scholarly journals Risk and Protective Factors Analysis for Postoperative Delirium in Elderly Critically Ill Patients: A Multicenter Retrospective Study

2020 ◽  
Author(s):  
Shunpeng Xing ◽  
Shaolin Ma ◽  
Yuxi Zhou ◽  
Ming Lei ◽  
Gang Feng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Elderly Patients ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Postoperative Delirium ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Postoperative Hypertension

Abstract Objective: To study the incidence and risk factors of postoperative clinical delirium in critically ill elderly patients in order to devise strategies for prevention and treatment.Methods: We collected clinical data from 451 critically ill patients in the intensive care unit from four hospitals in Shanghai Pudong New Area. Postoperative delirium was measured using the Confusion Assessment Method for the ICU (CAM-ICU), and then the incidence of postoperative delirium was calculated. We used univariate analysis and multivariate logistic regression analysis to determine the risk factors associated with postoperative delirium in critically ill elderly patients.Results: Among the 451 critically ill patients, 56 had delirium after operation. The incidence of postoperative delirium was 12.4%. Univariate analysis showed that the incidence of postoperative delirium was significantly higher (P <0.05) in patients who had a past history of chronic obstructive pulmonary disease (COPD), underwent emergency surgery, were not administered intraoperative Propofol, had postoperative hypertension, were administered postoperative methylprednisolone, and did not have postoperative analgesia. Multivariate logistic regression analysis showed that age (OR=1.111, 95% CI, 1.056-1.168), surgical timing (OR=1.154, 95% CI, 1.058-7.200), and use of methylprednisolone postoperatively (OR=8.030, 95% CI, 1.050-61.408) were risk factors. Use of Propofol intraoperatively (OR=0.315, 95%CI, 0.124-0.800) was protective factors for postoperative delirium in elderly critically ill patients.Conclusion: Adavanced age, COPD history, emergency surgery, postoperative hypertension, use of methylprednisolone, and no postoperative analgesia are risk factors for postoperative delirium in critically ill elderly patients. Medical staff should be educated in evaluating delirium in postoperative patients and conducting risk assessment in order to prevent and treat the disease earlier, and reduce the incidence of delirium.

scholarly journals A novel procalcitonin-based score for detecting sepsis among critically ill patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245748
Author(s):  
Tung-Lin Tsui ◽  
Ya-Ting Huang ◽  
Wei-Chih Kan ◽  
Mao-Sheng Huang ◽  
Min-Yu Lai ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Validation Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Sepsis Group ◽  
C Reactive Protein ◽  
Multivariate Logistic Regression ◽  
Reactive Protein

Background Procalcitonin (PCT) has been widely investigated as an infection biomarker. The study aimed to prove that serum PCT, combining with other relevant variables, has an even better sepsis-detecting ability in critically ill patients. Methods We conducted a retrospective cohort study in a regional teaching hospital enrolling eligible patients admitted to intensive care units (ICU) between July 1, 2016, and December 31, 2016, and followed them until March 31, 2017. The primary outcome measurement was the occurrence of sepsis. We used multivariate logistic regression analysis to determine the independent factors for sepsis and constructed a novel PCT-based score containing these factors. The area under the receiver operating characteristics curve (AUROC) was applied to evaluate sepsis-detecting abilities. Finally, we validated the score using a validation cohort. Results A total of 258 critically ill patients (70.9±16.3 years; 55.4% man) were enrolled in the derivation cohort and further subgrouped into the sepsis group (n = 115) and the non-sepsis group (n = 143). By using the multivariate logistic regression analysis, we disclosed five independent factors for detecting sepsis, namely, “serum PCT level,” “albumin level” and “neutrophil-lymphocyte ratio” at ICU admission, along with “diabetes mellitus,” and “with vasopressor.” We subsequently constructed a PCT-based score containing the five weighted factors. The PCT-based score performed well in detecting sepsis with the cut-points of 8 points (AUROC 0.80; 95% confidence interval (CI) 0.74–0.85; sensitivity 0.70; specificity 0.76), which was better than PCT alone, C-reactive protein and infection probability score. The findings were confirmed using an independent validation cohort (n = 72, 69.2±16.7 years, 62.5% men) (cut-point: 8 points; AUROC, 0.79; 95% CI 0.69–0.90; sensitivity 0.64; specificity 0.87). Conclusions We proposed a novel PCT-based score that performs better in detecting sepsis than serum PCT levels alone, C-reactive protein, and infection probability score.

scholarly journals Risk factors for periprocedural ischemic stroke following endovascular treatment of intracranial aneurysms

