An Arrhythmia classification approach via deep learning using single-lead ECG without QRS wave detection.

Arrhythmia, a frequently encountered and life-threatening cardiac disorder, can manifest as a transient or isolated event. Traditional automatic arrhythmia detection methods have predominantly relied on QRS-wave signal detection. Contemporary research has focused on the utilization of wearable devices for continuous monitoring of heart rates and rhythms through single-lead electrocardiogram (ECG), which holds the potential to promptly detect arrhythmias. However, in this study, we employed a convolutional neural network (CNN) to classify distinct arrhythmias without QRS wave detection step. The ECG data utilized in this study were sourced from the publicly accessible PhysioNet databases. Taking into account the impact of the duration of ECG signal on accuracy, this study trained one-dimensional CNN models with 5-s and 10-s segments, respectively, and compared their results. In the results, the CNN model exhibited the capability to differentiate between Normal Sinus Rhythm (NSR) and various arrhythmias, including Atrial Fibrillation (AFIB), Atrial Flutter (AFL), Wolff-Parkinson-White syndrome (WPW), Ventricular Fibrillation (VF), Ventricular Tachycardia (VT), Ventricular Flutter (VFL), Mobitz II AV Block (MII), and Sinus Bradycardia (SB). Both 10-s and 5-s ECG segments exhibited comparable results, with an average classification accuracy of 97.31%. It reveals the feasibility of utilizing even shorter 5-s recordings for detecting arrhythmias in everyday scenarios. Detecting arrhythmias with a single lead aligns well with the practicality of wearable devices for daily use, and shorter detection times also align with their clinical utility in emergency situations.

Deep convolutional neural network for rib fracture recognition on chest radiographs.

Introduction: Rib fractures are a prevalent injury among trauma patients, and accurate and timely diagnosis is crucial to mitigate associated risks. Unfortunately, missed rib fractures are common, leading to heightened morbidity and mortality rates. While more sensitive imaging modalities exist, their practicality is limited due to cost and radiation exposure. Point of care ultrasound offers an alternative but has drawbacks in terms of procedural time and operator expertise. Therefore, this study aims to explore the potential of deep convolutional neural networks (DCNNs) in identifying rib fractures on chest radiographs. Methods: We assembled a comprehensive retrospective dataset of chest radiographs with formal image reports documenting rib fractures from a single medical center over the last five years. The DCNN models were trained using 2000 region-of-interest (ROI) slices for each category, which included fractured ribs, non-fractured ribs, and background regions. To optimize training of the deep learning models (DLMs), the images were segmented into pixel dimensions of 128 × 128. Results: The trained DCNN models demonstrated remarkable validation accuracies. Specifically, AlexNet achieved 92.6%, GoogLeNet achieved 92.2%, EfficientNetb3 achieved 92.3%, DenseNet201 achieved 92.4%, and MobileNetV2 achieved 91.2%. Discussion: By integrating DCNN models capable of rib fracture recognition into clinical decision support systems, the incidence of missed rib fracture diagnoses can be significantly reduced, resulting in tangible decreases in morbidity and mortality rates among trauma patients. This innovative approach holds the potential to revolutionize the diagnosis and treatment of chest trauma, ultimately leading to improved clinical outcomes for individuals affected by these injuries. The utilization of DCNNs in rib fracture detection on chest radiographs addresses the limitations of other imaging modalities, offering a promising and practical solution to improve patient care and management.

Exploring medical students' metacognitive and regulatory dimensions of diagnostic problem solving.

