Patient age affects sex-based differences in post-traumatic mortality: a national trauma registry study in Japan

Abstract Purpose Sex-based differences in post-traumatic mortality have been widely discussed for quite some time. We hypothesized that age-related pathophysiologic changes would affect sex-based differences in post-traumatic mortality and aimed to verify the hypothesis using a nationwide trauma registry in Japan. Methods This was a retrospective analysis of trauma patients registered in The Japanese Trauma Data Bank. We stratified the study population into the following three subsets based on age: (1) pediatric subset (age ≤ 14), (2) adult subset (age 15–50) and (3) senior adult subset (age ≥ 51). We evaluated both sex-based differences in mortality in each subset separately using multivariate logistic regression analysis and the two-way interaction effect for predicted survival between the continuous increase of age and the sexes using a nonlinear multivariate regression model. Results We included 122,819 trauma patients who fulfilled the inclusion criteria and classified them into the 3 subsets according to age. Male patients were more likely to die compared to female patients only in the senior adult subset (adjusted odds ratio: 1.26; 95% confidence interval: 1.18–1.36), whereas there were no statistically significant differences in the other two subsets. Furthermore, non-linear logistic regression analysis revealed that predicted survival probability in male patients decreased more sharply in accordance with the increase of age compared to that in female patients (p for interaction: 0.051). Conclusion Age-related change in post-traumatic mortality was significantly different between males and females, and male patients had a relatively higher risk of death in the older population.

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Sex-Disaggregated Data on Clinical Characteristics and Outcomes of Hospitalized Patients With COVID-19: A Retrospective Study

Frontiers in Cellular and Infection Microbiology ◽

10.3389/fcimb.2021.680422 ◽

2021 ◽

Vol 11 ◽

Author(s):

Mengdie Wang ◽

Nan Jiang ◽

Changjun Li ◽

Jing Wang ◽

Heping Yang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Clinical Characteristics ◽

Random Effect ◽

Hospitalized Patients ◽

Male And Female ◽

Female Patients ◽

Disease Outcomes ◽

Male Patients

BackgroundSex and gender are crucial variables in coronavirus disease 2019 (COVID-19). We sought to provide information on differences in clinical characteristics and outcomes between male and female patients and to explore the effect of estrogen in disease outcomes in patients with COVID-19.MethodIn this retrospective, multi-center study, we included all confirmed cases of COVID-19 admitted to four hospitals in Hubei province, China from Dec 31, 2019 to Mar 31, 2020. Cases were confirmed by real-time RT-PCR and were analyzed for demographic, clinical, laboratory and radiographic parameters. Random-effect logistic regression analysis was used to assess the association between sex and disease outcomes.ResultsA total of 2501 hospitalized patients with COVID-19 were included in the present study. The clinical manifestations of male and female patients with COVID-19 were similar, while male patients have more comorbidities than female patients. In terms of laboratory findings, compared with female patients, male patients were more likely to have lymphopenia, thrombocytopenia, inflammatory response, hypoproteinemia, and extrapulmonary organ damage. Random-effect logistic regression analysis indicated that male patients were more likely to progress into severe type, and prone to ARDS, secondary bacterial infection, and death than females. However, there was no significant difference in disease outcomes between postmenopausal and premenopausal females after propensity score matching (PSM) by age.ConclusionsMale patients, especially those age-matched with postmenopausal females, are more likely to have poor outcomes. Sex-specific differences in clinical characteristics and outcomes do exist in patients with COVID-19, but estrogen may not be the primary cause. Further studies are needed to explore the causes of the differences in disease outcomes between the sexes.

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15081769 ◽

2018 ◽

Vol 15 (8) ◽

pp. 1769 ◽

Cited By ~ 6

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.

