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Naoko Mori

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Open access Aug 2026

Impact of cognitive impairment on postoperative delirium and discharge disposition following knee arthroplasty: a Japanese nationwide propensity score–matched study

As populations age, the number of older patients undergoing knee arthroplasty continues to increase. Cognitive impairment is prevalent among older adults and has been associated with adverse perioperative outcomes; however, its impact on postoperative delirium and discharge disposition following knee arthroplasty remains insufficiently defined, particularly in large Asian populations. We conducted a nationwide retrospective cohort study using Japan’s Diagnosis Procedure Combination database from April 2016 to March 2023. Older patients who underwent primary total knee arthroplasty (TKA) or unicompartmental knee arthroplasty (UKA) were identified. Cognitive impairment was defined using ICD-10 diagnostic codes at admission. The primary outcome was postoperative delirium, and secondary outcomes included discharge to home, length of hospital stay, and perioperative blood transfusion. Propensity score matching (1:1) was performed to adjust for demographic factors, comorbidities, and surgical characteristics. Multivariable logistic regression and sensitivity analyses were conducted. Among 259,319 eligible patients, 3,934 matched pairs were identified after propensity score matching. Patients with cognitive impairment had a significantly higher risk of postoperative delirium compared with those without cognitive impairment (absolute risk difference, 3.2%; 95% CI, 2.5–3.9). Cognitive impairment was independently associated with postoperative delirium (odds ratio [OR], 4.47; 95% CI, 3.11–6.41) and a reduced likelihood of direct discharge to home (OR, 0.64; 95% CI, 0.57–0.71). Length of hospital stay was modestly longer in patients with cognitive impairment, whereas no clinically meaningful differences were observed in other postoperative complications after adjustment. Cognitive impairment is a strong and independent risk factor for postoperative delirium and reduced likelihood of direct discharge to home following knee arthroplasty in older patients. Incorporating cognitive assessment into perioperative risk stratification may help optimize geriatric orthopedic care and postoperative planning.

Yuri Mori, K. Tarasawa, Hidetatsu Tanaka et al. · Archives of Orthopaedic and... · 0 citations

Open access 2026

Parameter Estimation for the Intravoxel Incoherent Motion-diffusional Kurtosis Imaging Model Using Synthetic Q-space Learning Toward Breast Tumor Diagnosis.

PURPOSE Synthetic Q-space learning (synQSL), which uses only synthetic data in the training of regressors, has demonstrated promising results in parameter estimation for brain diffusion MRI (dMRI). This study aimed to evaluate the performance of synQSL in breast dMRI for intravoxel incoherent motion-diffusional kurtosis imaging (IVIM-DKI) parameter estimation, with comparing several types of regressors and conventional fitting by nonlinear least squares fitting (NL-LSF). METHODS In synthesizing data for synQSL, IVIM-DKI parameters were sampled from uniform distributions and substituted into the signal model along with b-values to generate diffusion-weighted imaging (DWI) signals. In addition, Rician noise was mixed to the signals. We prepared datasets of 105 and 106 samples, and trained multi-layer perceptron (MLP), Kolmogorov-Arnold networks (KAN), and random forest (RF) regressors for synQSL. The performance of the parameter estimation methods including NL-LSF was evaluated using a digital phantom including various value combinations of IVIM-DKI parameters and clinical data of 67 cases (13 benign and 54 malignant lesions) through quantitative analysis and visual assessment. RESULTS In the digital phantom, the regressors of synQSL achieved significantly lower root mean square error (RMSE) for f, D∗, and D than NL-LSF (P < 0.05) with less variation among the parameter sets. In clinical datasets, synQSL not only improved the visual quality of parameter maps but also showed significant differences between benign and malignant lesions in parameters while the NL-LSF failed. Furthermore, the estimation times for all synQSL regressors were substantially shorter than that of NL-LSF. Among the synQSL regressors, MLP showed superior properties including computational cost. CONCLUSION synQSL demonstrated superior parameter estimation performance compared to NL-LSF in breast IVIM-DKI analysis. In this study, MLP was considered the most suitable regressor for synQSL among those we examined, based on the balance between estimation accuracy and computational costs.

Kousei Konya, Yuki Ichinoseki, Erina Kato et al. · Magnetic Resonance in Medica... · 0 citations