Nafamostat mesilate (NM) is used clinically for the prevention and treatment of pancreatitis. Electrolyte monitoring is necessary in geriatric patients receiving NM as it may cause hyperkalemia with the possibility of inducing arrhythmias. We attempted to evaluate the risk of hyperkalemia with aging and its background in this retrospective cohort study. Thirty-six of 290 patients (12.4%) who were receiving NM for the prevention and treatment of pancreatitis experienced hyperkalemia at the Kanazawa Medical Center over the past 2 years. A multiple logistic regression analysis was performed to identify the risk factors for hyperkalemia. The results showed that signi cant predictors of hyperkalemia were increasing age (per 10 years; odds ratio [OR]: 1.41, 95% con dence interval [CI]: 1.01 -1.96, P < 0.045), fever (OR: 3.11, 95% CI: 1.25 -7.71, P < 0.015), a high daily dose (per 10 mg/body/day; OR: 1.10, 95% CI: 1.01 -1.20, P < 0.038), and a high serum potassium level at the start of treatment (per mEq/L; OR: 2.86, 95% CI: 1.40 -5.83, P < 0.004). Thus, prior to the initiation of treatment with NM, it is necessary to assess the patientʼs medical background and to perform electrolyte monitoring frequently. We suggest that dosage reduction should be considered in the treatment of geriatric patients undergoing long-term treatment with NM.
Objective: To develop a clinical prediction rule (CPR) that predicts treatment responses to mechanical lumbar traction (MLT) among patients with lumbar disc herniation (LDH). Method: This studywas an uncontrolled prospective cohort study. The subjects included 103 patients diagnosed with LDH for which they underwent conservative therapy. The subjects received MLT for 2 weeks, and the application of any other medication was left at the discretion of the attending physician. The initial evaluation was performed prior to the initiation of treatment. The independent variables from the initial evaluation were imaging diagnosis, Oswestry Disability Index (ODI), Fear-Avoidance Beliefs Questionnaire score, visual analog scale, medical interview, physical examination. The patients whose ODI after 2 weeks of treatment improved by ! 50% of that at the initial evaluation were defined as responders. Results: Of the 103 subjects, 24 were responders, and the five predictors selected for the CPR were limited lumbar extension range of motion, low-level fear-avoidance beliefs regarding work, no segmental hypomobility in the lumbar spine, short duration of symptoms, and sudden onset of symptoms. For the patients with at least three of the five predictors, the probability of their ODI greatly improving increased from 23.3% to 48.7% compared with the patients without these predictors (positive likelihood ratio, 3.13). Conclusion: Five factors were selected for the CPR to predict whether patients with LDH would demonstrate short-term improvement following conservative therapy with MLT.
Digoxin toxicity (plasma digoxin concentration ≥0.9 ng/mL) is associated with worsening heart failure (HF). Decision tree (DT) analysis, a machine learning method, has a flowchart-like model where users can easily predict the risk of adverse drug reactions. The present study aimed to construct a flowchart using DT analysis that can be used by medical staff to predict digoxin toxicity. We conducted a multicenter retrospective study involving 333 adult patients with HF who received oral digoxin treatment. In this study, we employed a chi-squared automatic interaction detection algorithm to construct DT models. The dependent variable was set as the plasma digoxin concentration (≥ 0.9 ng/mL) in the trough during the steady state, and factors with p < 0.2 in the univariate analysis were set as the explanatory variables. Multivariate logistic regression analysis was conducted to validate the DT model. The accuracy and misclassification rates of the model were evaluated. In the DT analysis, patients with creatinine clearance <32 mL/min, daily digoxin dose ≥1.6 µg/kg, and left ventricular ejection fraction ≥50% showed a high incidence of digoxin toxicity (91.8%; 45/49). Multivariate logistic regression analysis revealed that creatinine clearance <32 mL/min and daily digoxin dose ≥1.6 µg/kg were independent risk factors. The accuracy and misclassification rates of the DT model were 88.2 and 46.2 2.7%, respectively. Although the flowchart created in this study needs further validation, it is straightforward and potentially useful for medical staff in determining the initial dose of digoxin in patients with HF.
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