PurposeAlthough chronic low back pain (CLBP) has profound effects on patients, society, and economy, its causes are difficult to identify. Psychogenic effects or social stress is known to affect CLBP; hence, investigation of its underlying causes requires a multifactorial approach. We determined the factors associated with CLBP by using an Internet-based survey. To prevent CLBP, we need to understand its cause and background.Patients and methodsA total of 1000 participants either with (+) or without (−) CLBP answered the Japanese Orthopaedic Association Back Pain Evaluation Questionnaire (JOABPEQ), which assesses five domains of CLBP: low back pain, lumbar function, walking ability, social life function and mental health. We also administered a new questionnaire for participants, that comprised five different domains: Body, Lifestyle, Emotion, Diet, and Social. To evaluate psychogenic effects on CLBP, we added two original factors, namely outshout and HIE, which have not yet been studied. HIE is a traditional concept (sense) of “feeling cold” or “chilly.” All participants completed both questionnaires.ResultsMultivariate logistic regression analysis extracted four factors (sleep, room temperature, outshout, and HIE) that were associated with CLBP. The mental health domain was assessed using the JOABPEQ for each of these factors. The factors outshout and HIE differed between CLBP (+) and CLBP (−) patients. CLBP (−) participants also showed a difference in Sleep and HIE factors.ConclusionAmong psychogenic effects, Emotion was common to all the four extracted factors. There was no common physical divisor. Therefore, we hypothesized that acute low back pain might develop into CLBP in the presence of psychological stress or other emotional factors such as outshout or HIE. Hence, we need to consider both physical and psychogenic effects in the prevention and treatment of CLBP. Furthermore, appropriate evaluation and treatment of psychological stress may be effective in reducing CLBP.

Combination therapy with IFX plus AZA appears to be a cost-effective treatment for drug-refractory CD when compared with IFX monotherapy. Furthermore, the additional lymphoma risk of combination therapy has little significance on its cost-effectiveness.

An accurate diagnosis of acute appendicitis in the early stage is often difficult, and decision support tools to improve such a diagnosis might be required. This study compared the levels of accuracy of artificial neural network models and logistic regression models for the diagnosis of acute appendicitis. Data from 169 patients presenting with acute abdomen were used for the analyses. Nine variables were used for the evaluation of the accuracy of the two models. The constructed models were validated by the ".632+ bootstrap method". The levels of accuracy of the two models for diagnosis were compared by error rate and areas under receiver operating characteristic curves. The artificial neural network models provided more accurate results than did the logistic regression models for both indices, especially when categorical variables or normalized variables were used. The most accurate diagnosis was obtained by the artificial neural network model using normalized variables.

Objective:We investigated the relationships between body weight (BWt) and metabolic syndrome (MS) risk factors to elucidate the effect of BWt (ΔBWt) change and body mass index (BMI) on these factors in the Japanese population.Methods:Data were collected on MS-related parameters measured during two annual examinations of 16,640 men (mean age: 41.7±11.6 years) and 10,184 women (mean age: 45.0±12.2 years) without prior treatment of hypertension, diabetes mellitus, or dyslipidemia in 2006 and 2011 in Fukuoka, Japan. The subjects were divided into three groups according to BMI in 2006 (low, middle and high BMI) and into three groups according to change in BMI between 2006 and 2011 (decreased, stable, and increased BMI). Mean values for blood pressure (BP), systolic BP (SBP), diastolic BP (DBP), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), hemoglobin A1c (HbA1c), and fasting blood glucose (FBG) for each group were determined by sex and subjected to statistical analysis for comparison.Results:High BMI (>26) was associated with higher SBP, LDL-C, FBG, and TG in both sexes. An increase ≥ 1.1 BMI units in 5 years was associated with increased DBP, LDL-C, TG, HbA1c, and FBG and decreased HDL-C. In contrast, decreased BMI was associated with decreased BP and LDL-C and increased HDL-C in both sexes, and decreased TG in men and FBG in women.Conclusions:Maintaining a desirable weight or losing weight may help prevent hypertension and MS, even in non-obese individuals.

Aim This study evaluated an online mental health literacy intervention to improve help‐seeking for psychosis amongst parents of adolescents. Methods A total of 2496 parents of first‐grade junior high school students, recruited from a Japan‐based survey company, participated in a randomized controlled trial in July 2016; participants were randomly allocated to the intervention (n = 1248) or control group (n = 1248). They were assessed at baseline and one‐week post intervention. The intervention group received a 30‐minute online educational programme that included a narrative of the mother of an adolescent with psychosis. Results There were no between‐group differences in changes in the rate of ‘no help‐seeking’ in any hypothetical situations of a child's psychosis and prodromal symptoms. Conclusions The intervention might have been suboptimal to improve mental health literacy for psychosis amongst parents of adolescents. A narrative message from a service user may be helpful to encourage parents in help‐seeking.