSpA) patients. This analysis aims to identify whether any baseline characteristics or Week 12 clinical outcomes in nr-axSpA patients with elevated C-reactive protein (CRP) and/or sacroiliitis on magnetic resonance imaging (MRI) enrolled in the C-axSpAnd study are predictive of achieving clinical response after 1 year of certolizumab pegol (CZP).MethodsC-axSpAnd (NCT02552212) was a phase 3, multicentre study, including a 52-Week double-blind, placebo-controlled period. Enrolled patients were randomised to CZP 200 mg Q2W or placebo. Predictors of Week 12 (CZP group only) and Week 52 clinical response were identified using a multivariate stepwise logistic regression analysis. Response variables included Ankylosing Spondylitis Disease Activity Score major improvement (ASDAS-MI), Assessment of SpondyloArthritis International Society 40% response (ASAS40), Bath Ankylosing Spondylitis Disease Activity Index 50% response (BASDAI50) and ASDAS inactive disease (ASDAS-ID). Predictive factors assessed included demographic and baseline characteristics and clinical outcomes at Week 12. A p-value <0.05 was required for forward selection into the model and p ≥0.1 for backward elimination. Missing data or values collected after switching to open-label treatment were accounted for using non-responder imputation. Sensitivity analyses accounted for patients with changes in non-biologic background medication.ResultsOf 317 enrolled patients, 159 and 158 were randomised to CZP and placebo, respectively. Younger age and male sex were identified as predictors of Week 12 response across all assessed efficacy outcomes in CZP-treated patients. Consistent predictors of Week 52 response, measured by ASDAS-MI, ASAS40 and BASDAI50, included human leukocyte antigen (HLA)-B27 positivity and sacroiliitis on MRI at baseline. MRI positivity was also predictive of achieving ASDAS-ID at Week 52. Sensitivity analyses were generally consistent with the primary analysis. In placebo-treated patients, no meaningful predictors of Week 52 response were identified.ConclusionsIn this 52-Week, placebo-controlled study in nr-axSpA patients with elevated CRP and/or active sacroiliitis on MRI at baseline, MRI sacroiliitis and HLA-B27 positivity, but not elevated CRP or responses at Week 12, were predictive of long-term clinical response to CZP. Findings may support rheumatologists to identify patients suitable for TNFi treatment.Trial registrationClinicalTrials.gov, NCT02552212. Registered on 15 September 2015

Outcomes for Cosmetic and Reconstructive Surgeries of the Periorbital Complex from the “Tracking Operations and Outcomes for Plastic Surgeons” Database

GOALS/PURPOSE: Eyelid surgery for both aesthetic and reconstructive purposes are common plastic surgery procedures. However, there is a paucity of data from multi-institutional studies with large sample sizes. The purpose of this study was to utilize a national database and perform a comprehensive analysis of surgical outcomes for blepharoplasty. METHODS/MATERIALS: This is a retrospective cohort review from 2003 to 2018 using the Tracking Operations and Outcomes for Plastic Surgeons database. The dataset was evaluated using Current Procedural Terminology codes for blepharoplasties and its related procedures (15820, 15821, 15822, 15823). These codes correspond to lower eyelid blepharoplasty, lower with extensive herniated fat pad, upper eyelid blepharoplasty, and upper with excessive skin weighting down. The core groups analyzed are those with upper, lower, or combined blepharoplasties. Categorical variables are described as frequencies and compared with Fisher exact or Pearson chi-squared test. Continuous variables, based on normality, are described as means (SD) or medians (IQR) and compared with Student T or Wilcoxon Rank-sum test, respectively. A stepwise backward multivariate logistic regression analysis was performed to assess the effect size of risk factors for adverse events with a P value set at 0.05 for significance. RESULTS/COMPLICATIONS: A total of 20,275 eyelid procedures were included. Mean age was 54.7 years (SD 12.26), female rate was 86.2% (17,466), and mean BMI was 24.77 (SD 5.65). In demographics and comorbidities, 68.4% were Whites, followed by Asians (8.7%), diabetes rate was 2.9%, and 5.9% were smokers. We analyzed 15,720 (77.5%) upper and 13,359 (65.9%) lower eyelids; of those, 8804 (43.4%) were combined. The complication rate was 2.47% for upper, 3.97% for lower eyelid, and 4.68% for combined. Comparing combined blepharoplasties to single eyelid, there was a statistically significant higher rate of hematoma (P < 0.001) eyelid malposition/asymmetry (P = 0.004) and chemosis (P < 0.001) in the combined group. For lower eyelid blepharoplasty, ectropion was more common compared with combined (P < 0.001). On the multivariate regression analysis, combined blepharoplasty (OR 1.49 95%CI 1.08–2.08; P = 0.01), performing over three procedures at the same case (OR 1.80 95%CI 1.34–2.41; P < 0.001), and Hispanic ethnicity (OR 3.1 95%CI 1.17–8.21; P = 0.02) were associated with a higher likelihood to have complications. However, being a non-tobacco smoker (OR 0.56 95%CI 0.36-–0.86; P = 0.009) lowers that probability by 44%. CONCLUSIONS: The results from this study provide insight into the national complication rate for blepharoplasty to be up to 4%, with hematoma and return to the OR as the most common. Risk factors identified for developing complications are performing a combined upper and lower blepharoplasty, having over three procedures at the same time and being of Hispanic ethnicity, while no history of smoking was associated with a decreased probability for morbidity.