Solving clinical problems requires an individual to apply not only domain-specific medical knowledge and cognitive skills for reasoning, but also to be consciously aware of, monitor, and evaluate their thinking processes (i.e., metacognition). The purpose of this study was to map critical metacognitive dimensions of clinical problem solving and to explore the structural relationships among them, which may help frame a conceptual framework and better pedagogy for effective intervention. A context-specific inventory was adapted and modified from a domain-general instrument to capture essential metacognitive skills for learning and solving clinical problems. This inventory was administered to 72 undergraduate medical students to survey their capabilities in five dimensions: knowledge of cognition, objectives, problem representation, monitoring, and evaluation. The interplay among these dimensions was further examined using partial least squares structural equation modeling.Our findings revealed that the medical students fell short of some expert-like, metacognitive, and regulatory competence, even after receiving years of medical education and on-site training. In particular, they did not know when a holistic understanding of a problem had been reached. Many of them often do not have a set of clear diagnostic procedures in mind, nor do they concurrently monitor their thinking during diagnostic reasoning. Moreover, their lack of self-improving approaches seemed to worsen their learning. Finally, the structural equation model indicated that knowledge of cognition and objectives significantly predicted problem representation, suggesting that medical learners' knowledge of and goals for learning are influential in framing the clinical problems at hand. A significant linear prediction path was observed from problem representation, monitoring, to evaluation, signifying a possible sequenced process of clinical problem solving. Metacognitive-based instruction can help improve clinical problem-solving skills and awareness of potential biases or errors.

Using a chatbot to reduce emergency department visits and unscheduled hospitalizations among patients with gynecologic malignancies during chemotherapy: A retrospective cohort study.

Background: A chatbot is an automatic text-messaging tool that creates a dynamic interaction and simulates a human conversation through text or voice via smartphones or computers. A chatbot could be an effective solution for cancer patients' follow-up during treatment, and could save time for healthcare providers. Objective: We conducted a retrospective cohort study to evaluate whether a chatbot-based collection of patient-reported symptoms during chemotherapy, with automated alerts to clinicians, could decrease emergency department (ED) visits and hospitalizations. A control group received usual care. Methods: Self-reporting symptoms were communicated via the chatbot, a Facebook Messenger-based interface for patients with gynecologic malignancies. The chatbot included questions about common symptoms experienced during chemotherapy. Patients could also use the text-messaging feature to speak directly to the chatbot, and all reported outcomes were monitored by a cancer manager. The primary and secondary outcomes of the study were emergency department visits and unscheduled hospitalizations after initiation of chemotherapy after diagnosis of gynecologic malignancies. Multivariate Poisson regression models were applied to assess the adjusted incidence rate ratios (aIRRs) for chatbot use for ED visits and unscheduled hospitalizations after controlling for age, cancer stage, type of malignancy, diabetes, hypertension, chronic renal insufficiency, and coronary heart disease. Result: Twenty patients were included in the chatbot group, and 43 in the usual-care group. Significantly lower aIRRs for chatbot use for ED visits (0.27; 95% CI 0.11-0.65; p = 0.003) and unscheduled hospitalizations (0.31; 95% CI 0.11-0.88; p = 0.028) were noted. Patients using the chatbot approach had lower aIRRs of ED visits and unscheduled hospitalizations compared to usual-care patients. Conclusions: The chatbot was helpful for reducing ED visits and unscheduled hospitalizations in patients with gynecologic malignancies who were receiving chemotherapy. These findings are valuable for inspiring the future design of digital health interventions for cancer patients.

Correction: A Novel mHealth Approach for a Patient-Centered Medication and Health Management System in Taiwan: Pilot Study.

[This corrects the article DOI: 10.2196/mhealth.9987.].

Is the Yale Global Tic Severity Scale a valid tool for parent-reported assessment in the paediatric population? A prospective observational study in Taiwan.

