Data on asthma medications were collected, and multivariable regression models analysed the association of SABA prescriptions with clinical outcomes. Patients  were mostly female (68.6%); 58.3% had uncontrolled/partly controlled asthma and 38.8% experienced ≥1 severe exacerbation (reported in 39% of patients with mild asthma). Overall, 44.9% of patients were prescribed ≥3 SABA canisters (over-prescription) and 21.5% purchased SABA over-the-counter. Higher SABA prescriptions (vs 1−2 canisters) were associated with significantly decreased odds of having at least partly controlled asthma (6–9 and 10–12 canisters) and an increased incidence rate of severe exacerbations (10–12 and ≥13 canisters). Findings revealed a high disease burden, even in patients with ‘mild’ asthma, emphasising the need for local primary care guidelines based on international recommendations.Short-acting β Despite the availability of a range of effective treatment options, asthma continues to impose a significant socioeconomic burden on patients and healthcare systems worldwide3. Although healthcare policies and evidence-based treatment recommendations at both national and international levels are available to guide clinical practice, asthma remains uncontrolled in a considerable proportion of patients5.Asthma is one of the most common chronic conditions affecting over 300 million people worldwide6. Consequently, they play an essential role in the holistic management of asthma8 and are uniquely positioned to exert a major influence on asthma care6. Indeed, the World Health Organization (WHO) recognises that healthcare systems with strong primary care services are crucial to improve treatment outcomes and deliver comprehensive care9. However, the availability of good-quality primary care remains highly variable, with the WHO reporting that the average health spending per person in 2017 was approximately 70 times lower in low income countries (US $41) than in high income countries (US $2937)10. Moreover, results from a systematic review reported that in 18 countries representing approximately 50% of the global population, PCPs spent 5 min or less per consultation with their patients11. In addition, PCPs are often faced with a multitude of challenges, particularly diagnostic uncertainties in patients with mild asthma13 or those with normal lung function parameters14. Additionally, implementation of evidence-based recommendations in the primary care setting may be hindered by factors such as non-availability of diagnostic resources in many geographical regions, limited time for in-depth diagnostic assessments, and lack of specific primary care guidelines16.Among all healthcare practitioners (HCPs), primary care physicians (PCPs) represent the first point of contact for most patients with asthma17, in the form of excessive use of short-acting β2-agonists (SABAs), possibly combined with underuse of inhaled corticosteroids (ICS)20, remains a major challenge in respiratory care, contributing to poor treatment outcomes21. Therefore, following a landmark update in 201922, the Global Initiative for Asthma (GINA) no longer recommends as-needed SABA without concomitant ICS for patients ≥12 years of age3. These updated treatment recommendations largely impact PCPs who represent the frontline of patient management. However, PCPs are often not familiar with GINA23, and there is often a time lag between revised GINA recommendations and updates to local guidelines. This may contribute to clinical practices not being aligned with the latest treatment recommendations, resulting in PCPs prescribing SABAs to patients at the time of asthma diagnosis, thereby delaying the initiation of regular preventer medication24. In addition, most patients with asthma have mild disease and are therefore commonly prescribed SABA-only treatment25. However, all patients, including those with mild asthma, are at risk of exacerbations3, with clinical trial data reporting that patients with mild asthma using as-needed SABA experience a 60% higher rate of moderate-to-severe exacerbations than those receiving ICS-containing treatment26. Therefore, a detailed understanding of SABA prescription practices across asthma severities in primary care, including the potential impact of SABA over-the-counter (OTC) purchase, would be of considerable value, particularly in less well-resourced countries where current data on SABA use are lacking.Inappropriate use of asthma medications27. Moreover, SABA over-prescription was associated with poor asthma-related health outcomes27. To better understand how asthma is managed globally in the primary care setting, we assessed prescriptions of SABA and other asthma medications , OTC purchases of SABA, and clinical outcomes associated with SABA prescriptions in the cohort of patients from the SABINA III study who were treated by PCPs.To continue to assess the global extent of SABA use and its clinical consequences, the SABA use IN Asthma (SABINA) III  study was initiated in 24 countries across 5 continents in 8351 patients treated by both PCPs and specialists. Results reported that more than a third of patients with asthma were over-prescribed SABAs (≥3 canisters) in the 12 months prior to study entryn = 1440) were managed exclusively by PCPs. Patients had a mean (standard deviation [SD]) age of 47.9 (16.73) years (Table 2 (63.8%), and had never smoked (78.7%). Over one-third of patients (35.5%) reported no healthcare reimbursement.Of the 8351 patients in the SABINA III study, 17.2%  and ≥3  severe asthma exacerbations in the previous 12 months. The level of asthma symptom control was assessed as well controlled in 41.7%, partly controlled in 34.9%, and uncontrolled in 23.3% of patients.Overall, 44.9% of patients received prescriptions for ≥3 SABA canisters in the 12 months prior to study entry, and 26.3% received prescriptions for ≥10 SABA canisters; 33.4% of patients were not prescribed any SABA canisters , 57.9% had received SABA prescriptions as well  was prescribed to 49.4% of patients  of 7.2 (7.0) ICS canisters in the preceding 12 months Table . An ICS/ts Table .Table 4PIn