Prediction models using artificial intelligence and longitudinal data from electronic health records: a systematic methodological review.

OBJECTIVE: To describe and appraise the use of artificial intelligence (AI) techniques that can cope with longitudinal data from electronic health records (EHRs) to predict health-related outcomes. METHODS: This review included studies in any language that: EHR was at least one of the data sources, collected longitudinal data, used an AI technique capable of handling longitudinal data, and predicted any health-related outcomes. We searched MEDLINE, Scopus, Web of Science, and IEEE Xplorer from inception to January 3, 2022. Information on the dataset, prediction task, data preprocessing, feature selection, method, validation, performance, and implementation was extracted and summarized using descriptive statistics. Risk of bias and completeness of reporting were assessed using a short form of PROBAST and TRIPOD, respectively. RESULTS: Eighty-one studies were included. Follow-up time and number of registers per patient varied greatly, and most predicted disease development or next event based on diagnoses and drug treatments. Architectures generally were based on Recurrent Neural Networks-like layers, though in recent years combining different layers or transformers has become more popular. About half of the included studies performed hyperparameter tuning and used attention mechanisms. Most performed a single train-test partition and could not correctly assess the variability of the model's performance. Reporting quality was poor, and a third of the studies were at high risk of bias. CONCLUSIONS: AI models are increasingly using longitudinal data. However, the heterogeneity in reporting methodology and results, and the lack of public EHR datasets and code sharing, complicate the possibility of replication. REGISTRATION: PROSPERO database (CRD42022331388).

Polypharmacy Patterns in Multimorbid Older People with Cardiovascular Disease: Longitudinal Study.

(1) Introduction: Cardiovascular disease is associated with high mortality, especially in older people. This study aimed to characterize the evolution of combined multimorbidity and polypharmacy patterns in older people with different cardiovascular disease profiles. (2) Material and methods: This longitudinal study drew data from the Information System for Research in Primary Care in people aged 65 to 99 years with profiles of cardiovascular multimorbidity. Combined patterns of multimorbidity and polypharmacy were analysed using fuzzy c-means clustering techniques and hidden Markov models. The prevalence, observed/expected ratio, and exclusivity of chronic diseases and/or groups of these with the corresponding medication were described. (3) Results: The study included 114,516 people, mostly men (59.6%) with a mean age of 78.8 years and a high prevalence of polypharmacy (83.5%). The following patterns were identified: Mental, behavioural, digestive and cerebrovascular; Neuropathy, autoimmune and musculoskeletal; Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological; Non-specific; Multisystemic; Respiratory, cardiovascular, behavioural and genitourinary; Diabetes and ischemic cardiopathy; and Cardiac. The prevalence of overrepresented health problems and drugs remained stable over the years, although by study end, cohort survivors had more polypharmacy and multimorbidity. Most people followed the same pattern over time; the most frequent transitions were from Non-specific to Mental, behavioural, digestive and cerebrovascular and from Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological to Non-specific. (4) Conclusions: Eight combined multimorbidity and polypharmacy patterns, differentiated by sex, remained stable over follow-up. Understanding the behaviour of different diseases and drugs can help design individualised interventions in populations with clinical complexity.

Pilot study of dietary influences on mammographic density in pre- and postmenopausal Hispanic and non-Hispanic white women.

OBJECTIVE: The extent to which modifiable dietary factors may account for some of the variability demonstrated in mammographic density across ethnic groups is unknown. The purpose of this study was to provide pilot data describing the relationship between dietary variables and mammographic density in pre- and postmenopausal Hispanic and non-Hispanic white (NHW) women (N=238) ranging in age from 41 to 50 years (premenopausal only) or 56 to 70 years (postmenopausal only). DESIGN: Using a cross-sectional design, computer-assisted density assessments were performed on mammograms of both breasts and averaged for analysis. The Arizona Food Frequency Questionnaire was used to estimate dietary intake. RESULTS: Study participants were well educated and overweight, with mean mammographic densities ranging from 20.25% for postmenopausal Hispanic women to 46.94% for premenopausal NHW women. Hispanic women reported higher energy intake than NHW women, but energy-adjusted intake of other nutrients was generally comparable. There was preliminary evidence of ethnic variability in diet-mammographic density associations. Among premenopausal Hispanic women, density was inversely associated with dairy, calcium, and vitamin D intakes (P

Population and parity levels of Aedes aegypti collected in Tucson.

Oviposition traps were used to follow changes in the population of Aedes aegypti (L.) (Diptera:Culicidae) in a seven-block area in midtown region of Tucson, Arizona. About 20,000 eggs were collected over a period from 1 June to 14 October 2000. Peak mosquito populations were correlated with the late summer rains. Mosquitoes seeking a blood meal were collected and dissected to determine if they had previously fed, i.e. if they were parous. Of the 241 females examined, 44% were parous, with a range from 0% to 80%. Females that had blood in their guts were collected and the source of blood was identified using an ELISA. Preliminary results suggest that 80% of them had fed on humans. These data suggest that the reproductive history of Tucson populations of Ae. aegypti could be conducive for transmission of dengue viruses.