Establishment of Routine Clinical Indicators-Based Nomograms for Predicting the Mortality in Patients With COVID-19.

This study aimed to establish and validate the nomograms to predict the mortality risk of patients with coronavirus disease 2019 (COVID-19) using routine clinical indicators. This retrospective study included a development cohort enrolled 2,119 hospitalized patients with COVID-19 and a validation cohort included 1,504 patients with COVID-19. The demographics, clinical manifestations, vital signs, and laboratory tests of the patients at admission and outcome of in-hospital death were recorded. The independent factors associated with death were identified by a forward stepwise multivariate logistic regression analysis and used to construct the two prognostic nomograms. The nomogram 1 was a full model to include nine factors identified in the multivariate logistic regression and nomogram 2 was built by selecting four factors from nine to perform as a reduced model. The nomogram 1 and nomogram 2 showed better performance in discrimination and calibration than the Multilobular infiltration, hypo-Lymphocytosis, Bacterial coinfection, Smoking history, hyper-Tension and Age (MuLBSTA) score in training. In validation, nomogram 1 performed better than nomogram 2 for calibration. We recommend the application of nomogram 1 in general hospitals which provide robust prognostic performance though more cumbersome; nomogram 2 in the out-patient, emergency department, and mobile cabin hospitals, which depend on less laboratory examinations to make the assessment more convenient. Both the nomograms can help the clinicians to identify the patients at risk of death with routine clinical indicators at admission, which may reduce the overall mortality of COVID-19.

Noninvasive prediction of late potentials in the signal-averaged ECG in patients with chronic Chagas disease

IntroductionConsidering the importance of ventricular arrhythmias in the prediction of sudden cardiac death in chronic Chagas heart disease, the aim of the present study was to associate late potentials observed in the signal-averaged electrocardiogram (SAECG) with either non-sustained ventricular tachycardia in the 24-hour Holter monitoring or reduced left ventricular ejection fraction in the 2-dimension echocardiogram. MethodsThis was a retrospective transversal study. The medical charts of 49 patients with chronic Chagas heart disease that underwent 24-hour Holter monitoring at our institution from September 2012 to December 2015 were reviewed. In the univariate analysis, variables associated with SAECG at a p value <0.05 were entered a multivariate stepwise logistic regression analysis through the model forward. A p value <0.05 was considered to have statistical significance. ResultsIn the univariate analysis, right bundle branch block, left atrial diameter, left ventricular systolic diameter, and left ventricular ejection fraction were associated with late potential in the SAECG. In the multivariate analysis, however, right bundle branch block and left atrial diameter were retained as independent predictors of late potentials in the SAECG. ConclusionsNeither ventricular arrhythmias in the 24-Holter monitoring nor reduced left ventricular ejection fraction in the 2-D echocardiogram were associated with late potentials in the SAECG of patients with chronic Chagas heart disease.