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yisen Zhang ◽  
Chao Wang ◽  
Zhongbin Tian ◽  
Wei Zhu ◽  
Wenqiang Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Treatment Modality ◽  
Intracranial Aneurysms ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Flow Diverter ◽  
Multivariate Logistic Regression

Abstract Background The aim of this study was to comprehensively evaluate the risk factors of periprocedural ischemic stroke associated with endovascular treatment of intracranial aneurysms using a real-world database. Methods From August 2016 to March 2017, 167 patients were enrolled. Univariate analysis and multivariate logistic regression analysis were used to examine the risk factors for periprocedural ischemic stroke. Results Among the 167 cases, periprocedural ischemic stroke occurred in 20 cases (11.98%). After univariate analysis, the ischemic group had a higher proportion of large (≥ 10 mm) aneurysms than the control group (45.0% vs. 23.1%, p = 0.036). The incidence of periprocedural ischemic stroke was higher in cases treated by flow diverter (21.6%) or stent-assisted coiling (11.8%) than in cases treated by coiling only (2.7%), and the differences were statistically significant (p = 0.043). After multivariate logistic regression analysis, treatment modality was the independent risk factor for periprocedural ischemic stroke. Compared with the coiling-only procedure, flow diverter therapy was associated with a significantly higher rate of periprocedural ischemic stroke (OR 9.931; 95% CI 1.174–84.038; p = 0.035). Conclusions Aneurysm size and treatment modality were associated with periprocedural ischemic stroke. Larger aneurysms were associated with increased risk of periprocedural ischemic stroke. Flow diverter therapy was associated with significantly more periprocedural ischemic stroke than the coiling procedure alone.

scholarly journals Risk Factors of Thromboembolism in Lymphoma Patients Undergoing Chemotherapy and its Clinical Significance

2021 ◽  
Vol 27 ◽  
pp. 107602962110379
Author(s):  
Xiao Li ◽  
Shu-Ling Hou ◽  
Xi Li ◽  
Li Li ◽  
Ke Lian ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Clinical Significance ◽  
Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Stage Iii ◽  
Multivariate Logistic Regression ◽  
Ann Arbor

This study investigated the risk factors of thromboembolism (TE) in lymphoma patients undergoing chemotherapy and its clinical significance. A total of 304 lymphoma patients who received chemotherapy from January 2012 to July 2019 were retrospectively analyzed, including 111 patients with and 193 patients without TE. The clinical characteristics and related laboratory test results were compared between the 2 groups using univariate analysis, while the risk factors for TE in lymphoma patients undergoing chemotherapy were analyzed using multivariate logistic regression analysis. Univariate analysis revealed an increase in the risk of TE among lymphoma patients with chemotherapy in the following categories: female patients, patients with body mass index <18.5 or > 24, patients aged ≥60 years, those with platelet abnormality before chemotherapy, single hospital-stay patients, and Ann Arbor stage III/IV patients. Multivariate logistic regression analysis revealed that for platelet count abnormality before chemotherapy, Ann Arbor stage III/IV and female patients represented independent risk factors for TE among lymphoma patients after chemotherapy ( P < .05). For lymphoma patients treated with chemotherapy, the risk of TE occurring in women, patients with platelet abnormalities before chemotherapy, and patients at Ann Arbor stage III/IV was significantly higher compared with other patients. For these patients, we recommend prophylactic anticoagulant therapy.

scholarly journals Risk Factors for Periprocedural Ischemic Stroke following Endovascular Treatment of Intracranial Aneurysms

2021 ◽  
Author(s):  
Yisen Zhang ◽  
Chao Wang ◽  
Zhongbin Tian ◽  
Wei Zhu ◽  
Wenqiang Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Intracranial Aneurysms ◽  
Endovascular Procedures ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Flow Diverter ◽  
Multivariate Logistic Regression

Abstract BackgroundThe aim of this study was to comprehensively evaluate the risk factors of periprocedural ischemic stroke associated with endovascular treatment of intracranial aneurysms using a real-world prospective database.MethodsFrom August 2016 to March 2017, 200 patients with 217 aneurysms who underwent 206 endovascular procedures were enrolled. Univariate analysis and multivariate logistic regression analysis were used to examine the risk factors for periprocedural ischemic stroke.ResultsAmong the 206 endovascular procedures, periprocedural ischemic stroke occurred in 23 procedures (11.17%). After univariate analysis, the ischemic group had a higher proportion of large (≥ 10 mm) aneurysms than the control group (39.1% vs. 20.2%, p = 0.040). The incidence of periprocedural ischemic stroke was higher in cases treated by flow diverter (18.60%) or stent-assisted coiling (12.28%) than in cases treated by coiling only (2.04%), and the differences were statistically significant (p = 0.036). After multivariate logistic regression analysis, treatment modality was the independent risk factor for periprocedural ischemic stroke. Compared with the coiling-only procedure, flow diverter therapy was associated with a significantly higher rate of periprocedural ischemic stroke (OR 13.839; 95% CI 1.617–118.416; p = 0.016). Stent-assisted coiling also tended to present more often with periprocedural ischemic stroke than coiling alone (OR 7.559; 95% CI 0.958–59.618; p = 0.055).ConclusionsAneurysm size and treatment modality were associated with periprocedural ischemic stroke. Larger aneurysms were associated with increased risk of periprocedural ischemic stroke. Flow diverter therapy was associated with significantly more periprocedural ischemic stroke than the coiling procedure alone.

