Pharmacist-initiated interventions to test quantitative bone mineral density and prescribe osteoporosis medications to prevent steroid-induced osteoporosis

Fragility fractures associated with glucocorticoid-induced osteoporosis (GIO) can markedly impair quality of life. However, only 20% of patients are treated in compliance with the relevant management guidelines, and bone mineral density analysis with dual-energy X-ray absorptiometry (DXA) is only rarely performed. We report the intervention methods suggested by pharmacists and describe their efficacy. Patients who visited the outpatient clinic of the General Medicine Department of Ogaki Municipal Hospital and received steroids were enrolled. The rates of DXA implementation and compliance with GIO pharmacotherapy guidelines before and after pharmacist to physician-suggested interventions were compared. Guideline compliance was defined as prescription of osteoporosis drugs to patients with a score of ≥3. Administered prophylaxes and bone mineral density were subsequently assessed. The before and after intervention DXA rates were 1% (1/100 patients) and 96.0% (96/100 patients; P<0.01), respectively. Overall, 96.9% (93/96) of the patients met the GIO criteria for pharmacotherapy initiation (score ≥3), and the guideline compliance rates before and after the intervention were 39.8% (37/93) and 93.5% (87/93; P<0.01), respectively. Of the 56 patients who did not receive prophylaxis, 52 were recommended treatment, yielding an acceptance rate of 82.7% (43/52). Among the 37 patients receiving prophylaxis, 20 (54.1%) had a DXA-related young adult mean of ≤70%, of whom 11 (55.0%) agreed to drug therapy. The acceptance rate of pharmacotherapy recommendations for patients not receiving prophylaxis was higher than that for those receiving prophylaxis (P=0.03). Pharmacist-initiated interventions for GIO facilitates the administration of appropriate pharmacotherapy.

Comparison of the Effects of Desflurane and Sevoflurane on Variations in Salivary Melatonin and Sleep Disturbance After Total Knee Arthroplasty: A Single-center, Prospective, Randomized, Controlled, Open-label Study

PURPOSE

Anesthesia has been shown to disrupt the circadian rhythm. Recovery of the circadian rhythm after general anesthesia might help alleviate symptoms of insomnia and postoperative delirium. We hypothesized that recovery of the circadian rhythm is faster after total knee arthroplasty (TKA) with desflurane than with sevoflurane. This study compared the influence of sevoflurane versus desflurane anesthesia on the postoperative circadian rhythm of melatonin in adults undergoing TKA.

DESIGN

Single-center, prospective, randomized, controlled, open-label study.

METHODS

This study involved adult patients undergoing TKA at a university hospital in Japan from May 1, 2018 to December 31, 2019. The primary outcome of the study was the comparison of the effect of sevoflurane and desflurane on the circadian rhythm of salivary melatonin for 3 days postoperatively. The secondary outcomes were postoperative fatigue and sleep quality for 3 days postoperatively.

FINDINGS

Twenty-eight patients (American Society of Anesthesiologists physical status of I or II) were scheduled for TKA and randomized to receive sevoflurane (n = 14) or desflurane (n = 14) anesthesia. There was no significant difference in the melatonin concentration between the sevoflurane and desflurane groups. The salivary melatonin concentration after sevoflurane or desflurane anesthesia was significantly higher at 9:00 p.m. on a postoperative day (POD)0 and POD1 than on POD3 (P < .05). Patients in the desflurane group had significantly greater fatigue than those in the sevoflurane group at 7:00 a.m. and 12:00 p.m. on POD3 (P < .05). Patients in the sevoflurane group had a deeper sleep than those in the desflurane group on POD0 (P < .05). In the sevoflurane group, the sleep time during the night of POD2 was longer than that on POD0 (6.1 vs 4.2 hours, P < .05).

CONCLUSIONS

Under the current study conditions, desflurane was equivalent to sevoflurane in terms of the postoperative salivary melatonin concentration and sleep disturbance after TKA but not in terms of recovering the postoperative circadian rhythm.

Proton and Carbon Ion Radiotherapy for Operable Early-Stage Lung Cancer: 3-Year Results of a Prospective Nationwide Registry

PURPOSE/OBJECTIVE(S)

The purpose of this analysis was to report subset analysis as to progression-free survival (PFS) and overall survival (OS) of particle-beam radiation therapy for operable early-stage lung cancer.

MATERIALS/METHODS

Patients of early-stage lung cancer (T1-T2aN0) who were eligible for radical surgery but did not wish to undergo surgery were treated by proton-ion (PT) or carbon-ion (CT) radiation therapy and enrolled in Japanese prospective registry. In this analysis, PFS and OS by clinical stage, tumor location, pathological confirmation and particle-ion type were evaluated.