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Effect of acute alcohol intoxication on mortality, coagulation, and fibrinolysis in trauma patients

PLoS ONE ◽

10.1371/journal.pone.0248810 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0248810

Author(s):

Il-Jae Wang ◽

Byung-Kwan Bae ◽

Young Mo Cho ◽

Suck Ju Cho ◽

Seok-Ran Yeom ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Hospital Mortality ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Alcohol Intoxication ◽

Trauma Patients ◽

Blood Alcohol ◽

Fibrinolysis Shutdown

Background The effect of alcohol on the outcome and fibrinolysis phenotype in trauma patients remains unclear. Hence, we performed this study to determine whether alcohol is a risk factor for mortality and fibrinolysis shutdown in trauma patients. Materials and methods A total of 686 patients who presented to our trauma center and underwent rotational thromboelastometry were included in the study. The primary outcome was in-hospital mortality. Logistic regression analysis was performed to determine whether alcohol was an independent risk factor for in-hospital mortality and fibrinolysis shutdown. Results The rate of in-hospital mortality was 13.8% and blood alcohol was detected in 27.7% of the patients among our study population. The patients in the alcohol-positive group had higher mortality rate, higher clotting time, and lower maximum lysis, more fibrinolysis shutdown, and hyperfibrinolysis than those in the alcohol-negative group. In logistic regression analysis, blood alcohol was independently associated with in-hospital mortality (odds ratio [OR] 2.578; 95% confidence interval [CI], 1.550–4.288) and fibrinolysis shutdown (OR 1.883 [95% CI, 1.286–2.758]). Within the fibrinolysis shutdown group, blood alcohol was an independent predictor of mortality (OR 2.168 [95% CI, 1.030–4.562]). Conclusions Alcohol is an independent risk factor for mortality and fibrinolysis shutdown in trauma patients. Further, alcohol is an independent risk factor for mortality among patients who experienced fibrinolysis shutdown.

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Association between Reproductive Span and Sarcopenia

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18010154 ◽

2020 ◽

Vol 18 (1) ◽

pp. 154

Author(s):

Eun Young Park ◽

Kyoung Hee Han ◽

Tae Ha Chung ◽

Nam Yun Kim ◽

Ji Min Lee ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Physical Inactivity ◽

Dietary Habits ◽

Multiple Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

National Institutes Of Health ◽

Health And Nutrition ◽

Age Related

Sarcopenia is defined as an age-related loss of skeletal muscle and is associated with several health disorders. Causes of sarcopenia, which included physical inactivity, alcohol, dietary habits, and smoking, have been researched. The present study was undertaken to examine the association between reproductive span and sarcopenia in Korean women. Data obtained from 2008 to 2011 Korea National Health and Nutrition Examination Surveys (KNHANES) were analyzed. We defined sarcopenia based on the cut-off values of the Foundation for the National Institutes of Health (FNIH) sarcopenia project criteria: ASM/BMI < 0.512 for women. Reproductive span was defined as years from menarche to menopause, and we divided the 3970 study subjects into three groups by reproductive span tertile. Multivariate logistic regression analysis was used to determine adjusted ORs for the relation between reproductive span and sarcopenia. The prevalence of sarcopenia in the study was 17.7% (704 of 3970). Multiple logistic regression analysis was performed using weighted populations. After adjusting for covariates, reproductive span was found to be inversely associated with the risk of sarcopenia [Tertile 1 = 1 (reference); Tertile 2, odds ratio (OR) = 0.927, 95% confidence interval (CI) = 0.863–0.995; Tertile 3, OR = 0.854, 95% CI = 0.793–0.915].

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Association of Japan Coma Scale score on hospital arrival with in-hospital mortality among trauma patients

BMC Emergency Medicine ◽

10.1186/s12873-019-0282-x ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 2

Author(s):

Tetsuya Yumoto ◽

Hiromichi Naito ◽

Takashi Yorifuji ◽

Toshiyuki Aokage ◽

Noritomo Fujisaki ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Hospital Mortality ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Trauma Patients ◽