scholarly journals Perioperative Factors Affecting Length of Hospital Stay Among Elderly Patients

Medicina ◽  
2013 ◽  
Vol 49 (6) ◽  
pp. 40 ◽  
Author(s):  
Gytė Damulevičienė ◽  
Vita Lesauskaitė ◽  
Jūratė Macijauskienė ◽  
Kastytis Šmigelskas ◽  
Donatas Venskutonis
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Elderly Patients ◽  
Hospital Stay ◽  
Multivariate Logistic Regression Analysis ◽  
Length Of Hospital Stay ◽  
Cognitive Disorder ◽  
Multivariate Logistic Regression

Background and Objective. Timely assessment and prevention of risk factors for the main perioperative complications in elderly patients provide an opportunity to avoid them, decrease mortality, and diminish costs associated with longer hospital stay. The aim of this study was to estimate perioperative factors that could potentially predict the length of stay and to estimate their predictive value using a comprehensive geriatric assessment among elderly patients. Material and Methods. The study population comprised 99 surgical patients aged 65 and more. The patients were followed up until discharge. Study data analysis included questionnaires, anthropometric measurements before surgery, assessment and interviews after surgery, and case histories. Univariate and multivariate logistic regression analysis was performed. Results. Malnutrition was detected in 53.5% of the patients. Postoperative cognitive disorder was documented in 18.2% of elderly patients. The mean length of hospital stay was 10.1 days (SD, 9.14). Multivariate logistic regression analysis revealed that the best predictors for longer hospital stay in elderly patients were malnutrition (OR, 4.2; 95% CI, 1.5–11.8; P=0.007) together with postoperative cognitive impairment (OR, 9.2; 95% CI, 1.0–83.3; P=0.048). The total predictive value of the model was 70.5%. Conclusions. Malnutrition and a postoperative cognitive disorder were independent risk factors for longer hospital stay, while depression, cognitive impairment, functional dependence, and poor physical status were not independently associated with longer hospital stay. A comprehensive geriatric assessment can help assess the risk factors for longer treatment and predict the length of hospital stay, thus enabling the planning of optimal healthcare management of elderly patients.

scholarly journals The association between hypoglycemia and glycemic variability in elderly patients with type 2 diabetes: a prospective observational study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Takahisa Handa ◽  
Akinobu Nakamura ◽  
Aika Miya ◽  
Hiroshi Nomoto ◽  
Hiraku Kameda ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Observational Study ◽  
Elderly Patients ◽  
Prospective Observational Study ◽  
Multivariate Logistic Regression Analysis ◽  
Glycemic Variability ◽  
Multivariate Logistic Regression

Abstract Background This study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes. Methods We conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%. Results In the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses. Conclusions Among elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined. Trial registration UMIN-CTR: UMIN000029993. Registered 16 November 2017

scholarly journals Risk factors for tissue expander infection in scar reconstruction: a retrospective cohort study of 2374 consecutive cases

2020 ◽  
Vol 8 ◽  
Author(s):  
Chen Dong ◽  
Minhui Zhu ◽  
Luguang Huang ◽  
Wei Liu ◽  
Hengxin Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Treatment Failure ◽  
Logistic Regression Analysis ◽  
Disease Duration ◽  
Multivariate Logistic Regression Analysis ◽  
Tissue Expansion ◽  
Multivariate Logistic Regression ◽  
Hematoma Evacuation

