Effectiveness of antipsychotics for managing agitated delirium in patients with advanced cancer: a secondary analysis of a multicenter prospective observational study in Japan (Phase-R).

PURPOSE: Delirium is a common and serious comorbidity in patients with advanced cancer, necessitating effective management. Nonetheless, effective drugs for managing agitated delirium in patients with advanced cancer remain unclear in real-world settings. Thus, the present study aimed to explore an effective pharmacotherapy for this condition. METHODS: We conducted a secondary analysis of a multicenter prospective observational study in Japan. The analysis included patients with advanced cancer who presented with agitated delirium and received pharmacotherapy. Agitation was defined as a score of the Richmond Agitation-Sedation Scale for palliative care (RASS-PAL) of ≥ 1. The outcome was defined as -2 ≤ RASS-PAL ≤ 0 at 72 h after the initiation of pharmacotherapy. Multiple propensity scores were quantified using a multinomial logistic regression model, and adjusted odds ratios (ORs) were calculated for haloperidol, chlorpromazine, olanzapine, quetiapine, and risperidone. RESULTS: The analysis included 271 patients with agitated delirium, and 87 (32%) showed -2 ≤ RASS-PAL ≤ 0 on day 3. The propensity score-adjusted OR of olanzapine was statistically significant (OR, 2.91; 95% confidence interval, 1.12 to 7.80; P = 0.030). CONCLUSIONS: The findings suggest that olanzapine may effectively improve delirium agitation in patients with advanced cancer.

A decision tree prediction model for a short-term outcome of delirium in patients with advanced cancer receiving pharmacological interventions: A secondary analysis of a multicenter and prospective observational study (Phase-R).

OBJECTIVE: There is no widely used prognostic model for delirium in patients with advanced cancer. The present study aimed to develop a decision tree prediction model for a short-term outcome. METHOD: This is a secondary analysis of a multicenter and prospective observational study conducted at 9 psycho-oncology consultation services and 14 inpatient palliative care units in Japan. We used records of patients with advanced cancer receiving pharmacological interventions with a baseline Delirium Rating Scale Revised-98 (DRS-R98) severity score of ≥10. A DRS-R98 severity score of <10 on day 3 was defined as the study outcome. The dataset was randomly split into the training and test dataset. A decision tree model was developed using the training dataset and potential predictors. The area under the curve (AUC) of the receiver operating characteristic curve was measured both in 5-fold cross-validation and in the independent test dataset. Finally, the model was visualized using the whole dataset. RESULTS: Altogether, 668 records were included, of which 141 had a DRS-R98 severity score of <10 on day 3. The model achieved an average AUC of 0.698 in 5-fold cross-validation and 0.718 (95% confidence interval, 0.627-0.810) in the test dataset. The baseline DRS-R98 severity score (cutoff of 15), hypoxia, and dehydration were the important predictors, in this order. SIGNIFICANCE OF RESULTS: We developed an easy-to-use prediction model for the short-term outcome of delirium in patients with advanced cancer receiving pharmacological interventions. The baseline severity of delirium and precipitating factors of delirium were important for prediction.

Increased prevalence of eating disorders in Japan since the start of the COVID-19 pandemic.

PURPOSE: The study aimed to investigate the effect of the COVID-19 pandemic on the prevalence of eating disorders in Japan. METHODS: We retrospectively reviewed the medical records of new patients with eating disorders who visited an outpatient eating disorders clinic of a single university hospital in Tokyo, Japan, from April 2020 to March 2021 (FY2020) and April 2019 to March 2020 (FY2019). We determined whether the onset or course in each patient in FY2020 was associated with the COVID-19 pandemic and classified COVID-19-associated medical histories into the following categories: (1) fatness phobia, (2) acceleration of dieting, (3) family relationships, (4) social factors, and (5) mood change. We performed the Kolmogorov-Smirnov test to compare the cumulative distribution of disease onset by month in FY2020 and FY2019. RESULTS: We reviewed the records of 112 and 77 patients with eating disorders in FY2020 and FY2019, respectively. The onset or course of 35 patients (31.3%) in FY2020 was associated with the COVID-19 pandemic. We classified 14 patients to fatness phobia category, 11 to acceleration of dieting, 4 to family relationships, 2 to social factors, and 4 to mood change. No COVID-19-associated cases were associated with fear of contracting the disease. The cumulative distribution of disease onset differed significantly in FY2020 and FY2019 (D = 0.248; P = 0.007). CONCLUSION: This chart review suggests that the COVID-19 pandemic may increase the prevalence of eating disorders. LEVEL OF EVIDENCE: III, cohort study.

