scholarly journals Early immunosuppression was associated with poor prognosis in elderly patients with sepsis: secondary analysis of the ETASS study

2020 ◽  
Author(s):  
Fei Pei ◽  
Guanrong Zhang ◽  
Lixin Zhou ◽  
Jiyun Liu ◽  
Gang Ma ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Elderly Patients ◽  
Hospital Mortality ◽  
Poor Prognosis ◽  
Regression Models ◽  
Immune Status ◽  
The Elderly ◽  
Logistic Regression Models ◽  
Definition Of

Abstract Background: Although immunosuppression has been investigated in adult septic patients, early immune status remains unclear. In this study, we aimed to assess early immune status in adult patients with sepsis stratified by age and its relevance to hospital mortality. Methods: From post hoc analysis of a multicenter, randomized controlled trial, 273 patients whose levels of monocyte human leukocyte antigen-DR (mHLA-DR) were obtained within 48 hours after onset of sepsis were enrolled. All patients were divided into elderly (≥60yrs) group and non-elderly (<60yrs) group. Early immune status was evaluated by the percentage of mHLA-DR in total monocytes within 48 hours after onset of sepsis and it was classified as immunosuppression (mHLA-DR≤30%) or non-immunosuppression (>30%). Changes in immune status were assessed by the value change in mHLA-DR on day 3 compared with the first measurement. Three logistic regression models were conducted to test the associations between early immunosuppression and hospital mortality. We also did a sensitivity analysis to find out if the definition of early immune status (24 vs. 48 hours after onset of sepsis) affects the outcomes. Results: Of the 181 elderly and 92 non-elderly septic patients, 71 (39.2%) elderly and 25 (27.2%) non-elderly died in hospital. The percentage of early immunosuppression in the elderly was twice of that of the non-elderly patients (32% vs. 16%, p=0.006). Immunosuppressed elderly had higher hospital mortality than the non-immunosuppressed elderly (53.4% vs. 32.5%, p=0.009), but there was no significant difference in mortality between immunosuppresed non-elderly patients and non-immunosuppressed non-elderly patients (33.5% vs. 26.0%, p=0.541). In all of the three logistic regression models, we found that early immunosuppression was independently associated with increased hospital mortality in elderly, but not in non-elderly patients. Sensitivity analysis further confirmed the definition of early immune status did not affect the outcomes. In addition, immune status improvement on day 3 was associated with reduced hospital mortality in both elderly and non-elderly patients. Conclusion: In adult patients with sepsis, the elderly were more susceptible to early immunosuppression after onset of sepsis. Early immunosuppression was independently associated with poor prognosis in elderly patients. Trial registration: ClinicalTrials.gov NCT00711620 , 9 July 2008, https://clinicaltrials.gov/ct2/show/NCT00711620

In-hospital mortality after traumatic brain injury surgery: a nationwide population-based comparison of mortality predictors used in artificial neural network and logistic regression models

2013 ◽  
Vol 118 (4) ◽  
pp. 746-752 ◽  
Author(s):  
Hon-Yi Shi ◽  
Shiuh-Lin Hwang ◽  
King-Teh Lee ◽  
Chih-Lung Lin
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Hospital Mortality ◽  
Regression Models ◽  
Logistic Regression Model ◽  
Global Sensitivity Analysis ◽  
Ann Model ◽  
Logistic Regression Models ◽  
Global Sensitivity