Multiple Logistic Regression ◽

Point Scale ◽

Hospital Arrival ◽

Coma Scale

Abstract Background The Japan Coma Scale (JCS) score has been widely used to assess patients’ consciousness level in Japan. JCS scores are divided into four main categories: alert (0) and one-, two-, and three-digit codes based on an eye response test, each of which has three subcategories. The purpose of this study was to investigate the utility of the JCS score on hospital arrival in predicting outcomes among adult trauma patients. Methods Using the Japan Trauma Data Bank, we conducted a nationwide registry-based retrospective cohort study. Patients 16 years old or older directly transported from the trauma scene between January 2004 and December 2017 were included. Our primary outcome was in-hospital mortality. We examined outcome prediction accuracy based on area under the receiver operating characteristic curve (AUROC) and multiple logistic regression analysis with multiple imputation. Results A total of 222,540 subjects were included; their in-hospital mortality rate was 7.1% (n = 15,860). The 10-point scale JCS and the total sum of Glasgow Coma Scale (GCS) scores demonstrated similar performance, in which the AUROC (95% CIs) showed 0.874 (0.871–0.878) and 0.878 (0.874–0.881), respectively. Multiple logistic regression analysis revealed that the higher the JCS score, the higher the predictability of in-hospital death. When we focused on the simple four-point scale JCS score, the adjusted odds ratio (95% confidence intervals [CIs]) were 2.31 (2.12–2.45), 4.81 (4.42–5.24), and 27.88 (25.74–30.20) in the groups with one-digit, two-digit, and three-digit scores, respectively, with JCS of 0 as a reference category. Conclusions JCS score on hospital arrival after trauma would be useful for predicting in-hospital mortality, similar to the GCS score.

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Age-Related Disparities in Stroke Knowledge Among Community Older Adults

Frontiers in Neurology ◽

10.3389/fneur.2021.717472 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiaochuan Liu ◽

Huiwen Gui ◽

Sichen Yao ◽

Zhongcheng Li ◽

Jing Zhao

Keyword(s):

Risk Factors ◽

Older Adults ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Oldest Old ◽

Multivariate Logistic Regression Analysis ◽

Bulletin Board ◽

Age Related ◽

Stroke Knowledge

Background: This study aimed to investigate the disparities in stroke knowledge between older adults and the oldest old.Methods: Family physicians conducted a cross-sectional survey through face-to-face interviews with the older and oldest old adults of two suburban communities in the Minhang district, Shanghai between October 1, 2020, and November 30, 2020. All participants were classified as oldest old (age ≥80 years) and older adults (age 60–79 years). Between-group differences in stroke knowledge were investigated by multivariate logistic regression analysis.Results: Overall, 466 older adults including 101 (21.67%) oldest old persons were qualified. Older adults were more familiar with the risk factors and symptoms of stroke than the oldest old. By multivariable logistic regression analysis, older adults were more familiar with the following risk factors: smoking [odds ratio (OR) 0.32, 95% confidence interval (CI) 0.16–0.61], alcohol abuse (OR 0.45, 95% CI 0.23–0.87), dyslipidemia (OR 0.51, 95% CI 0.31–0.85), and obesity (OR 0.30, 95% CI 0.17–0.53) than the oldest old. Regarding stroke symptoms, older adults were more aware regarding vision alteration (OR 0.42, 95% CI 0.25–0.69) and face-drop (OR 0.57, 95% CI 0.35–0.95) than the oldest old. The oldest old were less aware of acute stroke therapy (OR 0.11, 95% CI 0.02–0.48) and calling the emergency medical service (OR 0.30, 95% CI 0.12–0.70) than older adults. Finally, the older adults used television (OR 0.53, 95% CI 0.28–1.0), WeChat (OR 0.21, 95% CI 0.05–0.89), and the community bulletin board (OR 0.43, 95% CI 0.23–0.80) as knowledge sources more than the oldest old.Conclusion: The older adults and the oldest old had significantly high disparities in stroke knowledge. Given the aging population across China, the life expectancy is expected to be longer in future decades. These differences should be addressed in stroke educational campaigns targeting the oldest old.

