scholarly journals Factors associated with the occurrence of prehospital medical interventions provided by physicians among non-trauma patients: a single-centre retrospective observational study in Japan

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e029186
Author(s):  
Tomohiro Abe ◽  
Kenshi Iwatani ◽  
Takeshi Aoyama ◽  
Tatsunori Ameda ◽  
Hidenobu Ochiai
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Observational Study ◽  
Multiple Logistic Regression Analysis ◽  
Trauma Patients ◽  
Multiple Logistic Regression ◽  
Disease Category ◽  
Transportation Time ◽  
Factors Associated ◽  
Category Type

ObjectivesPhysician-staffed prehospital units are widely used in many countries. The criteria for predicting fatal injury are well recognised for trauma victims, but there are no criteria for predicting critical condition for non-trauma patients. This study aimed to identify the factors associated with non-trauma cases receiving prehospital interventions by physicians.DesignRetrospective observational study.SettingPhysician-staffed prehospital unit (car) at a single-base hospital in a suburban city in Japan.ParticipantsParticipants were 1058 non-trauma patients who received prehospital medical examinations from April 2014 to December 2017.Outcome measuresThe outcome was the occurrence of physician-only interventions (POIs) exceeding paramedics’ competencies. Univariate analysis and multiple logistic regression analysis were performed. Patient’s age and gender, presumed disease category, type of location of the emergency, time of alarm, activation time, activator’s occupation, time to arrival, transportation time and the destination facility were included as covariates.ResultsPOIs were provided to 380 (36%) patients. Patient’s age, presumed disease category, type of location of the emergency, activator’s occupation, time to arrival, transportation time and the destination facility were identified as potential independent factors. Multiple logistic regression analysis found that patient’s age, presumed disease category, type of location of the emergency, transportation time and destination facility were the significant independent factors. Transportation times of more than 15 min (adjusted ORs (AORs)=4.17, 95% CI 2.59 to 6.72, p<0.01) or 10 to 14 min (AOR=3.66, 95% CI 2.32 to 5.79, p<0.01) and patient age of 40–59 years (AOR=3.16, 95% CI 1.66 to 6.01, p<0.01) were the strongest independent factors.ConclusionsThis study identified the factors associated with non-trauma cases receiving prehospital POIs. Patient’s age, presumed disease category, type of location of the emergency and transportation time are independent factors associated with requiring POIs.

scholarly journals Analysis and Factors Associated with Measles in Larut, Matang and Selama Districts, Perak, Malaysia

2020 ◽  
Vol 27 (5) ◽  
pp. 130-140
Author(s):  
Asraf Ahmad Qamruddin ◽  
Reza Qamruddin ◽  
Ayu Malik
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Incidence Rate ◽  
Logistic Regression Analysis ◽  
Protective Factor ◽  
Multiple Logistic Regression Analysis ◽  
Prior History ◽  
Multiple Logistic Regression ◽  
Case Definitions ◽  
Factors Associated

Objectives: To determine the incidence rate of measles and the factors associated with confirmed measles cases in Larut, Matang and Selama districts. Methods: Cross-sectional analysis was carried out looking at all suspected and laboratoryconfirmed measles cases in Larut, Matang and Selama districts between 2015 and 2019. Multiple logistic regression analysis was used to determine the associated factors for laboratory-confirmed measles cases. Results: The incidence rate for suspected measles showed an increasing trend from 2015–2019. For laboratory-confirmed measles cases, the incidence rate showed more variation with an increase to 36.11 per million population in 2017 from 5.67 per million population in 2015. The incidence rate later decreased to 10.99 per million population in 2018 and increased again to 24.47 per million population in 2019. From multiple logistic regression analysis, cases that fulfilled the case definition of measles were more likely to be laboratory-confirmed measles. On the other hand, a prior history of measles immunisation was a protective factor. Conclusion: Measles incidence is increasing in trend. Any suspected measles cases that fulfilled the clinical case definitions need to be further investigated. Immunisation should be promoted as they are effective in preventing and eliminating measles.

scholarly journals Factors Associated with the 30-Day and 1-Year Smoking Abstinence of Women in Korea: The Effect of Nicotine Dependency, Self-Efficacy, and Mental Illness