the 12 months prior to study entry, 21.5% of patients were prescribed OCS burst treatment Table . OCS burP < 0.0001) and 90%  significantly increased incidence rate of severe exacerbations, respectively. Further details are provided in Fig. Disposition of patients included in the secondary analysis is shown in Supplementary Fig P = 0.016) and 57%  significantly lower odds of having at least partly controlled asthma (partly controlled plus well-controlled asthma), respectively. Further details are provided in Fig. Compared with prescription of 1–2 SABA canisters, prescription of 6–9 and 10–12 SABA canisters in the previous 12 months was associated with a 47% .Data were generally consistent between the two populations, although there were a few exceptions (Supplementary Table 27 were prescribed ≥3 (60.6% vs 53.6%) and ≥10 (45.0% vs 29.9%) SABA canisters in the 12 months prior to study entry. Although prescriptions for SABA in addition to maintenance therapy were comparable between the PCP cohort and overall SABINA III population 27, a higher proportion of patients treated in primary care were prescribed ≥3 (69% vs 61.7%) and ≥10 (38.2% vs 29.3%) SABA canisters.Of those patients prescribed SABA monotherapy, a higher proportion in the PCP cohort compared with the overall SABINA III populationThis large cross-sectional study in 24 countries provides valuable real-world insights into the management of asthma in primary care at a global scale. Although most patients were prescribed maintenance therapy in the form of ICS or ICS/LABA fixed-dose combination, SABA over-prescription was common, even in patients with mild asthma. Approximately half (44.9%) of all patients were prescribed SABA in excess of current treatment recommendations (≥3 SABA canisters in the previous 12 months), which was associated with poor asthma-related health outcomes, both in terms of increased incidence of severe exacerbations and poor asthma control.20, SABA over-prescription in primary care was high, with a greater proportion of patients in the PCP cohort being prescribed ≥3 and ≥10 SABA canisters (both as monotherapy and in addition to maintenance therapy) compared with the overall SABINA III population27. Notably, SABA over-prescription was more common in patients with mild asthma, suggesting potential under-estimation of asthma severity in patients with milder disease or the inappropriate management of patients with ‘mild’ asthma, resulting in poor symptom control.In line with previous studies28, healthcare policy makers and national governments should collaborate effectively to improve access to affordable care and regulate SABA OTC purchase to ensure optimal asthma care.Additionally, OTC purchase of SABA was common in primary care, with 21.5% of patients purchasing SABA OTC without a prescription in the preceding 12 months. Among patients with both SABA OTC purchase and prescriptions, most had already been prescribed ≥3 (72.7%) and ≥10 (39.1%) canisters, a trend that was more apparent in patients with mild than moderate-to-severe asthma (24.1% vs 18.4%). Since SABA OTC purchase has been associated with under-treatment of asthma29, whilst increasing OCS prescriptions (≥4 per year) is associated with deleterious adverse events regardless of dose, duration, or continuous sporadic use30. Hence, there is an urgent need to reduce inappropriate prescribing of both SABA and OCS and to accurately document prescriptions, dispensing and use of OCS for worsening asthma symptoms, and managing exacerbations. To this end, in those countries with adequate healthcare services and where physicians have sufficient time to engage in behaviour change counselling, PCPs could provide patients with self-management training to help them recognise symptom worsening and provide instructions on appropriate use of reliever and maintenance medication, as well as OCS3.The prescription of OCS bursts was common across all SABA prescription categories and asthma severities, especially in patients prescribed 1–2 SABA canisters and those with mild asthma. SABA overuse and high exposure to OCS have been associated with insufficient prescription of maintenance therapy27, this was not observed in this PCP cohort, likely due to the smaller patient population. However, findings from a larger cohort of patients  in the United Kingdom (UK) who were treated in primary care (SABINA I)18 were consistent with those reported in SABINA III. Nonetheless, SABA prescription patterns in the PCP cohort were in line with the overall SABINA III population, highlighting the importance of monitoring both SABA prescriptions and SABA use to identify patients at increased risk of exacerbations, especially those under-prescribed ICS. Indeed, over-prescription of SABAs and insufficient provision of ICS-containing treatments have been identified as preventable causes of death from asthma16. Following the National Review of Asthma Deaths (NRAD) in the UK, the Royal College of Physicians (London) in its report titled ‘Why asthma still kills’ recommends that PCPs have an oversight of the patient’s entire prescription history so that SABA over-prescription can be closely monitored31.Findings from this PCP cohort revealed that higher SABA prescriptions were, with a few exceptions, significantly associated with an increase in the rate of severe exacerbations (10–12 and ≥13 canisters) and lower odds of achieving at least partly controlled asthma (6–9 and 10–12 canisters). Although results from the overall SABINA III study showed a statistically significant association between increasing SABA prescriptions and poor asthma-related outcomes across all SABA categories3, and most patients were not prescribed multiple maintenance treatments, although in some cases, single ICS inhalers provide a ≥2-month supply. In addition, the majority of patients with mild asthma were prescribed ICS at a medium dose (57.6%) instead of the recommended low dose3. Taken together, these findings demonstrate the need for better alignment of both reliever and maintenance medication prescription practices with GINA recommendations by adapting asthma management