RESULTS

A total of 274 patients were enrolled and included in efficacy and safety analyses. Most tumors were adenocarcinoma (44%), and 105 (38%) were not histologically confirmed and diagnosed clinically. 250 (91%) of 274 patients had tumors that were peripherally situated. 138 (50%) and 136 (50%) patients were treated by PT and CT, respectively. The median follow-up time for all censored patients was 42.8 months (IQR 36.7 - 49.0). No grade 3 or severe treatment-related toxicity was observed. 3-year PFS was 81% (95% CI;76-86) and OS was 93% (95% CI;89-96), respectively. As to particle-ion type, 3-year PFS were 79.0% and 81.9% in PT and CT (p = 0.19), and 3-year OS were 93.9% and 91.1% in PT and CT (P = 0.72), respectively. For PFS, pathological confirmation, clinical stage was significant factors but there were no significant differences by tumor location or particle-ion type; for OS, clinical stage was significant factor but there was no significant difference on pathological confirmation, tumor location or particle-ion type (Table1). Table 1. 3-year PFS and OS CONCLUSION: Particle therapy for operable early-stage lung cancer resulted in excellent 3-year OS and PFS on each subset.

Association between lifestyle habits and presenteeism

BACKGROUND

Presenteeism is affected by work-related and individual factors. Among individual factors, the effect of combining various lifestyle habits on presenteeism is unknown.

AIMS

This study aimed to determine the relationship between changes in multiple good lifestyle habits with a change in presenteeism and to examine the effect of psychological factors on this relationship.

METHODS

We performed a 1-year retrospective cohort study on employees of large Japanese companies. Data were collected from health check-ups and a self-administered questionnaire. Changes in presenteeism were measured using the Quality and Quantity method. Changes in lifestyle habits were measured using a modified form of Breslow's seven health practices. Psychological factors were measured using the Kessler 6-Item Psychological Distress Scale. Linear regression was used for statistical analysis.

RESULTS

The number of practised lifestyle habit changes was negatively correlated with a change in presenteeism. This result was consistent when adjusted for age, sex and company (B, -0.010; P < 0.05), but became non-significant when additionally adjusted for psychological distress (B, -0.006). When analysed separately, only an improvement in the body mass index (B, -0.054; P < 0.05) and a worsened sleep habit (B, 0.040; P < 0.01) influenced a change in presenteeism.

CONCLUSIONS

This study suggests that improving various practised lifestyle habits in combination, rather than improving a single lifestyle habit, is beneficial in reducing presenteeism. Our finding that psychological distress altered the relationship of practised lifestyle habit changes with presenteeism indicates the importance of organizational-level intervention in presenteeism.

AB1335 BONE MARROW EDEMA SCORE IN HAND X-RAY FILM BY AI DEEP LEARNING ASSOCIATE WITH MRI BONE EDEMA IN RHEUMATOID ARTHRITIS

Background

Rapid radiographic progression (RRP) was reported to be one of clinical symptom in difficult to treat RA(D2T RA) (1). Eular recommendation for imaging showed BME is strong and independent prognostic factor for bone destruction(2). We reported bone marrow edema (BME) in MRI image was most associated with RRP compared with bone erosion, synovitis in Adalimumab add-on therapy in MTX-IR RA patients(3). To rescue RRP, early detection of BME is important although cost of MRI is expensive and hard to repeat.

Objectives

To investigate the score of BME in hand X ray film by deep learning between X ray film and MRI BME information can discriminate the differences between BME and non-BME images.

Methods

In this work, we use a neural network consisted of convolutional layers and fully connected layers to classify X-ray images (Figure 1) In this paper, the output is the socre of BME which ranges from 0 to1(threshold = 0.4). We also used an interpretation technique called the Grad-CAM for visual explanations. Hand MRI (1.5T) were used.

Figure 1.

The convolutional neural network design. A red block “Conv” means a convolutional block. It contains a 2D convolution layer, a leaky relu activation function, a maxpooling layer and a batch normalization layer. The numbers above each “Conv” block are (kernal size, kernal size, kernal number). A green block “FC” is a fully connection layer. The number above it is (neuron number). After the last Softmax layer, the output becomes the probability of BME which ranges from 0 to 1.