2021 ◽  
Vol 18 (21) ◽  
pp. 11171
Author(s):  
Bo-Yoon Jeong ◽  
Min-Kyung Lim ◽  
Sang-Hwa Shin ◽  
Yu-Ri Han ◽  
Jin-Kyoung Oh ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Smoking Cessation ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Self Efficacy ◽  
Multiple Logistic Regression Analysis ◽  
Multiple Logistic Regression ◽  
Factors Associated ◽  
Nicotine Dependency

Despite the success of tobacco control efforts in reducing smoking rates during the past 50 years, data on the factors contributing to quitting success are still lacking. Smoking-related mortality among women has also not declined. Therefore, this study aimed to characterize sociodemographic features, smoking-related behaviors, mental illness, and smoking cessation in woman smokers in Korea who were registered in the Quitline program. Furthermore, factors associated with 30-day and 1-year successful smoking cessation after enrollment in the Quitline program were investigated. A total of 3360 adult woman Quitline users from 2007 to 2018 were included in the final analysis, with information on their age, education level, marital status, body mass index, frequency of alcohol consumption per month, nicotine dependency, self-efficacy for smoking cessation, presence of a smoking cessation supporter, and mental health history collected upon registration with the Quitline program in Korea. Their cessation outcome was investigated with a 1-year follow-up until the end of 2019. A multiple logistic regression analysis was conducted to identify factors associated with smoking cessation at the 30-day and 1-year follow-ups. The results of the multiple logistic regression analysis indicated that lower nicotine dependency, higher self-efficacy, and the presence of a smoking cessation supporter improved the odds of smoking cessation at the 30-day and 1-year follow-ups. In contrast, users with a mental health condition were less likely to achieve smoking cessation. Incorporating methods to increase self-efficacy in women who decide to quit smoking will contribute to facilitating more attempts to quit and achieving greater success in smoking cessation among woman smokers.

scholarly journals 447 - Risk factors associated with sleep disturbance in a general elderly Japanese population: The Arao Cohort Study

2020 ◽  
Vol 32 (S1) ◽  
pp. 167-167
Author(s):  
Kazuki Honda ◽  
Tomohisa Ishikawa ◽  
Ryuji Fukuhara ◽  
Seiji Yuki ◽  
Yusuke Miyagawa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cohort Study ◽  
Sleep Disturbance ◽  
Logistic Regression Analysis ◽  
Barthel Index ◽  
Multiple Logistic Regression Analysis ◽  
Multiple Logistic Regression ◽  
Factors Associated

[Background]Sleep disturbance is a common symptom in elderly people. However, the associated risk factors have not been completely clarified. We examined possible risk factors associated with sleep disturbance in a community-based Japanese cohort study.[Methods]1521 community-dwelling individuals aged 65 years or older were selected from a consecutive series at a cohort study from 2016 to 2018 in Arao city, where located at south part of Japan. In this survey, the clinical valuables were collected as follows: age, sex, occupational status, education, lifestyle information, medical history, EuroQoL(EQ)-5D (a score of health-related quality of life [QOL]), Barthel index (a score of performance in activities of daily living), a score of Geriatric Depression Scale (GDS) and a score of Mini-Mental State Examination (MMSE). Sleep disturbance was assessed by the Pittsburgh Sleep Quality Index (when the global score was 6 or over, sleep disturbance was determined to be present). Multiple logistic regression analysis was used to examine the association between clinical valuables and sleep disturbance. This research was supported by AMED (Japan Agency for Medical Research and Development) under Grant Number JP18dk0207025h0003 and has been approved by the research ethics committee of Kumamoto University. Informed consent was obtained from all participants and their family members.[Results]Multiple logistic regression analysis revealed that Parkinson disease (Odds ratio[OR]=5.59), living alone (OR=1.93), liver disease (OR=1.89), hyperlipidemia (OR=1.36), higher score of GDS (OR=1.14), lower scores of both EQ-5D index (OR=1.11) and Barthel index (OR=1.03) were significantly associated as risk factors with sleep disturbance. Unexpectedly, lower score of MMSE was not a significant risk factor.[Conclusion]These results suggest that several physical illnesses, solitude, depressive symptoms and lower QOL, but not cognitive impairment, might be crucial risk factors associated with sleep disturbance in elderly population.