guidelines to the primary care setting. Most currently available guidelines are complex, long, and generally biased towards a secondary care perspective7, which may limit their utility and has led the GINA committee to acknowledge the difficulty in implementing their recommendations in primary care3; therefore, their adaptation for PCPs to ensure wider acceptance32 would be of considerable value.Most patients treated in primary care were prescribed maintenance medication, either ICS or fixed-dose combinations of ICS/LABA. However, patients were prescribed a mean of 7.2 canisters of ICS in the previous 12 months. This quantity suggests potential under-prescription on the basis that one canister per month is considered good clinical practice36, the level of asthma control in patients treated by PCPs was poor, suggesting that identification of patients with suboptimal asthma control remains a challenge in primary care. Our findings revealed that 57.2% of patients with mild disease reported having uncontrolled/partly controlled asthma, potentially due to inadequate treatment, and suggestive of under-recognition of both disease control and underlying asthma severity. Indeed, both PCPs38 and patients5 tend to overestimate the level of asthma control, leading to under-treatment of the disease37. Moreover, patients often perceive control as symptom relief and/or management of exacerbations, reflective of crisis-oriented disease management39, which may further contribute to SABA over-reliance. This could also account for the high SABA OTC purchase observed in this cohort of patients treated by PCPs, particularly in those with mild asthma. Consequently, use of objective and validated tools, such as the Asthma Control Test (ACT) and the Asthma Control Questionnaire (ACQ)3, can assist PCPs in promptly identifying patients who may require a more detailed assessment, thereby addressing the discrepancy between perceived and actual disease control.Consistent with earlier studies40, with results from a SABINA study conducted in the UK reporting that SABA over-prescription was associated with a 20% increased rate of exacerbations in patients with mild asthma, even after adjusting for various confounding factors18. Another possible explanation for this high disease burden is that healthcare reimbursement was not available to a substantial proportion of patients overall (35.5%), including a higher proportion of patients with mild than with moderate-to-severe asthma (43.1% vs 27.5%). Inadequate healthcare insurance coverage and limited access to healthcare continue to be major barriers in accessing cost-effective treatments in many of the countries included in this study41 and have been associated with a reduced use of regular preventive care, increased use of emergency care42, and consistently poorer quality of asthma care, including a lower likelihood of receiving ICS43. Furthermore, the high cost of maintenance medication, such as ICS/LABA combination inhalers, can limit its use, especially in low- and middle-income countries where access to affordable medicines represents an unmet need41.Poor asthma control translated into a high disease burden in this PCP cohort, with more than a third of patients (38.8%) experiencing ≥1 severe asthma exacerbation in the preceding 12 months. Moreover, 39.0 and 13.7% of patients with mild asthma experienced ≥1 and ≥3 severe asthma exacerbations, respectively. SABA over-prescription is a modifiable risk factor for exacerbationsOverall, our findings reveal that PCPs need to reconsider approaches for managing asthma effectively, particularly in relation to the regular monitoring of both asthma control and SABA prescriptions/use to identify patients at risk of poor health outcomes. Importantly, PCPs need to ensure an accurate evaluation of underlying asthma severity so that appropriate treatment may be initiated or maintained through a step-wise process.25, discussing treatment-related issues, providing educational support and, if available, referring patients to HCPs trained in asthma education3. Although patients recognise early signs of asthma worsening, their initial response is frequently to increase SABA rather than ICS intake. Therefore, symptom-based use of a fast-acting β2-agonist and ICS combination as the default reliever option44, which relies on patients’ inherent symptom relief–seeking behaviour45 and is supported by GINA3, offers a viable asthma management strategy to overcome poor adherence since these medications are available in most primary care and low-income settings44.Since many patients with mild asthma remain uncontrolled, frequently have poor treatment adherence and often underestimate the seriousness of their condition, some PCPs could play a role in establishing asthma action plans31. Therefore, putting practice systems in place whereby PCPs receive notifications from pharmacies for SABA inhalers supplied without a prescription would serve as a useful reminder to proactively review asthma control31. Since PCP consultation times can adversely affect patient care11, approaches such as arranging appointments so that they do not occur simultaneously, organising regular reviews in advance, and improving the system for scheduling walk-in patients could further optimise efficiency in the primary care setting46.Dispensing/prescription of excess SABA inhalers should be identified as a sign of poorly controlled asthma47, further improvements may be achieved by increasing awareness of the latest treatment recommendations and coordinating multidisciplinary care involving a closer collaboration between PCPs and other HCPs48. While pharmacists can help monitor prescriptions, educate patients on the benefits of ICS-containing medications, and encourage them to seek medical advice before dispensing SABA OTC, address factors such as poor adherence and incorrect inhaler technique, identify patients at risk of suboptimal control and teach self-management strategies to achieve asthma control49, a greater involvement of specialists can help with referrals48, especially following an exacerbation16. In addition, quality