Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test.

OBJECTIVE: The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). METHOD: Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. RESULTS: The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. CONCLUSIONS: Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Oral and oropharyngeal cancer screening and tobacco cessation discussions, NHANES 2011-2018.

OBJECTIVE: Oral cavity and oropharyngeal cancer (OOPC) is a devastating disease often caught in late stages. People who use tobacco are at higher risk of OOPC. Tobacco cessation discussions and OOPC screenings are important factors in decreasing the risk of OOPC or its late stage diagnosis. As research on sex differences has been increasing-from research on biomedical to psychological and sociological determinants-there is a potential difference, by sex, as to whom is more likely to have a tobacco cessation discussion and OOPC screening. The objective of this study is to determine if there is an association of sex with tobacco cessation discussions and OOPC screenings conducted by dental healthcare professionals among participants who currently use tobacco. METHOD: Data from 8 years of the National Health and Nutrition Examination Survey (2011-2018) were merged. Data from participants, ages 30 years and above, who self-reported current use of tobacco, a dental visit within the previous year and responsed to questions about oral cancer screening were analysed for frequency determination and logistic regression analysis. Having the combination of neither OOPC screening nor discussion about the benefits of not using tobacco was the outcome in the analysis. RESULTS: There were 22.1% who had an OOPC screening by a dental professional within the previous year. Of the 41% who reported having had a conversation with a dental professional within the previous year about the benefits of tobacco cessation, 9.8% reported having both the conversation and OOPC screening. Males were less likely than females to have the combination of neither OOPC screening nor advice about tobacco cessation than females (adjusted odds ratio: 0.74; 95%CI: 0.57, 0.96). CONCLUSION: There is an increased need for OOPC screening and the discussion of tobacco use by dental professionals among their patients who use tobacco, particularly for female patients.

Drug-resistant temporal lobe epilepsy with temporal encephaloceles: How far to resect.

PURPOSE: This study sought to evaluate the impact of surgical extent on seizure outcome in drug-resistant temporal lobe epilepsy (DR-TLE) with temporal encephaloceles (TE). METHODS: This was a single-institution retrospective study of patients who underwent surgery for DR-TLE with TE between January 2008 and December 2020. The impact of surgical extent on seizure outcome was evaluated. In a subset with dominant DR-TLE, the impact of surgical extent on neuropsychometric outcome was evaluated. RESULTS: Thirty-four patients were identified (female, 56%; median age at surgery, 43 years). TE were frequently overlooked on initial magnetic resonance imaging (MRI), with encephaloceles only detected after repeat or expert re-review of MRI, additional multi-modal imaging, or intra-operatively in 31 (91%). Sixteen (47%) underwent limited resections, including encephalocele resection only (n = 5) and encephalocele resection with more extensive temporal corticectomy sparing the amygdala and hippocampus (n = 11). The remainder (n = 18, 53%) underwent standard anterior temporal lobectomy and amygdalohippocampectomy (ATLAH). Limited resection was performed more frequently on the left (12/17 vs. 4/17, p = 0.015). Twenty-seven patients (79%) had a favourable outcome (Engel I/II), and 17 (50%) were seizure-free at the last follow-up (median seizure-free survival of 27.3 months). There was no statistically significant difference in seizure-free outcomes between limited resection and ATLAH. In dominant DR-TLE, verbal memory decline was more likely after ATLAH than limited resection (3/4 vs. 0/9, p = 0.014). CONCLUSION: Expert re-review of imaging and multi-modal advanced imaging improved TE identification. There was no statistical difference in seizure-free outcomes based on surgical extent. Preservation of verbal memory supports limited resection in dominant temporal cases.

Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records.

