scholarly journals Analysis of risk factors and preventive strategies for intracranial infection after neuroendoscopic transnasal pituitary adenoma resection

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Xin Huang ◽  
Xuejun Zhang ◽  
Jian Zhou ◽  
Gang Li ◽  
Gang Zheng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Pituitary Adenoma ◽  
Influencing Factors ◽  
Clinical Data ◽  
Univariate Analysis ◽  
Infected Group ◽  
Multivariate Logistic Regression ◽  
Intracranial Infection ◽  
Csf Leakage

Abstract Objective To analyse the risk factors for intracranial infection after neuroendoscopic transnasal pituitary adenoma resection (NTPAR) to provide a reference for the prevention and treatment of postoperative intracranial infection. Methods The clinical data of 387 patients who underwent NTPAR in the Department of Neurosurgery of the First People’s Hospital of Yichang from March 2013 to March 2021 were retrospectively analysed. The patients were divided into an infected group and a noninfected group according to the occurrence of intracranial infection. The detailed clinical data of the two groups were collected. Univariate and multivariate logistic regression was used to analyse the risk factors for intracranial infection after NTPAR. Results Among the 387 surgical patients, 32 patients (8.27%) were in the intracranially infected group and 355 patients (91.73%) were in the noninfected group. The results of the univariate analysis suggested that age > 45 years, tumour size > 1 cm, operation time > 240 min, blood loss > 400 ml, Kelly Grade of cerebrospinal fluid (CSF) leakage > Grade 2, postoperative CSF leakage, lumbar cistern drainage and blood transfusion were the influencing factors for postoperative intracranial infection, while the results of multivariate logistic regression analysis implied that intraoperative CSF leakage (Kelly Grade > 2) and postoperative CSF leakage were independent influencing factors for intracranial infection after NTPAR, and perioperative use of antibiotics was an independent protective factor for postoperative intracranial infection. Conclusions There are a variety of risk factors for intracranial infection after NTPAR, which indicates that it is necessary to develop different repair strategies for CSF leakage according to the Kelly Grade, timely treatment of postoperative CSF leakage and perioperative use of antibiotics. These measures have been shown to effectively reduce the probability of intracranial infection after NTPAR.

scholarly journals Risk Factors for and Outcomes Associated with Clinical Isolates ofEscherichia coliandKlebsiellaSpecies Resistant to Extended-Spectrum Cephalosporins among Patients Admitted to Canadian Hospitals

2009 ◽  
Vol 20 (3) ◽  
pp. e43-e48 ◽  
Author(s):  
Marianna Ofner-Agostini ◽  
Andrew Simor ◽  
Michael Mulvey ◽  
Alison McGeer ◽  
Zahir Hirji ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Care Facility ◽  
P Value ◽  
Third Generation ◽  
Multivariate Logistic Regression ◽  
Extended Spectrum ◽  
Third Generation Cephalosporins

BACKGROUND: Clinical features associated with Gram-negative bacterial isolates with extended-spectrum beta-lactamase (ESBL)- and AmpC-mediated resistance identified in Canadian hospitals is largely unknown. The objective of the present study was to determine the demographics, risk factors and outcomes of patients with ESBL- or AmpC-mediated resistant organisms in Canadian hospitals.METHODS: Patients with clinical cultures ofEscherichia coliorKlebsiellaspecies were matched with patients with a similar organism but susceptible to third-generation cephalosporins. Molecular identification of the AmpC or ESBL was determined using a combination of polymerase chain reaction and sequence analysis. Univariate and multivariate logistic regression analysis was performed to identify variables associated with becoming a case.RESULTS: Eight Canadian hospitals identified 106 cases (ESBL/AmpC) and 106 controls. All risk factors identified in the univariate analysis as a predictor of being an ESBL/AmpC cases at the 0.20 P-value were included in the multivariate analysis. No significant differences in outcomes were observed (unfavourable responses 17% versus 15% and mortality rates 13% versus 7%, P not significant). Multivariate logistic regression found an association of becoming an ESBL/AmpC case with: previous admission to a nursing home (OR 8.28, P=0.01) or acute care facility (OR 1.96, P=0.03), length of stay before infection (OR 3.05, P=0.004), and previous use of first-generation cephalosporins (OR 2.38, P=0.02) or third-generation cephalosporins (OR 4.52, P=0.01). Appropriate antibiotics were more likely to be given to controls (27.0% versus 13.3%, P=0.05) and number of days to appropriate antibiotics was longer for cases (median 2.8 days versus 1.2 days, P=0.05).CONCLUSION: The importance of patient medical history, present admission and antibiotic use should be considered for allE coliorKlebsiellaspecies patients pending susceptibility testing results.

