Multivariate Analysis of Clinical Predictors of Sleep Disturbance Related to Frequent Nighttime Heartburn and Acid Regurgitation Symptoms in Individuals Taking Esomeprazole 20 mg or Placebo

2014 ◽  
Vol 109 ◽  
pp. S20
Author(s):  
David Johnson ◽  
Anne LeMoigne ◽  
Jing Li ◽  
Charles Pollack ◽  
Peter Nagy
Keyword(s):  
Multivariate Analysis ◽  
Sleep Disturbance ◽  
Clinical Predictors ◽  
Acid Regurgitation

Impact of clinical and molecular features on risk of recurrence following curative intent resection of metastases in metastatic colorectal cancer.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 785-785
Author(s):  
Matthew E. Burge ◽  
Belinda Lee ◽  
Margaret Lee ◽  
Rachel Wong ◽  
Phillip Parente ◽  
...  
Keyword(s):  
Overall Survival ◽  
Multivariate Analysis ◽  
Primary Tumour ◽  
Clinical Predictors ◽  
Curative Intent ◽  
Mutation Status ◽  
Molecular Features ◽  
Kaplan Meier ◽  
Resection Of Metastases ◽  
Primary 76

785 Background: Resection of metastases with curative intent is an integral component of mCRC management. However, relapse rates are high and identifying patients most likely to benefit from this approach is of considerable importance. Among patients with mCRC, mutations (mt) in RAS and BRAF genes portent a worse prognosis. Our hypothesis, therefore, is that patients harbouring these mutations may have a higher relapse rate after resection of metastases. We also wished to analyse clinical predictors of relapse, including site of metastases. Methods: We interrogated the TRACC database of patients undergoing resection with curative intent who had mutation status available. The frequency of RAS and BRAF mt was established and their association with clinical parameters determined. Relapse free (RFS) and overall survival (OS), from the date of resection, was estimated for the mt and wild type (wt) groups using the Kaplan Meier method. Multivariate analysis is planned to investigate factors associated with RFS, including stage of the primary tumour, synchronous metastases, site and number of metastases, CEA, peri-operative chemotherapy use, site of the primary (left v right) and RAS and BRAF mutation status. Results: 188 patients were identified. 89 were KRAS/BRAF wt, 92 KRAS mt and 7 BRAF mt. 40% had presented with metastatic disease and 27% had a right sided primary. 76%, 22% and 2% underwent resection of liver, lung or both metastases. Microscopic resection margin was involved in 6%. Resection was performed prior to any chemotherapy in 48%. No difference was seen in relapse free or overall survival between the mt and wt groups. Conclusions: We found no difference in relapse free or overall survival by mutation subgroup suggesting this should not influence suitability for curative intent resection, but analyses is planned on a much larger cohort once data is available. A multivariate analysis, adjusting for important prognostic variables, is planned.

scholarly journals Volume of cerebrospinal fluid drainage as a predictor for pretreatment aneurysmal rebleeding

2018 ◽  
Vol 128 (6) ◽  
pp. 1778-1784 ◽  
Author(s):  
Jasper H. van Lieshout ◽  
Ina Pumplün ◽  
Igor Fischer ◽  
Marcel A. Kamp ◽  
Jan F. Cornelius ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Treatment Protocol ◽  
Definitive Treatment ◽  
Ventricular Catheter ◽  
Acute Management ◽  
Clinical Predictors ◽  
Csf Drainage ◽  
Highly Correlated

OBJECTIVEInitiation of external CSF drainage has been associated with a significant increase in rebleeding probability after aneurysmal subarachnoid hemorrhage (aSAH). However, the implications for acute management are uncertain. The purpose of this study was to evaluate the role of the amount of drained CSF on aneurysmal rebleeding.METHODSConsecutive patients with aSAH were analyzed retrospectively. Radiologically confirmed cases of aneurysmal in-hospital rebleeding were identified and predictor variables for rebleeding were retrieved from hospital records. Clinical predictors were identified through multivariate analysis, and logistic regression analysis was performed to ascertain the cutoff value for the rebleeding probability.RESULTSThe study included 194 patients. Eighteen cases (9.3%) of in-hospital rebleeding could be identified. Using multivariate analysis, in-hospital rebleeding was significantly associated with initiation of CSF drainage (p = 0.001) and CSF drainage volume (63 ml [interquartile range (IQR) 55–69 ml] vs 25 ml [IQR 10–35 ml], p < 0.001). Logistic regression showed that 58 ml of CSF drainage within 6 hours results in a 50% rebleeding probability. The relative risk (RR) for rebleeding after drainage of more than 60 ml in 6 hours was 5.4 times greater compared with patients with less CSF drainage (RR 5.403, 95% CI 2.481–11.767; p < 0.001, number needed to harm = 1.687).CONCLUSIONSVolume of CSF drainage was highly correlated with the probability of in-hospital aneurysmal rebleeding. These findings suggest that the rebleeding probability can be affected in acute management should the placement of an external ventricular catheter be necessary. This finding necessitates meticulous control of the amount of drained CSF and the development of a definitive treatment protocol for this group of patients.

