Citations

AbstractINTRODUCTIONIdentifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health record (EHR) data, applying Diagnostic and Statistical Manual of Mental Disorders criteria for dementia case identification.METHODSOur cohort (n = 1082) included individuals aged ≥ 60 with dementia identified through specialist clinics and a comparison group without dementia. Clinicians from Australia and the United States informed predictor selection. We developed algorithms through a biostatistics stream for structured data and a natural language processing (NLP) stream for text, synthesizing results via logistic regression.RESULTSThe final structured model retained 16 variables (area under the receiver operating characteristic curve [AUC] 0.853, specificity 72.2%, sensitivity 80.6%). NLP classifiers (logistic regression, support vector machine, and random forest models) performed comparably. The final, combined model outperformed all others (AUC = 0.951, P < 0.001 for comparison to structured model).DISCUSSIONEmbedding text‐derived insights within algorithms trained on structured medical data significantly enhances dementia identification capacity.Highlights Algorithmic tools for detection of individuals with dementia are available; however, previous work has used heterogeneous case definitions which are not clinically meaningful, and has relied on proxies such as diagnostic codes or medications for case ascertainment. We used a novel, dual‐stream algorithmic development approach, simultaneously and separately modeling a clinically meaningful outcome (diagnosis of dementia according to specialized clinical impression) using structured and unstructured electronic health record datasets. Our clinically grounded case definition supported the inclusion of key structured variables (such as dementia International Classification of Disease codes and medications) as modeling predictors rather than outcomes. Our algorithms, published in detail to support validation and replication, represent a major step forward in the use of routinely collected data for detection of diagnosed dementia.

ObjectivePatients with rheumatoid arthritis (RA) frequently visit emergency departments (EDs), but their clinical characteristics and admission factors are poorly understood. Our study investigates the epidemiology and outcomes of ED visits among patients with RA using the Nationwide Emergency Department Sample (NEDS).MethodsThis cross‐sectional study used the 2019 NEDS data to identify RA‐related ED visits using International Classification of Disease, Tenth Revision codes M05.X or M06.X. RA‐related ED visits were defined as encounters in which RA was recorded in any diagnostic position. Demographics, clinical features, and comorbidities were compared between RA and non‐RA ED visits. Racial variations were assessed, and multivariable logistic regression identified factors associated with inpatient admission.ResultsWe identified 905,811 (0.8%) ED visits for adults aged ≥18 years with RA. Compared to non‐RA visits, RA ED visits had a higher proportion of patients aged ≥65 years, women, White patients, and Medicare‐insured individuals with a greater comorbidity burden. Admission rates were 46% for RA visits versus 16% for non‐RA visits. Black and Hispanic patients with RA were younger than White patients and more likely to belong to the lowest income quartile. Older age, male sex, and comorbidities were associated with higher admission odds, whereas Black race, lowest income quartile, and Medicaid coverage correlated with lower odds of admission. Septicemia was the most common primary ED diagnosis in patients with RA.ConclusionPatients with RA visiting the ED were older, had a higher comorbidity burden, and were three times more likely to be admitted than patients without RA. Black patients and those in the lowest income quartile had lower odds of admission, highlighting potential disparities and the need for targeted interventions to improve health equity.

Abstract Aims This study aimed to establish 2D and M-mode echocardiographic reference values for cardiac chambers, outflow tracts, and great vessels for school children living at high altitudes, differentiated between males and females. Methods and results This post hoc analysis included children with normal echocardiography from a cluster randomized cross-sectional survey of rheumatic heart disease among school children in Peru. The echocardiograms were acquired with a portable machine and the images were analysed centrally with a standardized methodology. Body surface area (BSA) was used as an independent variable to predict the mean values of echocardiographic measurements for both male and female groups. Reference values are presented on z-scores and nomograms based on sex. Propensity score matching was used to compare sexes. A total of 985 students aged 5–16 years were included. The Haycock formula provided the best fit and was used when presenting data as predicted values for a given BSA. The z-score and nomograms for all essential parameters of cardiac chambers, great vessels, and functional surrogates are presented based on sex. The majority of the parameters were significantly different per sex after propensity score matching. Conclusion Normal reference values and nomograms of cardiac chambers, outflow tracts, and great arteries in healthy school children living at high altitudes based on sex were reported. These data partly addressed the existing gaps in paediatric echocardiographic nomograms.

