Machine Learning Models for Prediction of Diabetic Microvascular Complications.

IMPORTANCE AND AIMS: Diabetic microvascular complications significantly impact morbidity and mortality. This review focuses on machine learning/artificial intelligence (ML/AI) in predicting diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN). METHODS: A comprehensive PubMed search from 1990 to 2023 identified studies on ML/AI models for diabetic microvascular complications. The review analyzed study design, cohorts, predictors, ML techniques, prediction horizon, and performance metrics. RESULTS: Among the 74 identified studies, 256 featured internally validated ML models and 124 had externally validated models, with about half being retrospective. Since 2010, there has been a rise in the use of ML for predicting microvascular complications, mainly driven by DKD research across 27 countries. A more modest increase in ML research on DR and DN was observed, with publications from fewer countries. For all microvascular complications, predictive models achieved a mean (standard deviation) c-statistic of 0.79 (0.09) on internal validation and 0.72 (0.12) on external validation. Diabetic kidney disease models had the highest discrimination, with c-statistics of 0.81 (0.09) on internal validation and 0.74 (0.13) on external validation, respectively. Few studies externally validated prediction of DN. The prediction horizon, outcome definitions, number and type of predictors, and ML technique significantly influenced model performance. CONCLUSIONS AND RELEVANCE: There is growing global interest in using ML for predicting diabetic microvascular complications. Research on DKD is the most advanced in terms of publication volume and overall prediction performance. Both DR and DN require more research. External validation and adherence to recommended guidelines are crucial.

Recurrent Bacteriuria as a Prognosis Marker in the Adjuvant Treatment of Non-Muscle Invasive Bladder Cancer.

PURPOSE: Bacteriuria may affect the response to adjuvant therapy in non-muscle invasive bladder cancer (NMIBC). The main aim of this study was to examine the effect of recurrent bacteriuria (RB) on the prognosis of NMIBC in women receiving intravesical therapy. MATERIALS AND METHODS: We designed a prospective observational study from 2012 to 2019. We included women with bladder cancer treated with transurethral resection of the bladder (TURB) and adjuvant intravesical treatment. Significant bacteriuria was defined as a presence in urine cultures at or above 100,000 colony-forming units per millilitre. The recurrent bacteriuria group included patients with significant bacteriuria in at least two determinations in 6 months or in 3 or more determinations in a year. The institutional board approved the study. RESULTS: One hundred thirty-six patients diagnosed with NMIBC participate in the study, of whom 100 met the inclusion criteria. During follow-up, 48 were categorized in the RB group and 52 formed the non-bacteriuria group (NB). RB GROUP HAD A BETTER OUTCOME: Eight patients (16.67%) experiencing a recurrence of the same grade, with no progression to a higher-grade tumor or muscle-invasive tumor. In the NB group, 18 (34.6%) patients presented a recurrence (P = .001) and 22 (42.3%) progressed to a higher-grade tumor or muscular invasion (P = .001). The presence of RB was identified as a predictor of good response in multivariate regression with a relative risk of 0.13 (P = .018) CONCLUSIONS: Female patients with RB had a better response to adjuvant treatment for NMIBC. The RB group showed lower rates of tumor recurrences and progression.

Reporting guidelines for precision medicine research of clinical relevance: the BePRECISE checklist.

Precision medicine should aspire to reduce error and improve accuracy in medical and health recommendations by comparison with contemporary practice, while maintaining safety and cost-effectiveness. The etiology, clinical manifestation and prognosis of diseases such as obesity, diabetes, cardiovascular disease, kidney disease and fatty liver disease are heterogeneous. Without standardized reporting, this heterogeneity, combined with the diversity of research tools used in precision medicine studies, makes comparisons across studies and implementation of the findings challenging. Specific recommendations for reporting precision medicine research do not currently exist. The BePRECISE (Better Precision-data Reporting of Evidence from Clinical Intervention Studies & Epidemiology) consortium, comprising 23 experts in precision medicine, cardiometabolic diseases, statistics, editorial and lived experience, conducted a scoping review and participated in a modified Delphi and nominal group technique process to develop guidelines for reporting precision medicine research. The BePRECISE checklist comprises 23 items organized into 5 sections that align with typical sections of a scientific publication. A specific section about health equity serves to encourage precision medicine research to be inclusive of individuals and communities that are traditionally under-represented in clinical research and/or underserved by health systems. Adoption of BePRECISE by investigators, reviewers and editors will facilitate and accelerate equitable clinical implementation of precision medicine.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. RESULTS: Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. CONCLUSIONS: Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