Factors associated with the appropriate use of asthma medications among adult asthmatic patients attending asthma clinic in a teaching hospital.

Introductionasthma tends to be more severe with worse symptoms in Africa due to late diagnosis and delayed initiation of treatment. To identify patient and treatment-related factors which influence the appropriate use of asthma medications.Methodsthe study was institution based cross-sectional design. Patients were invited to provide information regarding the use of their asthma medications and factors potentially associated with appropriate use of these medications. A stepwise multivariate logistic regression analysis was used to evaluate the most important factor at a 0.05 level of significance.Resultsrespondents with better knowledge of their asthma medications were more likely to use them appropriately (OR 5.82 [CI 95% 2.25-15.04]) as were those with positive attitudes and beliefs towards asthma and asthma medications (OR 3.88 [CI 95% 1.44-10.44]).Conclusionpatients need to understand the importance of adhering to the prescribed regimen for their asthma medications even in the absence of overt symptoms in order to optimize clinical outcome.

425Artificial Intelligence Approaches to Type 2 Diabetes Risk Prediction and Exploration of Predictive Factors

Abstract Background Major barriers exist in incorporating artificial intelligence into epidemiology, particularly in data interpretation. Thus, we examined the application of highly interpretable machine-learning methods— Random Forest (RF) and Sparse Logistic Regression (SLR)— to a large-scale health check-up dataset, examining the advantages of creating prediction models using these. Methods This study involved 392,791 participants who underwent healthcare checkups in Japan from 1999 to 2018. Participants who received diabetes treatment, or had an HbA1c level of 6.5% or higher, were excluded. The objective variable examined was type 2 diabetes onset over five years. Each prediction model was created using 26 health status items over three consecutive years. We examined three analytical methods to compare their predictive powers: RF, SLR, and a multivariate stepwise logistic regression (MSLR) as a conventional method. Variable Importance (VI) was calculated in the RF analysis, with Standard Regression Coefficients (SRC) being calculated in the SLR and MSLR analyses. Results Predictive accuracy is highest in the SLR model (AUC:0.955), followed by the RF model (AUC:0.949), and then the MSLR model (AUC:0.939). The RF model measures blood glucose, HbA1c, height, red blood cells, and aspartate transaminase with a higher predictive power. In the SLR model, HbA1c, blood glucose, systolic blood pressure, HDL-Cholesterol, and age have higher SRC. Conclusions Machine learning techniques enable more accurate diabetes risk predictions than existing methods and suggest new ways of identifying associated predictors. Key messages Applying machine-learning methods to health check-up data achieves a high accuracy in predicting type 2 diabetes while maintaining data interpretability.

Guided Bone Regeneration with Concentrated Growth Factor Enriched Bone Graft Matrix (Sticky Bone) vs. Bone-Shell Technique in Horizontal Ridge Augmentation: A Retrospective Study.

Background: The purpose of this study was to compare clinical results of two different horizontal ridge augmentation techniques: guided bone regeneration with sticky bone (SB) and the bone-shell technique (BS). Methods: Records of patients who underwent horizontal ridge augmentation with SB (test) and BS (control) were screened for inclusion. Pre-operative and 6-month post-operative ridge widths were measured on cone beam computer tomography (CBCT) and compared. Post-operative complications and implant survival rate were recorded. Results: Eighty consecutive patients were included in the present study. Post-operative complications (flap dehiscence, and graft infection) occurred in ten patients, who dropped out from the study (12.5% complication rate). Stepwise multivariate logistic regression analysis showed a significant inverse correlation between the occurrence of post-operative complications and ridge width (p = 0.025). Seventy patients (35 test; 35 control) with a total of 127 implants were included in the final analysis. Mean ridge width gain was 3.7 ± 1.2 mm in the test and 3.7 ± 1.1 mm in the control group, with no significant difference between the two groups. No implant failure was recorded, with a mean follow-up of 42.7 ± 16.0 months after functional loading. Conclusions: SB and BS showed comparable clinical outcomes in horizontal ridge augmentation, resulting in sufficient crestal width increase to allow implant placement in an adequate bone envelope.