improvement strategies, including professional development initiatives, audits, and feedback interventions, can assist in closing the gap between best practices and care delivery, thereby improving treatment outcomes50 without impacting workload51.Since poor asthma-related health outcomes in primary care have been attributed to gaps between evidence-based recommendations and clinical practice9, it is essential that PCPs build strong partnerships with patients through shared decision-making, provision of training on self-management3 and effective communication skills to increase patient satisfaction, improve health outcomes3 and reduce healthcare resource utilisation52 without increasing the consultation time53. Notably, compared with patients who receive usual care, those who have greater involvement in treatment-related decisions through shared decision-making, where clinicians and patients negotiate a treatment regimen that accommodates patient goals and preferences, report significantly better clinical outcomes, in terms of quality of life, asthma-related healthcare utilisation, rescue medication use, lung function, and the likelihood of well-controlled asthma54. Therefore, PCPs can play a major part in encouraging patients to participate in treatment-related decisions and communicate their expectations and concerns3.Since primary care is the cornerstone of a strong healthcare system55. Owing to its observational nature, the study may also be prone to bias, e.g. therapies may be differently prescribed depending on disease severity56. In addition, as data for OTC purchase of SABA were self-reported, these findings may also be prone to recall bias56. Finally, as patients at many sites were predominantly recruited by specialists, results may not reflect primary care practices across all participating countries. However, aggregated data from 1440 patients across 24 countries, with a balanced distribution of those with mild and moderate-to-severe asthma, provide an understanding of global asthma management practices in the primary care setting.This study is not without limitations. Prescription data were used as a surrogate for actual medication use and do not provide information on medication adherence, potentially leading to an under-estimation or over-estimation of SABA use. Although OCS bursts were likely prescribed for managing asthma exacerbations, the association between SABA prescriptions and OCS bursts was not analysed. As asthma severity was classified by investigators (guided by GINA 2017 treatment steps), the underlying disease severity may have been misdiagnosed in some patients. However, a global, 3-year, prospective observational study of patients with asthma and/or chronic obstructive pulmonary disease (COPD) from real-world clinical practice demonstrated that investigator-classified disease severity was associated with several clinical and spirometric factors, including exacerbation history and symptom burden, in patients with asthmaIn conclusion, results from 1440 patients from the SABINA III study treated in primary care reported that SABA prescriptions were common, with approximately one in every two patients being prescribed ≥3 SABA canisters in the 12 months prior to the study visit (defined as over-prescription). Unregulated access to SABA was also common, with over one-fifth of patients purchasing SABA OTC, of whom approximately 40% purchased ≥3 SABA canisters in the previous 12 months. Among patients who purchased SABA OTC, most were already receiving SABA prescriptions, of whom over 70.0% received prescriptions for ≥3 SABA canisters. Higher SABA prescriptions (vs 1–2 canisters) were associated with poor asthma-related health outcomes. Prescription of OCS bursts was common across all SABA prescription categories, even in patients with low SABA prescriptions and mild asthma, regardless of asthma medications prescribed in the preceding 12 months. In addition, the level of asthma control was poor, with less than 50% of patients reporting well controlled asthma. Overall, these findings suggest misdiagnosis of disease severity and inappropriate prescribing practices, both of which are an important public health concern, necessitating professional development initiatives at the primary care level to reduce the burden of asthma. Policy changes to regulate SABA prescriptions and OTC purchase, while ensuring access to asthma medications, may help ensure that clinical practices are aligned with the current evidence-based treatment recommendations. Reducing SABA over-reliance at the primary care level and per current evidence-based guidelines may result in improved clinical outcomes.27. Patients were recruited from March 2019 to January 2020. Retrospective data from existing medical records and patient data collected during a study visit were entered into an eCRF. Data on exacerbation history and comorbidities and information on prescriptions for asthma medications were entered in the eCRF by physicians based on patient medical records. At the study visit, physicians also enquired as to whether patients had experienced exacerbations that were not captured in their medical records. Findings from the cohort of patients treated by PCPs are presented here.SABINA III was a multi-country, observational, cross-sectional study conducted in 24 countriesThe primary objective of the study was to describe SABA prescription patterns in the asthma patient population treated by PCPs at an aggregated multi-country level. The secondary objective was to determine the associations between SABA prescriptions and asthma-related health outcomes. In addition, prescriptions of OCS in patients stratified by SABA prescription categories , investigator-classified asthma severity, and SABA monotherapy and ICS-containing treatments were evaluated post hoc.The study was conducted in accordance with the study protocol, the Declaration of Helsinki, and local ethics committees. Informed consent was obtained from all patients or their legal guardians per country regulations.Eligible patients included those aged ≥12 years, with a documented diagnosis