Object Most reports compare artificial neural network (ANN) models and logistic regression models in only a single data set, and the essential issue of internal validity (reproducibility) of the models has not been adequately addressed. This study proposes to validate the use of the ANN model for predicting in-hospital mortality after traumatic brain injury (TBI) surgery and to compare the predictive accuracy of ANN with that of the logistic regression model. Methods The authors of this study retrospectively analyzed 16,956 patients with TBI nationwide who were surgically treated in Taiwan between 1998 and 2009. For every 1000 pairs of ANN and logistic regression models, the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow statistics, and accuracy rate were calculated and compared using paired t-tests. A global sensitivity analysis was also performed to assess the relative importance of input parameters in the ANN model and to rank the variables in order of importance. Results The ANN model outperformed the logistic regression model in terms of accuracy in 95.15% of cases, in terms of Hosmer-Lemeshow statistics in 43.68% of cases, and in terms of the AUC in 89.14% of cases. The global sensitivity analysis of in-hospital mortality also showed that the most influential (sensitive) parameters in the ANN model were surgeon volume followed by hospital volume, Charlson comorbidity index score, length of stay, sex, and age. Conclusions This work supports the continued use of ANNs for predictive modeling of neurosurgery outcomes. However, further studies are needed to confirm the clinical efficacy of the proposed model.

Abstract P394: Association Between Admission Dehydration and In-Hospital Mortality in Patients With Intracerebral Hemorrhage

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Bin Gao ◽  
Hongqiu Gu ◽  
Shimeng Liu ◽  
Qi Zhou ◽  
Kang Kaijiang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Intracerebral Hemorrhage ◽  
Hospital Mortality ◽  
Blood Urea Nitrogen ◽  
Regression Models ◽  
Fluid Management ◽  
Urea Nitrogen ◽  
Logistic Regression Models ◽  
Acute Intracerebral Hemorrhage ◽  
Stroke Center

Background and purpose: Our aim was to investigate the associations between dehydration status at admission and in-hospital mortality in patients with intracerebral hemorrhage. Methods: Data of consecutive patients with intracerebral hemorrhage between August 2015 and July 2019 based on China Stroke Center Alliance (CSCA) were analyzed. The patients were stratified based on the blood urea nitrogen (BUN) to creatinine (CR) ratio (BUN/CR) on admission, into dehydrated (BUN/CR ≥ 15) and non-dehydrated (BUN/CR < 15) groups. Data were analyzed with multi-variate logistic regression models to analyze the risks of death at hospital and baseline dehydration status. Results: A total number of 84043 patients with intracerebral hemorrhage were included in the study. The median age of patients on admission was 63.0 years, and 37.5% of them were women. Based on the baseline BUN/CR, 59153 (70.4%) patients were classified into dehydration group. Patients with admission dehydration (BUN/CR ≥ 15) had 13% lower risks of in-hospital mortality than those without dehydration (BUN/CR < 15, adjusted OR=0.87, 95%CI: [0.78-0.96]). In patients aged <65 years, patients with baseline dehydration (BUN/CR ≥ 15) showed 19% lower risks of in-hospital mortality (adjusted OR=0.81, 95%CI: [0.70-0.94].adjusted p=0.0049) than non-dehydrated patients (BUN/CR<15). Conclusion: Admission dehydration is associated with lower in-hospital mortality in intracerebral hemorrhage,which provides an imaging clue that fluid management could be important for acute intracerebral hemorrhage.

scholarly journals Examine the Association between Metabolic Syndrome and Frailty in an Older Asian Population

2021 ◽  
Author(s):  
Hiep Huu Hoang Dao ◽  
Anh Trung Nguyen ◽  
Huyen Thi Thanh Vu ◽  
Tu Ngoc Nguyen
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Sex Education ◽  
Regression Models ◽  
Asian Population ◽  
Frailty Phenotype ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Asian Populations ◽  
Definition Of