Peak C-reactive protein levels do not predict 30-day mortality for bacteremia: A retrospective cohort study.

INTRODUCTION: Although peak C-reactive protein (CRP) levels are correlated with the prognosis of some diseases, there have been no reports regarding the association between peak CRP levels and mortality in patients with bacteremia. The present study aimed to determine the association between peak CRP levels and prognosis in patients with bacteremia. METHODS: This retrospective cohort study was conducted in a single tertiary hospital and included patients with bacteremia admitted to the emergency department from November 2012 to March 2017. Cox regression analysis was performed to examine the association between peak CRP levels and 30-day mortality. We also performed propensity score adjustment using potential confounding factors. RESULTS: One hundred fifty-nine patients were included in the study. Peak CRP levels were significantly higher in the ß-hemolytic streptococci (P = 0.001) and Streptococcus pneumoniae (P = 0.003) groups. The C-statistic of the multivariate logistic regression model for the propensity score was 0.88. For 30-day mortality, peak CRP levels >20 mg/dL did not show significance in the Cox regression analysis (hazard ratio, 0.866; 95% confidence interval, 0.489-1.537; P = 0.62). Even after propensity score adjustment, no significance was noted (hazard ratio, 0.865; 95% confidence interval, 0.399-1.876; P = 0.71). CONCLUSIONS: Peak CRP levels were not an independent predictor of mortality in patients with bacteremia in the emergency department. Clinicians should consider that patients with extremely high peak CRP levels do not necessarily have high mortality and vice versa.

Predicting extremely low body weight from 12-lead electrocardiograms using a deep neural network.

Previous studies have successfully predicted overweight status by applying deep learning to 12-lead electrocardiogram (ECG); however, models for predicting underweight status remain unexplored. Here, we assessed the feasibility of deep learning in predicting extremely low body weight using 12-lead ECGs, thereby investigating the prediction rationale for highlighting the parts of ECGs that are associated with extremely low body weight. Using records of inpatients predominantly with anorexia nervosa, we trained a convolutional neural network (CNN) that inputs a 12-lead ECG and outputs a binary prediction of whether body mass index is ≤ 12.6 kg/m2. This threshold was identified in a previous study as the optimal cutoff point for predicting the onset of refeeding syndrome. The CNN model achieved an area under the receiver operating characteristic curve of 0.807 (95% confidence interval, 0.745-0.869) on the test dataset. The gradient-weighted class activation map showed that the model focused on QRS waves. A negative correlation with the prediction scores was observed for QRS voltage. These results suggest that deep learning is feasible for predicting extremely low body weight using 12-lead ECGs, and several ECG features, such as lower QRS voltage, may be associated with extremely low body weight in patients with anorexia nervosa.

Developing Action Plans Based on Machine Learning Analysis to Prevent Sick Leave in a Manufacturing Plant.

OBJECTIVE: We aimed to develop action plans for employees' health promotion based on a machine learning model to predict sick leave at a Japanese manufacturing plant. METHODS: A random forest model was developed to predict sick leave. We developed plans for workers' health promotion based on variable importance and partial dependence plots. RESULTS: The model showed an area under the receiving operating characteristic curve of 0.882. The higher scores on the Brief Job Stress Questionnaire stress response, younger age, and certain departments were important predictors for sick leave due to mental disorders. We proposed plans to effectively use the Brief Job Stress Questionnaire and provide more support for younger workers and managers of high-risk departments. CONCLUSIONS: We described a process of action plan development using a machine learning model, which may be beneficial for occupational health practitioners.