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Association betweenHelicobacter pyloriInfection and Risk of Osteoporosis in Elderly Taiwanese Women with Upper Gastrointestinal Diseases: A Retrospective Patient Record Review

Gastroenterology Research and Practice ◽

10.1155/2014/814756 ◽

2014 ◽

Vol 2014 ◽

pp. 1-5 ◽

Cited By ~ 6

Author(s):

Shih-Chun Lin ◽

Malcolm Koo ◽

Kun-Wei Tsai

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

Gastrointestinal Diseases ◽

Multivariate Logistic Regression ◽

Female Patients ◽

H Pylori ◽

Record Review ◽

Upper Gastrointestinal

Introduction. Helicobacter pylori (H. pylori)infection could lead to chronic local and systemic immune response. The resulting increase in proinflammatory cytokines could affect bone resorption and might increase the risk of osteoporosis. This study aimed to investigate the association betweenH. pyloriinfection and osteoporosis in elderly female patients with upper gastrointestinal diseases.Methods. A retrospective patient record review study was conducted in a regional teaching hospital in south Taiwan. Relevant information on female patients aged 65 and over who were diagnosed with diseases of esophagus, gastric ulcer, or duodenal ulcer during January 2008 to December 2010 were abstracted. Association betweenH. pyloriinfection and osteoporosis was evaluated using multivariate logistic regression analysis.Results. Of the 365 patients with a mean age of 77.3 years, 77 (21.1%) hadH. pyloriinfection and 101 (27.7%) had been diagnosed with osteoporosis. Multivariate logistic regression analysis revealed that osteoporosis was significantly associated withH. pyloriinfection (adjusted odds ratio = 2.03, 95% confidence interval = 1.14–3.62) after adjusting for age group, body mass index group, and use of proton pump inhibitor.Conclusion. Osteoporosis was found to be associated withH. pyloriinfection in Taiwanese female patients with upper gastrointestinal diseases. Further studies with information on potential confounders are needed to confirm the association.

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Sjögren’s Syndrome: The Clinical Spectrum of Male Patients

Journal of Clinical Medicine ◽

10.3390/jcm9082620 ◽

2020 ◽

Vol 9 (8) ◽

pp. 2620 ◽

Cited By ~ 1

Author(s):

Loukas Chatzis ◽

Vasileios C. Pezoulas ◽

Francesco Ferro ◽

Saviana Gandolfo ◽

Valentina Donati ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Sjogren’S Syndrome ◽

Sjogren's Syndrome ◽

Data Driven ◽

Multivariable Logistic Regression Analysis ◽

Multivariable Logistic Regression ◽

Male Patients ◽

Sjögren‘S Syndrome

Background: To compare the clinical, serological and histologic features between male and female patients with Sjögren’s syndrome (SS) and explore the potential effect of gender on lymphoma development. Methods: From a multicenter population (Universities of Udine, Pisa and Athens, Harokopion and Ioannina (UPAHI)) consisting of consecutive SS patients fulfilling the 2016 ACR/EULAR criteria, male patients were identified, matched and compared with female controls. Data-driven multivariable logistic regression analysis was applied to identify independent lymphoma-associated factors. Results: From 1987 consecutive SS patients, 96 males and 192 matched female controls were identified and compared. Males had a higher frequency of lymphoma compared to females (18% vs. 5.2%, OR = 3.89, 95% CI: 1.66 to 8.67; p = 0.0014) and an increased prevalence of serum anti-La/SSB antibodies (50% vs. 34%, OR = 1.953, 95% CI: 1.19 to 3.25; p = 0.0128). No differences were observed in the frequencies of lymphoma predictors between the two genders. Data-driven multivariable logistic regression analysis revealed negative association of the female gender with lymphoma and positive association with lymphadenopathy. Conclusion: Male SS patients carry an increased risk of lymphoma development. Although statistics showed no difference in classical lymphoma predictors compared to females, data-driven analysis revealed gender and lymphadenopathy as independent lymphoma-associated features.

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Lipoprotein(a) and coronary artery disease in Chinese postmenopausal female patients: a large cross-sectional cohort study

Postgraduate Medical Journal ◽

10.1136/postgradmedj-2019-136591 ◽

2019 ◽

Vol 95 (1128) ◽

pp. 534-540 ◽

Cited By ~ 1

Author(s):

Shuo-Lin Liu ◽

Na-Qiong Wu ◽

Yuan-Lin Guo ◽

Cheng-Gang Zhu ◽

Ying Gao ◽

...

