Background: The effects of nonsteroidal anti-inflammatory drugs (NSAIDs)/cyclooxygenase (COX)-2 inhibitors on postoperative fracture-healing are controversial. Thus, we investigated the association between NSAID/COX-2 inhibitor administration and postoperative nonunion or delayed union of fractures. We aimed to determine the effects of NSAID/COX-2 inhibitor administration on postoperative fracture-healing with use of a common data model. Methods: Patients who underwent operative treatment of a fracture between 1998 and 2018 were included. To determine the effects of NSAID/COX-2 inhibitor administration on fracture-healing, postoperative NSAID/COX-2 inhibitor users were compared and 1:1 matched to nonusers, with 3,264 patients matched. The effect of each agent on bone-healing was determined on the basis of the primary outcome (nonunion/delayed union), defined as having a diagnosis code for nonunion or delayed union ≥6 months after surgery. The secondary outcome was reoperation for nonunion/delayed union. To examine the effect of NSAIDs/COX-2 inhibitors on bone union according to medication duration, a Kaplan-Meier survival analysis was performed. Results: Of the 8,693 patients who were included in the analysis, 208 had nonunion (178 patients; 2.05%) or delayed union (30 patients; 0.35%). Sixty-four (30.8%) of those 208 patients had a reoperation for nonunion or delayed union. NSAID users showed a significantly lower hazard of nonunion compared with the matched cohort of nonusers (hazard ratio, 0.69 [95% confidence interval, 0.48 to 0.98]; p = 0.040) but did not show a significant difference in the other matched comparison for any other outcomes. Kaplan-Meier survival analysis revealed significantly lower and higher nonunion/delayed union rates when the medication durations were ≤3 and >3 weeks, respectively (p = 0.001). For COX-2 inhibitors, the survival curve according to the medication duration showed no significant difference among the groups (p = 0.9). Conclusions: Our study demonstrated no short-term impact of NSAIDs/COX-2 inhibitors on long-bone fracture-healing. However, continued use of these medications for a period of >3 weeks may be associated with higher rates of nonunion or delayed union. Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

We developed a novel quantification method named “shape feature” by combining the features of amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) and evaluated its significance in predicting the conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. From the ADNI database, 334 patients with MCI were included. The brain amyloid smoothing score (AV45_BASS) and brain atrophy index (MR_BAI) were calculated using the surface area and volume of the region of interest in AV45 PET and MRI. During the 48-month follow-up period, 108 (32.3%) patients converted from MCI to AD. Age, Mini-Mental State Examination (MMSE), cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog), apolipoprotein E (APOE), standardized uptake value ratio (SUVR), AV45_BASS, MR_BAI, and shape feature were significantly different between converters and non-converters. Univariate analysis showed that age, MMSE, ADAS-cog, APOE, SUVR, AV45_BASS, MR_BAI, and shape feature were correlated with the conversion to AD. In multivariate analyses, high shape feature, SUVR, and ADAS-cog values were associated with an increased risk of conversion to AD. In patients with MCI in the ADNI cohort, our quantification method was the strongest prognostic factor for predicting their conversion to AD.

Patient-generated health data (PGHD) can be managed easily by a mobile personal health record (mPHR) and can increase patient engagement. This study investigated the effect of PGHD functions on mPHR usage. We collected usage log data from an mPHR app, My Chart in My Hand (MCMH), for seven years. We analyzed the number of accesses and trends for each menu by age and sex according to the version-up. Generalized estimating equation (GEE) analysis was used to determine the likelihood of continuous app usage according to the menus and version-up. The total number of users of each version were 15,357 and 51,553, respectively. Adult females under 50 years were the most prevalent user group (30.0%). The “My Chart” menu was the most accessed menu, and the total access count increased by ~10 times after the version-up. The “Health Management” menu designed for PGHD showed the largest degree of increase in its likelihood of continuous usage after the version-up (1.245; p < 0.0001) across menus (range: 0.925–1.050). Notably, improvement of PGHD management in adult females over 50 years is needed.

