The Risk Factors of Diabetes among Children - Case Study

This report examined a population of data extracted from one population of 100.000 inpatients was the first eligible as statistical surveillance review of clinical data during the study and it is about the higher risks of developing diabetes in children. Then, we selected 8.500 positive susceptible individuals from the initial population, and we consider child individuals as an uncenter cohort, subjected to this study. Some data indicate the possibility to measure the hypertension, heart disease, the smoking history, BMI, the blood glucose level and the haemoglobin A1c level of the overall population of clinical inpatients while positive statistical population of individuals draw a prospective scenario for future patients in the same conditions and for future audience segmentation of more populations of individuals evaluating the knowledge of healthcare conditions from real data, they were processed in R Studio.

Keywords: R Studio; diabetes; surveillance analysis; risk factors; pathogenicity

Reasons for performing study: Information on precision medicine of diabetic individuals in the healthcare structures for disease prevention and control during the collection of data from new inpatients.

Objective: To prevent clinical findings in healthcare structures among inpatients with diabetes disease to describe the distribution of positive population of some groups of populations for studying hospital outbreaks.

Background: Diabetes diseases and pathogenicity-related genes are studying through the positivity rate ranking all possible and the types of diabetes disease of involved individuals for assisting hospital onsets. We aim to estimate the sensibility of illness presentation which it is associated with higher levels of some indicators used as confoundments in our statistical analysis, studying the proportion of risk factors by means of the risk and fitness factors studying the interactions regardless the hypertension, heart disease, the smoking history, BMI, the blood glucose level and the haemoglobin A1c level, deducing human susceptibility to diabetes disease. During laboratory cross-contamination, receptors are recognizing pathogenic profiles in the environment of humans and their sequential event reading permits to diagnostic several acute episodes of the disease.

Study design: Prospective cohort study.

Methods: Demographic data on the individuals involving admission and stool, sampling inpatients from 100.000 of recorded individuals were used to estimate the proportion of risk factors related to the developing of the diabetes disease. The association between heterogeneous data with age and gender are fixed effects whereas data wards are including as a random effect in the statistical analysis. A cross sectional Point Prevalence Study (PPS) is conducted in a sample of inpatients as described. The surveillance methodology is based on machine learning approaches and different techniques in R Studio had applied for the obtaining results.

Results: This case study identified 8.500 positive of 100.000 adherent inpatients. The uncenter cohort dataset characterizes 82 susceptible children. The presence of an uncenter control cohort resistant organism is documented for % of patients. There are 17.219 children present in 100.000 patients. The prevalence of patients who are of type age as children is 17.2% whose female individuals is the 58.5% and the 41.5% are male. Hospital positivity rates ranged from 0.02% among young adult and to 4.9% among elderly people. Body Mass Index (BMI) ranged from 10.01 to 95.69 kg/m2. The most common positive inpatients --with other cofounder-- are comprising % of all patients identified.

Main limitations: The dataset of patients is not related to some hospital structure in specific Italian Region or other and few demographic data are conditioning the results onto treatments. Then, the outcomes of principal pathology and life tenure of the patient is a priori unknown because of the absence of some features characterizing the initial data. No distinction into type I and type II of the disease is present in the data.