Prognostic understanding in hematologic malignancies: A multicenter longitudinal study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 11524-11524
Author(s):  
Kah Poh Loh ◽  
Thomas William LeBlanc ◽  
Stephanie Lee ◽  
Anthony Back ◽  
Paul Duberstein ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Longitudinal Study ◽  
Secondary Analysis ◽  
College Education ◽  
Hematologic Malignancies ◽  
Cancer Type ◽  
Clinical Predictors ◽  
Patient Demographics ◽  
Lower Education Level ◽  
And Coping

11524 Background: Accurate prognostic understanding facilitates the receipt of goal-concordant medical care. Few studies have evaluated prognostic understanding in patients with hematologic malignancies. In this secondary analysis of a multicenter, longitudinal study of patients with hematologic malignancies referred for a second opinion hematology subspecialty consultation, we assessed changes in prognostic understanding after consultation, and predictors of post-consultation patient-oncologist prognostic discordance. Methods: Patients were recruited from 4 academic centers. Before and 1-7 days after consultation, patients were asked about their perceived chance of cure (options < 10%, 10-19%, and up to 90-100% in 10% increments, and “do not wish to answer”). Oncologists were asked the same question after consultation. Discordance was defined as a difference in response by 2 levels in the patient-oncologist dyads. We used multivariate analysis to assess the demographic and clinical predictors of patient-oncologist discordance. Results: We included 216 patients (median age 55 years, range 22-79) and 46 oncologists (47, 30-70). Overall, ≥On multivariate analysis, discordance before consultation [Odds Ratio (OR) 6.05, 95% Confidence Interval (CI) 2.96-12.36) and < college education (vs. post-graduate education; OR 2.34, 95% CI 1.09-5.14) were associated with discordance after consultation. Other patient demographics, comorbidity, cancer type, psychological distress, social support, decision-making preference, and coping strategies were not associated with discordance. Conclusions: Patient-oncologist concordance in prognostic understanding improved after subspecialty consultation, but over half of patients’ views of their prognosis remained discordant with those of their oncologists. Interventions to improve patient-oncologist communication about prognosis are needed, especially in patients with lower education level.

scholarly journals Exploring sleep disturbance among adults with primary or secondary malignant brain tumors and their caregivers

2020 ◽  
Author(s):  
Megan S Jeon ◽  
Haryana M Dhillon ◽  
Eng-Siew Koh ◽  
Anna K Nowak ◽  
Elizabeth Hovey ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Sleep Disturbance ◽  
Binary Logistic Regression ◽  
Severity Index ◽  
Self Report ◽  
Poor Sleep ◽  
Clinical Predictors ◽  
Malignant Brain Tumors ◽  
Underlying Mechanisms ◽  
Md Anderson

Abstract Background Emerging evidence supports the clinical impact of sleep disturbance (SD) on cancer patients. This study aimed to determine the prevalence and predictors of SD in people with malignant brain tumors and caregivers, and explore any relationship between the patient-caregiver dyad’s sleep. Methods Eighty-one adults with primary malignant (91%) or metastatic (9%) brain tumors and their family caregivers (n = 44) completed a series of self-report questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index, and the drowsiness item of The MD Anderson Symptom Inventory-Brain Tumor in an Australian ambulatory neuro-oncology setting. Participants were grouped by the PSQI cutoff (SD &gt; 5), and binary logistic regression analyses were performed to identify risk factors. Results Of patients, 53% reported SD and 15% of those clinically significant insomnia, and 27% reported moderate to severe daytime drowsiness. Whereas anxiety, depression, fatigue, pain, neurocognitive symptoms, and antiemetic use were higher in patients with SD, fatigue and KPS were strong predictors of SD. In caregivers, 55% reported poor sleep and 13% clinical insomnia. Anxiety, caregiver burden, and comorbid illness were significantly associated with caregivers’ SD. The individual’s SD did not affect the chance of the other member of the patient-caregiver dyad experiencing SD. Conclusions More than half the sample had sleep disturbance, which was linked to many concomitant symptoms, such as fatigue in patients and anxiety in caregivers, potentially contributing to distress and functional impairment. Understanding underlying mechanisms of SD, the potential use of these clinical predictors in care settings, and options for management is warranted.