of asthma, ≥3 consultations with their HCP, and medical records containing data for ≥12 months prior to the study visit. Patients with a diagnosis of other chronic respiratory diseases, such as COPD, or with an acute or chronic condition that, in the opinion of the investigator, would limit their ability to participate in the study were excluded. Potential study sites were selected using purposive sampling with the aim of obtaining a sample representative of asthma treatment patterns within each participating country by a national coordinator, who also facilitated the selection of investigators.57. For consistency across the whole SABINA programme, one SABA canister was assumed to contain 150 inhalations57. ICS canister prescriptions in the 12 months before the study visit were recorded and expressed according to the average daily dose .SABA prescriptions in the 12 months before the study visit were recorded and categorised as 0, 1–2, 3–5, 6–9, 10–12, and ≥13 canisters. Prescription of ≥3 SABA canisters in the previous 12 months was defined as over-prescription40, asthma duration, and prescriptions for asthma medications in the 12 months prior to the study visit . All patients were also asked about pharmacy purchases of OTC SABA without a prescription, irrespective of whether individual countries permitted SABA purchase OTC; these data were subsequently entered in the eCRF by the investigator. Other variables, including healthcare insurance , education level , BMI, number of comorbidities, and smoking status, were also recorded.Secondary variables included investigator-classified asthma severity 40 and categorised as well controlled, partly controlled, and uncontrolled. Severe exacerbations in the preceding 12 months were based on the American Thoracic Society/European Respiratory Society recommendations58 and defined as a deterioration in asthma resulting in hospitalisation or emergency room treatment or the need for intravenous corticosteroids or OCS for ≥3 days or a single dose of an intramuscular corticosteroid.Asthma symptom control was evaluated according to the GINA 2017 assessment for asthma controlAll analyses were conducted at the overall country-aggregated population level. The association of SABA prescriptions  in the previous 12 months with the incidence rate of severe exacerbations and the odds of achieving at least partly controlled asthma (uncontrolled asthma as the reference) was analysed using negative binomial and logistic regression models, respectively.18). Both ORs and IRRs were adjusted for the same pre-specified covariates ; however, the adjustments differed in the potential confounders used in the two regression models . Patients with zero SABA prescriptions were excluded from the analyses as it was not possible to determine the alternative reliever medication used. To ensure that the overall SABINA III study was adequately powered, the aim was to enrol up to 500 patients from each participating country, with 20−25 patients recruited from each participating site. All statistical tests were two-sided at a 5% level of significance and were performed using R statistical software (version 3.6.0).The regression models, based on complete-case analyses, were adjusted for pre-specified covariates and potential confounders (based on the literature and modelling data from SABINA IFurther information on research design is available in the Supplementary materialReporting Summary


Diabetes mellitus is a disease with no cure that can cause complications and even death. Moreover, over time, it will lead to chronic complications. Predictive models have been used to identify people with a tendency to develop diabetes mellitus. At the same time, there is limited information regarding the chronic complications of patients with diabetes. Our study is aimed at creating a machine-learning model that will be able to identify the risk factors of a diabetic patient developing chronic complications such as amputations, myocardial infarction, stroke, nephropathy, and retinopathy. The design is a national nested case-control study with 63,776 patients and 215 predictors with four years of data. Using an XGBoost model, the prediction of chronic complications has an AUC of 84%, and the model has identified the risk factors for chronic complications in patients with diabetes. According to the analysis, the most crucial risk factors based on SHAP values (Shapley additive explanations) are continued management, metformin treatment, age between 68 and 104 years, nutrition consultation, and treatment adherence. But we highlight two exciting findings. The first is a reaffirmation that high blood pressure figures across patients with diabetes without hypertension become a significant risk factor at diastolic > 70 mmHg  or systolic > 120 mmHg . Furthermore, people with diabetes with a BMI > 32   have a statistically significant protective factor, which the paradox of obesity may explain. In conclusion, the results we have obtained show that artificial intelligence is a powerful and feasible tool to use for this type of study. However, we suggest that more studies be conducted to verify and elaborate upon our findings. Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation, resulting in short and long-term health complications and even death if not properly managed. Unfortunately, there is no cure for DM , 2. HencComplications from DM represent the leading cause of morbidity and mortality among the population with diabetes . TherefoAdditionally, the use of prediction models to identify people at high risk of DM has been recommended by NICE , EuropeaScientists can tailor learning models to find complex patterns within big data  using maDue to the high prevalence of DM in the Mexican population and the lack of a model trained within such a population, we decided to develop a machine learning model on a national program's electronic medical records for patients with diabetes. Our goal is to identify risk factors for patients with diabetes complications through artificial intelligence.We have conducted the study under the Declaration of Helsinki