The major significance of the 2018 gingivitis classification criteria is utilizing a simple, objective, and reliable clinical sign, bleeding on probing score (BOP%), to diagnose gingivitis. However, studies report variations in gingivitis diagnoses with the potential to under- or over-estimating disease occurrence. This study determined the agreement between gingivitis diagnoses generated using the 2018 criteria (BOP%) versus diagnoses using BOP% and other gingival visual assessments. We conducted a retrospective study of 28,908 patients' electronic dental records (EDR) from January-2009 to December-2014, at the Indiana University School of Dentistry. Computational and natural language processing (NLP) approaches were developed to diagnose gingivitis cases from BOP% and retrieve diagnoses from clinical notes. Subsequently, we determined the agreement between BOP%-generated diagnoses and clinician-recorded diagnoses. A thirty-four percent agreement was present between BOP%-generated diagnoses and clinician-recorded diagnoses for disease status (no gingivitis/gingivitis) and a 9% agreement for the disease extent (localized/generalized gingivitis). The computational program and NLP performed excellently with 99.5% and 98% f-1 measures, respectively. Sixty-six percent of patients diagnosed with gingivitis were reclassified as having healthy gingiva based on the 2018 diagnostic classification. The results indicate potential challenges with clinicians adopting the new diagnostic criterion as they transition to using the BOP% alone and not considering the visual signs of inflammation. Periodic training and calibration could facilitate clinicians' and researchers' adoption of the 2018 diagnostic system. The informatics approaches developed could be utilized to automate diagnostic findings from EDR charting and clinical notes.

Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data.

Established classifications exist to confirm Sjögren's Disease (SD) (previously referred as Sjögren's Syndrome) and recruit patients for research. However, no established classification exists for diagnosis in clinical settings causing delayed diagnosis. SD patients experience a huge dental disease burden impairing their quality of life. This study established criteria to characterize Indiana University School of Dentistry (IUSD) patients' SD based on symptoms and signs in the electronic health record (EHR) data available through the state-wide Indiana health information exchange (IHIE). Association between SD diagnosis, and comorbidities including other autoimmune conditions, and documentation of SD diagnosis in electronic dental record (EDR) were also determined. The IUSD patients' EDR were linked with their EHR data in the IHIE and queried for SD diagnostic ICD9/10 codes. The resulting cohorts' EHR clinical findings were characterized and classified using diagnostic criteria based on clinical experts' recommendations. Descriptive statistics were performed, and Chi-square tests determined the association between the different SD presentations and comorbidities including other autoimmune conditions. Eighty-three percent of IUSD patients had an EHR of which 377 patients had a SD diagnosis. They were characterized as positive (24%), uncertain (20%) and negative (56%) based on EHR clinical findings. Dry eyes and mouth were reported for 51% and positive Anti-Ro/SSA antibodies and anti-nuclear antibody (ANA) for 17% of this study cohort. One comorbidity was present in 98% and other autoimmune condition/s were present in 53% respectively. Significant differences were observed between the three SD clinical characteristics/classifications and certain medical and autoimmune conditions (p<0.05). Sixty-nine percent of patients' EDR did not mention SD, highlighting the huge gap in reporting SD during dental care. This study of SD patients diagnosed in community practices characterized three different SD clinical presentations, which can be used to generate SD study cohorts for longitudinal studies using EHR data. The results emphasize the heterogenous SD clinical presentations and the need for further research to diagnose SD early in community practice settings where most people seek care.

Effect of modernized collaborative care for depression on depressive symptoms and cardiovascular disease risk biomarkers: eIMPACT randomized controlled trial.