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

2019 ◽  
Vol 19 (1) ◽  
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.

Factors associated with prolonged psychiatric intensive care unit admission at Somdet Chaophraya Institute of Psychiatry, Thailand

2020 ◽  
Vol 16 (1) ◽  
pp. 9-14
Author(s):  
Poom Chompoosri ◽  
Thatsani Kunchanaphongphan
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Multiple Logistic Regression Analysis ◽  
Compulsory Admission ◽  
Multiple Logistic Regression ◽  
Factors Associated

Aim: Our objective is to determine factors associated with prolonged psychiatric intensive care unit (PICU) admission at Somdet Chaophraya Institute of Psychiatry (SCIP).<br/> Method: We reviewed the medical records of patients admitted to the PICU between 1 July 2016 and 31 December 2016 meeting PICU admission criteria. We defined prolonged admission as PICU clinical stay of longer than five days. We then performed univariate binary logistic regression analysis to analyse the association between factors and prolonged PICU admission. Factors with p-value <0.25 were then included in backward stepwise multiple logistic regression analysis.<br/> Results: We included 293 cases then excluded 42 of them using our exclusion criteria (30 were discharged by other means and 12 cases were due to inability to obtain essential information). Of 251 studied cases, 112 cases (44.6%) had prolonged PICU admission. Univariate logistic regression analysis found that a history of prior PICU admission, compulsory admission, treatment with electroconvulsive therapy (ECT), and primary diagnosis were associated with prolonged PICU admission with p-value <0.25. Using multiple logistic regression analysis, factors associated with prolonged PICU admission were: compulsory admission (adjusted odds ratio 2.45, 95% CI 1.06–5.69 when adjusted with treatment with ECT) and treatment with ECT during PICU admission (adjusted odds ratio 9.01, 95% CI 2.57–31.59 when adjusted with compulsory admission).<br/> Conclusions: Factors associated with prolonged PICU admission at SCIP were compulsory admission and treatment with ECT during PICU admission. We propose that further study of these two groups should provide clues on how to improve treatment in PICU.

Psychiatric diagnoses and their influencing factors in patients complaining of sleep problems: A study of a psychiatric consultation-liaison service

2018 ◽  
Vol 53 (3) ◽  
pp. 197-206 ◽  
Author(s):  
Yan Chen ◽  
Enyan Yu ◽  
Zhengluan Liao ◽  
Yunfei Tan ◽  
Yaju Qiu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Psychiatric Disorders ◽  
Logistic Regression Analysis ◽  
Sleep Problems ◽  
Multiple Logistic Regression Analysis ◽  
Recognition Rate ◽  
Psychiatric Diagnoses ◽  
Multiple Logistic Regression ◽  
Factors Associated

Objective This study aimed to identify misdiagnosed or undiagnosed psychiatric disorders and the factors associated with these disorders in patients with sleep problems who are referred to a consultation-liaison service. Method Records of all inpatients receiving a consultation from the Psychiatry Department between January and December 2016 were retrospectively reviewed. Psychiatric diagnoses were analyzed using descriptive statistics, and the factors associated with the risk of these disorders in patients with sleep problems were determined by multiple logistic regression analysis. Results Of the 331 referral patients whose referral reason was simply having trouble in sleeping, only 97 patients were diagnosed with primary sleep disorder after consultation. The recognition rate of psychiatric disorders in inpatients with sleep problems among nonpsychiatric physicians was 29.3%. Anxiety (107, 45.7%) was the most common psychiatric diagnosis in patients with sleep problems followed by organic mental disorder (83, 35.5%), depression (37, 15.8%), and other mental disorders (8, 3.4%). Multiple logistic regression analysis revealed that a course >1 month (OR = 3.656, 95% CI = 2.171–6.156, p = 0.000) and sleep–wake rhythm disturbances (OR = 25.008, 95% CI = 5.826–107.341, p = 0.000) were associated with increased risks of psychiatric disorders. Conclusions The study showed that recognition rate of psychiatric disorders in inpatients with sleep problems was very low. A course >1 month and sleep–wake rhythm disturbances were associated with increased risks of disorders and could be used as indicators by nonpsychiatric physicians to improve diagnoses.

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