Examining Initial Post-Concussion Dizziness and Postural Stability as Potential Recovery Predictors

ObjectiveTo examine the association between acute post-concussion dizziness, initial symptom severity, and postural stability with time to symptom resolution among adolescents.BackgroundIdentifying early post-concussion symptoms and functional deficits that predict symptom resolution can guide treatment strategies. Dizziness is among the most common concussion symptoms, and existing literature investigating the association between dizziness and recovery time is mixed.Design/MethodsParticipants underwent initial evaluation = 14 days post-concussion, and self-reported symptom severity using the Post-Concussion Symptom Inventory (PCSI). We used PSCI dizziness ratings to group participants: a difference between current and pre-injury dizziness ≥3 = dizzy; difference <3 = not dizzy. We evaluated postural stability using modified Balance Error Scoring System (mBESS) and tandem gait (TG). Patients were followed until symptom resolution, and our primary outcome of interest was time from concussion to symptom resolution. Using a univariable Cox proportional hazard model, we examined the association of dizziness and symptom resolution time. We then used a multivariable Cox proportional hazard model to adjust for variables that differed between groups.ResultsWe examined 89 participants, grouped as dizzy (n = 34; age = 14.7 ± 2.7 years; 7.1 ± 3.4 days post-injury; symptom resolution time = 40.8 ± 5.7 days) or not dizzy (n = 55; age = 14.4 ± 2.3 years; 7.2 ± 3.1 days post-injury; symptom resolution time = 23.3 ± 3.2 days). Upon univariable examination, dizziness was independently associated with symptom resolution time (HR = 0.49; 95% CI: 0.28, 0.83; p = 0.009). After adjusting for potential confounding variables (initial symptom severity, mBESS tandem stance errors, TG time, and loss of consciousness) multivariable model results indicated initial symptom severity was the only variable associated with symptom resolution time (HR = 0.98; 95% CI: 0.96, 0.997; p = 0.025).ConclusionsTotal symptom severity, but not dizziness or postural stability, was significantly associated with symptom resolution time among adolescents following concussion. Individuals with moderate to severe post-concussion dizziness had higher average symptom scores indicating self-reported dizziness should be interpreted in the context of total concussion symptom burden.

Influence of the trajectory of the urine output for 24 h on the occurrence of AKI in patients with sepsis in intensive care unit

Background Sepsis-associated acute kidney injury (S-AKI) is a common and life-threatening complication in hospitalized and critically ill patients. This condition is an independent cause of death. This study was performed to investigate the correlation between the trajectory of urine output within 24 h and S-AKI. Methods Patients with sepsis were studied retrospectively based on the Medical Information Mart for Intensive Care IV. Latent growth mixture modeling was used to classify the trajectory of urine output changes within 24 h of sepsis diagnosis. The outcome of this study is AKI that occurs 24 h after sepsis. Cox proportional hazard model, Fine–Gray subdistribution proportional hazard model, and doubly robust estimation method were used to explore the risk of AKI in patients with different trajectory classes. Results A total of 9869 sepsis patients were included in this study, and their 24-h urine output trajectories were divided into five classes. The Cox proportional hazard model showed that compared with class 1, the HR (95% CI) values for classes 3, 4, and 5 were 1.460 (1.137–1.875), 1.532 (1.197–1.961), and 2.232 (1.795–2.774), respectively. Competing risk model and doubly robust estimation methods reached similar results. Conclusions The trajectory of urine output within 24 h of sepsis patients has a certain impact on the occurrence of AKI. Therefore, in the early treatment of sepsis, close attention should be paid to changes in the patient's urine output to prevent the occurrence of S-AKI.

Prognostic Value of Baseline Medications Plus Neutrophil-to-Lymphocyte Ratio in the Effectiveness of Nivolumab and Pembrolizumab in Patients With Advanced Non-Small-Cell Lung Cancer: A Retrospective Study

BackgroundNivolumab and pembrolizumab are the standard treatments for patients with advanced non-small-cell lung cancer (NSCLC). While there are reports on several inflammatory indices and the prognosis of patients with cancer, no study has combined baseline medication with the neutrophil-to-lymphocyte ratio (NLR) to predict clinical outcomes. This study investigated the efficacy of baseline medications plus NLR to predict the effectiveness of nivolumab and pembrolizumab in a real-world clinical setting.MethodsWe conducted a single-center retrospective observational study of consecutive patients with advanced NSCLC who received nivolumab or pembrolizumab as first-line, second-line, or beyond treatment between December 2015 and November 2018 at the National Cancer Center Hospital in Japan. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan–Meier method. The drug-based prognostic score for baseline medications plus NLR was weighed based on the regression β coefficients. The multivariable Cox proportional hazard model was used to assess the association between the prognostic score-stratified groups and survival outcomes.ResultsIn total, 259 patients were evaluated in this study. A prognostic score calculated from the baseline medications plus NLR was used to categorize the patients into good (score 0), intermediate (scores 1–2), and poor (scores 3–6) -prognosis groups. The multivariable Cox proportional hazard model revealed a significant association between the poor-prognosis group and reduced OS. The hazard ratio of OS was 1.75 (95% confidence interval: 1.07–2.99; P = 0.031). In contrast, no association between these prognosis groups and PFS was observed.ConclusionsThe findings suggest that the baseline medications with nivolumab or pembrolizumab plus NLR could lead to progressively shorter survival outcomes in patients with advanced NSCLC and could be used as a prognostic index for poor outcomes. However, to ascertain the clinical application of these findings, these concomitant medications need further validation in a large-scale multicenter study.