and Guidelines on Good Clinical Practice. Furthermore, the ethics committee of the Faculty of Medicine of the University of Colima approved the project under the deidentification of medical records 2020-01-02). The protocol also complies with the FAIR principles for handling scientific data  and the 20-01-02.We conducted a national nested case-control study , 23 withWe have included all patients older than 18 years of age, diagnosed with diabetes mellitus type 2, and captured in the electronic medical record of the national program for patients with diabetes of the public health sector ISSSTE of Mexico, included in the period from 2011 to 2016. In addition, we have excluded all records from outside the period and all patients with hypertension patients. Finally, we have eliminated all empty and duplicated records.We considered five complications: amputations, myocardial infarction, stroke, nephropathy, and retinopathy. They have all been joined into a category labeled as a chronic complication.Every patient within the study population with a physician's diagnosis of one or more of the five events of interest in their medical record.Every patient within the study population with no physician's diagnosis of any of the five events of interest in his medical record.Among the variables included, we noted information on addictions, obstetric-gynecological history, medications , physical activity, acute complications , the performance of routine tests , education, marital status, infections, hospitalizations, symptoms, referral to specialty, among others.The sample was nonprobabilistic, in accordance with the minimum of 10 observations for each variable –26. All We deleted medical records containing empty records, and “no imputation” technique was used.All predictors used in the model were introduced in numerical form. The categorical variables were managed with dummy encoding, while the continuous numerical variables were stratified by quantiles , 28. XGBMachine learning models are usually seen as a “black box.” It takes some features as input and produces some predictions as output, “Shapley additive explanations” is the acronym for Shapley values, which are widely used in cooperative game theory. Essentially, Shapley's value measures the contributions to the outcome of each variable separately within the dataset while maintaining that their sum equals the outcome –33, whicIn addition, we have provided the odds ratio with its confidence interval, which provides a proper measure of association in case-control studies. In probability models, odds ratios are used to compare the relative probabilities that the outcome of interest will occur given exposure to the variable in question , 35.The initial database consisted of 1,852,766 records and 166 columns (predictors), with 97,044 patients receiving medical care from 2011 to 2016. After preprocessing, such as normalization, elimination of outliers, elimination of columns of identity (empty), data type conversion, and application of inclusion, exclusion, and elimination criteria, the final database consists of 234,847 records and 215 columns with a total of 63,776 patients only diagnosed with DM.The reduction in the number of patients is mainly due to excluding patients diagnosed with hypertension. The reason why the number of columns is increased in the final database is due to preprocessing. We used percentiles to categorize continuous numerical columns to study the influence of the strata on the variables of interest. Thus, in the end, we have 153 binary columns, 31 categorical columns, and 31 numeric variables.Men comprised 40.42% of the study population and women represented 59.58%. Of the patients, 10.69% suffered from alcoholism and 12.2% from smoking. There are 13 antidiabetic medications, 32 antihypertensive medications, and 8 lipid-lowering treatments. While 46.78% of patients took at least one antidiabetic drug, 14.71% took antihypertensive drugs, and 26.84% took lipid-lowering drugs. Concerning self-care, 50.98% were attached to treatment, 14.03% measured glucose by themselves, 68.79% received education on diabetes mellitus, and 64.90% performed physical activity. Only 2.95% had been hospitalized during the period studied, with only 1.80% referring to a specialty consultation. In addition, 15.63% had acute complications, while 51.66% had chronic complications. 23.40% presented at least one type of infection . Preventive examinations are as follows: 14.42% of eyes, 50.09% of feet, and 43.57% of urine.While the average age of the patients was 59.01 ± 10.75, the average diagnosis was 52.67 ± 9.63, and the time with DM was 14.42 ± 11.13. Anthropometrically, the population has a BMI of 30.64 ± 5.35, a weight of 76.82 ± 15.58, and a height of 1.6 ± 0.1. Systolic blood pressure is 129.73 ± 17.48, diastolic is 80.3 ± 9.9, and pulse pressure is 52.85 ± 15. The general lipid profile presents total cholesterol of 206.47 ± 52.19, HDL 46.85 ± 12.63, LDL 110.26 ± 36.57, and triglycerides 226.8 ± 118.06. Their glycemic control with HbA1c was 8.78 ± 2.26, and their fasting blood glucose was 249.61 ± 99.48.For this study, we utilized 14 predictive models such as random forest, linear regression, support vector machines, and naive Bayes. We evaluated all of them with the same training and test data. In addition to having been assessed with the same metrics, we present them in the following table. Given these metrics, the best performant algorithm during the selection phase was the XGBoost model, which went into the thorough process of fine-tuning its hyperparameters. In P value.The risk factors identified in descending SHAP order are continuing in management increases the odds by 1.75 times. Being treated with metformin increases the odds by 3.90 times. The age between 68 and 104 years increases the odds by 1.44 times. Having been referred and consulted about nutrition increases the odds by 1.66 times. Finally, attaching to the treatment increases the odds by 1.35 times see .For a more detailed review of the results obtained from the model, refer to U test for the numeric variables. Although many