Although depression is a risk and prognostic factor for cardiovascular disease (CVD), clinical trials treating depression in patients with CVD have not demonstrated cardiovascular benefits. We proposed a novel explanation for the null results for CVD-related outcomes: the late timing of depression treatment in the natural history of CVD. Our objective was to determine whether successful depression treatment before, versus after, clinical CVD onset reduces CVD risk in depression. We conducted a single-center, parallel-group, assessor-blinded randomized controlled trial. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized to 12 months of the eIMPACT intervention (modernized collaborative care involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). Outcomes were depressive symptoms and CVD risk biomarkers at 12 months. Intervention participants, versus usual care participants, exhibited moderate-to-large (Hedges' g = -0.65, p < 0.01) improvements in depressive symptoms. Clinical response data yielded similar results - 43% of intervention participants, versus 17% of usual care participants, had a ≥ 50% reduction in depressive symptoms (OR = 3.73, 95% CI: 1.93-7.21, p < 0.01). However, no treatment group differences were observed for the CVD risk biomarkers - i.e., brachial flow-mediated dilation, high-frequency heart rate variability, interleukin-6, high-sensitivity C-reactive protein, ß-thromboglobulin, and platelet factor 4 (Hedges' gs = -0.23 to 0.02, ps ≥ 0.09). Our modernized collaborative care intervention - which harnessed technology to maximize access and minimize resources - produced clinically meaningful improvements in depressive symptoms. However, successful depression treatment did not lower CVD risk biomarkers. Our findings indicate that depression treatment alone may not be sufficient to reduce the excess CVD risk of people with depression and that alternative approaches are needed. In addition, our effective intervention highlights the utility of eHealth interventions and centralized, remote treatment delivery in safety net clinical settings and could inform contemporary integrated care approaches. Trial Registration:ClinicalTrials.gov Identifier: NCT02458690.

Developing Automated Computer Algorithms to Track Periodontal Disease Change from Longitudinal Electronic Dental Records.

OBJECTIVE: To develop two automated computer algorithms to extract information from clinical notes, and to generate three cohorts of patients (disease improvement, disease progression, and no disease change) to track periodontal disease (PD) change over time using longitudinal electronic dental records (EDR). METHODS: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between 1 January 2009, and 31 December 2014, at Indiana University School of Dentistry (IUSD) clinics. We utilized various Python libraries, such as Pandas, TensorFlow, and PyTorch, and a natural language tool kit to develop and test computer algorithms. We tested the performance through a manual review process by generating a confusion matrix. We calculated precision, recall, sensitivity, specificity, and accuracy to evaluate the performances of the algorithms. Finally, we evaluated the density of longitudinal EDR data for the following follow-up times: (1) None; (2) Up to 5 years; (3) > 5 and ≤ 10 years; and (4) >10 and ≤ 15 years. RESULTS: Thirty-four percent (n = 9954) of the study cohort had up to five years of follow-up visits, with an average of 2.78 visits with periodontal charting information. For clinician-documented diagnoses from clinical notes, 42% of patients (n = 5562) had at least two PD diagnoses to determine their disease change. In this cohort, with clinician-documented diagnoses, 72% percent of patients (n = 3919) did not have a disease status change between their first and last visits, 669 (13%) patients' disease status progressed, and 589 (11%) patients' disease improved. CONCLUSIONS: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We provided detailed steps and computer algorithms to clean and preprocess the EDR data and generated three cohorts of patients. This information can now be utilized for studying clinical courses using artificial intelligence and machine learning methods.

Unstable Middle Phalanx Base Fractures Treated With an Internal Joint Stabilizer: Preliminary Results.

BACKGROUND: Unstable fractures of the base of the middle phalanx are notorious for causing chronic loss of proximal interphalangeal (PIP) joint function, and they remain a challenge for the hand surgeon. We report on a temporary intraoperatively constructed internal joint stabilizer for unstable PIP joint injuries. METHODS: Across 2 institutions, a retrospective chart review was performed for cases with acute presentation of pilon fracture or fracture-dislocation of the base of the middle phalanx which were surgically treated with an internal joint stabilizer. Information collected included time from injury to surgical intervention, time from implantation to device removal, complications, and preoperative and postoperative range of motion. RESULTS: Seven patients met the inclusion criteria with a mean age of 51 (range: 24-72) years and a mean follow-up of 29 (range: 11-72) months. After removal of the fixator, the mean arc of PIP joint motion was 8° to 88° (range: 0°-100°). There were no infections, no hardware loosening or failures, and no revision procedures. CONCLUSION: The current findings are comparable to the results for dynamic external fixators. An internal joint stabilizer for unstable injuries to the base of the middle phalanx provides satisfactory functional outcomes, allows early postoperative motion, and mitigates the routine complications which may arise with external fixation.