Background: There has been evidence that metabolic syndrome (MetS) may increase the risk of frailty. However, there is limited evidence on this association in Asian populations. Aims: This study aims to identify the association between MetS and frailty in older people in Vietnam. Methods: This is a cross-sectional analysis of a dataset obtained from an observational study on frailty and sarcopenia in patients aged &ge;60 at a geriatric hospital in Vietnam. Frailty was defined by the frailty phenotype. Participants were defined as having MetS if they had &ge;3 out of 5 criteria from the definition of the National Cholesterol Education Program (NCEP) Adults Treatment Panel (ATP) III. Multiple logistic regression models were performed to estimate the risk of having frailty in patients with MetS. Results: There were 669 participants (mean age 71, 60.2% female), 62.3% had MetS and 39.0% was frail. The prevalence of frailty was 42.2% in participants with MetS, 33.7% in participants without MetS (p=0.029). On logistic regression models, MetS was associated with increased likelihood of being frail (adjusted OR 1.52, 95%CI 1.01-2.28), allowing for age, sex, education, nutritional status, history of hospitalisation and chronic diseases. Conclusion: There was a significant association between MetS and frailty in this population. Further longitudinal studies are required to confirm this association.

scholarly journals Use of plasma lactate level to predict 28-day mortality in non-elderly and elderly sepsis patients based on the MIMIC-III database

2020 ◽  
Author(s):  
Yihua Dong ◽  
Xiaoyang Miao ◽  
Yufeng Hu ◽  
Yueyue Huang ◽  
Jie Chen ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Elderly Patients ◽  
Lactate Level ◽  
Regression Models ◽  
Logistic Regression Model ◽  
Plasma Lactate ◽  
Logistic Regression Models ◽  
Lactate Levels ◽  
Plasma Lactate Level

Abstract Purpose: We co mpared the use of lactate level for predicting 28-day mortality in non-elderly (<65 years) and elderly (≥65 years) sepsis patients who were admitted to an intensive care unit (ICU). A multivariate logistic regression model was established to predict 28-day mortality for each group. Methods: This retrospective study used the Medical Information Mart for Intensive Care Ⅲ, a publicly available database of ICUs. Eligible sepsis patients were at least 18 years-old, hospitalized for at least 24 h, and had lactate levels measured in the ICU. Univariate logistic regression analysis and step-wise multivariable logistic regression models were used to identify factors associated with 28-day mortality. Results: The 28-day mortality was 30.9% among the 2482 patients, and was significantly greater in elderly than non-elderly patients. Within each age group, the lactate level was greater for non-survivors than survivors. Among non-survivors, the lactate level was significantly higher for the non-elderly than the elderly. Adjusted logistic regression analysis showed that non-elderly patients with lactate levels of 2.0–4.0 mmol/L and above 4.0 mmol/L had greater risk of death than those with normal lactate levels. For all patients, the stepwise logistic regression model had an area under the receiver operating curve (AUROC) of 0.752; for non-elderly patients, the model had an AUROC of 0.793; for elderly patients, the model had an AUROC of 0.711. The Hosmer-Lemeshow test indicated acceptable goodness-of-fit for each group (P=0.206, P=0.646, and P= 0.482, respectively). Conclusion: In our population of sepsis patients, the lactate level was about 0.9 mmol/L lower in elderly non-survivors than non-elderly survivors. A plasma lactate level above 2.0 mmol/L was an independent risk factor for death at 28-days among non-elderly patients. Our logistic regression models effectively predicted 28-day mortality of sepsis patients in different age groups.

In-Hospital Mortality and Trends Associated with Splenectomy in Patients with Immune-Mediated Thrombocytopenia (ITP).

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 1398-1398
Author(s):  
Samantha M. Jaglowski ◽  
John C. Byrd ◽  
Jeffrey A. Jones
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Mortality Risk ◽  
Medical Management ◽  
Regression Models ◽  
Multivariate Logistic Regression ◽  
Logistic Regression Models ◽  
Risk Of Death ◽  
Teaching Status ◽  
Observation Period