Primary Care Professionals' Self-Efficacy Surrounding Advance Care Planning and Its Link to Sociodemographics, Background and Perceptions: A Cross-Sectional Study.

Primary care (PC) professionals have been considered the most appropriate practitioners for leading Advance care planning (ACP) processes with advanced chronic patients. Aim: To explore how PC doctors’ and nurses’ self-efficacy surrounding ACP is linked to their sociodemographic characteristics, background and perceptions of ACP practices. Methods: A cross-sectional study was performed. Sociodemographics, background and perceptions about ACP in practice were collected using an online survey. The Advance Care Planning Self-Efficacy Spanish (ACP-SEs) scale was used for the self-efficacy measurement. Statistical analysis: Bivariate, multivariate and backward stepwise logistic regression analyses were performed to identify variables independently related to a higher score on the ACP-SEs. Results: N = 465 participants, 70.04% doctors, 81.47% female. The participants had a mean age of 46.45 years and 66.16% had spent >15 years in their current practice. The logistic regression model showed that scoring ≤ 75 on the ACP-SEs was related to a higher score on feeling sufficiently trained, having participated in ACP processes, perceiving that ACP facilitates knowledge of preferences and values, and perceiving that ACP improves patients’ quality of life. Conclusion: Professionals with previous background and those who have a positive perception of ACP are more likely to feel able to carry out ACP processes with patients.

Diagnostic Role of Diffusion-Weighted and Dynamic Contrast-Enhanced Perfusion MR Imaging in Paragangliomas and Schwannomas in the Head and Neck.

Distinguishing schwannomas from paragangliomas in the head and neck and determining succinate dehydrogenase (SDH) mutation status in paragangliomas are clinically important. We aimed to assess the clinical usefulness of DWI and dynamic contrast-enhanced MR imaging in differentiating these 2 types of tumors, as well as the SDH mutation status of paragangliomas. This retrospective study from June 2016 to June 2020 included 42 patients with 15 schwannomas and 27 paragangliomas (10 SDH mutation-positive and 17 SDH mutation-negative). ADC values, dynamic contrast-enhanced MRI parameters, and tumor imaging characteristics were compared between the 2 tumors and between the mutation statuses of paragangliomas as appropriate. Multivariate stepwise logistic regression analysis was performed to identify significant differences in these parameters. Fractional plasma volume (P ≤ .001), rate transfer constant (P = .038), time-to-maximum enhancement (P < .001), maximum signal-enhancement ratio (P < .001) and maximum concentration of contrast agent (P < .001), velocity of enhancement (P = .002), and tumor characteristics including the presence of flow voids (P = .001) and enhancement patterns (P = .027) showed significant differences between schwannomas and paragangliomas, though there was no significant difference in ADC values. In the multivariate logistic regression analysis, fractional plasma volume was identified as the most significant value for differentiation of the 2 tumor types (P = .014). ADC values were significantly higher in nonhereditary than in hereditary paragangliomas, while there was no difference in dynamic contrast-enhanced MR imaging parameters. Dynamic contrast-enhanced MR imaging parameters show promise in differentiating head and neck schwannomas and paragangliomas, while DWI can be useful in detecting SDH mutation status in paragangliomas.

Using angiographic parametric imaging-derived radiomics features to predict complications and embolization outcomes of intracranial aneurysms treated by pipeline embolization devices

BackgroundPipeline embolization devices (PEDs) have gained widespread popularity in the treatment of intracranial aneurysms (IAs). However, precise predictors of treatment outcomes are still lacking. This study aimed to use angiographic...