Humeral loosening in reverse shoulder arthroplasty: an analysis of 2,342 cases.

INTRODUCTION: Humeral loosening is a rare complication in reverse shoulder arthroplasty (RSA) representing approximately 1% of total complications. The purpose of this study is to identify patients who underwent RSA and were revised because of loosening of the humeral component, identify patients who are at increased risk, and report on their surgical outcomes. MATERIALS AND METHODS: A retrospective review of all patients who received a primary RSA or revision RSA (rRSA) by a single surgeon from 2002-2021 identified a total of 1591 primary RSA and 751 rRSA procedures. These procedures were then organized based on indication for surgery. Further analysis was performed to identify RSAs that were subsequently revised because of aseptic loosening of the humeral component. A total of 41 surgeries met the inclusion criterion for the study, which was any RSA or rRSA that was revised because of loosening of the humeral component. Exclusion criterion was revision for a reason other than humeral loosening, neurogenic arthritis, or revision for loosening that was not originally implanted by the senior author (9 surgeries). Ultimately, 32 surgeries met criteria for further analysis. These 32 surgeries were organized by indication for preceding RSA or rRSA and were assessed for an association between indication for RSA or rRSA and eventual revision for humeral loosening. Additionally, these procedures were compared to a "control cohort" of procedures that were not revised and that had minimum 2 years' follow-up. To assess outcomes for these patients, pre- and postoperative Simple Shoulder Test, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (ASES), and ranges of motion were compared. Twenty procedures had sufficient data for outcomes analysis and were followed for an average of 54 months (range: 24-132 months). RESULTS: In primary RSAs, procedures performed for fracture or fracture sequelae were associated with revision for humeral-sided loosening (P = .009). In rRSAs, procedures performed for failed hemiarthroplasty for CTA were associated with rerevision for humeral-sided loosening (P = .009). Nine percent of patients revised for humeral loosening required rerevision for recurrent humeral loosening. Analysis of patients with 2-year clinical follow-up for humeral-sided loosening showed improvement in ASES pain (P = .014), ASES function (P = .042), and total ASES scores (P = .007). CONCLUSION: Humeral loosening is rare in RSA. In our cohort, 0.7% of the primary RSAs performed and 2.8% of the rRSAs performed were eventually revised for humeral loosening. Revisions of RSA for humeral loosening yield modest clinical improvements. Rerevision for humeral loosening was 6.3% of patients in our cohort.

Automatic Identification of Self-Reported COVID-19 Vaccine Information from Vaccine Adverse Events Reporting System.

BACKGROUND: The short time frame between the coronavirus disease 2019 (COVID-19) pandemic declaration and the vaccines authorization led to concerns among public regarding the safety and efficacy of the vaccines. The Food and Drug Administration uses the Vaccine Adverse Events Reporting System (VAERS) where general population can report their vaccine side effects in the text box. This information could be utilized to determine self-reported vaccine side effects. OBJECTIVE: To develop a supervised and unsupervised natural language processing (NLP) pipeline to extract self-reported COVID-19 vaccination side effects, location of the side effects, medications, and possibly false/misinformation seeking further investigation in a structured format for analysis and reporting. METHODS: We utilized the VAERS dataset of COVID-19 vaccine reports from November 2020 to August 2022 of 725,246 individuals. We first developed a gold-standard (GS) dataset of randomly selected 1,500 records. Second, the GS was split into training, testing, and validation sets. The training dataset was used to develop the NLP applications (supervised and unsupervised) and testing and validation datasets were used to test the performances of the NLP application. RESULTS: The NLP application automatically extracted vaccine side effects, body locations of the side effects, medication, and possibly misinformation with moderate to high accuracy (84% sensitivity, 82% specificity, and 83% F-1 measure). We found that 23% people (386,270) faced arm soreness, 31% body swelling (226,208), 23% fatigue/body weakness (168,160), and 22% (159,873) cold/flue-like symptoms. Most of the complications occurred in the body locations such as the arm, back, chest, neck, face, and head. Over-the-counter pain medications such as Tylenol and Ibuprofen and allergy medication like Benadryl were most reported self-reported medications. Death due to COVID-19, changes in the DNA, and infertility were possible false/misinformation reported by people. CONCLUSION: Some self-reported side effects such as syncope, arthralgia, and blood clotting need further clinical investigations. Our NLP application may help in extracting information from big free-text electronic datasets to help policy makers and other researchers with decision making.

