Dexmedetomidine and Mortality From Sepsis Requiring Mechanical Ventilation: A Japanese Nationwide Retrospective Cohort Study

2020 ◽  
pp. 088506662094215
Author(s):  
Shotaro Aso ◽  
Hiroki Matsui ◽  
Kiyohide Fushimi ◽  
Hideo Yasunaga
Keyword(s):  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Propensity Score ◽  
Logistic Regression Analysis ◽  
Instrumental Variable ◽  
Diagnosis Procedure Combination ◽  
Instrumental Variable Analysis ◽  
Mechanically Ventilated ◽  
Variable Analysis

Background: Dexmedetomidine has a mild sedative effect and may reduce mortality in mechanically ventilated critically ill patients. However, few studies have examined the effects of dexmedetomidine in patients with sepsis who require mechanical ventilation. The aim of this study was to investigate the association between dexmedetomidine and mortality in patients with sepsis requiring mechanical ventilation, using a nationwide inpatient database in Japan. Methods: Using the Diagnosis Procedure Combination database from July 1, 2010, to March 31, 2016, we identified adult patients with sepsis who required mechanical ventilation for more than 2 days. Patients were divided into those who received dexmedetomidine and those who received midazolam or propofol within 1 day after admission. Logistic regression analysis, propensity score-matched analysis, and instrumental variable analysis were performed to compare all-cause 28-day mortality and duration of mechanical ventilation between the groups. Results: In total, 50 671 were eligible patients, including dexmedetomidine group (n = 13 759) and propofol or midazolam group (n = 36 912). The dexmedetomidine group had significantly lower all-cause 28-day mortality compared with the group receiving midazolam or propofol, as shown by the logistic regression analysis (odds ratio [OR]: 0.78; 95% confidence interval [CI]: 0.73-0.84), the propensity score–matched analysis (OR: 0.85; 95% CI: 0.80-0.91), and the instrumental variable analysis (OR: 0.64; 95% CI: 0.57-0.73). The duration of mechanical ventilation in the dexmedetomidine group was significantly shorter than that in the midazolam or propofol group. Conclusions: Dexmedetomidine was associated with a reduction in all-cause 28-day mortality and duration of mechanical ventilation.

scholarly journals Effect of Hypothermia in the Emergency Department on the Outcome of Trauma Patients: A Cross-Sectional Analysis

2018 ◽  
Vol 15 (8) ◽  
pp. 1769 ◽  
Author(s):  
Ting-Min Hsieh ◽  
Pao-Jen Kuo ◽  
Shiun-Yuan Hsu ◽  
Peng-Chen Chien ◽  
Hsiao-Yun Hsieh ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Body Temperature ◽  
Propensity Score ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Trauma Patients ◽  
Body Temperatures ◽  
Multivariate Logistic Regression ◽  
Mortality Outcome

This study aimed to assess whether hypothermia is an independent predictor of mortality in trauma patients in the condition of defining hypothermia as body temperatures of <36 °C. Data of all hospitalized adult trauma patients recorded in the Trauma Registry System at a level I trauma center between 1 January 2009 and 12 December 2015 were retrospectively reviewed. A multivariate logistic regression analysis was performed in order to identify factors related to mortality. In addition, hypothermia and normothermia were defined as temperatures <36 °C and from 36 °C to 38 °C, respectively. Propensity score-matched study groups of hypothermia and normothermia patients in a 1:1 ratio were grouped for mortality assessment after adjusting for potential confounders such as age, sex, preexisting comorbidities, and injury severity score (ISS). Of 23,705 enrolled patients, a total of 401 hypothermic patients and 13,368 normothermic patients were included in this study. Only 3.0% of patients had hypothermia upon arrival at the emergency department (ED). Compared to normothermic patients, hypothermic patients had a significantly higher rate of abbreviated injury scale (AIS) scores of ≥3 in the head/neck, thorax, and abdomen and higher ISS. The mortality rate in hypothermic patients was significantly higher than that in normothermic patients (13.5% vs. 2.3%, odds ratio (OR): 6.6, 95% confidence interval (CI): 4.86–9.01, p < 0.001). Of the 399 well-balanced propensity score-matched pairs, there was no significant difference in mortality (13.0% vs. 9.3%, OR: 1.5, 95% CI: 0.94–2.29, p = 0.115). However, multivariate logistic regression analysis revealed that patients with low body temperature were significantly associated with the mortality outcome. This study revealed that low body temperature is associated with the mortality outcome in the multivariate logistic regression analysis but not in the propensity score matching (PSM) model that compared patients with hypothermia defined as body temperatures of <36 °C to those who had normothermia. These contradicting observations indicated the limitation of the traditional definition of body temperature for the diagnosis of hypothermia. Prospective randomized control trials are needed to determine the relationship between hypothermia following trauma and the clinical outcome.

Is Propensity Score Analysis a Valid Surrogate of Randomization for the Avoidance of Allocation Bias?