Association of psychosocial factors with physical activity among Japanese adults aged 65 and older: a 6-year repeated cross-sectional study from the Nakanojo Study.

BACKGROUND: Physical activity (PA) provides substantial mental and physical health benefits for individuals of all ages. A limited number of long-term or longitudinal studies have investigated the association between psychosocial factors and PA in healthy older adults aged 65 and above. This study aimed to determine the long-term relationship between psychosocial factors, such as vitality, mental health, anxiety, and depression, and objectively measure PA in older adults. METHODS: Healthy participants from Nakanojo, Japan, aged 65-90, capable of walking, were included in this study and were followed up from 2008 to 2013. Those diagnosed with dementia and depression were excluded. Using a repeated cross-sectional dataset, a multilevel model was developed with psychosocial variables as independent variables and an average daily duration of PA volume of > 3 metabolic equivalents (METs) as the outcome. The Akaike information criterion was used to select the final model. RESULTS: This study included 1108 records from 319 participants. In the multilevel model, age (coefficient = -0.106, 95% confidence interval [CI] = -0.127 to -0.086, p < 0.001) and the Hospital Anxiety and Depression Scale depression scores (coefficient = -0.019, 95% CI = -0.036 to -0.002, p = 0.026) were negatively associated with the duration of PA volume > 3 METs, whereas male sex (coefficient = 0.343, 95% CI = 0.115 to 0.571, p = 0.003) was positively associated with PA volume. CONCLUSION: Depressive symptoms were related to a reduced duration of PA volume of > 3 METs among these adults aged 65 and above.

Regional disparities in suicide among patients with cancer: A nationwide population-based study in Japan.

BACKGROUND: This study aimed to explore prefecture-level differences in suicide risk among patients with cancer in Japan. METHODS: Data from the National Cancer Registry, which covers the entire Japanese population, were used. Patients diagnosed with cancer between 2016 and 2017 were included. The standardized mortality ratio (SMR) for suicide within 2 years after cancer diagnosis was quantified compared with the general population for each prefecture. Multivariate Poisson regression analysis was conducted to quantify the adjusted relative risk using Hokkaido as the reference. RESULTS: The analysis included 2,133,502 patients. The SMRs were high among patients with cancer residing in certain prefectures, such as the Hokuriku region (the middle and western parts of Japan's main island). These areas also exhibited a significant relative risk in the Poisson regression model. CONCLUSION: The results demonstrated that patients with cancer in certain prefectures in Japan have a high suicide risk.

Thrombocytopenia and PT-INR in patients with anorexia nervosa and severe liver dysfunction.

BACKGROUND: We previously reported a case that led us to hypothesize that decreased production of thrombopoietin (TPO) leads to thrombocytopenia in patients with anorexia nervosa (AN) with severe liver dysfunction and that prolonged prothrombin time-international normalized ratio (PT-INR) predicts thrombocytopenia in such cases. To validate this hypothesis, we report another case in which TPO levels were measured. In addition, we examined the association between prolonged PT-INR and thrombocytopenia in such patients. MAIN BODY: Similar to the previously reported patient, a patient with AN with severe liver dysfunction showed that TPO levels increased after improvements in liver enzyme levels and PT-INR, followed by recovery of platelet count. In addition, a retrospective study was also conducted to review patients with AN whose liver enzyme levels were > 3 × the upper limit of normal (aspartate aminotransferase > 120 U/L or alanine aminotransferase > 135 U/L). The study included 58 patients and showed a correlation coefficient of -0.486 (95% confidence interval [CI], -0.661 to -0.260; P < 0.001) between maximum PT-INR and minimum platelet count. These patients showed higher PT-INR (ß, 0.07; 95% CI, 0.02 to 0.13; P = 0.005) and lower platelet count (ß, -5.49; 95% CI, -7.47 to -3.52; P < 0.001) than the 58 matched control patients without severe liver dysfunction, even after adjusting for body mass index. CONCLUSIONS: In patients with AN with severe liver dysfunction, prolongation of PT-INR could predict thrombocytopenia, which may be mediated by decreased TPO production due to decreased hepatic synthetic function.