Results

Regarding data split, 104 images including 79 non-BME images and 25 BME images are used as a hold-out test set. The rest of the images (473 images) are used as training data and validation data. Five fold cross-validation is used for these 473images. For each fold, there are about 378 images including 297 non-BME images and 81 BME images in the training set. There are about 95 images including 74 non-BME images and 21 BME images in the validation set. In order to fully utilize every image and unify the distribution of the training set and the validation set, the ratio of non-BME and BME is controlled to be the same which is about 3.66:1. The five folds showed similar performance on the hold-out test set. AUC is the area under the ROC curve. As the result, AUC which indicates the general performance of this model, ranged from 0.88 to 0.91. The average precision was 63% and the average recall rate was 87%. In this experiment, the initialization seed will greatly influence the final result. For example, AUC can be reduced to 0.73 from 0.89 because of a different initialization seed. It perhaps results from the shortage of data, which can easily make the neural network drop into a local minimum.We also utilized Grad-cam to visualize the result. The result of Grad-cam shows the importance of each part to the final prediction(Figure 2).

Figure 2.

Result of Grad-cam. Numbers in the parenthesises are the possibilities of BME. The middle case is unexpected because red region is the surrounding of the hand. The left and right cases may indicate the evidence for prediction.

Conclusion

The preliminary result is much better than a random guess. According to this result, there should be a certain difference between BME and non-BME images. If it’s the characteristic of BME that domains this difference, our classification algorithm will be feasible for BME. Our future work is to justify the evidence of the predictions and improve performance.

References

[1]Nagy G et al. Eular definition of difficult- to - treat to rheumatoid arthritis. Ann Rheum Dis 2021;80:31-35

[2]Colebatch AN et al. Eular recommendation for the use of imaging of joints in the clinical management of rheumatoid arthritis. Ann Rheum Dis 2013;72: 804-814

[3]Katayama K et al. Bone marrow OEDEMA is more associated with rapid radiographic progression than in synovitis or bone erosion by using low field MRI in bio-naiive rheumatoid arthritis patients treated with adalimumab and methotrexate combination therapy. Ann Rheum Dis 2014, eular meeting SAT0100.

Disclosure of Interests

None declared

Prevalence of and risk factors for depressive symptoms in non-tuberculous mycobacterial pulmonary disease

BACKGROUND: The presence of depressive symptoms in patients with non-tuberculous mycobacterial pulmonary disease (NTM-PD) is an important research topic; however, the prevalence of depressive symptoms and the factors that influence their development are unclear.OBJECTIVE: To analyse the association between CES-D (Center for Epidemiological Studies Depression Scale) scores and clinical parameters such as age, disease duration, pulmonary function, imaging findings, blood data, physical functions, sleep disturbances, respiratory symptoms and health-related quality of life (HRQOL).METHODS: We conducted a cross-sectional retrospective study of 114 patients with NTM-PD at a single centre from March 2016 to January 2021 to evaluate the relationship between CES-D scores and clinical parameters.RESULTS: Participants had a median age of 64 years; 32.5% of them had depressive symptoms. Disease duration, albumin, C-reactive protein, pulmonary function, dyspnoea, exercise capacity, respiratory symptoms, cough-related HRQOL and sleep disturbances were associated with depressive symptoms. Binomial logistic regression analyses indicated that the CES-D score was significantly associated with cough-related HRQOL and sleep disturbances.CONCLUSION: A high percentage of NTM-PD patients in this study experienced depressive symptoms, and these patients had abnormalities of various clinical parameters. Cough-related HRQOL and sleep disturbance had a strong influence on the development of depressive symptoms.

Effect of intensive care provided by nurse practitioners for postoperative patients: A retrospective observational before-and-after study

Nurse practitioners are increasingly now members of intensive care teams in Japan, but no data exist about their effect on the outcomes for critically ill patients. This study aimed to compare the outcomes of postoperative patients on mechanical ventilators before and after the participation of nurse practitioners in intensive care teams. We retrospectively identified 387 patients who underwent postoperative mechanical ventilation at a University Hospital in Japan, using data from medical records from 1 April 2015 to 31 March 2017. We extracted data and compared patients' length of stay in the intensive care unit and the hospital, mechanical ventilation days, postoperative rehabilitation start date, rehabilitation prescription, intensive care unit and hospital mortality, and intensive care unit readmission. Multiple regression analysis was used to analyze the factors affecting length of stay in the intensive care unit. Patients who received care from nurse practitioners and physicians had significantly shorter stays in intensive care (4.8 ± 4.8 days versus 6.7 ± 10.3 days, p < 0.021). Mechanical ventilation days, total length of hospital stay, rehabilitation prescription, mortality in intensive care and hospital, and readmission to intensive care were all similar to those who received care only from physicians. The multiple regression analysis suggests that participation of nurse practitioners in intensive care reduced the length of stay in the unit by 2.6 days (p = 0.003). These findings could help to increase use of non-physician healthcare providers in intensive care. Our results demonstrated that it is both effective and safe for nurse practitioners to participate in intensive care teams that provide care for postoperative patients receiving mechanical ventilation.