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 Sero-epidemiological Investigation of the Major Abortive Bacterial Agents in Ewes of M’Sila Governorate, Algeria

2020 ◽  
Vol 77 (2) ◽  
pp. 24
Author(s):  
Laatra ZEMMOURI ◽  
Mohamed BESBACI ◽  
Adel MAMMERI ◽  
Mohamed LAFRI
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Univariate Analysis ◽  
Economic Losses ◽  
Epidemiological Investigation ◽  
Multivariate Logistic Regression ◽  
Serum Samples ◽  
Chlamydia Abortus ◽  
Breeding Management

The aim of this study was to evaluate the seroprevalence, risk factors and zoonotic threats of the major abortive bacterial agents in sheep of M’Sila Governorate. A total of 184 serum samples were collected from ewes among 16 sheep flocks and tested for Coxiella burnetti, Chlamydia abortus, Brucella spp. and Salmonella abortusovis via ELISA. Simultaneously, a questionnaire was used to collect breeding management data. Seropositive results were as follows : Coxiella burnetti (27.9%), Salmonella abortusovis (15.9%), Chlamydia abortus (10.9%) and Brucella spp. (3.8%).The use of univariate analysis and multivariate logistic regression showed a highly significant correlation between Coxiella burnetti seropositivity and presence of cats in farms (OR = 5.75; 95% CI = 1.86-19.9; p= 0.001), while promiscuity with newly introduced animals was associated to Chlamydia abortus seropositivity (OR=3.37; 95%CI=1.01-14.9; p= 0.04). Additionally to the economic losses, the dissemination of Coxiella burnetti and Brucella spp. presents uncontrollable zoonotic hazards.

scholarly journals To Analyze the Influencing Factors of Senile Coronary Heart Disease Patients Complicated with Frailty Syndrome

2022 ◽  
Vol 2022 ◽  
pp. 1-6
Author(s):  
Tian Qin ◽  
Wang Sheng ◽  
Guoheng Hu
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Logistic Regression ◽  
Uric Acid ◽  
Heart Disease ◽  
Cell Count ◽  
Influencing Factors ◽  
Neutrophil Count ◽  
Frailty Syndrome ◽  
Multivariate Logistic Regression

To analyze the influencing factors of senile coronary heart disease patients complicated with frailty syndrome. A total of 80 elderly patients with coronary heart disease admitted to our hospital from March 2020 to March 2021 were selected as the research subjects. The Fried Frailty Symptom Scale was used to evaluate whether the 80 patients were complicated with frailty syndrome. According to the evaluation results, the patients were divided into a nonfrailty syndrome group (52 cases in total) and frailty syndrome group (28 cases in total). Clinical data of two groups of patients were collected, and multivariate logistic regression was used to analyze the influencing factors of senile coronary heart disease patients complicated with frailty syndrome. Among 80 patients, the incidence of frailty syndrome was 35.00% (28/80), including 18 cases in early frailty and 10 cases in frailty stage. Univariate analysis showed that age, body mass (BMI), diabetes mellitus, congestive heart failure, chronic renal insufficiency, chronic obstructive pulmonary disease (COPD), tumor, high uric acid hematic disease, arrhythmia, interleukin-6 (IL-6), c-reactive protein (CRP), fibrinogen (FIB), brain natriuretic peptide (BNP), uric acid (UA), serum creatinine (Scr), serum protein (ALB), white blood cell count (WBC), and neutrophil count were the possible risk factors for senile coronary heart disease complicated with frailty syndrome ( P  < 0.05). Multivariate logistic regression analysis showed that combined COPD, combined tumor, IL-6, BNP, UA, SCR, ALB, and neutrophil count were independent risk factors for senile CHD complicated with frailty syndrome ( P  < 0.05). Combined with COPD, combined with tumor, IL-6, BNP, UA, SCR, ALB, and neutron cell count are the influencing factors for senile coronary heart disease patients complicated with frailty syndrome. These factors can be used as the basis for the diagnosis of frailty syndrome and guide the clinical development of targeted diagnosis and treatment plan.