OBJECTIVE: The Yale Global Tic Severity Scale (YGTSS) is the most commonly used clinician-rated evaluation tool for Tourette syndrome (TS), with established reliability and validity. This study aims to determine whether the YGTSS is a valid parent-reported assessment in the TS population. DESIGN: A prospective cohort study. SETTING: A major medical centre in Taiwan. METHODS: A total of 594 patients were enrolled. A revised traditional Chinese version of the YGTSS was made available to parents via Google docs. Parents were encouraged to complete the YGTSS the day before each outpatient clinic visit. At each visit, a paediatric neurology fellow also administered the YGTSS assessment. We investigated whether differences in scores between physicians and parents changed as the number of parent evaluations increased. The results of the physician assessments were also taken as the expert standard for evaluating the sensitivity and specificity of the parent-reported assessments was conducted for the same visit. RESULTS: The differences in the YGTSS scores between participants and physicians were small. The mean difference in the total assessment score was 4.15 points. As the number of times the parent evaluation was performed increased, the difference between the parent and physician scores decreased. Discrimination of moderate-to-severe attacks was good using the parent-assessed YGTSS (area under the receiver operating characteristic curve, 0.858; 95% CI 0.839 to 0.876). The sensitivity for detecting a moderate-to-severe attack by YGTSS parent assessment was 79.7% (95% CI 76.6 to 82.8), and the specificity was 91.8% (95% CI 89.9 to 93.7). CONCLUSION: The parent-reported YGTSS is a promising tool for TS assessment, demonstrating good discriminative ability for disease severity, with user precision increasing with experience.

The Association between Metabolically Healthy Obesity, Cardiovascular Disease, and All-Cause Mortality Risk in Asia: A Systematic Review and Meta-Analysis.

We investigated the association among metabolically healthy obesity (MHO), cardiovascular disease (CVD)risk, and all-cause mortality in the Asian population. We searched databases from inception to 16 November, 2019 and pooled data using a random-effects model. Subgroup analysis was conducted according to the following comparison groups: MHNW (without overweight or underweight participants) and MHNO (non-obese, including overweight and underweight participants). Nineteen studies were included. The mean Newcastle-Ottawa Scale score was 7.8. Participants with MHO had a significantly higher CVD risk (odds ratio (OR) = 1.36, 95% confidence interval (CI) = 1.13-1.63) and significantly lower risk of all-cause mortality (OR = 0.88, 95% CI = 0.78-1.00) than the comparison group. Subgroup analyses revealed participants with MHO had a significantly higher CVD risk than MHNW participants (OR = 1.61; 95% CI = 1.24-2.08; I2 = 73%), but there was no significant difference compared with MHNO participants (OR, 1.04; 95% CI, 0.80-1.36; I2 = 68%). Participants with MHO had a significantly lower risk of all-cause mortality (OR = 0.83; 95% CI = 0.78-0.88; I2 = 9%) than MHNO participants, but a borderline significantly higher risk of all-cause mortality than MHNW participants (OR = 1.30; 95% CI = 0.99-1.72; I2 = 0%). The CVD risk and all-cause mortality of the MHO group changed depending on the control group. Thus, future studies should select control groups carefully.

Association of Hyperhomocysteinemia with Increased Coronary Microcirculatory Resistance and Poor Short-Term Prognosis of Patients with Acute Myocardial Infarction after Elective Percutaneous Coronary Intervention.

BACKGROUND: This study aims to investigate the coronary microcirculatory resistance and prognosis of patients with acute myocardial infarction (AMI) concomitant with hyperhomocysteinemia (HHcy) after an elective percutaneous coronary intervention (PCI). METHODS: A total of 101 patients that underwent elective PCI between May 2015 and July 2018 due to AMI were consecutively enrolled in this study. Patients were divided into a HHcy group (53) and a normal Hcy group (control; 48) based on their plasma homocysteine concentration. The characteristics of coronary angiography, the index of microcirculatory resistance (IMR) of infarct-related vessels (IRV), changes in left ventricular end diastolic diameter (LVEDd) and left ventricular ejection fraction (LVEF) before and after PCI, and the incidence of major adverse cardiovascular events (MACE) three months after PCI were compared between these groups. RESULTS: Compared to the results from the Hcy group, the HHcy group had a higher IMR. The HHcy group had significantly higher LVEDd and a lower LVEF than the Hcy group 3 months after PCI. Additionally, the incidence of MACE at three months after PCI was higher in the HHcy group than in the Hcy group. Pearson correlation analysis revealed a positive correlation with IMR in the HHcy group. Furthermore, there was a difference in the LVEDd measured at one day after PCI and at three months after PCI in the HHcy group. CONCLUSION: AMI patients concomitant with HHcy that undergo elective PCI are prone to coronary microcirculatory dysfunction and have a poor cardiac function and poor prognosis at three months after PCI.