Abstract Abstract 1398 Poster Board I-420 Background: Splenectomy remains a standard treatment for ITP patients not responding to medical management, but anecdotal reports suggest that use of the procedure is in decline. We studied patterns of use and outcome of splenectomy performed for ITP at the population level. Methods: Using data from the Nationwide Inpatient Sample and ICD-9 diagnosis and procedure codes, we identified 39,543 splenectomies among hospital admissions including a diagnosis of ITP (ICD-9 287.3) from 1993-2005. Admissions were characterized by patient and hospital facility characteristics. Laparascopic procedures were identified by published procedure coding algorithms. Factors influencing in-hospital mortality for 2005 were further evaluated using multivariate logistic regression models. Results: Annual estimates for incidence of splenectomy are displayed in Figure 1. Between 1993 and 2005, there was a decrease in the total number of splenectomies performed for ITP, with the most significant drop occurring from 1997 to 2000, concurrent with the FDA approval of rituximab. Over the same period, there has been an increase in the proportion of splenectomies performed laparoscopically from 3.4% to 18.6%. Patient gender, age, presence of comorbid malignancy, and Charlson score were not significantly associated with type of splenectomy procedure. Among facility factors, only hospital teaching status was a statistically significant predictor of laparoscopic splenectomy use, early but not later in the observation period. On an annual basis, in-hospital mortality did not vary significantly over the observation period, with risks ranging from 1.5% (95% CI 0.83-2.86%) in 1993 to 4% (95% CI 2.8%-5.7%) in 1997. Annual mortality risk between open and laparoscopic procedures likewise did not significantly differ. However, over the total 13-year observation period there was a >60% increased risk of death with an open versus laparoscopic procedure (OR 1.669, p<0.0001). In 2005, 2869 splenectomy procedures were performed. Multivariate logistic regression models for in-hospital mortality that year found that presence of a malignancy (OR 9.65, p=0.003) significantly increased mortality risk. Charlson comorbidity approached statistical significance (0 v. ≥1, OR 6.83, p=0.087). Hospital bed-size (OR 0.87, p=0.73), location (rural v. urban, OR 3.80, p=0.127), and teaching status (OR 0.39, p=0.203) were not significantly associated with outcome. Conclusions: While the overall mortality risk from splenectomy in ITP is low, it is influenced by the presence of malignancy and other comorbid conditions. Further studies designed to evaluate newer medical management strategies (e.g. rituximab, thrombopoeitin mimetics, etc.) versus surgical intervention in these higher-risk populations are warranted. Disclosures: No relevant conflicts of interest to declare.

Multiple Myeloma in the Afro-Caribbean Inner City Population: Conventional Cytogenetics and Survival

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 5710-5710
Author(s):  
Dhvani Thakker ◽  
Charles Yun ◽  
Adam Goldrich ◽  
Helzner Elizabeth ◽  
Daniel Fein ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Logistic Regression ◽  
Survival Data ◽  
Poor Prognosis ◽  
Regression Models ◽  
Chromosome Banding ◽  
Newly Diagnosed ◽  
Cytogenetic Abnormalities ◽  
Logistic Regression Models ◽  
Adjusted Logistic Regression