articles on machine learning mention having performed these tests, it is not required to publish those results.To complete the results section, we present two tables. In Despite current scientific advances, the vast amount of data prevents humans from extracting the maximum benefit. This has become the main limitation for scientific research since as researchers, we cannot operate at the scope, scale, and speed necessary for the amount and complexity of the collected data. For this reason, artificial intelligence is the most appropriate tool to make the most of all this data and transform it into helpful information for doctors and patients .For example, it was previously mentioned that the first studies consulted had preselected the predictive variables through a literature review and not a statistical method –39. HoweDespite this, there are authorities such as the Centers for Disease Control and Prevention (CDC) that issue publications with reported risk factors for patients with diabetes: smoking, overweight or obesity, physical inactivity, systemic arterial hypertension, and hyperglycemia , 41.Starting with smoking, we agree that this risk factor increases the risk of suffering any of the five events studied by 2.045 times. However, our study dove deeper into smoking as a risk factor. Stratifying the patient's years of smoking, we find an almost constant risk ratio, where smoking from 1 to 56 years increases the risk 1.22-1.33 times.Obesity has been recognized as a health risk factor for many years. The risk of morbidity and mortality associated with it is high, as is insulin resistance, which frequently causes diabetes. But a growing body of research indicates that patients with obesity have a higher chance of surviving –44. AccoTurning to physical activity, we found that this variable acts as a risk factor with an increase of 1.33 times the probability of suffering from a chronic complication as a person with diabetes. We understand that these results are controversial. However, we remind readers that this study is based on what was recorded in the patient files. Therefore, there was no way physicians ensured that the patients that carried out the said activity knew the type of activity, its duration, or its intensity. Furthermore, given the study's observational nature, we limit ourselves only to reporting what was found, recognizing its limitations.This study used arterial hypertension as an exclusion criterion for patients, so the hypertension effect cannot be reflected on the variables. However, we have the blood pressure data of the patients involved in this study. We found that diastolic pressure becomes a risk factor from 70 mmHg with an increase of 1.09-1.20 times the risk. On the other hand, systolic pressure is presented as a risk factor from 120 mmHg, increasing the risk 1.14-1.23 times. In addition, we calculated the pulse pressure, which was a risk factor from 40 mmHg with an increase of 1.04-1.20 times the risk. These results conclude that in patients with diabetes but without hypertension, high blood pressure does act as a risk factor even when there is no official diagnosis.The JNC 8 recommends a therapeutic control goal in patients with diabetes and hypertension less than 140/90 mmHg without a clinical trial as evidence. Based on a national analysis of patients with nonhypertensive diabetics, we add evidence to this recommendation. Despite being a more stringent goal (120/70 mmHg), it seeks to prevent the same complications exposed by JNC 8 . We base this goal on the data presented in After obesity, arterial hypertension is the second most common cause of cardiovascular disease, which is the leading cause of morbidity and mortality. Therefore, preventing, diagnosing, and controlling high blood pressure are a global health priority only achieved by measuring blood pressure. In today's modern world, self-measurement with validated devices would be beneficial to involve the patient in treatment and follow-up .Thus, the CDC's last variable is the risk factor hyperglycemia. In this case, we find that hyperglycemia recorded as an acute complication is a risk factor that increases the probability of a chronic complication by 4.5 times. However, we can again use the stratification of the numerical variables to provide specificity to these variables. Thus, fasting blood glucose is presented as a risk factor from 185 mg/dL, increasing 1.16-1.7 times the probability of suffering from a chronic complication. In addition, the fasting glucose gives us a view of these patients' adaptation to the variation in their blood glucose. Studying it through HbA1c, it appears to be a risk factor from 6%, increasing 1.07-1.18 times the probability of a chronic complication.In addition to the variables considered by the CDC, there are publications, such as Abhari et al. and James et al., mentioning that blood pressure variables should be studied independently with machine learning techniques , 47. ThiKnuiman et al. reported that age is the primary variable related to complications of diabetes mellitus . HoweverRoss et al. published that by including all the variables of the electronic medical record, there was a decrease in its predictive performance . HoweverAdditionally, in 2018, Dagliati et al. carried out a study with a similar approach to the present . HoweverIt is important to note that this study was conducted to identify risk factors for chronic complications, encompassing amputations, myocardial infarction, stroke, nephropathy, and retinopathy, without focusing on any particular affliction. Nevertheless, our results have generated information that supports future research aimed at the genesis of applicable instruments or strategies to benefit patients. In this sense, we must continue promoting the use of current and validated strategies and instruments for the care and prevention of complications in patients with DM, such as the determination of the degree of stiffness of the ankle, the use of the Foot Posture Index, or the use of the DFSQ, beneficial to prevent injuries or amputations of the pelvic limbs , 52.We are no strangers