Combined procalcitonin and hemogram parameters contribute to early differential diagnosis of Gram‐negative/Gram‐positive bloodstream infections

BackgroundHemogram parameters and procalcitonin (PCT) play auxiliary roles in the diagnosis and outcome of sepsis. However, it is not clear whether these indicators can quickly distinguish bacterial classification or guide the choice of empirical antibiotics.MethodsWe retrospectively enrolled 381 patients with bloodstream infections (BSI), divided into Gram‐positive bloodstream infections (GP‐BSI) and Gram‐negative bloodstream infections (GN‐BSI). Demographic parameters, hemogram parameters, and PCT were recorded and compared between the two groups.ResultsThe mean platelet volume (MPV), platelet distribution width (PDW), and PCT in the GN‐BSI group were significantly higher than those in the GP‐BSI group, while the platelet count (PLT), plateletcrit, platelet count‐to‐white blood cell count ratio (PWR), platelet count‐to‐neutrophil count ratio (PNR), platelet count‐to‐PCT ratio (PLT/PCT), and mean platelet volume‐to‐PCT ratio (MPV/PCT) were significantly lower in the GN‐BSI group. Multivariate stepwise logistic regression analysis revealed that the independent predictors of GN‐BSI were MPV, PWR, and PCT. The areas under the curve (AUC) for this prediction model was 0.79, with sensitivity =0.75 and specificity =0.71.ConclusionsThere were significant differences in terms of PCT, platelet parameters, and platelet‐related index‐PCT ratio between GN‐BSI and GP‐BSI. Combined PCT and hemogram parameters are more conducive to the early differential diagnosis of bacterial classification of BSI.

A nomogram for preoperative prediction of prolonged air leak after pulmonary malignancy resection.

BackgroundProlonged air leak (PAL) is one of the most common postoperative complications after lung surgery. This study aimed to identify risk factors of PAL after lung resection and develop a preoperative predictive model to estimate its risk for individual patients.MethodsPatients with pulmonary malignancies or metastasis who underwent pulmonary resection between January 2014 and January 2018 were included. PAL was defined as an air leak more than 5 days after surgery, risk factors were analyzed. Forward stepwise multivariable logistic regression analysis was performed to identify independent risk factors, and a derived nomogram was built. Data from February 2018 to September 2018 were collected for internal validation.ResultsA total of 1,511 patients who met study criteria were enrolled in this study. The overall incidence of PAL was 9.07% (137/1,511). Age, percent forced expiratory volume in 1 second, surgical type, surgical approach and smoking history were included in the final model. A nomogram was developed according to the multivariable logistic regression results. The C-index of the predictive model was 0.70, and the internal validation value was 0.77. The goodness-of-fit test was non-significant for model development and internal validation.ConclusionsThe predictive model and derived nomogram achieved satisfied preoperative prediction of PAL. Using this nomogram, the risk for an individual patient can be estimated, and preventive measures can be applied to high-risk patients.

Allogeneic Red Blood Cell Transfusion Rate and Risk Factors After Hemiarthroplasty in Elderly Patients With Femoral Neck Fracture.

ObjectiveThis study aimed to determine the rate and risk factors of allogeneic red blood cell transfusions (ABT) after hemiarthroplasty (HA) in elderly patients with femoral neck fracture (FNF).MethodsThe subjects of the study were elderly patients (≥65 years old) who were admitted to the geriatric trauma orthopedics ward of Beijing Jishuitan Hospital between March 2018 and June 2019 for HA treatment due to an FNF. The perioperative data were collected retrospectively, and univariate and multivariate stepwise logistic regression analyses were performed to determine the post-operative ABT rate and its risk factors.ResultsThere were 445 patients in the study, of whom 177 (39.8%) received ABT after surgery. Multivariate stepwise logistic regression analysis showed that preoperative low hemoglobin (Hb), high intraoperative blood loss (IBL), advanced age, and a low body mass index (BMI) are independent risk factors of ABT after HA in elderly FNF patients.ConclusionABT after HA is a common phenomenon in elderly patients with FNF. Their post-operative ABT needs are related to preoperative low Hb, high IBL, advanced age, and low BMI. Therefore, ABT can be reduced by taking these factors into account. When the same patient had three risk factors (preoperative low hemoglobin, advanced age, and low BMI), the risk of ABT was very high (78.3%). Also, when patients have two risk factors of preoperative low hemoglobin and low BMI, the risk of ABT was also high (80.0%).

Serum Osteoprotegerin Level Is Negatively Associated with Bone Mineral Density in Patients Undergoing Maintenance Hemodialysis.