PURPOSE Several lines of treatment can be used sequentially in patients with metastatic colorectal cancer. We investigated the evolution of patient/tumor characteristics and their prognostic impact across treatment lines to develop an overall prognostic score (OPS). PATIENTS AND METHODS Individual patient data from 48 randomized trials were analyzed. The end point was overall survival (from random assignment to death). Missing data were imputed. The complete data set was then separated into construction (80%) and validation sets (20%). The Cox's model was used to define risk groups for survival using the OPS. The discrimination capability was assessed in each treatment-line via bootstrapping to obtain optimism-corrected calibration and discrimination C-indices. Internal validation was done in the validation set. RESULTS A total of 37,560 patients (26,974 in first-line [1L], 7,693 in second-line [2L], and 2,893 in third-line [3L]) were analyzed. Some clinical, biological, and molecular characteristics of patients/tumors included in therapeutic trials evolve over the lines. Seven independent prognostic variables were retained in the final multivariate model common to all lines: Eastern Cooperative Oncology Group performance status, hemoglobin, platelet count, WBC/absolute neutrophil count ratio, lactate dehydrogenase, alkaline phosphatase, and the number of metastatic sites. The OPS was used to define four patient subgroups with significantly different prognoses in 1L, 2L, and 3L, separately, with adequate C-indices: 0.65, 0.66, and 0.69 in the construction set and 0.65, 0.66, and 0.68 in the validation set, respectively. The OPS was not predictive, with 3L drugs ( v placebo) or subsequent line (2L/1L or 3L/2L) extending survival in all prognostic groups. CONCLUSION The same prognostic model using practical variables can be used before all treatment lines. The OPS could better stratify patients in future clinical trials and help to therapeutic decision in routine practice.

Background: When injuring the anterior cruciate ligament (ACL), simultaneous meniscal tears often occur. However, little data describe ACL reconstruction (ACLR) and the subsequent risk of revision ACLR, as well as cartilaginous and meniscal damage after primary ACLR with different treatments for injury of the lateral meniscus (LM). Purpose: To investigate (1) how different LM treatments during primary ACLR affect the odds of revision ACLR and the cartilaginous and meniscal status at revision in a long-term follow-up and (2) whether the increased risk of subsequent meniscal and cartilaginous injuries seen with meniscal resection in the short term would continue in the long term, and (3) the increased risk with subsequent meniscal injuries with meniscal repair. Study Design: Cohort study; Level of evidence, 3. Methods: Data from the Swedish National Knee Ligament Registry were used. The study compared 2 groups: patients with isolated ACLR and patients with ACLR and concomitant LM injury, further subdividing the latter into 4 treatment types: repair, resection, both, and left in situ. Patients with medial meniscal injuries were excluded. The main outcomes studied were the odds for revision ACLR and the cartilaginous and meniscal status at revision 5 and 10 years after primary surgery. Results: Data for 5 years were available for 22,208 patients and data for 10 years were available for 11,058 patients. Compared with isolated ACLR, patients with concomitant LM injury left in situ had higher odds of revision ACLR at both 5 years (odds ratio [OR], 1.49; 95% CI, 1.14-1.95; P = .004) and 10 years (OR, 1.55; 95% CI, 1.09-2.19; P = .01), while those with LM repair had higher odds at 5 years (OR, 1.73; 95% CI, 1.23-2.43; P = .002). LM repair also increased the odds of subsequent meniscal injuries at 5 years (OR, 3.52; 95% CI, 1.76-7.03; P = .0004) and 10 years (OR, 7.26; 95% CI, 1.67-31.52; P = .008). Partial meniscectomy did not show an increased risk of cartilage injury, subsequent meniscal injury, or revision ACLR at long-term follow-up compared with the control group. Conclusion: This demonstrates that over 5 and 10 years, LM repair during primary ACLR is associated with an increased risk of revision ACLR and subsequent meniscal injuries. The higher risk of revision ACLR when the LM is left in situ emphasizes the need for careful consideration of treatment methods. Conversely, partial meniscectomy did not show an associated increased risk of cartilaginous injury in the long term and is associated with a lower risk of subsequent meniscal injury and revision ACLR than other treatment options, raising questions about whether preserving the meniscus at all costs is always the best approach.