Abstract Background: Multiple Myeloma (MM) is the second most common hematologic malignancy in the United States. African Americans have among the highest risks of MM and MGUS with several distinct features compared to existing literature. Furthermore, the prevalence of MM is even higher in the Afro-Caribbean population. Cytogenetic and molecular genetic abnormalities predict outcome in patients with MM. Hyperdiploid MM (H-MM) generally has a better prognosis than nonhyperdiploid MM (NH-MM). In addition, patients with additional chromosome 1 abnormalities, loss of chromosome 13, translocation t(14;16) and t(4;14) tend to have a worse survival while patients with translocations t(11;14) are associated with improved survival. In our patient population, the most common cytogenetic abnormalities and their effect on survival remain unknown. Objective: This study was performed to establish a profile of Afro-Caribbean patients with newly diagnosed Multiple Myeloma in order to gain further insight into unique cytogenetic abnormalities and their effects on survival. Methods: Patients with Multiple Myeloma at Kings County Hospital Center and University Hospital at Brooklyn from 2000-2013 were identified by our tumor registries (n=311). We included all the newly diagnosed patients from 2000-2013 who underwent a bone marrow biopsy and conventional cytogenetic by chromosome banding and FISH (n= 173). Patients who did not have a cytogenetic analysis were excluded. Data was collected at the time of initial presentation to include demographics and cytogenetic abnormalities. Survival data was obtained from Social Security Death Index. Differences in frequency of each cytogenetic abnormality by mortality status were examined using Chi-Square or Fisher’s Exact Tests. Two sets of age-adjusted logistic regression models were used to examine potential cytogenetic correlates of both poor (less than two years) and good (4 years or more) survival. Data analysis was performed using SPSS Advanced Statistics. Results: The median age at the time of diagnosis was 65 (Range 36-90). Chromosome banding and FISH showed abnormal cytogenetics in 46% of our patients (n=79). These patients were also found to have multiple abnormal clones. NH-MM was found in 24% (n=19) and H-MM was found in 39% (n=31) of the 79 patients. The most commonly affected abnormalities were trisomiesof odd-numbered chromosomes; +1 (47%), +3 (19%), +5 (21%), +7 (24%), +9 (47%), +11 (42%), +15 (44%), +17 (9%) and +19 (29%). Thirty five percent of 173 patients have expired (n=60). The median survival in the deceased patients was 6.2 years (Range 0.34-12.9). When we examined all patients who lived greater than four years post-diagnosis (n=152), we found significant abnormalities including +5 (p=0.052), NH-MM (p=0.009) and t(11;14) (p=0.03) (See Table 1). Indicators of poor prognosis including 1q gain (p=0.13), loss of chromosome 13 (p=0.21) and del17 (p=0.08) were not significant. In patients who are living, 19% (n=29) have not yet reached the four-year post-diagnosis survival. Less than ten percent underwent autologous stem cell transplantation. Excludes patients who lived less than 3 months post diagnosis August 5 2014 Table 1: Age-Adjusted Logistic Regression Models Predicting Good Survival (lived 4 years or more post-diagnosis) Chromosome abnormality ( + gain, - loss) Age-Adjusted Odds Ratio (95% CI) N=152 P-value 1+ 0.77 (0.26, 2.29) 0.63 1- 2.91 (0.58, 14.57) 0.19 3+ 1.05 (0.35, 3.17) 0.93 5+ 0.47 (0.22, 1.00) 0.052 7+ 0.39 (0.14, 1.10) 0.08 11+ 0.80 (0.36, 1.75) 0.57 14+ 2.07 (0.62, 6.91) 0.24 15+ 0.74 (0.34,1.60) 0.44 19+ 1.20 (0.46, 3.13) 0.71 X- 0.42 (0.11, 1.50) 0.18 Y- 0.40 (0.13, 1.26) 0.12 Hyperdiploidy 0.88 (0.39, 2.00) 0.88 Nonhyperdiplody 0.24 (0.08, 0.70) 0.009 t(4;14) 0.76 (0.27, 2.15) 0.60 t(11;14) 0.18 (0.04, 0.86) 0.03 Conclusion: In this group of Afro-Caribbean patients, median survival (6 years) was higher than Surveillance, Epidemiology, and End Results (SEER) data and more recent review of literature. Gain of chromosome 5 and t(11;14) are consistent with existing data for good prognosis. However, NH-MM which is usually an indicator of poor prognosis was also highly significant in the four-year post-diagnosis survival. This further supports the notion that prognostic value of cytogenetic analysis in this population requires further exploration. Disclosures No relevant conflicts of interest to declare.

scholarly journals Primary admission and secondary transfer of trauma patients to Dutch level I and level II trauma centers: predictors and outcomes

2021 ◽  
Author(s):  
Claire R. L. van den Driessche ◽  
Charlie A. Sewalt ◽  
Jan C. van Ditshuizen ◽  
Lisa Stocker ◽  
Michiel H. J. Verhofstad ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Trauma Center ◽  
Regression Models ◽  
Trauma Patients ◽  
Trauma Centers ◽  
Logistic Regression Models ◽  
Level Ii ◽  
Secondary Transfer ◽  
Level I

