Naoya Kobayashi

Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign data; however, it remains uncertain whether incorporating individual patient baselines could enhance accuracy. This study aimed to investigate improving the accuracy by incorporating deviations from baseline patient vital signs and the concurrence of the predicted artificial intelligence values with the probability of critical care pain observation tool (CPOT) ≥ 3 after fentanyl administration. The study included adult patients in intensive care who underwent multiple pain-related assessments. We employed a random forest model, utilizing arterial pressure, heart rate, respiratory rate, gender, age, and Richmond Agitation–Sedation Scale score as explanatory variables. Pain was measured as the probability of CPOT scores of ≥ 3, and subsequently adjusted based on each patient's baseline. The study included 10,299 patients with 117,190 CPOT assessments. Of these, 3.3% had CPOT scores of ≥ 3. The random forest model demonstrated strong accuracy with an area under the receiver operating characteristic curve of 0.903. Patients treated with fentanyl were grouped based on CPOT score improvement. Those with ≥ 1-h of improvement after fentanyl administration had a significantly lower pain index (P = 0.020). Therefore, incorporating deviations from baseline patient vital signs improved the accuracy of pain visualization using machine learning techniques.

Transcatheter aortic valve implantation (TAVI) is an effective treatment for severe aortic stenosis (AS); however, postoperative delirium (POD) can worsen patient outcomes. This study aimed to examine the risk factors for POD after TAVI, including possible intervening factors. We included 87 patients (mean age: 83) who underwent TAVI between May 2014 and September 2018. POD was defined by the presence or absence of delirium on ICU admission, assessed using the Confusion Assessment Method for the ICU. Factors that showed significant differences in the univariate analysis were analyzed using a multiple logistic regression analysis. In total, 31 patients (36%) had POD after ICU admission, and 56 (64%) did not. The preoperative frailty score and aortic valve opening area (AVA) were significant risk factors for POD. The multivariate analysis also showed that both factors were independent risk factors for POD (area under the receiver operating characteristic curve: 0.805). There were no significant differences in the number of ICU days. However, postoperative hospitalization was significantly longer in the POD group (19 (17–31) days vs. 16 (13–22) days; p = 0.002). POD was associated with a narrow AVA and frailty; this suggests that frailty prevention interventions according to the AVA may be important.

Monitoring the pain intensity in critically ill patients is crucial because intense pain can cause adverse events, including poor survival rates; however, continuous pain evaluation is difficult. Vital signs have traditionally been considered ineffective in pain assessment; nevertheless, the use of machine learning may automate pain assessment using vital signs. This retrospective observational study was performed at a university hospital in Sendai, Japan. Objective pain assessments were performed in eligible patients using the Critical-Care Pain Observation Tool (CPOT). Three machine-learning methods—random forest (RF), support vector machine (SVM), and logistic regression (LR)—were employed to predict pain using parameters, such as vital signs, age group, and sedation levels. Prediction accuracy was calculated as the harmonic mean of sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Furthermore, 117,190 CPOT assessments were performed in 11,507 eligible patients (median age: 65 years; 58.0% males). We found that pain prediction was possible with all three machine-learning methods. RF demonstrated the highest AUROC for the test data (RF: 0.853, SVM: 0.823, and LR: 0.787). With this method, pain can be objectively, continuously, and semi-automatically evaluated in critically ill patients.

The dynamic model for rotation which is achieved by only lifting up at the end of the object is proposed. The model allows the rotation around the picking point and the slide of the contact point on the ground. According to the rotation model, a dynamic simulation is conducted to show the feasibility. As a result of the simulation, the required force for manipulation indicates the object pose so that the object can be rotated to the target pose by monitoring the picking force.