Anatomic shoulder arthroplasty with high side reaming versus reverse shoulder arthroplasty for eccentric glenoid wear patterns with an intact rotator cuff: comparing early versus midterm outcomes with minimum 7 years of follow-up.

BACKGROUND: Eccentric glenoid bone loss patterns (B- and C-type glenoid) pose a difficult challenge when performing shoulder arthroplasty. Anatomic total shoulder arthroplasty with preferential high-side reaming (ATSA + HSR) has been an accepted method to treat this problem. Reverse shoulder arthroplasty (RSA) has become an alternative method to manage these cases with eccentric glenoid wear. The purpose of this study was to compare the early 2-year outcomes with the midterm outcomes for patients who underwent ATSA + HSR vs. RSA for eccentric glenoid wear patterns with an intact rotator cuff. MATERIALS AND METHODS: From 2008 to 2014 there were 242 shoulder arthroplasties performed in the setting of eccentric glenoid wear patterns. Of that initial cohort 101 ATSA + HSR and 93 RSA had both 2-year and final follow-up with a minimum of 7 years from surgery. American Shoulder and Elbow Surgeons (ASES) scores, Simple Shoulder Test (SST), range of motion, patient satisfaction, and radiographs were evaluated for each cohort and contrasted at the 2-year follow-up point and last follow-up time point. RESULTS: The average follow-up in the ATSA + HSR cohort was 8.3 years compared with 7.8 years in the RSA cohort. At the 2-year follow-up point, the ATSA + HSR group had better average ASES scores (85 vs. 80 [P < .001]), SST scores (10 vs. 9.6 [P < .001]), forward elevation (162° vs. 151° [P < .001]), external rotation (47° vs. 42° [P < .001]), and internal rotation (IR) (80% full IR vs. 55% full IR [P < .001]). At the 2-year follow-up, 95% of the ATSA + HSR cohort were satisfied compared with 93% in the RSA cohort. At the final follow-up, the RSA group had better average ASES scores (80 vs. 77 [P < .001]) and SST scores (9.4 vs. 8 [P < .001]) and a similar forward elevation (152° vs. 149° [P = .025]). The ATSA + HSR had better external rotation (45° vs. 41° [P < .001]) and IR (74% full IR vs. 54% full IR [P = .005]). Patient satisfaction at the final follow-up had decreased to 82% in the ATSA + HSR group, compared with 95% satisfied in the RSA group. Of the initial ATSA + HSR cohort, 8% of patients had undergone revision compared with 2% in the RSA cohort. CONCLUSION: ATSA with HSR had better outcome scores and range of motion with a similar patient satisfaction rating to RSA at the 2-year point. Over time, the ATSA + HSR results deteriorated, and at the final midterm follow-up, the RSA group had more durable results with better outcome scores, a higher patient satisfaction rating, and a lower revision rate.

Developing and testing a prediction model for periodontal disease using machine learning and big electronic dental record data.