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 Prevalence and risk factors of depression and anxiety for inpatients with lung cancer in China: A hospital-based cross-sectional study

2022 ◽  
Author(s):  
Xueqian Wang ◽  
Xuejiao Ma ◽  
Mo Yang ◽  
Yan Wang ◽  
Yi Xie ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Logistic Regression ◽  
Risk Factor ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression Model ◽  
Depression And Anxiety ◽  
Multivariate Logistic Regression ◽  
Cross Sectional

Abstract Background Lung cancer was often accompanied by depression and anxiety. Nowadays, most investigations for depression and anxiety were concentrated in western medical hospitals, while few related studies have been carried out in the tradition Chinese medicine (TCM) ward. It was necessary to understand the prevalence and risk factors of depression and anxiety in the inpatients with lung cancer in TCM hospital. Methods This study adopted cross-sectional research method, which enrolled a total of 222 inpatients with lung cancer in TCM hospital. PHQ-9 and GAD-7 scales were used to assess depression and anxiety for the inpatients, respectively. Demographic and clinical data were also collected. Statistical methods of the univariate analysis and the multivariate logistic regression model were used. Results The prevalence of depression and anxiety in the inpatients with lung cancer were 58.1% and 34.2%, respectively. Multivariate logistic regression analysis prompted that the common risk factor of depression and anxiety was the symptom of insomnia. Constipation and gender were the two anther risk factors of depression. Conclusion Depression and anxiety were common for the inpatients with lung cancer in TCM hospital. Gender, insomnia and constipation were risk factors for depression, and insomnia was risk factor for anxiety. Therefore, medical workers should pay close attention to the emotional changes of these high-risk patients and intervene the symptoms as early as possible.

scholarly journals Risk factors and prediction model construction of post-operative atrial fibrillation after thoracic surgery in Chinese patients

2021 ◽  
Author(s):  
Yunling Lin ◽  
Jianmin Sun ◽  
Xun Yuan ◽  
Hui Liu
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Thoracic Surgery ◽  
Prediction Model ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Chinese Patients ◽  
Multivariate Logistic Regression ◽  
Post Operative Atrial Fibrillation

IntroductionThe purpose of this study was to analyze the risk factors of post-operative atrial fibrillation (POAF) after thoracic surgery, and to build a predictive model for accurate preoperative identification of high-risk patients.Material and methodsIn this study, data of 2072 patients with pulmonary masses and esophageal cancer who attended our hospital in the period from January 1, 2017 to December 31, 2018 were analyzed retrospectively. According to whether AF occurred after the operation, the patients were divided into atrial fibrillation (AF) and non-AF (NAF) groups. The general information (age, sex, height, etc.), previous medical history (chronic lung disease, hypertension, etc.), medication history, preoperative ultrasound and cardiogram results, and preoperative and postoperative electrocardiogram (ECG) were collected. The operation mode, resection scope, histopathology and hospitalization were recorded. Univariate and multivariate logistic regression were used to screen out the risk factors of AF and establish a prediction model.ResultsThe incidence of POAF was 5.98%. Univariate analysis showed that sex, age, body mass index, left atrial diameter and operation organ were the risk factors of POAF. The above factors were included in the multivariate logistic regression analysis, and the results showed that male sex, age, anteroposterior diameter of left atrium and surgical organs were related to POAF. On this basis, a POAF prediction model was constructed, which had good discrimination and calibration. The area under the curve (AUC) is 0.784 with 95% CI: 0.746–0.822.ConclusionsThe prediction model of POAF based on the risk factors selected in this study can accurately predict the occurrence of AF after thoracic surgery.

scholarly journals Assessment of severity of illness on admission using SICK score and evaluation of the risk factors associated with mortality in children admitted in a paediatric urban tertiary care centre in south India

2021 ◽  
Vol 8 (4) ◽  
pp. 636
Author(s):  
N. Rajeshwari ◽  
A. Savitha ◽  
J. Prahada
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Univariate Analysis ◽  
Tertiary Care ◽  
Assisted Ventilation ◽  
Receiver Operating Curve ◽  
Multivariate Logistic Regression Model ◽  
Operating Characteristics ◽  
Multivariate Logistic Regression ◽  
Receiver Operating

Background: “Signs of inflammation that can kill” (SICK) score is one of the severities scoring systems used for predicting outcome of children at admission. The aim of the present study was to study the clinical and demographic profile of children admitted to Paediatric ward, to assess the usefulness of SICK score in predicting the mortality and evaluate the risk factors in predicting mortality.  Methods: SICK scoring was done for 369 children on admission. The outcome was recorded as death or discharge. The associated factors were analysed using SPSS software package analysis. Receiver operating curve was used to arrive at the cut-off point of SICK score for predicting mortality. Quantitative data differences between children who died and children who were discharged from the hospital were analysed using student independent t test. Need for assisted ventilation, presence of shock, age less than 3 years, and SICK score>2 were studied to find their association with mortality. Statistical analysis was done using univariate analysis and those factors that were significantly associated with mortality were subjected multivariate logistic regression analysis.Results: The performance of SICK score was “excellent” in discriminating between death and survival with area under the receiver operating characteristics curve 0.94. Age<3-year presence of shock, need for mechanical ventilation and SICK score>2 showed statistically significant association with mortality as evidenced by multivariate logistic regression model.  Conclusions: SICK score performed extremely well in predicting mortality on admission. Age<3 years, SICK score>2, Presence of Shock and need for assisted ventilation showed statistically significant association with mortality.