Although induced pluripotent stem (iPS) cells have significant implications for overcoming most of the ethical issues associated with embryonic stem cells, several issues related to the use of iPS cells in clinical applications remain unresolved, including the issue of teratoma formation. We previously reported that the induction of induced tissue-specific stem (iTS) cells from the pancreas (iTS-P) or liver (iTS-L) by the transient overexpression of reprogramming factors, combined with tissue-specific selection and the generation of iTS cells, could have important implications for the clinical application of stem cells. At the same time, we also generated “induced fibroblast-like (iF) cells” that were capable of self-renewal, which had a similar morphology to fibroblast cells. In this study, we evaluated iF cells. iF cells are unlikely to show adipogenic/osteogenic differentiation. Moreover, iF cells have the ability to form tumors and behave similarly to pancreatic cancer cells. The technology used in the generation of iPS/iTS cells is also associated with the risk of generating cancer-like cells.

We report a patient who developed drug-eluting stent (DES) thrombosis induced by discontinuation of dual antiplatelet therapy (DAPT) and subsequently had a massive surgical site bleed caused by restarting heparin and DAPT during the perioperative period. An 85-year-old man visited a local hospital owing to complaints dyspnea. He was diagnosed with laryngeal cancer and was scheduled for a total laryngectomy. Preoperative examinations showed an anteroseptal myocardial infarction. A DES was placed at segment 6 of the coronary artery and DAPT was initiated 27 days before surgery. After admission to our hospital, DAPT was replaced with unfractionated heparin. On the operation day, heparin was discontinued, and a tracheotomy, total laryngectomy and right hemi-thyroidectomy were performed. While recovering from anesthesia, ischemic ST elevation appeared. Cardiac catheterization revealed complete obstruction of the DES by a white thrombus. After recanalization, heparin and DAPT were restarted, and bleeding occurred. The next day, total blood loss was 2755 mL and surgical hemostasis was performed. Because his serum creatine kinase value was elevated at the cessation of heparin, anticoagulation by unfractionated heparin could not have prevented platelet thrombosis. Therefore, we should performed the tracheostomy to secure the patient’s airway under DAPT or only aspirin therapy a month after the DES implantation, and performed the laryngectomy and right hemi-thyroidectomy five months after the first surgery. This case is serious warnings of perioperative major adverse cardiac events induced by discontinuation of DAPT; unfractionated heparin was an insufficient safeguard against platelet thrombosis, and perioperative massive bleeding induced by restarting antiplatelet and anticoagulation therapy. In addition, a series of human errors, which the cardiologist chosen DES regardless of scheduled total larygectomy, the discontinuation of antiplatelet therapy shortly after a DES placement, and the surgical staffs failed to share the elevated serum CK and CK-MB values, caused life-threatening complications.

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Liver diseases still have a high mortality even though liver transplantation has become a standard treatment. Currently, hepatocyte transplantation has been proposed as another promising strategy. One limitation is the availability of human livers as a source of hepatocytes. Because of an unlimited supply, the use of porcine hepatocytes might address this problem. Regardless of the source, once isolated hepatocytes lose specific functionality due to the loss of the natural microenvironment. For this reason, we tested the ability of a self-assembling peptide nanofiber (SAPNF) to provide a provisional three-dimensional (3D) support to interact with cells to control their function in vivo. Isolated porcine hepatocytes were embedded in SAPNF, or collagen type I and transplanted by direct injection into the splenic pulp of SCID mice suffering from acute liver failure (ALF) by 90% hepatectomy. SAPNF porcine hepatocyte transplantation produced engraftment that was far superior to that obtained using collagen and prolonged the survival of mice with ALF, in contrast with controls. An ultrastructural evaluation using transmission electron microscopy indicated extensive cell–cell communication and preservation of hepatocyte architecture. The transplanted SAPNF hepatocytes showed higher expression of albumin and PAS and lower apoptotic events assessed by TUNEL staining. Hepatocytes culture in a truly 3D network allows in vivo maintaining of differentiated functions, and once transplanted between widely divergent species can function to correct acute liver failure in mice and prolong their survival.