Bioinspired Self-assembling Peptide Hydrogel with Proteoglycan-assisted Growth Factor Delivery for Therapeutic Angiogenesis.

Critical challenges still exist in surgical theaters and emergency rooms to stop bleeding effectively and facilitate wound healing efficiently. In circumstances of tissue ischemia, it is essential to induce proper angiogenesis to provide adequate vascular supply to the injury site. Methods: In view of these clinical unmet needs, we propose an applicable approach by designing functionalized self-assembling peptide (SAP) hydrogel with two sequences of RADA16-GGQQLK (QLK) and RADA16-GGLRKKLGKA (LRK) in this study. The SAP hydrogel conjugated with QLK functional motif could be crosslinked by endogenous transglutaminase, one of the intrinsic factors secreted during the coagulation process, the mechanical property of the hydrogel can then be enhanced without the need of external support. On the other hand, the LRK sequence exhibited a good binding affinity with the proteoglycan heparan sulfate and could act as a cofactor by sustaining the release of embedded growth factors. Results: The results showed that this SAP solution underwent self-assembling process in a physiological environment, formed hydrogel in situ, and possessed good shear thinning property with injectability. After pH adjustment, the SAP developed densely-compacted fiber entanglement that closely mimicked the three-dimensional fibrous framework of natural extracellular matrix. Such scaffold could not only support the survival of encapsulating cells but also promote the capillary-like tubular structure formation by dual angiogenic growth factors. The ex ovo chicken chorioallantoic membrane assay demonstrated that the growth factor-loaded hydrogel promoted the sprout of surrounding vessels in a spoke-wheel pattern compared to growth factor-free counterparts. Conclusion: The designer bioinspired SAP hydrogel may be an attractive and promising therapeutic modality for minimally-invasive surgery, ischemic tissue disorders and chronic wound healing.

A network pharmacology study on the triterpene saponins from Medicago sativa L. for the treatment of Neurodegenerative diseases.

Neurodegenerative diseases (NDDs) are characterized by progressive and irreversible, is a kind of complex illnesses, and the long-term therapy which is frequently associated with adverse side effects. Medicago sativa L., widely consumed as a vegetable, has the effects of improving memory and relieving central nervous system diseases. However, there are less studies on its specific mechanism for NDDs. In this investigation, we applied a method of network pharmacology, which combined molecular docking and network analysis to decipher the mechanisms of M. sativa in NDDs. The pharmacological system generated 55 triterpene saponins from M. sativa, and predicted 27 potential targets with 100 pathways in the treatment of NDDs. As a result, 13 compounds, 10 target proteins, and 6 signaling pathways were found to play important roles in the treatment of NDDs. In addition, in vitro experiments of isolates confirmed activities for NDDs, which were consistent with the results of network pharmacology prediction. PRACTICAL APPLICATIONS: Medicago sativa L. has been widely consumed as a vegetable, which possesses many nutritional components. As a functional food stuff, M. sativa can improve human health, such as memory improving activities, relieving central nervous system diseases, immunomodulatory, antioxidant, anticancer, and anti-inflammatory. In this article, the mechanism of triterpene saponins from M. sativa against NDDs was successfully predicted by network pharmacology method. The results will serve as a reference of M. sativa against NDDs.