Abstract Background Tissue expansion is used for scar reconstruction owing to its excellent clinical outcomes; however, the complications that emerge from tissue expansion hinder repair. Infection is considered a major complication of tissue expansion. This study aimed to analyze the perioperative risk factors for expander infection. Methods A large, retrospective, single-institution observational study was carried out over a 10-year period. The study enrolled consecutive patients who had undergone tissue expansion for scar reconstruction. Demographics, etiological data, expander-related characteristics and postoperative infection were assessed. Univariate and multivariate logistic regression analysis were performed to identify risk factors for expander infection. In addition, we conducted a sensitivity analysis for treatment failure caused by infection as an outcome. Results A total of 2374 expanders and 148 cases of expander infection were assessed. Treatment failure caused by infection occurred in 14 expanders. Multivariate logistic regression analysis identified that disease duration of ≤1 year (odds ratio (OR), 2.07; p &lt; 0.001), larger volume of expander (200–400 ml vs &lt;200 ml; OR, 1.74; p = 0.032; &gt;400 ml vs &lt;200 ml; OR, 1.76; p = 0.049), limb location (OR, 2.22; p = 0.023) and hematoma evacuation (OR, 2.17; p = 0.049) were associated with a high likelihood of expander infection. Disease duration of ≤1 year (OR, 3.88; p = 0.015) and hematoma evacuation (OR, 10.35; p = 0.001) were so related to high risk of treatment failure. Conclusions The rate of expander infection in patients undergoing scar reconstruction was 6.2%. Disease duration of &lt;1 year, expander volume of &gt;200 ml, limb location and postoperative hematoma evacuation were independent risk factors for expander infection.

Risk Factors for Aortic Valve Calcification in Patients on Regular Hemodialysis

2009 ◽  
Vol 32 (3) ◽  
pp. 173-179 ◽  
Author(s):  
Dejan Petrović ◽  
Radmila Obrenović ◽  
Biljana Stojimirović
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Risk Factor ◽  
Aortic Valve ◽  
Independent Risk Factor ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Aortic Valve Calcification ◽  
Valve Calcification ◽  
Regular Hemodialysis

Introduction Aortic valve calcification (AVC) accelerates development of aortic valve stenosis and cardiovascular complications. Hyperphosphatemia is one of the key risk factors for aortic valve calcification. Aim The aim of this study was to evaluate the prevalence of AVC in patients on regular hemodialysis and to assess the impact of different factors on its appearance. Method: The study investigated a total of 115 patients treated in the Hemodialysis Department of the Urology and Nephrology Clinic at the Kragujevac Clinical Center in Serbia. The variables investigated were: serum albumin, C-reactive protein (CRP), homocysteine, total cholesterol, LDL-cholesterol (LDL-C), HDL-cholesterol (HDL-C), triglycerides (TG), Apolipoprotein A-I (Apo A-I), Apolipoprotein B (Apo B) and lipoprotein (a), calcium, phosphate and parathormone, and calcium-phosphorus product (Ca × P). Patients were evaluated by echocardiography for AVC. Statistical analysis included univariate and multivariate logistic regression analysis. Results Univariate regression analysis showed that serum phosphate levels and Ca × P are the most important risk factors for AVC (p<0.001). Multivariate logistic regression analysis revealed that hyperphosphatemia is an independent risk factor for AVC (p<0.001). Conclusion Hyperphosphatemia is an independent risk factor for aortic valve calcification.

scholarly journals Predictive risk factors for worse outcomes in COVID-19 patients with different clinical features at baseline

2021 ◽  
Author(s):  
Elisabetta Schiaroli ◽  
Anna Gidari ◽  
Giovanni Brachelente ◽  
Sabrina Bastianelli ◽  
Alfredo Villa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Critical Illness ◽  
Serum Ferritin ◽  
Logistic Regression Analysis ◽  
Severe Disease ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Neutrophil Lymphocyte Ratio

IntroductionCOVID-19 is characterized by a wide range of clinical expression and by possible progression to critical illness and death. Therefore it is essential to identify risk factors predicting progression towards serious and fatal diseases. The aim of our study was to identify laboratory predictive markers of clinical progression in patients with moderate/severe disease and in those with acute respiratory distress syndrome (ARDS).Material and methodsUsing electronic medical records for all demographic, clinical and laboratory data, a retrospective study on all consecutive patients with COVID-19 admitted to the Infectious Disease Clinic of Perugia was performed. The PaO2/FiO2 ratio (P/F) assessment cut‑off of 200 mm Hg was used at baseline to categorize the patients into two clinical groups. The progression towards invasive ventilation and/or death was used to identify critical outcome. Statistical analysis was performed. Multivariate logistic regression analysis was adopted to identify risk factors of critical illness and mortality.ResultsIn multivariate logistic regression analysis neutrophil/lymphocyte ratio (NLR) was the only significant predictive factor of progression to a critical outcome (p = 0.03) and of in-hospital mortality (p = 0.03). In ARDS patients no factors were associated with critical progression. Serum ferritin > 1006 ng/ml was the only predictive value of critical outcome in COVID-19 subjects with moderate/severe disease (p = 0.02).ConclusionsNeutrophil/lymphocyte ratio and serum ferritin are the only biomarkers that can help to stratify the risk of severity and mortality in patients with COVID-19.

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