2017 ◽  
Vol 37 (03) ◽  
pp. 275-286 ◽  
Author(s):  
José Ríos ◽  
Joaquín Saez-Peñataro ◽  
Caridad Pontes ◽  
Ferran Torres
Keyword(s):  
Propensity Score ◽  
Gold Standard ◽  
Instrumental Variable ◽  
Randomized Clinical Trials ◽  
Propensity Score Analysis ◽  
Added Value ◽  
Dynamic Allocation ◽  
Instrumental Variable Analysis ◽  
Score Analysis ◽  
Variable Analysis

AbstractRandomized clinical trials are the gold standard when experimental designs are feasible. Randomization allows the handling of allocation bias for known and unknown confounders. Specific tools such as blocking, stratification, and dynamic allocation provide additional guarantees to simple randomization. When an experimental design is not feasible, the propensity score (PS) has been shown to produce greater benefit than traditional methods (i.e., restriction, stratification, matching and adjusting). There appears to be a hierarchy in terms of the effectiveness of balancing for PS techniques: matching or weighting above stratification above covariate adjustment (which is discouraged due to its drawbacks). Instrumental variable analysis and its variants might provide added value because they aim to balance for unknown confounders as well, thus mimicking randomization, but at present, are considered more useful for sensitivity rather than primary analyses.

scholarly journals A Composite Index Predicts Disease Progression in Early Stages of COVID-19: a Propensity Score-matched Cohort Study

2020 ◽  
Author(s):  
Jianjun Xu ◽  
Shaobo Hu ◽  
Suzhen Li ◽  
Weimin Wang ◽  
Yuzhe Wu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Propensity Score ◽  
Disease Progression ◽  
Logistic Regression Analysis ◽  
Independent Predictor ◽  
Early Stage ◽  
Multivariable Logistic Regression Analysis ◽  
Matched Cohort ◽  
Early Stages

Abstract Background: Thus far, studies on COVID-19 have focused on the epidemiology of the disease and clinical characteristics of patients (14-19), as well as on the risk factors associated with mortality during hospitalization in critical COVID-19 cases. However, no research has been performed on the prediction of progression in patients in the early stages of the disease. The aim of this work was to identify the early predictors of COVID-19 progression.Methods: The study included 338 patients with COVID-19 treated at two hospitals in Wuhan, Chian, from December, 2019 to March, 2020. Predictors of the progression of COVID-19 from mild to severe stages were selected by the logistic regression analysis. The predictive accuracy was evaluated further in the propensity score-matched cohort.Results: COVID-19 progression to severe and critical stages was confirmed in 78(23.1%) patients. The average value of the neutrophil-to-lymphocyte ratio (NLR) was higher in patients in the disease progression group than in the improvement group. Multivariable logistic regression analysis revealed that elevated NLR, LDH, and IL-10, were independent predictors of disease progression. The optimal cut-off value of NLR for predicting the progression of COVID-19 was 3.75. In the propensity score-matched cohort, NLR ≥ 3.75 was still an independent predictor of COVID-19 progression after multivariate analysis.Conclusions: The performed analysis demonstrates that NLR qualifies as an independent predictor of disease progression in COVID-19 patients at the early stage of the disease. The combined evaluation of NLR and LDH improved the accuracy of the prediction of COVID-19 progression. Assessment of predictors might facilitate early identification of COVID-19 patients at high risk for disease progression and ensure timely administration of appropriate treatment to prevent mild cases from becoming severe.

scholarly journals Tracheal stenosis in prolonged mechanically ventilated patients: prevalence, risk factors, and bronchoscopic management

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Alessandro Ghiani ◽  
Konstantinos Tsitouras ◽  
Joanna Paderewska ◽  
Dieter Munker ◽  
Swenja Walcher ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Tracheal Stenosis ◽  
Percutaneous Tracheostomy ◽  
Binary Logistic Regression Analysis ◽  
Interventional Bronchoscopy ◽  
Mechanically Ventilated ◽  
Ventilated Patients

Abstract Background Various complications may arise from prolonged mechanical ventilation, but the risk of tracheal stenosis occurring late after translaryngeal intubation or tracheostomy is less common. This study aimed to determine the prevalence, type, risk factors, and management of tracheal stenoses in mechanically ventilated tracheotomized patients deemed ready for decannulation following prolonged weaning. Methods A retrospective observational study on 357 prolonged mechanically ventilated, tracheotomized patients admitted to a specialized weaning center over seven years. Flexible bronchoscopy was used to discern the type, level, and severity of tracheal stenosis in each case. We described the management of these stenoses and used a binary logistic regression analysis to determine independent risk factors for stenosis development. Results On admission, 272 patients (76%) had percutaneous tracheostomies, and 114 patients (32%) presented mild to moderate tracheal stenosis following weaning completion, with a median tracheal cross-section reduction of 40% (IQR 25–50). The majority of stenoses (88%) were located in the upper tracheal region, most commonly resulting from localized granulation tissue formation at the site of the internal stoma (96%). The logistic regression analysis determined that obesity (OR 2.16 [95%CI 1.29–3.63], P < 0.01), presence of a percutaneous tracheostomy (2.02 [1.12–3.66], P = 0.020), and cricothyrotomy status (5.35 [1.96–14.6], P < 0.01) were independently related to stenoses. Interventional bronchoscopy with Nd:YAG photocoagulation was a highly effective first-line treatment, with only three patients (2.6%) ultimately referred to tracheal surgery. Conclusions Tracheal stenosis is commonly observed among prolonged ventilated patients with tracheostomies, characterized by localized hypergranulation and mild to moderate airway obstruction, with interventional bronchoscopy providing satisfactory results.