Despite advances in periodontal disease (PD) research and periodontal treatments, 42% of the US population suffer from periodontitis. PD can be prevented if high-risk patients are identified early to provide preventive care. Prediction models can help assess risk for PD before initiation and progression; nevertheless, utilization of existing PD prediction models is seldom because of their suboptimal performance. This study aims to develop and test the PD prediction model using machine learning (ML) and electronic dental record (EDR) data that could provide large sample sizes and up-to-date information. A cohort of 27,138 dental patients and grouped PD diagnoses into: healthy control, mild PD, and severe PD was generated. The ML model (XGBoost) was trained (80% training data) and tested (20% testing data) with a total of 74 features extracted from the EDR. We used a five-fold cross-validation strategy to identify the optimal hyperparameters of the model for this one-vs.-all multi-class classification task. Our prediction model differentiated healthy patients vs. mild PD cases and mild PD vs. severe PD cases with an average area under the curve of 0.72. New associations and features compared to existing models were identified that include patient-level factors such as patient anxiety, chewing problems, speaking trouble, teeth grinding, alcohol consumption, injury to teeth, presence of removable partial dentures, self-image, recreational drugs (Heroin and Marijuana), medications affecting periodontium, and medical conditions such as osteoporosis, cancer, neurological conditions, infectious diseases, endocrine conditions, cardiovascular diseases, and gastroenterology conditions. This pilot study demonstrated promising results in predicting the risk of PD using ML and EDR data. The model may provide new information to the clinicians about the PD risks and the factors responsible for the disease progression to take preventive approaches. Further studies are warned to evaluate the prediction model's performance on the external dataset and determine its usability in clinical settings.

Associations of somatic depressive symptoms with body mass index, systemic inflammation, and insulin resistance in primary care patients with depression.

The somatic depressive symptom cluster (including appetite and sleep disturbances) is more strongly associated with insulin resistance (a diabetes risk marker) than other depressive symptom clusters. Utilizing baseline data from 129 primary care patients with depression but no diabetes in the eIMPACT trial (Mage = 59 years, 78% female, 50% Black), we examined associations of somatic depressive symptoms with insulin resistance (HOMA-IR), body mass index (BMI), and high-sensitivity C-reactive protein (hsCRP). We tested BMI and hsCRP as mediators and race as a moderator of these relationships. Hyperphagia was positively associated HOMA-IR (ß = 0.19, p = .048) and BMI (ß = 0.30, p < .001); poor appetite was negatively associated with HOMA-IR (ß = -0.24, p = .02); hypersomnia was positively associated with HOMA-IR (ß = 0.28, p = .003), BMI (ß = 0.26, p = .003), and hsCRP (ß = 0.23, p = .01); and disturbed sleep was positively associated with hsCRP (ß = 0.21, p = .04). BMI partially mediated hyperphagia and hypersomnia's associations with HOMA-IR; hsCRP partially mediated the hypersomnia-HOMA-IR association; and race moderated the hyperphagia-HOMA-IR association (positive for White participants but null for Black participants). People with depression experiencing hyperphagia and/or hypersomnia may be a subgroup with greater insulin resistance; BMI and hsCRP are likely pathways in these relationships. This study highlights the importance of considering the direction of somatic depressive symptoms in the context of cardiometabolic disease risk.

Retrospective Study of the Reasons and Time Involved for Dental Providers' Medical Consults.

Background: Patient-reported medical histories and medical consults are primary approaches to obtaining patients' medical histories in dental settings. While patient-reported medical histories are reported to have inconsistencies, sparse information exists regarding the completeness of medical providers' responses to dental providers' medical consults. This study examined records from a predoctoral dental student clinic to determine the reasons for medical consults; the medical information requested, the completeness of returned responses, and the time taken to receive answers for medical consult requests. Methods: A random sample of 240 medical consult requests for 179 distinct patients were selected from patient encounters between 1 January 2015 and 31 December 2017. Descriptive statistics and summaries were calculated to determine the reasons for the consult, the type of information requested and returned, and the time interval for each consult. Results: The top two reasons for medical consults were to obtain more information (46.1%) and seek medical approval to proceed with treatment (30.3%). Laboratory and diagnostic reports (56.3%), recommendations/medical clearances (39.6%), medication information (38.3%), and current medical conditions (19.2%) were the frequent requests. However, medical providers responded fewer times to dental providers' laboratory and diagnostic report requests (41.3%), recommendations/medical clearances (19.2%), and current medical conditions (13.3%). While 86% of consults were returned in 30 days and 14% were completed after 30 days. Conclusions: The primary reasons for dental providers' medical consults are to obtain patient information and seek recommendations for dental care. Laboratory/diagnostic reports, current medical conditions, medication history, or modifications constituted the frequently requested information. Precautions for dental procedures, antibiotic prophylaxis, and contraindications included reasons to seek medical providers' recommendations. The results also highlight the challenges they experience, such as requiring multiple attempts to contact medical providers, the incompleteness of information shared, and the delays experienced in completing at least 25% of the consults. Practical Implications: The study results call attention to the importance of interdisciplinary care to provide optimum dental care and the necessity to establish systems such as integrated electronic dental record-electronic health record systems and health information exchanges to improve information sharing and communication between dental and medical providers.