Effect of music interventions on anxiety during labor: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Anxiety is commonly experienced during the delivery process and has shown to have adverse effects on maternal and infant health outcomes. Music interventions tend to reduce the effects of anxiety in diverse populations, are low cost, are easily accessible, and have high acceptability. The aim of this review and meta-analysis was to assess the effectiveness of music interventions in reducing anxiety levels among women during labor. METHODS: Seven databases from inception to the end of December, 2018, without any language or time restriction including Embase, PubMed, the Cochrane Library, the Cumulative Index to Nursing and Allied Health, PsycINFO, Airiti Library, and PerioPath: Index to Taiwan Periodical Literature were searched using key terms related to pregnancy, anxiety, and music. Randomized controlled trials that assessed the effect of music during labor and measured anxiety levels as an outcome were included. Meta-analyses were conducted to assess anxiety reduction following a music intervention compared to that after placebo treatment. RESULTS: A total of 14 studies that investigated a total of 1,310 participants were included in this review. The meta-analyses indicated that those in the intervention group had a significant decrease in anxiety scores (standardized mean difference = -2.40, 95% confidence interval (CI) [-3.29 to -1.52], p < 0.001; I 2 = 97.66%), heart rate (HR) (difference in means = -3.04 beats/min, 95% CI [-4.79 to -1.29] beats/min, p = 0.001; I 2 = 0.00%), systolic blood pressure (SBP) (difference in means = -3.71 mmHg, 95% CI [-7.07 to -0.35] mmHg, p = 0.031; I 2 = 58.47%), and diastolic blood pressure (DBP) (difference in means = -3.54 mmHg, 95% CI [-5.27 to -1.81] mmHg, p < 0.001; I 2 = 0.00%) as compared to the women in the control group. CONCLUSIONS: Music interventions may decrease anxiety scores and physiological indexes related to anxiety (HR, SBP, and DBP). Music interventions may be a good non-pharmacological approach for decreasing anxiety levels during labor.

Chloroplast genome structure and phylogeny of Spiranthes sinensis, an endangered medicinal orchid plant.

Spiranthes sinensis is an important medicinal plant of Spiranthes family and is currently in an endangered state. To better guide the systematic classification of S. sinensis, the complete genome of its chloroplast was sequenced and characterized. The complete chloroplast genome is 152,786 bp in length and contains a large single copy (LSC) region of 83,446 bp, a small single copy (SSC) region of 17,938 bp, and two inverted repeat (IRA and IRB) regions of 25,701 bp. The genome encodes 132 genes (112 unique genes), including 86 protein-coding genes (78 unique genes), 8 rRNA genes (4 unique genes), and 38 tRNA genes (30 unique genes). The total GC content of plasmid genome is 36.18%. Phylogenetic results indicated that S. sinensis is more closely related to Ludisia discolor, Goodyera schlechtendaliana, Goodyera fumata, and Goodyera procera. The study enriches the plasmid genomic information of S. sinensis and is of great significance for the genetic protection of this species.

Transplantation of human limbus-derived mesenchymal stromal cells via occipital approach improves hearing in animal auditory neuropathy.

OBJECTIVE: To develop a surgical approach for cell transplantation into mouse cochlear nerves via an intracranial route and investigate whether transplantation of human limbus-derived mesenchymal stromal cells (HL-MSCs) can improve hearing in this model of auditory neuropathy. METHODS: We used 8-week-old CBA/CaJ male mice and created ouabain-induced auditory neuropathy. The surgical approach passed through the cerebellum to reveal the superior semicircular canal and brainstem, allowing access to the auditory nerve. Then HL-MSCs were injected around the cochlear nerve trunk using a micropipette driven by a micropump. Hearing thresholds in the mice were determined by auditory brainstem responses (ABRs) and distortion product otoacoustic emissions (DPOAEs). RESULTS: We produced ouabain-induced neuropathy in mice with an elevated hearing threshold but normal DPOAE. Using immunohistological staining, we detected HL-MSCs were localized in the cochlear nerve trunk 2 days after cell transplantation via this occipital approach. More spiral ganglion neurons were detected in ouabain-treated cochleae 3 months after HL-MSCs transplantation compared to those without HL-MSCs transplantation. The ABR showed significant hearing improvement 3 months after HL-MSCs transplantation. CONCLUSIONS: We successfully established a mouse model for cell transplantation into the intracranial cochlear nerve trunk and showed that HL-MSCs potentially can be applied as cell therapy to treat sensorineural hearing loss.