Clinical Predictors of Intra-Abdominal Injury in Severe Blunt Trauma Patient

2009 ◽  
Vol 16 (2) ◽  
pp. 76-83
Author(s):  
PL Goh ◽  
MJ Schull
Keyword(s):  
Risk Factors ◽  
Multivariate Analysis ◽  
Blunt Trauma ◽  
Pelvic Fracture ◽  
Chest Tube ◽  
Abdominal Injury ◽  
Trauma Patients ◽  
Clinical Predictors ◽  
Tube Insertion ◽  
Chest Tube Insertion

Introduction The early recognition of intra-abdominal injury (IAI) in patients with blunt trauma is essential, yet physical examination is often unreliable. Computed tomography (CT) scans are used widely to further evaluate possible IAI but these require time and expense. IAI may be associated with certain objective risk factors or other specific injuries, but this association has not been widely studied. Identification of such risk factors will help to prioritize patients in need for further evaluation of possible IAI. Methods A retrospective chart review was conducted of all 622 adult severe blunt trauma patients (Injury Severity Score [ISS] >12) presenting to a level 1 trauma centre in 2004. Various clinical predictors of IAI were analyzed statistically with univariate and multivariate analysis using SAS software. Results In multivariate analysis, four significant predictors of IAI were found: positive focused assessment with sonography for trauma (FAST) (OR=48.5, p<0.0001), presence of pelvic fracture (OR=2.4, p=0.0002), chest tube insertion (OR=1.8, p=0.0211), and systolic blood pressure (SBP), where every 10 mmHg decrease indicates a 14% increase in risk (OR=0.986, p=0.001). The absence of all four predictors predicted the absence of IAI with a specificity of 0.776 (95% CI 0.741 to 0.808) and a LR of 2.7 (95% CI 2.0 to 3.5). Conclusion This study suggests that positive FAST, presence of pelvic fracture, chest tube insertion, and SBP are significant predictors of IAI in adult blunt trauma patients with ISS > 12. The absence of all four predictors is associated with a reduced risk of IAI.

Correlation Analysis of Mental Health Status and Sleep Quality in Helicobacter pylori Positive Patients

2019 ◽  
Vol 9 (8) ◽  
pp. 1600-1606
Author(s):  
Min Liu ◽  
Cai-Feng Luo
Keyword(s):  
Mental Health ◽  
Helicobacter Pylori ◽  
Multivariate Analysis ◽  
Abdominal Pain ◽  
Sleep Quality ◽  
Univariate Analysis ◽  
Abdominal Distension ◽  
Attack Frequency ◽  
Acid Regurgitation ◽  
Spicy Food

Objective: To analyze the correlation between mental health and sleep quality in Helicobacter pylori Positive Patients (Hp-positive patients). Methods: Patients with 13C exhalation test stomach discomfort were taken as the subjects of study. The gastrointestinal symptoms table, Kessler10 scale and Pittsburgh sleep quality index (PSQI) scale questionnaires were used. Single factor and multi-factor linear regression analysis was performed using SPSS 22.0. Results: Univariate analysis showed that Kessler10 scale was related to 11 factors, including sex, drinking, preference for spicy food, current Hp situation, abdominal pain, abdominal distension, acid regurgitation, heartburn, belching, severity of gastrointestinal tract, and frequency of gastrointestinal attacks. The difference was statistically significant (P < 0.05). Multivariate analysis showed that Hp (P = 0.00) and gastrointestinal attack frequency (P = 0.002) were the influencing factors (P < 0.05). In addition, univariate analysis showed that PSQI scale was related to 10 factors, namely gender, preference for spicy food, current Hp situation, abdominal pain, abdominal distension, acid regurgitation, diarrhea, belching, severity of gastrointestinal tract and frequency of gastrointestinal attack, with statistically significant difference (P < 0.05). Multivariate analysis showed that gender (P = 0.009), current Hp situation (P = 0.020) and gastrointestinal attack frequency (P = 0.043) were the influencing factors (P < 0.05). Conclusion: Helicobacter pylori infection affects the mental health and sleep quality of patients.

scholarly journals ABO phenotype and clinical correlates of COVID-19 severity in hospitalized patients

2021 ◽  
pp. FSO735
Author(s):  
David J Hermel ◽  
Samantha R Spierling Bagsic ◽  
Carrie L Costantini ◽  
James R Mason ◽  
Zhubin J Gahvari ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Multivariate Analysis ◽  
Intensive Care ◽  
Intensive Care Unit Admission ◽  
Exploratory Analysis ◽  
Blood Type ◽  
San Diego County ◽  
Clinical Predictors ◽  
Clinical Correlates ◽  
Male Sex

Aim: This study investigates the association between ABO blood phenotype and COVID-19 severity, measured by intensive care unit admission, need for intubation, hospitalization length and death. It further explores clinical predictors of COVID-19 severity within a primarily Hispanic demographic in San Diego County. Materials & methods: We retrospectively reviewed 942 total patients, 473 with available blood type, hospitalized at five Scripps Health hospitals with COVID-19. Results: No significant association was found between ABO phenotype and COVID-19 severity on multivariate analysis, while a diagnosis of anemia and male sex was associated with all severity outcomes on exploratory analysis. Conclusion: Our results provide relevant clinical correlates of COVID-19 severity and help better elucidate the association between ABO phenotype and COVID-19.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

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