Background: Clinical decision support systems are designed to utilize medical data, knowledge, and analysis engines and to generate patient-specific assessments or recommendations to health professionals in order to assist decision making. Artificial intelligence–enabled clinical decision support systems aid the decision-making process through an intelligent component. Well-defined evaluation methods are essential to ensure the seamless integration and contribution of these systems to clinical practice. Objective: The purpose of this study was to develop and validate a measurement instrument and test the interrelationships of evaluation variables for an artificial intelligence–enabled clinical decision support system evaluation framework. Methods: An artificial intelligence–enabled clinical decision support system evaluation framework consisting of 6 variables was developed. A Delphi process was conducted to develop the measurement instrument items. Cognitive interviews and pretesting were performed to refine the questions. Web-based survey response data were analyzed to remove irrelevant questions from the measurement instrument, to test dimensional structure, and to assess reliability and validity. The interrelationships of relevant variables were tested and verified using path analysis, and a 28-item measurement instrument was developed. Measurement instrument survey responses were collected from 156 respondents. Results: The Cronbach α of the measurement instrument was 0.963, and its content validity was 0.943. Values of average variance extracted ranged from 0.582 to 0.756, and values of the heterotrait-monotrait ratio ranged from 0.376 to 0.896. The final model had a good fit (χ262=36.984; P=.08; comparative fit index 0.991; goodness-of-fit index 0.957; root mean square error of approximation 0.052; standardized root mean square residual 0.028). Variables in the final model accounted for 89% of the variance in the user acceptance dimension. Conclusions: User acceptance is the central dimension of artificial intelligence–enabled clinical decision support system success. Acceptance was directly influenced by perceived ease of use, information quality, service quality, and perceived benefit. Acceptance was also indirectly influenced by system quality and information quality through perceived ease of use. User acceptance and perceived benefit were interrelated.

The high cost and low availability of polysomnography (PSG) limits the timely diagnosis of OSA. Herein, we developed and validated a simple-to-use nomogram for predicting OSA. We collected and analyzed the cross-sectional data of 4162 participants with suspected OSA, seen at our sleep center between 2007 and 2016. Demographic, biochemical and anthropometric data, as well as sleep parameters were obtained. A least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data dimensionality, select factors, and construct the nomogram. The performance of the nomogram was assessed using calibration and discrimination. Internal validation was also performed. The LASSO regression analysis identified age, sex, body mass index, neck circumference, waist circumference, glucose, insulin, and apolipoprotein B as significant predictive factors of OSA. Our nomogram model showed good discrimination and calibration in terms of predicting OSA, and had a C-index value of 0.839 according to the internal validation. Discrimination and calibration in the validation group was also good (C-index = 0.820). The nomogram identified individuals at risk for OSA with an area under the curve (AUC) of 0.84 [95% confidence interval (CI), 0.83–0.86]. Our simple-to-use nomogram is not intended to replace standard PSG, but will help physicians better make decisions on PSG arrangement for the patients referred to sleep center.

Background: Elbow stiffness is a severe complication after trauma. Surgical or conservative treatments may be ineffective for restoring functional elbow motion. We aim to evaluate intrinsic and extrinsic factors for the occurrence and severity of elbow stiffness.Methods: This retrospective case–control study included mild/moderate stiffness, severe stiffness, and non-stiffness groups between January 2011 and December 2017 at a single orthopedic center. Multivariable logistic regression analysis and subgroup analysis were used to evaluate age, gender, body mass index, muscle strength, fracture type and site, injury mechanism, immobilization time, elbow dysfunction time, multiple surgeries, nerve symptoms, physical therapy, smoking and alcohol abuse, and dominant hand of stiff elbow as potential risk factors for the occurrence and severity of elbow stiffness.Results: There were 461 patients in the stiffness group and 227 patients in the non-stiffness group. The odds ratios (ORs) of the age, muscle strength, and injury mechanism were 0.960, 0.333, and 0.216 for the occurrence of elbow stiffness. In subgroup evaluation, increased cast immobilization time might be a risk factor for patients receiving conservative therapies (OR = 2.02; p = 0.014). In the evaluation on factors for progression of elbow stiffness, “multiple surgeries” might be a risk factor in surgical treatment by subgroup analysis (OR = 1.943; p = 0.026). Nevertheless, alcohol abuse might increase severity of elbow stiffness in conservatively treated patients (OR = 3.082; p = 0.025).Conclusion: Increased cast immobilization time in the conservative therapy might be a risk factor for stiffness occurrence. Multiple surgeries might be risk factors for stiffness progression. Alcohol abuse potentially increased stiffness severity after conservative treatment.