Suicide, other externally caused injuries, and cardiovascular disease within 2 years after cancer diagnosis: A nationwide population-based study in Japan (J-SUPPORT 1902).

BACKGROUND: This study aimed to investigate the risk of death by suicide, other externally caused injuries (ECIs), or cardiovascular disease for patients with cancer. METHODS: We used data from the National Cancer Registry, which include the entire population in Japan. Patients diagnosed with cancer from January 1 to December 31, 2016 were included, and their follow-up period was set to 2 years. The standardized mortality ratio (SMR) of death by suicide, other ECIs, and cardiovascular disease was calculated compared with the general population. Multivariate Poisson or negative binomial regression analysis was used to quantify the adjusted relative risks of factors of interest. RESULTS: We evaluated 1,070,876 patients with cancer. The 2-year follow-up SMR was 1.84 (95% confidence interval [CI]: 1.71-1.99) for suicide, 1.30 (95% CI: 1.24-1.37) for other ECIs, and 1.19 (95% CI: 1.17-1.21) for cardiovascular disease. The SMR was higher with shorter follow-up periods but was significant 13-24 months after cancer diagnosis. The SMRs at 0-1 month and 13-24 months, respectively, were 4.40 (95% CI: 3.51-5.44) and 1.31 (95% CI: 1.14-1.50) for suicide; 2.27 (95% CI: 1.94-2.63) and 1.27 (95% CI: 1.18-1.37) for other ECIs; and 2.38 (95% CI: 2.27-2.50) and 1.07 (95% CI: 1.04-1.10) for cardiovascular disease. The multivariate analyses showed that patients with cancers other than localized tumors had significantly high relative risks of death for each cause. CONCLUSION: Suicide prevention countermeasures for patients with cancer, especially those with advanced disease immediately after diagnosis, are warranted.

Economic costs for outpatient treatment of eating disorders in Japan.

BACKGROUND: Few studies have examined the economic costs of outpatient care for eating disorders in Japan. This study aimed to clarify the reimbursement for outpatient treatment of eating disorders and compare the costs between the departments of Psychosomatic Medicine and Psychiatry in Japan. METHOD: A multicenter, prospective, observational study of patients with an eating disorder was conducted in the Psychosomatic Medicine departments of three centers and the Psychiatry departments of another three centers in Japan. We analyzed medical reimbursement for an outpatient revisit, time of clinical interviews, and the treatment outcome measured by the Eating Disorder Examination Questionnaire (EDE-Q) global scores and body mass index (BMI) at 3 months. Multivariate linear regression models were performed to adjust for covariates. RESULTS: This study included 188 patients in the Psychosomatic Medicine departments and 68 in the Psychiatry departments. The average reimbursement cost for an outpatient revisit was 4670 yen. Even after controlling for covariates, the Psychosomatic Medicine departments had lower reimbursement points per minute of interviews than the Psychiatry departments (coefficient = - 23.86; 95% confidence interval = - 32.09 to - 15.63; P < 0.001). In contrast, EDE-Q global scores and BMI at 3 months were not significantly different between these departments. CONCLUSIONS: This study clarifies the economic costs of treating outpatients with eating disorders in Japan. The medical reimbursement points per interview minute were lower in Psychosomatic Medicine departments than in Psychiatry departments, while there were no apparent differences in the treatment outcomes. Addressing this issue is necessary to provide an adequate healthcare system for patients with eating disorders in Japan.

This study examined the cost of outpatient care for eating disorders in Japan, comparing treatment costs between the Psychosomatic Medicine and Psychiatry departments. The actual cost of outpatient care for eating disorders in Japan was clarified. The results indicate that Psychosomatic Medicine departments have lower reimbursement points per interview time compared to the Psychiatry departments, but there were no noticeable differences in treatment outcomes between the two. This highlights the need to address this cost difference to improve the healthcare system for patients with eating disorders in Japan.