Comparison of the validity of checklist assessment in cardiac arrest simulations with an app in an academic hospital in Taiwan: a retrospective observational study.

INTRODUCTION: Robust assessment is a crucial component in Advanced Cardiac Life Support (ACLS) training to determine whether participants have achieved learning objectives with little or no variation in their overall outcomes. This study aimed to evaluate resuscitation performance by real-time logs. We hypothesised that instructors may not be able to evaluate time-sensitive parameters, namely, chest compression fraction, time to initiating chest compression and time to initiating defibrillation accurately in a subjective manner. METHODS: Video records and formal checklist-based test results of Megacode scenarios for the ACLS certification examination at several hospitals in Taipei were examined. For the study interest, three time-sensitive parameters were measured via video review assisted by a mobile phone application, and were used for evaluation. We evaluated if the pass/fail results made by instructors via checklists were correlated with these parameters. RESULTS: A total of 185 Megacode scenarios were eligible for the final analysis. Among the three parameters, good chest compression fraction was statistically significant with a higher OR of passing (OR=3.65; 95% CI 1.36 to 9.91; p=0.01). In 112 participants with one parameter that did not meet the criteria, 25 were graded as fail, making the specificity 22.3% (95% CI 15.0% to 31.2%). CONCLUSIONS: Visual observation of cardiopulmonary resuscitation performance is not accurate when evaluating time-sensitive parameters. Objective results should be offered for training outcome evaluation, and also for feedback to participants.

Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course.

OBJECTIVE: In addition to high-quality chest compression, parameters of resuscitation efficiency such as early chest compression, early defibrillation, and decreased hands-off time are also vital in the Advanced Cardiac Life Support (ACLS) protocol. However, because of limited time and equipment in ACLS courses, efficiency of performance is difficult to evaluate. MATERIALS AND METHODS: A free, easy-to-use iOS and Android app (CodeTracer®) was developed for real-time recording of cardiopulmonary resuscitation (CPR) performance. Interventions performed during resuscitation were set up as buttons. When the simulated scenario in the ACLS course began, instructors recorded every intervention and the team performed by pushing the appropriate buttons. When the scenario ended, the CodeTracer® automatically computed parameters, including the percentage of no-flow time, time to initiating CPR, and time to initiating defibrillation and also generated a graphic log for later discussion. RESULTS: A total of 76 resuscitation episodes were recorded, 27 in the practice scenarios and 49 in the final Megacode simulations. After the course, the average percentage of no-flow time decreased 5.79%, time to initiating CPR decreased 3.05 s, and time to initiating defibrillation decreased up to 20.27 s. Of note, physicians as leaders seem to have better performance after the ACLS course than before, but the results were insignificant except for the percentage of no-flow time. CONCLUSIONS: CodeTracer® can record and calculate objective parameters for resuscitation performance in ACLS courses and can assist instructors in disseminating important concepts to participants. It can be a useful tool in ACLS courses.

A Novel mHealth Approach for a Patient-Centered Medication and Health Management System in Taiwan: Pilot Study.