The prognosis of Chinese patients with eyelid sebaceous carcinoma (SC) has not been updated for >3 decades. The prognostic predictors are multifactorial, and there is no validated prognostic model for eyelid SC. This study included 238 consecutive patients with eyelid SC. All eligible patients were followed up for metastasis and mortality. The predictors of tumor-related survival were explored by Cox analyses. A prognostic nomogram was developed and validated using bootstrap resampling. The predictive accuracy and discriminative ability were compared between the nomogram and the Tumor, Node, Metastasis (TNM) staging system. After a median follow-up period of 55.5 months, 27 (11.3%) patients died of metastatic SC, with a median survival time of 48.0 months. The 5-year and 10-year tumor-related survival rates were 88.1% and 77.9%, respectively. Orbital involvement (HR: 3.11, p = .022), the greatest tumor basal diameter (HR: 1.06, p = .003), the presence of pagetoid spread (HR: 2.90, p = .017), and having lymph node metastasis at initial diagnosis (HR: 13.66, p < .001) were independent risk factors for tumor-related death. A nomogram integrating these 4 factors was developed with a C-index of 0.887, which is significantly better than that of the TNM staging system (p = .002). The risk groups stratified by nomogram scores (p < .001 (low vs intermediate risk); p = .001 (intermediate vs high risk)) displayed better discrimination ability than TNM staging (T1 vs T2: p = .358; T2 vs T3: p = .171; T3 vs T4: p < .001) in patients at an early stage. The prognosis of Chinese patients with eyelid SC has improved over the last 3 decades, and it is comparable to that of patients from other countries. This nomogram provides more accurate individualized estimates of survival for eyelid SC patients and may guide clinicians in their therapeutic decisions.

Background: Obstructive sleep apnea (OSA) and excessive daytime sleepiness (EDS) were considered to contribute to MetS. This study was performed to assess the association between MetS and EDS in two independent large-scale populations, and in subjects who underwent upper-airway surgery. Methods: A total of 6312 patients without self-reported depression and 3578 suspected OSA patients were consecutively recruited, during health screening examinations and from our sleep center, respectively. A total of 57 subjects with OSA who underwent upper-airway surgery were also included. Demographic, anthropometric, biochemical, and polysomnographic data were obtained. Results: In the health screening examination group, 233 (9.23%) women and 350 (10.93%) men had complaints of EDS. A total of 229 (7.04%) women and 1182 (36.88%) men met the criteria for MetS. In the OSA group, 147 (21.18%) women and 1058 (36.69%) men reported EDS. In addition, 93 (13.4%) women and 1368 (47.43%) men reported MetS. In the health screening examination group, EDS did not contribute significantly to MetS (OR = 1.125, 95% CI: 0.907–1.395; p = 0.283). In the OSA group, EDS significantly contributed to MetS (OR = 1.249, 95% CI: 1.063–1.468; p = 0.007); however, the results were not significant after adjusting for sleep variables (OR = 1.071, 95% CI: 0.905–1.268; p = 0.423). Upper-airway surgery did not affect cardio-metabolic variables in OSA patients with or without EDS. Conclusions: EDS was not associated with MetS in two independent large-scale cohorts. In addition, upper-airway surgery did not affect components of MetS in OSA patients with and without EDS.

Purpose: Local recurrence predicts dismal prognosis in eyelid sebaceous carcinoma (SC). Recurrence predictors vary across studies. Accurate recurrence estimation is essential for individualized therapy in eyelid SC. This study aims to identify recurrence predictors and develop a nomogram for personalized prediction in eyelid SC. Methods: We conducted a multicenter retrospective cohort study. Chart reviews were performed in 418 consecutive patients with eyelid SC. All patients were followed up after their initial surgery. Multivariate Cox regression was used to explore the independent predictors of recurrence. A nomogram for recurrence prediction was developed and validated with bootstrap resampling. The predictive accuracy and discriminative ability were compared with the Tumor, Node, Metastasis (TNM) staging system. Results: Over a median of 60-month follow-up, 167 patients (40%) had local recurrence. The median time from diagnosis to recurrence was 14 months. The 1-year cumulative recurrence rate was 18%. Diagnostic delay (hazard ratio [HR] = 1.01, 95% confidence interval [CI] = 1.00–1.01, P = 0.001), orbital involvement (HR = 4.47, 95% CI = 3.04–6.58, P < 0.001), Ki67 (HR = 1.01, 95% CI = 1.00–1.02, P = 0.008) and initial surgery of Mohs micrographic surgery with intraoperative frozen section control (HR = 0.53, 95% CI = 0.35–0.80, P = 0.003) were independent influencing factors of recurrence. A nomogram integrating these four factors combined with pagetoid spread displayed satisfactory discriminative ability (C-index = 0.80–0.83; area under the curve [AUC] = 0.82–0.84), which compared favorably than TNM staging (all P < 0.05). Conclusions: The recurrence rate is high in eyelid SC. Early detection and primary resection with Mohs micrographic surgery are recommended in controlling recurrence. Patients with orbital involvement, high Ki67 expression, and pagetoid spread may require adjuvant measures. This nomogram offers more accurate recurrence estimates, aiding in therapeutic decision making.