Development of computer adaptive testing for measuring depression in patients with cancer.

The usefulness of depression scales for patients with cancer based on item response theory (IRT) and computer adaptive testing (CAT) has not yet been fully explored. This study thus aimed to develop an IRT-based tool for measuring depression in patients with cancer. We analyzed data from 393 patients with cancer from four tertiary centers in Japan who had not received psychiatric treatment. They answered 62 questions across five categories regarding their psychiatric status over the previous week. We selected 28 items that satisfied the assumptions of IRT, fitted a graded response model to these items, and performed CAT simulations. The CAT simulation used an average of 6.96 items and showed a Pearson's correlation coefficient of 0.916 (95% confidence interval, 0.899-0.931) between the degree of depression estimated by simulation and that estimated using all 28 items. The measurement precision of CAT with only four items was superior to that of the estimation using the calibrated Patient Health Questionnaire-9. These results imply that this scale is useful and accurate for measuring depression in patients with cancer.

Comparison of Antipsychotics for the Treatment of Patients With Delirium and QTc Interval Prolongation: A Clinical Decision Analysis.

Background: Antipsychotics are frequently used to treat delirium but often induce corrected QT (QTc) prolongation, which can be lethal by causing torsade de pointes. Nonetheless, the selection of antipsychotics to treat delirium patients with prolonged baseline QTc intervals remains unclear. We aimed to assess the utility of antipsychotics based on their effects on treatment outcomes and QTc intervals. Methods: A clinical decision analysis was conducted using data on the effects of antipsychotics on treatment outcomes and QTc intervals from published network meta-analyses. We quantified the utility of six antipsychotics (amisulpride, haloperidol, olanzapine, quetiapine, risperidone, and ziprasidone) using a decision tree and the obtained effect sizes. Subsequently, we conducted sensitivity analyses using multiple utility settings and another dataset. We also performed a probabilistic sensitivity analysis using Monte Carlo simulation, in which the effects of antipsychotics were randomly sampled given the plausible range. Results: Amisulpride showed the highest utility when the baseline QTc interval was 420 ms. Quetiapine showed the highest utility when the baseline QTc interval was ≥450 ms. The sensitivity analyses also showed the superiority of quetiapine when the baseline QTc intervals were prolonged. Conclusions: Decision analysis suggests that quetiapine is the optimal antipsychotic drug for the treatment of patients with delirium and prolonged baseline QTc intervals.

A clinical course of a patient with anorexia nervosa receiving surgery for superior mesenteric artery syndrome.

BACKGROUND: Superior mesenteric artery (SMA) syndrome is a well-known but relatively rare complication of anorexia nervosa. Although several reports have proposed surgery for SMA syndrome associated with anorexia nervosa, these have shown poor outcomes or did not reveal the long-term weight course. Thus, the long-term effectiveness of surgery for SMA syndrome in such cases remains unclear. This case report describes a patient with anorexia nervosa who underwent surgery for SMA syndrome. CASE PRESENTATION: An 18-year-old woman presented with anorexia nervosa when she was 16 years old. She also presented with SMA syndrome, which seemed to be caused by weight loss due to the eating disorder. Nutrition therapy initially improved her body weight, but she ceased treatment. She reported that symptoms related to SMA syndrome had led to her weight loss and desired to undergo surgery. Laparoscopic duodenojejunostomy was performed, but her body weight did not improve after the surgery. The patient eventually received conservative nutritional treatment along with psychological approaches, which led to an improvement in her body weight. CONCLUSIONS: The case implies that surgery for SMA syndrome in patients with anorexia nervosa is ineffective for long-term weight recovery and that conservative treatment can sufficiently improve body weight; this is consistent with the lack of evidence on the topic and reports on potential complications of surgery. Due to difficulties in assessing psychological status, consultation with specialists on eating disorders is necessary for treating patients with severely low body weight.

Association between polypharmacy and the persistence of delirium: a retrospective cohort study.