Introduction of Two-Dose Mumps-Containing Vaccine into Routine Immunization Schedule in Quzhou, China, Using Cox-Proportional Hazard Model

Mumps is a vaccine-preventable disease caused by the mumps virus, but the incidence of mumps has increased among the children who were vaccinated with one-dose measles-mumps-rubella (MMR) in recent years. In this study, we analyzed the influence of different doses of mumps-containing vaccine (MuCV) against mumps using Cox-proportional hazard model. We collected 909 mumps cases of children who were born from 2006 to 2010 and vaccinated with different doses of MuCV in Quzhou during 2006-2018, which were all clinically diagnosed. Kaplan-Meier survival methods and Cox-proportional hazard model were used to estimate the hazard probabilities. Kaplan–Meier curves showed that the cumulative hazard of male and female has no difference; lower hazards were detected among those who were vaccinated with two-dose MuCV, born in 2006, and infected after supplementary immunization activities (SIA). Cox-proportional hazard regression suggested that onset after SIA, born in 2006, and vaccinated with two-dose MuCV were protective factors against infection even after adjusting for potential confounding effects. Our study showed that it was necessary to revise the diagnostic criteria of mumps and identify RT-PCR as the standard for mumps diagnosis in China. We suggested that routine immunization schedule should introduce two doses of MMR and prevaccination screening should be performed before booster immunization in vaccinated populations.

Risk factors of recurrence in patients with cancer-associated venous thromboembolism: from the COMMAND VTE Registry

Background/Introduction Cancer is a strong risk factor for the development of venous thromboembolism (VTE) including pulmonary embolism (PE) and deep vein thrombosis (DVT). Patients with VTE have a long-term risk of recurrence, which can be prevented by anticoagulation therapy. Prolonged anticoagulation therapy is recommended for patients with cancer-associated VTE, although the risk of recurrence might depend on the individual patient. Purpose We aimed to identify the risk factors of recurrence in patients with cancer-associated VTE. Methods The COMMAND VTE Registry is a multicenter retrospective registry enrolling 3027 consecutive patients with acute symptomatic VTE among 29 Japanese centers between January 2010 and August 2014. The present study population consisted of 695 cancer-associated VTE patients. The primary outcome measure in the present study was recurrent VTE, which was defined as PE and/or DVT with symptoms accompanied by confirmation of a new thrombus or exacerbation of the thrombus by objective imaging examinations or autopsy. Discontinuation of anticoagulation was defined as a withdrawal of anticoagulation therapy lasting &gt;14 days for any reason. We selected clinically relevant variables and variables with P values &lt;0.1 in a univariate analysis as potential risk factors, and constructed a multivariable Cox proportional hazard model for recurrent VTE incorporating the anticoagulation therapy status as a time-updated covariate. Results Among the 695 study patients, recurrent VTE occurred in 78 patients, of whom 54 (69%) occurred within 6 months. The cumulative incidence of recurrent VTE was 7.7% at 3-months, 8.9% at 6-months, 11.8% at 1-year, and 17.7% at 5-years. The cumulative incidence of discontinuation of anticoagulation therapy was 18.0% at 3-months, 29.5% at 6-months, 43.4% at 1-year, and 66.5% at 5-years. The cumulative 5-year incidence of recurrent VTE was most frequent in patients with uterus/ovary cancer (26.0%), followed by those with lung cancer (24.7%). The multivariable Cox proportional hazard model revealed that chronic kidney disease (HR, 2.27; 95% CI, 1.36–3.77, P=0.002), a high D-dimer level at the time of VTE diagnosis (HR, 2.85; 95% CI, 1.71–4.74, P&lt;0.001), advanced cancer (HR, 1.69; 95% CI, 1.05–2.72, P=0.03) and discontinuation of anticoagulation therapy (HR, 2.66; 95% CI, 1.53–4.63, P&lt;0.001) were independently associated with an increased risk of recurrent VTE. No cancer site was independently associated with an increased risk for recurrent VTE when adjusting for the above mentioned risk factors in the multivariable Cox proportional hazard model, although the risk of recurrent VTE numerically differed according to the cancer site. Conclusions Among patients with cancer-associated VTE, chronic kidney disease, a high D-dimer level at the time of VTE diagnosis, advanced cancer, and discontinuation of anticoagulation therapy were independent risk factors of recurrence. FUNDunding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Research Institute for Production Development, Mitsubishi Tanabe Pharma Corporation Figure 1 Figure 2