Background/Objectives: This study aimed to investigate the predictive power of integrated longitudinal amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) data for determining the likelihood of conversion to Alzheimer’s disease (AD) in patients with mild cognitive impairment (MCI). Methods: We included 180 patients with MCI from the Alzheimer’s Disease Neuroimaging Initiative, with baseline and 2-year follow-up scans obtained using F-18 florbetapir PET and MRI. Patients were categorized as converters (progressing to AD) or nonconverters based on a 6-year follow-up. Quantitative analyses included the calculation of amyloid burden using the standardized uptake value ratio (SUVR), brain amyloid smoothing scores (BASSs), brain atrophy indices (BAIs), and their integration into shape features. Longitudinal changes and receiver operating characteristic analyses assessed the predictive power of these biomarkers. Results: Among 180 patients with MCI, 76 (42.2%) were converters, who exhibited significantly higher baseline and 2-year follow-up values for SUVR, BASS, BAI, and shape features than nonconverters (p < 0.001). Shape features demonstrated the highest predictive accuracy for conversion, with areas under the curve of 0.891 at baseline and 0.898 at 2 years. Percent change analyses revealed significant increases in brain atrophy; amyloid deposition changes showed a paradoxical decrease in converters. Additionally, strong associations were observed between longitudinal changes in shape features and neuropsychological test results. Conclusions: The integration of amyloid PET and MRI biomarkers enhances the prediction of AD progression in patients with MCI. These findings support the potential of combined imaging approaches for early diagnosis and targeted interventions in AD.

The incidence of postoperative pneumonia (POP) in patients with cancer is high, but its incidence following major cancer surgeries is unclear. Therefore, we investigated the incidence and risk factors of POP after surgery in patients with the five most common cancers in Korea using a common data model (CDM). Patients aged >19 years who underwent gastric, colon, liver, lung, or breast cancer surgery between January 2011 and December 2020 were included, excluding patients who underwent chemotherapy or radiotherapy. Pneumonia was defined as a pneumonia diagnosis code in patients hospitalized postoperatively. Gastric, colon, lung, breast, and liver cancers were noted in 4004 (47.4%), 622 (7.4%), 2022 (24%), 958 (11.3%), and 839 (9.9%) of 8445 patients, respectively. The cumulative POP incidence was 3.1% (n = 262), with the highest incidence in lung cancer (n = 91, 4.5%), followed by gastric (n = 133, 3.3%), colon (n = 19, 3.1%), liver (n = 14, 1.7%), and breast (n = 5, 0.5%) cancers. In multivariable analysis, older age, male sex, history of chronic pulmonary disease, mood disorder, and cerebrovascular disease were POP predictors. The cumulative POP incidence in the five cancers using the CDM was approximately 3%. Older age, male sex, chronic pulmonary disease, mood disorder, and cerebrovascular disease were POP risk factors in patients with cancer.

We developed a novel quantification method named shape feature using F-18 florapronol positron emission tomography–computed tomography (PET/CT) and evaluated its sensitivity and specificity for discriminating between patients with Alzheimer’s disease (AD) and patients with mild cognitive impairment or other precursors dementia (non-AD). We calculated the cerebral amyloid smoothing score (CASS) and brain atrophy index (BAI) using the surface area and volume of the region of interest in PET images. We calculated gray and white matter from trained CT data, prepared using U-net. Shape feature was calculated by multiplying CASS with BAI scores. We measured region-based standard uptake values (SUVr) and performed receiver operating characteristic (ROC) analysis to compare SUVr, shape feature, CASS, and BAI score. We investigated the relationship between shape feature and neuropsychological tests. Fifty subjects (23 with AD and 27 with non-AD) were evaluated. SUVr, shape feature, CASS, and BAI score were significantly higher in patients with AD than in those with non-AD. There was no statistically significant difference between shape feature and SUVr in ROC analysis. Shape feature correlated well with mini-mental state examination scores. Shape feature can effectively quantify beta-amyloid deposition and atrophic changes in the brain. These results suggest that shape feature is useful in the diagnosis of AD.