Abstract Purpose The importance and impact of determining which trauma patients need to be transferred between hospitals, especially considering prehospital triage systems, is evident. The objective of this study was to investigate the association between mortality and primary admission and secondary transfer of patients to level I and II trauma centers, and to identify predictors of primary and secondary admission to a designated level I trauma center. Methods Data from the Dutch Trauma Registry South West (DTR SW) was obtained. Patients ≥ 18 years who were admitted to a level I or level II trauma center were included. Patients with isolated burn injuries were excluded. In-hospital mortality was compared between patients that were primarily admitted to a level I trauma center, patients that were transferred to a level I trauma center, and patients that were primarily admitted to level II trauma centers. Logistic regression models were used to adjust for potential confounders. A subgroup analysis was done including major trauma (MT) patients (ISS > 15). Predictors determining whether patients were primarily admitted to level I or level II trauma centers or transferred to a level I trauma center were identified using logistic regression models. Results A total of 17,035 patients were included. Patients admitted primarily to a level I center, did not differ significantly in mortality from patients admitted primarily to level II trauma centers (Odds Ratio (OR): 0.73; 95% confidence interval (CI) 0.51–1.06) and patients transferred to level I centers (OR: 0.99; 95%CI 0.57–1.71). Subgroup analyses confirmed these findings for MT patients. Adjusted logistic regression analyses showed that age (OR: 0.96; 95%CI 0.94–0.97), GCS (OR: 0.81; 95%CI 0.77–0.86), AIS head (OR: 2.30; 95%CI 2.07–2.55), AIS neck (OR: 1.74; 95%CI 1.27–2.45) and AIS spine (OR: 3.22; 95%CI 2.87–3.61) are associated with increased odds of transfers to a level I trauma center. Conclusions This retrospective study showed no differences in in-hospital mortality between general trauma patients admitted primarily and secondarily to level I trauma centers. The most prominent predictors regarding transfer of trauma patients were age and neurotrauma. These findings could have practical implications regarding the triage protocols currently used.

Definition of At-Risk Occlusal Surfaces of Permanent Molars—A Descriptive Study

2009 ◽  
Vol 34 (1) ◽  
pp. 35-42 ◽  
Author(s):  
M Muller-Bolla ◽  
F Courson ◽  
D Droz ◽  
L Lupi-Pégurier ◽  
AM Velly
Keyword(s):  
At Risk ◽  
Logistic Regression ◽  
Regression Models ◽  
Descriptive Study ◽  
Occlusal Surface ◽  
Multivariate Logistic Regression ◽  
Logistic Regression Models ◽  
Occlusal Surfaces ◽  
Permanent Molars ◽  
Definition Of

The objective of this descriptive study was to define the at-risk occlusal surface to guide the practitioner in the decision of whether to seal or not. Method: All dentists affiliated with the French Society of Pediatric Odontology (SFOP) and general practitioners (GP) registered in postgraduate courses in three French dental schools answered the same questionnaire illustrating four occlusal surfaces of permanent molars. It was focused on obtaining an optimal definition of an at-risk occlusal surface. The corresponding four molars were later sectioned to check the answers. Univariate logistic regression analyses and multivariate logistic regression models were tested to identify the factors associated with the at-risk occlusal surface. Results:Eighty-six SFOP dentists and 136 GP filled in the form. Multivariate logistic regression models stratified by type of practice demonstrated that stained fissures (p=0.001) were only associated with at-risk occlusal surface among GP and the morphology of primary fissure (p=0.001) when considering SFOP dentists alone. The multivariate analyses demonstrated that stained fissures, and primary and secondary fissures were linked to the perception of an at-risk occlusal surface. Conclusion: An at-risk occlusal surface has narrow and deep primary fissures. Numerous secondary fissures could increase the risk. The coloration of fissures should not be used in the definition because it depends on tooth integrity.

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