The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model

An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values. The root means square error (RMSE) and the proportion of falsely classified entries (PFC) are two standard statistics to evaluate imputation accuracy. However, the Cox proportional hazards model using various types requires deliberate study, and the validity under different missing mechanisms is unknown. In this research, we propose supervised and unsupervised imputations and examine four machine learning-based imputation strategies. We conducted a simulation study under various scenarios with several parameters, such as sample size, missing rate, and different missing mechanisms. The results revealed the type-I errors according to different imputation techniques in the survival data. The simulation results show that the non-parametric “missForest” based on the unsupervised imputation is the only robust method without inflated type-I errors under all missing mechanisms. In contrast, other methods are not valid to test when the missing pattern is informative. Statistical analysis, which is improperly conducted, with missing data may lead to erroneous conclusions. This research provides a clear guideline for a valid survival analysis using the Cox proportional hazard model with machine learning-based imputations.

Prognostic relevance of elevated plasma osmolality on admission in acute decompensated heart failure with preserved ejection fraction: insights from PURSUIT-HFpEF registry

Background Complicated pathophysiology makes it difficult to identify the prognosis of heart failure with preserved ejection fraction (HFpEF). While plasma osmolality has been reported to have prognostic importance, mainly in heart failure with reduced ejection fraction (HFrEF), its prognostic meaning for HFpEF has not been elucidated. Methods We prospectively studied 960 patients in PURSUIT-HFpEF, a multicenter observational study of acute decompensated HFpEF inpatients. We divided patients into three groups according to the quantile values of plasma osmolality on admission. During a follow-up averaging 366 days, we examined the primary composite endpoint of cardiac mortality or heart failure re-admission using Kaplan–Meier curve analysis and Cox proportional hazard testing. Results 216 (22.5%) patients reached the primary endpoint. Kaplan–Meier curve analysis revealed that the highest quantile of plasma osmolality on admission (higher than 300.3 mOsm/kg) was significantly associated with adverse outcomes (Log-rank P = 0.0095). Univariable analysis in the Cox proportional hazard model also revealed significantly higher rates of adverse outcomes in the higher plasma osmolality on admission (hazard ratio [HR] 7.29; 95% confidence interval [CI] 2.25–23.92, P = 0.0009). Multivariable analysis in the Cox proportional hazard model also showed that higher plasma osmolality on admission was significantly associated with adverse outcomes (HR 5.47; 95% CI 1.46–21.56, P = 0.0113) independently from other confounding factors such as age, gender, comorbid of atrial fibrillation, hypertension history, diabetes, anemia, malnutrition, E/e′, and N-terminal pro-B-type natriuretic peptide elevation. Conclusions Higher plasma osmolality on admission was prognostically important for acute decompensated HFpEF inpatients.

Combining hematoxylin and eosin (H&E) stained images and RNA sequencing (RNA-Seq) data to predict overall survival (OS) in patients with non-small cell lung cancer (NSCLC).

1547 Background: IMpower150 was a phase 3 clinical trial that evaluated the efficacy of atezolizumab in patients with metastatic nonsquamous NSCLC; it demonstrated no significant OS benefit in the ACP (atezolizumab+carboplatin+paclitaxel) arm vs the BCP (bevacizumab+carboplatin+paclitaxel) control arm (hazard ratio [HR]=0.85; 95%CI, 0.71-1.03). The objective of this analysis was to identify a subpopulation of patients that benefits from ACP using H&E stained images and RNA-Seq data. Methods: Spatial statistics algorithms were applied to the coordinates of tumor cells and lymphocytes of the H&E stained images to capture spatial heterogeneity of the tumor microenvironment. The normalized and log-transformed RNA-Seq data underwent a nested feature selection procedure using a Cox proportional hazard model with L1 regularization and stability selection. Cutoffs for gene selection were determined using a permutation strategy with a false discovery rate <0.001. To investigate the association between the 41 derived spatial features, significant genes and OS, a Cox proportional hazard model with L2 regularization was fitted only for the ACP group. Survival groups were further identified using nested Monte Carlo Cross Validation to prevent over-fitting. Results: A total of 236 ACP and 235 BCP patients who had both H&E stained images and RNA-Seq data were analyzed. In the predicted long survival group, ACP patients had significantly longer median OS vs BCP patients based on H&E stained images (HR=0.61; 95%CI, 0.41-0.90; P=0.013) and RNA-Seq data (HR=0.64; 95%CI, 0.41-0.99; P=0.042). The combination of both modalities further improved the OS benefit between the arms (HR=0.44; 95%CI, 0.27-0.73; P=0.001). Data-driven selection of genes relevant for the prediction of OS included MAML3, AC024475.4, RGPD1, LCE3D and AC004156.1. Conclusions: Our approach was able to stratify a subpopulation of patients that significantly benefited from ACP compared with BCP treatment, particularly when integrating both H&E stained images and RNA-Seq data, which demonstrated the complementary value of both modalities. Our results could inform the development of a companion diagnostic that predicts individualized treatment response. Clinical trial information: NCT02366143.