People living with type 2 diabetes (T2D) are more likely to develop problems with their heart or blood circulation, known as cardiovascular disease (CVD), than people who do not have T2D. However, it can be difficult to predict which people with T2D are most likely to develop CVD. This is because current approaches, such as blood tests, do not identify all people with T2D who are at an increased risk of CVD. In this study we reviewed published papers that investigated the differences between people with T2D who experienced CVD compared to those who did not. We found some indicators that could potentially be used to determine which people with T2D are most likely to develop CVD. More studies are needed to determine how useful these are. However, they could potentially be used to enable clinicians to provide targeted advice and treatment to those people with T2D at most risk of developing CVD.

Presence of gastrointestinal parasites in swine and human of four swine production farms in Cundinamarca- Colombia / Presencia de parásitos gastrointestinales en cerdos y humanos de cuatro granjas porcícolas de Cundinamarca- Colombia

Objective. Determine the presence and the type of endoparasites with zoonotic potential in swine and human of two technified and two semi-technified farms in the department of Cundinamarca, Colombia. Materials and methods. Three serial samplings of feces were taken in a pen row within intervals of 15 days, in two technified and two semi-technified farms in different age groups distributed as follows: pregnant-sows, nursing-females, boars, weaners, suckling-piglets, and growing-pig. By means of informed consent thirty-three people agreed to enter the study. Thirty-three samples from men and women of different ages were received. The pool and individual samples of fecal were evaluated by direct analysis, qualitative flotation and sedimentation techniques and modified Ziehl-Neelsen stain. Results. For the porcine population, on the average, the results obtained from both technified farms showed that Balantidium coli (42%), Endolimax nana (21.9%) and Iodamoeba bütschlii (7.8%) were the most common parasites. In semi-technified farms they were: Entamoeba coli (40%), Endolimax nana (35%), Iodamoeba bütschlii (25%) and Balantidium coli (5%). By means of the test chi² it is possible to conclude that there is a significant difference between the parasites species and the type of farm. The results obtained in human showed the presence of parasites as: E. coli (42.2%), Entamoeba hystolitica/dispar (12.1%), E. nana (9.1%), B. coli (9.1%), I. bütschlii (3.0%) and Blastocystis hominis (3.0%). Conclusions. The presence of parasites such as Balantidium coli, Endolimax nana, Iodamoeba bütschlii and Entamoeba coli in swine and human suggests a possible rotation of parasitic species between hosts.

Objetivo. Determinar la presencia y el tipo de endoparásitos con potencial zoonótico en porcinos y humanos de dos granjas tecnificadas y dos semi-tecnificadas del departamento de Cundinamarca-Colombia. Materiales y métodos. Se realizaron tres muestreos seriados de materia fecal con intervalos de 15 días, en dos granjas tecnificadas (92 muestras) y dos semi-tecnificadas (60 muestras) en diferentes grupos etarios distribuidos así: Hembras de cría, hembras de reemplazo, reproductores, lechones, pre-cebo y ceba. Se recibieron 33 muestras de hombres y mujeres de diferentes edades, que mediante consentimiento informado asintieron participar en el estudio. Las muestras de materia fecal colectivas e individuales (de humanos y de cerdos) fueron evaluadas mediante: Análisis directo, técnica de flotación cualitativa, técnica de sedimentación cualitativa y tinción de Ziehl-Neelsen modificado. Resultados. En promedio para la población porcina, los resultados obtenidos de las dos granjas tecnificadas mostraron que los parásitos en común son Balantidium coli (42%), Endolimax nana (21.9%) y Iodamoeba bütschlii (7.8%). En las dos granjas semi-tecnificadas: Entamoeba coli (40%), Endolimax nana (35%), Iodamoeba bütschlii (25%) y Balantidium coli (5%). Por medio de la prueba chi² se puede concluir que hay una diferencia significativa entre la especie de parásitos y el tipo de granja. Los resultados obtenidos en humanos mostraron la presencia de parásitos como: E. coli (42.2%), Entamoeba hystolitica/dispar (12.1%), E. nana (9.1%), B. coli (9.1%), I. bütschlii (3.0%) y Blastocystis hominis (3.0%). Conclusiones. La presencia de parásitos como Balantidium coli, Endolimax nana, Iodamoeba bütschlii y Entamoeba coli en cerdos y humanos sugiere una posible rotación de especies parásitas entre los hospedadores.