scholarly journals Performance of Logistic Regression, Propensity Scores, and Instrumental Variable for Estimating Their True Target Odds Ratios in the Absence and Presence of Unmeasured Confounder

2020 ◽  
Author(s):  
Tianqi Yu ◽  
Chengyu Ke ◽  
Wentao Xu ◽  
Jing Li
Keyword(s):  
Logistic Regression ◽  
Propensity Score ◽  
Instrumental Variable ◽  
Propensity Scores ◽  
Unbiased Estimation ◽  
Odds Ratios ◽  
Instrumental Variable Analysis ◽  
Unmeasured Confounder ◽  
True Target ◽  
Mean Square Errors

Abstract Background: A lot of studies have compared the ability of statistical methods to control for confounding. However, a majority of studies mistakenly assumed these methods estimate the same effect. The aim of this study was to use Monte Carlo simulations to compare logistic regression, propensity scores and instrumental variable analysis for estimating their true target odds ratios in terms of bias and precision in the absence and presence of unmeasured confounder. Methods: We established the formula allowing us to compute the true odds ratio of each method. We varied the instrument’s strength and the unmeasured confounder to cover a large range of scenarios in the simulation study. We then use logistic regression, propensity score matching, propensity score adjustment and two-stage residual inclusion to obtain estimated odds ratios in each scenario. Results: In the absence of unmeasured confounder, instrumental variable without direct effect on the outcome could produce unbiased estimates as propensity score did, but the mean square errors of instrumental variable were greater. When unmeasured confounder existed, no other method could produce unbiased estimation except instrumental variable, provided that the proposed instrument is not directly related to the outcome. Using the defined instrument, which affected the outcome directly, resulted in positive biased estimation of the treatment effect and this bias was greater compared to that from other methods. Conclusions: Overall, with good implementation, instrumental variable can lead to unbiased results. However, the bias caused by violating the required assumptions of instrumental variable can overweigh the positive effect of its ability to control for unmeasured confounder.

Perioperative Diabetes Insipidus in Patients Undergoing Off-Pump Coronary Bypass Grafting Surgery: A Study on Incidence, Related Factors and Clinical Significance

2020 ◽  
Author(s):  
Peng Zhong ◽  
Zijian Guo ◽  
Jiakai Lu ◽  
Weiping Cheng ◽  
Jin Mu ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Diabetes Insipidus ◽  
Logistic Regression Analysis ◽  
Bypass Grafting ◽  
Off Pump ◽  
Ventilation Time ◽  
Icu Stay ◽  
Mechanical Ventilation Time

Abstract BackgroundPerioperative diabetes insipidus (DI) is a serious complication occurring in patients undergoing off-pump coronary artery bypass grafting (OPCABG). MethodsThis was a retrospective study of 199 patients who underwent OPCABG surgery in Anzhen hospital, Beijing, China, between January 2019 to December 2019. Patients were divided into a DI(+) group and a DI(-) group according to perioperative urine condition. The incidence of perioperative DI in patients undergoing OPCABG surgery was calculated as the main outcome. Multivariable binary logistic regression analysis was used to identify independent prognostic factors of DI.ResultsPerioperative DI occurred in 43.2% (86/199) of these patients. Mean patient age was 62.5 ± 9.0 years, and 156 (78.4%) were male. Multivariable logistic regression analysis showed a correlation between BMI(OR=0.772, 95%CI[0.670-0.890], P＜0.001), Crystal quantity(OR=1.001, 95%CI[1.000-1.001], P=0.008), perioperative Cr(OR=0.965, 95%CI[0.937-0.993], P=0.016). The DI(+) group had a significantly higher imbalance postoperative PH condition(41.9% vs 28.3%, P<0.05), higher median mechanical ventilation time than the DI(-) group (22.0 vs. 20.5, P<0.01) and higher median of ICU stay hours(27.0 vs 31.0, P=0.041).ConclusionCoronary artery disease(CAD) patients underwent OPCABG surgery were easy to have perioperative DI, which had a higher ICU stay and mechanical ventilation time than those without DI. BMI, Crystal quantity, perioperative creatinine was associated with the presence of DI. Prospective studies are needed to validate these findings.

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