BACKGROUND: Mobile health (mHealth) apps have recently demonstrated the potential to engage and empower people to improve their own health. Although the availability of health-related apps is increasing, their adoption rate in Taiwan is exceptionally low mainly due to the preponderance of Western culture-based app designs that are challenging for non-English-speaking individuals. To our knowledge, no mHealth app is available in Taiwan that is culturally tailored for Chinese-speaking users and that applies a patient-centered approach to self-manage medication and health. OBJECTIVE: The purpose of this study was to design and deploy a culturally tailored mHealth system that could be easily integrated into current clinical practice and to evaluate how this mHealth system could support the continuity of patient care in Taiwan. METHODS: An mHealth information system and a mobile app were designed. To promote the best patient experience, a Quick Response (QR) code system was developed to enable efficient registration of personal medication information through the mobile app. The app also supported notifications for drug utilization, refills, and symptom checks. Patients were encouraged to record medication use, symptoms, and self-assessments in the app during their treatment period. Evaluation of the novel mHealth system was conducted from August 1, 2016 to December 31, 2016 at MacKay Memorial Hospital, Taipei, Taiwan. Population data and app usage statistics were analyzed. RESULTS: During the 5-month implementation period, a total of 25,909 users downloaded the app with an overall 7-day retention rate of 15.4% (SD 3.9). Young male adults (range 25-44 years) were the predominant user population. Patients' feedback on app usability and design, QR code system as drug input method, medication reminders, and linking family or friends into care networks was generally positive. Physicians showed great interest in utilizing patient-generated data in their care process, and the positive medication adherence rate was the most highly valued component of this system. CONCLUSIONS: This pilot study demonstrated the value of a novel mHealth approach for individualized medication and health management in Taiwan. The mHealth system shows the potential to optimize personalized care into existing clinical services and may help hospitals and health authorities perform continuous quality improvement and policy development.

Proportional dose of rapid-onset opioid in breakthrough cancer pain management: An open-label, multicenter study.

BACKGROUND: The management of breakthrough pain (BTP) in cancer patients is a challenge. It is clinically useful to evaluate the effectiveness of rapid-onset opioid at a starting dose in proportional to the background opioid regimen. This open-label, multicenter, noncomparative study aimed to assess the efficacy and safety of proportional doses of fentanyl buccal soluble film (FBSF) in patients with breakthrough cancer pain. METHODS: Thirty patients aged 20 to 70, experiencing 1 to 3 BTP per day, receiving regimens equivalent to 60 to 360 mg/day of oral morphine or 25 to 150 µg/h of transdermal fentanyl ≥1 week, were prospectively recruited. FBSF was administered proportionally based on their current opioid regimen for baseline pain. The percentage of patients requiring dose titration was evaluated. For each BTP episode, changes in pain intensity at 30 minutes (PID30) after dosing, patient's satisfaction, the percentage of episodes requiring rescue medication, and adverse events (AEs) were recorded. RESULTS: The percentage of patients who required dose titration was 21.4% (6/28) and 12.0% (3/25) in the full analysis set and per-protocol populations, respectively. The average PID30 was 3.9, and a pain score ≤3 was achieved in 95.1% of the events. Eight out of 367 (2.2%) BTP episodes needed rescue medication. The majority of subjects (75.8%) rated their experience of pain management as good to excellent. A total of 6 drug-related AEs were reported by 3 (10.7%) patients in the safety population. CONCLUSIONS: FBSF dose in proportional to the regimen of opioid for baseline pain management is efficacious and well tolerated for the treatment of cancer patients with BTP.

Intelligent system to predict intradialytic hypotension in chronic hemodialysis.

BACKGROUND: Intradialytic hypotension (IDH) is a serious complication and a major risk factor of increased mortality during hemodialysis (HD). However, predicting the occurrence of intradialytic blood pressure (BP) fluctuations clinically is difficult. This study aimed to develop an intelligent system with capability of predicting IDH. METHODS: In developing and training the prediction models in the intelligent system, we used a database of 653 HD outpatients who underwent 55,516 HD treatment sessions, resulting in 285,705 valid BP records. We built models to predict IDH at the next BP check by applying time-dependent logistic regression analyses. RESULTS: Our results showed the sensitivity of 86% and specificity of 81% for both nadir systolic BP (SBP) of <90 mmHg and <100 mmHg, suggesting good performance of our prediction models. We obtained similar results in validating via test data and data of newly enrolled patients (new-patient data), which is important for simulating prospective situations wherein dialysis staff are unfamiliar with new patients. This compensates for the retrospective nature of the BP records used in our study. CONCLUSION: The use of this validated intelligent system can identify patients who are at risk of IDH in advance, which may facilitate well-timed personalized management and intervention.