Keyword(s):

Coronary Artery Disease ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Coronary Artery ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Lipoprotein A ◽

Female Patients ◽

Artery Disease

BackgroundIt has been reported that lipoprotein(a) (Lp(a)) is associated with the risk of cardiovascular disease. The present study aimed to examine the association of Lp(a) levels with the presence and severity of coronary artery disease (CAD) in female patients.MethodsA total of 3712 female patients who received coronary angiography were consecutively enrolled. The levels of Lp(a) were measured and compared among patients with or without CAD, myocardial infarction and menopause. Spearman correlation analysis and logistic regression analysis were used to examine the association of Lp(a) with the presence of CAD and the severity of coronary atherosclerosis assessed by Gensini score (GS).ResultsThe average of Lp(a) levels was elevated as age increased in female subjects. Notably, women after menopause had higher Lp(a) levels compared with that before menopause (16.8 mg/dL (IQR 7.54–41.12 mg/dL) vs 14.7 mg/dL (IQR 6.72–30.82 mg/dL), p=0.002). Furthermore, multiple logistic regression analysis identified that Lp(a)>30 mg/dL was an independent risk factor of CAD in the postmenopausal females (OR: 1.33, 95% CI: 1.08 to 1.63, p=0.007). Finally, Lp(a) had a positive correlation with GS (r=0.11, p<0.001), and Lp(a)>30 mg/dL was an independent risk factor for high GS (OR: 1.43, 95% CI: 1.14 to 1.79, p=0.02) in the postmenopausal females.ConclusionCirculating Lp(a) levels were independently associated with the presence and severity of CAD in the postmenopausal females, suggesting that Lp(a) may be useful for prevention and risk-stratification of CAD in female individuals.

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Optimizing Pelvic X-Ray indication in blunt trauma patients using clinical criteria

Revista do Colégio Brasileiro de Cirurgiões ◽

10.1590/0100-6991e-20202624 ◽

2020 ◽

Vol 47 ◽

Author(s):

JÚLIO PATROCÍNIO MORAES ◽

JOSÉ GUSTAVO PARREIRA ◽

PEDRO DE SOUZA LUCARELLI-ANTUNES ◽

GIOVANNA ZUCCHINI RONDINI ◽

JACQUELINE ARANTES GIANNINNI PERLINGEIRO ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Blunt Trauma ◽

Trauma Registry ◽

Probability Model ◽

Pelvic Fractures ◽

Trauma Patients ◽

Pelvic Examination ◽

X Ray ◽

Clinical Criteria

ABSTRACT Objective: to identify a subgroup of blunt trauma patients with very low chance of sustaining pelvic fractures based on clinical criteria. Methods: retrospective analysis of the trauma registry data, collected in a period of 24 months. We selected adult blunt trauma patients who had a PXR on admission. The frequency of pelvic fractures was calculated for the following groups: Normal neurological examination at admission (NNE), hemodynamical stability (HS), normal pelvic examination at admission (NPE), less than 60 years old (ID<60) and absence of distracting injuries (ADI). Logistic regression analysis was carried out in order to create a probability model of negative PXR. Results: an abnormal PXR was identified in 101 (3.3%) out of the 3,055 patients who had undergone a PXR at admission. Out of these, 1,863 sustained a NNE, with 38 positive CXRs (2.0%) in this group. Considering only the 1,535 patients with NNE and HS, we found 28 positive PXRs (1.8%). Out of these, 1,506 have NPE, with 21 abnormal PXRs (1.4%). Of these, 1,202 were younger than 60 y, with 11 positive PXRs (0.9%). By adding all these criteria to the ADI, we found 2 abnormal PXRs in 502 (0.4%) cases. The probability model including all these variables had a 0,89 area under the ROC curve. Conclusions: by adding clinical criteria, it is possible to identify a group of trauma patients with very low chance of sustaining pelvic fractures. The necessity of PXR in these patients needs to be reassessed.

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