Efficacy and Durability of Opioid Restrictive State Legislation Two Years After Implementation for Total Knee Arthroplasty.

BACKGROUND: To curtail the U.S. opioid crisis, many states have instituted regulations that mandate time and/or dosage limits for opioid prescriptions. This study evaluates the impact of one such law, Florida House Bill 21, on postoperative opioid prescribing patterns for patients undergoing total knee arthroplasty (TKA) and the durability of the law's impact over time. METHODS: All patients who underwent TKA at a single institution during the same three-month period in 2017 (pre-law), 2018 (post-law), and 2020 (2 years post-law) were identified. Outcomes and measures included: prescribed morphine milligram equivalents (MME) at discharge and for the 90-day surgical episode, refill quantity with associated MME, and quantity of opioid prescribers. Patients with established chronic pain or those who underwent contralateral TKA during the 90-day window were excluded. Data was compared using a one-way analysis of variance. Significance was set at alpha <0.05. RESULTS: The average MME of filled opioid prescriptions per patient during the 90-day post-surgical episode decreased from 1310 MME in 2017 to 891 MME in 2018 (P < .001). The average MME in 2020 was 814 MME, which was significantly lower than the average in 2017 (P < .001), and statistically stable compared to the average in 2018 (P = .215). CONCLUSION: Restrictive opioid state policy implementation was associated with reduced overall MME prescription to patients undergoing TKA at discharge and for the 90-day surgical episode. There was no increase in the number of opioid refills or opioid prescribers. Durable change and continued improvement were observed 2 years after implementation of law.

A Data-Driven Assessment of the U.S. Health Informatics Programs and Job Market.

BACKGROUND: Health Informatics (HI) is an interdisciplinary field, integrating health sciences, computer science, information science, and cognitive science to assist health information management, analysis, and utilization. As the HI field is broad, it is impossible that a student will be able to master all the diverse HI topics. Thus, it is important to train the HI students based on the offering of the various HI programs and needs of the current market. This project will study the U.S. HI programs, training materials, HI job market, the skillset required by the employers, competencies taught in HI programs, and comparisons between them. METHODS: We collected the training information for the 238 U.S. universities that offered MS, PhD, or postbaccalaureate certificate programs in HI or related professions. Next, we explored the HI job market by randomly checking 200 jobs and their required skillsets and domain knowledge. Then, we compared these skillsets with those offered by the HI programs and identified the gaps and overlaps for program enhancements. RESULTS: Among the 238 U.S. universities, 94 universities offer HI programs: 92 universities with MS (Master of Science), 43 with doctoral, 42 with both MS and doctoral, and 54 with certificate programs. The most offered HI courses are related to practicum, data analytics, research, and ethics. For the HI job postings, the three most technical skillsets required in HI job posting are data analysis, database management, and knowledge of electronic health records. However, only 58% of HI programs offer courses in database management and analytics. Compared with American Medical Informatics Association's recommended 10 fundamental domains, the HI curriculum generally lacks training in socio-technical systems, social-behavioral aspects of health, and interprofessional collaborative practice. CONCLUSION: There are gaps between the industry expectations of HI and the training received in HI programs. Advance level technical courses are needed in HI programs to meet industry expectations.

Enhancing an AI-Empowered Periodontal CDSS and Comparing with Traditional Perio-risk Assessment Tools.