scholarly journals Coxiella Burnetii in Horses of Algeria: Seroprevalence and Associated Risk Factors

2020 ◽  
Vol 10 (4) ◽  
pp. 602-608
Author(s):  
Samir Ansel ◽  
Karima Benfodil ◽  
Abdellah Mohamed Cherif ◽  
Amine Abdelli ◽  
Rachid Kaidi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Coxiella Burnetii ◽  
Q Fever ◽  
Univariate Analysis ◽  
Small Ruminants ◽  
Water Source ◽  
Enzyme Linked Immunosorbent Assay ◽  
Multivariate Logistic Regression ◽  
Prophylactic Measures

The Q fever is a worldwide zoonotic disease caused by Coxiella burnetii (an obligate intracellular bacterium). This pathogen affects humans, ruminants, equines, carnivores, rodents, and birds. A cross-sectional study was carried out from March 2017 to May 2018 to assess the seroprevalence and identify the risk factors of C. burnetii infection in horses (Equus Caballus) residing in three districts of Algerian, namely Tiaret, El-Bayadh, and Ghardaia. Serum samples collected from 182 horses were analyzed via enzyme-linked immunosorbent assay (ELISA). Association of seropositivity with potential risk factors related to animals (e.g., age, gender, breed, housing, and presence of ticks), breeding characteristics (e.g., geographical localization, contact with animals), and environmental characteristics (i.e., presence of water source) was analyzed by univariate and multivariate logistic regression. An overall seroprevalence of 9.9% (18/182) was obtained. The univariate analysis of risk factors for C. burnetii seroprevalence demonstrated higher seropositivity in horses that had contact with small ruminants (p=0.004) and dromedaries (p=0.002) as well as in those living near a water source (p=0.036) and in El-Bayadh district (p=0.005). The multivariate logistic regression analysis indicated that the risk of C. burnetii infection was significantly higher in horses that were in contact with small ruminants (RR: 15.6). Algeria is endemic for Q fever in horses and prophylactic measures must be taken to reduce /prevent its transmission to animals and humans.

scholarly journals A Novel Nomogram for Predicting the Risk of Short-Term Recurrence After Surgery in Glioma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Tianwei Wang ◽  
Chihao Zhu ◽  
Shuyu Zheng ◽  
Zhijun Liao ◽  
Binghong Chen ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clinical Data ◽  
Univariate Analysis ◽  
Concurrent Chemotherapy ◽  
Age At Diagnosis ◽  
Recurrent Glioma ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Short Term ◽  
Glioma Recurrence

ObjectiveThe aim of this study was to establish a nomogram model for predicting the risk of short-term recurrence in glioma patients.MethodsThe clinical data of recurrent glioma patients were summarized and analyzed in this study. Univariate and multivariate logistic regression analyses were performed to analyze the correlation between clinical data and the risk of short-term recurrence after operation. A nomogram was established based on the multivariate logistic regression model results.ResultsA total of 175 patients with recurrent glioma were enrolled, with 53 patients in the short-term recurrence (STR) group (recurrent time ≤6 months) and 122 patients in the long-term recurrence (LTR) group (recurrent time ≥36 months). Univariate analysis revealed that age at diagnosis, Karnofsky performance scores (KPSs), tumor location, glioma grade, glioma type, extent of resection (EOR), adjuvant chemotherapy (ad-CT), concurrent chemotherapy (co-CT), and isocitrate dehydrogenase (IDH) status were significantly associated with the short-term glioma recurrence. Multivariate analyses revealed that age at diagnosis, KPS, glioma grade, EOR, and IDH were independent risk factors for short-term glioma recurrence. A risk nomogram for the short-term recurrence of glioma was established, with the concordance index (C-index) of 0.971. The findings of calibration and receiver operating characteristic (ROC) curves showed that our nomogram model had good performance and discrimination to estimate short-term recurrence probability.ConclusionThis nomogram model provides reliable information about the risk of short-term glioma recurrence for oncologists and neurosurgeons. This model can predict the short-term recurrence probability and give assistance to decide the interval of follow-up or formulate individualized treatment strategies based on the predicted results. A free online prediction risk tool for this nomogram is provided: https://rj2021.shinyapps.io/Nomogram_ recurrence-risk/.

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