BACKGROUND: Although the association between polypharmacy and the occurrence of delirium has been well studied, the influence of polypharmacy on the persistence of delirium remains unclear. We aimed to explore the effect of polypharmacy on the persistence of delirium. METHODS: This retrospective cohort study was conducted at a tertiary hospital. The medical records of patients diagnosed with delirium who were referred to the Department of Psychosomatic Medicine were reviewed. Presentation with delirium on day 3 was set as the outcome in this study. We counted the number of drugs prescribed on the date of referral, excluding general infusion fluids, nutritional or electrolytic products, and psychotropics. To define polypharmacy, we developed a classification and regression tree (CART) model and drew a receiver operating characteristic (ROC) curve. The odds ratio (OR) of polypharmacy for the persistence of delirium on day 3 was calculated using a logistic regression model with the propensity score as a covariate. RESULTS: We reviewed the data of 113 patients. The CART model and ROC curve indicated an optimal polypharmacy cutoff of six drugs. Polypharmacy was significantly associated with the persistence of delirium both before [OR, 3.02; 95% confidence interval (CI), 1.39-6.81; P = 0.0062] and after (OR, 3.19; 95% CI, 1.32-8.03; P = 0.011) propensity score adjustment. CONCLUSION: We discovered an association between polypharmacy and worsening courses of delirium and hypothesize that polypharmacy might be a prognostic factor for delirium.

Intra-individual association between C-reactive protein and insulin administration in postoperative lumbar spinal canal stenosis patients: A retrospective cohort study.

The association of intra-individual variability in insulin requirements with C-reactive protein levels among acute phase patients remains unclear. This retrospective cohort study aimed to evaluate this association. Patients with type 2 diabetes undergoing surgery for lumbar spinal canal stenosis were included in the study. We analyzed 286 records of 49 patients using the linear mixed effects model. The model showed C-reactive protein levels to be significantly associated with insulin requirements, with an effect size of 0.60 U/day for an elevation of 1 mg/dL. The effect size was increased in patients with higher hemoglobin A1c levels. Our findings imply that C-reactive protein levels could be a useful clinical biomarker when blood glucose levels are controlled in acute phase patients.

Machine learning analysis to identify the association between risk factors and onset of nosocomial diarrhea: a retrospective cohort study.

BACKGROUND: Although several risk factors for nosocomial diarrhea have been identified, the detail of association between these factors and onset of nosocomial diarrhea, such as degree of importance or temporal pattern of influence, remains unclear. We aimed to determine the association between risk factors and onset of nosocomial diarrhea using machine learning algorithms. METHODS: We retrospectively collected data of patients with acute cerebral infarction. Seven variables, including age, sex, modified Rankin Scale (mRS) score, and number of days of antibiotics, tube feeding, proton pump inhibitors, and histamine 2-receptor antagonist use, were used in the analysis. We split the data into a training dataset and independant test dataset. Based on the training dataset, we developed a random forest, support vector machine (SVM), and radial basis function (RBF) network model. By calculating an area under the curve (AUC) of the receiver operating characteristic curve using 5-fold cross-validation, we performed feature selection and hyperparameter optimization in each model. According to their final performances, we selected the optimal model and also validated it in the independent test dataset. Based on the selected model, we visualized the variable importance and the association between each variable and the outcome using partial dependence plots. RESULTS: Two-hundred and eighteen patients were included. In the cross-validation within the training dataset, the random forest model achieved an AUC of 0.944, which was higher than in the SVM and RBF network models. The random forest model also achieved an AUC of 0.832 in the independent test dataset. Tube feeding use days, mRS score, antibiotic use days, age and sex were strongly associated with the onset of nosocomial diarrhea, in this order. Tube feeding use had an inverse U-shaped association with the outcome. The mRS score and age had a convex downward and increasing association, while antibiotic use had a convex upward association with the outcome. CONCLUSION: We revealed the degree of importance and temporal pattern of the influence of several risk factors for nosocomial diarrhea, which could help clinicians manage nosocomial diarrhea.