Periodontal disease (PD) is one of the most prevalent dental diseases. Fortunately, it can be prevented if identified early, especially for high-risk patients. Dental electronic health records (EHRs) could help develop a data-driven personalized prediction model using advanced machine learning development of clinical decision support system (CDSS) as in our Phase I, II AMIA-AI showcase. In phase II, we created a CDSS, the Perio-Risk Scoring system (PRSS), to help clinicians generate perio-scores and diagnoses and identify the influential factors. In Phase III (this study), we implemented and compared the patient's risk factors information in five periodontal risk assessment tools [periodontal risk assessment (PRA), PreViser, Sonicare, Cigna, and Periodontal Risk Scoring System (PRSS)]. We examined 1) agreement between the risk scores provided by each of the five risk assessment tools of 20 patients' information and 2) compare the risk scores provided by each tool to the original outcomes (five years outcomes). Fleiss Kappa, Cohen's Kappa, and percentage agreements were performed to determine the agreements between risk scores and original outcomes. We found a -1.24 Kappa value which indicates disagreement between the risk scores provided by five risk assessment tools. Compared to the original outcomes (five-year disease outcomes), PRSS provided the most accurate prediction (70%), followed by Previser (55%), PRA (35%), Phillips (35%), and Cigna (25%). We conclude that using advanced state-of-the-art informatics methods could help us utilize EHR data optimally to represent the current patient populations and their risk factors to provide the most accurate disease risk score. This may promote preventive strategies at the chairside, hoping to reduce PD prevalence, improve quality of life, and reduce healthcare costs.

Associations of somatic depressive symptoms with food attentional bias and eating behaviors.

Recent evidence suggests that atypical major depressive disorder (MDD) - whose key features include the reversed somatic symptoms of hyperphagia (increased appetite) and hypersomnia (increased sleep) - is a stronger predictor of future obesity than other MDD subtypes. The mechanisms underlying this relationship are unclear. The present study sought to elucidate whether the individual symptoms of hyperphagia, hypersomnia, poor appetite, and disturbed sleep have differential relationships with food attentional bias, emotional eating, external eating, and restrained eating. This cross-sectional laboratory study involved 103 young adults without obesity (mean age = 20 years, 79% female, 26% non-White, mean BMI = 23.4 kg/m2). We measured total depressive symptom severity and individual symptoms of hyperphagia, poor appetite, and disturbed sleep using the Hopkins Symptom Checklist-20 (SCL-20) and added an item to assess hypersomnia; food attentional bias using a Food Stroop task; and self-reported eating behaviors using the Dutch Eating Behavior Questionnaire. Hyperphagia was positively associated with emotional eating but negatively associated with food attentional bias. Hypersomnia was negatively associated with emotional eating. Poor appetite was negatively associated with emotional eating. Disturbed sleep was positively associated with food attentional bias and emotional eating. An aggregate of the remaining 15 depressive symptoms (SCL-15) was positively associated with emotional and restrained eating. Our findings highlight the importance of examining the direction of somatic depressive symptoms, and they set the stage for future research to identify subgroups of people with depression at greatest risk for obesity (e.g., those with hyperphagia and/or disturbed sleep) and the mechanisms responsible for this elevated risk (e.g., emotional eating).

Antiviral T Cell Receptor Complementarity Determining Region-3 Sequences Are Associated with a Worse Cancer Outcome: A Pancancer Analysis.

Human papilloma virus has a clearly demonstrated role in cervical and head and neck cancers, but viral etiology for other solid tumors is less well understood. To expand this area of research, we obtained and analyzed the immune receptor recombinations available from both blood and tumor samples, through mining of exome files produced from those sources, for 32 cancer types represented by the cancer genome atlas (TCGA). Among TCGA data sets, the recovery frequency for antiviral complementarity determining region-3 sequences (CDR3s), for T cell receptor-alpha and T cell receptor-beta, ranged from 0% to 21% of the patients, for the different cancer types, with breast, lung, pancreatic, and thymus cancers representing the highest of that range, particularly for tumor tissue resident T cells. In several cases, recovery of the antiviral CDR3s associated with distinct survival rates, and in all of these cases, the recovery of an antiviral CDR3 associated with a worse survival rate.