Background and Objectives: Osteoprotegerin (OPG), a potent osteoclast activation inhibitor, decreases bone resorption and plays a role in mediating bone mineral density (BMD). Our aim was to evaluate the relationship between BMD and serum OPG in maintenance hemodialysis (MHD) patients. Materials and Methods: Fasting blood samples were obtained from 75 MHD patients. BMD was measured by dual-energy X-ray absorptiometry in lumbar vertebrae (L2–L4). The WHO classification criteria were applied to define osteopenia and osteoporosis. A commercial enzyme-linked immunosorbent assay was used to measure serum OPG values. Results: Among all MHD patients, seven (9.3%) and 20 patients (26.7%) were defined as osteoporosis and osteopenia, respectively. Female patients had lower lumbar BMD than males (p = 0.002). Older age (p = 0.023), increased serum OPG (p < 0.001) urea reduction rate (p = 0.021), Kt/V (p = 0.027), and decreased body mass index (p = 0.006) and triglycerides (p = 0.020) were significantly different between the normal, osteopenia, and osteoporosis groups. Lumbar spine BMD was positively correlated with body mass index (BMI) (p < 0.001) but negatively correlated with OPG (p < 0.001) and age (p = 0.003). After grouping patients into T scores < −1 and < −2.5, female sex and OPG (adjusted odds ratio [aOR] 1.022, 95% confidence interval [C.I.] 1.011–1.034, p < 0.001) were predictors of T scores < −1, whereas only OPG was predictive of T scores < −2.5 (aOR 1.015, 95% C.I. 1.005–1.026, p = 0.004) by multivariate stepwise logistic regression analysis. The areas under the curve for predicting T scores < −1 or < −2.5 were 0.920 (95% C.I. 0.834–0.970, p < 0.001) and 0.958 (95% C.I. 0.885–0.991, p < 0.001), respectively. Conclusions: Increased serum OPG negatively correlated with lumbar BMD and could be a potential biomarker predictive of osteoporosis in MHD patients.

Comparison study of patient demographics and patient-related risk factors for peri-prosthetic joint infections following primary total shoulder arthroplasty

BackgroundWhile studies have demonstrated favorable outcomes in utilization of primary total shoulder arthroplasty (TSA) for the treatment of glenohumeral osteoarthritis (OA), adverse events such as infections can still occur. Periprosthetic joint infections (PJIs) are associated with worse outcomes and patient morbidity. The purpose of this study was to: (1) compare patient demographics amongst TSA patients with and without PJIs following primary TSA; and (2) identify patient-related risk factors for PJIs following primary TSA. MethodsPatients undergoing primary TSA for the treatment of glenohumeral OA were identified using the Mariner administrative claims database by CPT code 23,472. Laterality modifiers were utilized to ensure PJIs were developing in the correct laterality as those patients undergoing primary TSA. Inclusion for the study group consisted of patients who developed PJIs within 2-years after the index procedure, whereas patients who did not develop PJIs served as the comparison cohort. Primary outcomes analyzed included patient demographics and patient-related risk factors for PJIs following primary TSA. A stepwise backwards elimination multivariate binomial logistic regression analyses was performed to determine the odds (OR) of PJIs in patients undergoing primary TSA. A P value less than .05 was considered statistically significant. ResultsThe query yielded 15,396 patients who underwent primary TSA for glenohumeral OA, of which 191 patients developed PJIs and 15,205 did not develop PJIs. The study found statistically significant differences amongst patients who did and did not develop PJIs following primary TSA with respect to age, sex, and presence of comorbid conditions. Risk factors associated with developing PJIs following primary TSA included: pathologic weight loss (OR: 2.06, P < .0001), obesity (OR: 1.56, P = .0001), male sex (OR: 1.52, P = .007), and peripheral vascular disease (OR: 1.46, P = .022). ConclusionAs the number of primary TSAs for the treatment of glenohumeral OA increase worldwide, identifying modifiable risk-factors to reduce the incidence of infection is critical. The study found various modifiable and non-modifiable risk factors associated with developing PJIs following primary TSA. This study is valuable to orthopedists in order to identify and risk-stratify patients with regard to PJI in the setting of primary TSA for OA. Level of EvidenceLevel III; Case-Control Study