to the wide variety of initiatives on machine learning focused on diabetes mellitus that have been launched since 2005 in the United States, Europe, Asia, and Australia. The Nordic Precision Medicine Initiative is the largest, formed in 2015, and intended to collect data from more than one million Nordic citizens . UnfortuWe recognize that all the subjects in this study share the same pathology, diabetes mellitus type 2, declared in the inclusion criteria. Therefore, the results cannot be generalized to all individuals, although the complications studied occur in other conditions.Machine learning can be applied to medical records to develop robust risk models. However, our healthcare system is reluctant to entrust a machine with a human's task with mistakes. However, if we change the vision, this may sound acceptable. Machine learning is not here to replace any human job. It is here to help as a second opinion based on our population's thousands or even millions of records .There is a dissociation between machine learning developers, regulatory bodies, health services researchers, doctors, and patients to generate new or more in-depth knowledge about the pathologies under study . In addiMost studies do not use longitudinal data, employ relatively few predictive variables with a median of 27, and rarely develop multicenter models . In our Furthermore, this is the first Mexican national study that uses machine learning to predict complications in Mexican patients with diabetes mellitus. The published articles have indicated their scale, volume, and quantity of medical records as strengths . HoweverTherefore, we can refine their results and compare them with ours.This work intentionally ignored factors such as the researcher's experience, the use of specific algorithms in the literature, dependencies of hypothetical variables, and the interpretability of the model . Thus, fIn addition, we have used a hypothesis-free machine learning approach for the research question. Thus, a prediction model capable of detecting variables that had not been previously reported as risk factors for complications in this population of patients was created . In someAs far as we know, we have tried to extract as much information as possible from the data source and provide some new insights on the risk factors facing our Mexican population with diabetes mellitus.Although this section is separate from the structure, we included it because we know that we exposed a large amount of information, which was reflected in the tables and could not be discussed in the same way.We remind readers that this study is not intended to find causes of effects but possible cofactors that lead to the effect. Therefore, we usually are brief in discussions to avoid misinterpreting the data. For this reason, we provide the tables with raw information as we obtained it after processing.Many results may lack published support, but one of the study's objectives was to show the tool's scope with a certain degree of supervision without causing bias. We avoid theorizing or arguing through logic or experience that specific values do not adhere to what is published.However, these contrasting results also support our starting premise. Each population provides different information. Perhaps the white European and North American people differ at a specific level from the Mexican population. Nevertheless, if we see it in general, the results are similar. Therefore, this study invites further studies with the Mexican people with artificial intelligence to provide our medical colleagues with accurate information about our patient population.Artificial intelligence identified risk factors for complications in patients with diabetes with an AUC above 80%. Artificial intelligence provides a vision of medical data that is not influenced by the medical literature when utilized in exploratory medical data analysis. Various outcomes may result from this, such as new research, theories, or public health measures. The advent of personalized medicine appears increasingly likely given the large amount of data that can be exploited by this tool and the fact that the results are not all unexpected.


To explore the prevalence of risk factors of retinal diseases among patients seeking services from Madang Provincial Hospital Eye Clinic in Papua New Guinea. p-value of <0.05 was considered statistically significant.  A hospital-based retrospective study was conducted at the only eye clinic serving the entire Madang province of Papua New Guinea. Purposive sampling was used to obtain data from patients' record cards at the eye clinic from January to June 2021. The data collected included gender, age, presenting visual acuity, blood pressure, blood sugar level, body mass index, smoking habits, and history of cataract surgery. The data was analyzed using the International Business Machines Corporation's Statistical Package for Social Sciences version 21. A 2 or > 25 kg/m2). Overweight was significantly associated with hypertension (p < 0.001) and diabetes mellitus (p < 0.001). A few of them were smokers or had a history of cataract surgery .  Two hundred and fifty-five (255) patients went through diabetes and hypertension screening during the period of the study (January to June 2021). The mean age of the patients was 53.14 ± 11.20 years and there were more males (56.86%) than females. Nearly half of the patients (43.6%) were either visually impaired or blind. More than half (52.6%) had diabetes mellitus. Majority of the patients (73.3%) were hypertensive and more than half (57.0%) of the patients had unhealthy body mass index (BMI <18.525 kg/m There is a high prevalence of diabetes, hypertension, and overweight among ophthalmic patients in Madang. It is important that measures are put in place to eliminate barriers to health care and to strengthen eye care services in Papua New Guinea. The retina is the light-sensitive part of the eye and plays significant role in visual function –3. RetinTherefore, there is a need to identify the risk factors of these diseases among different populations and develop measures to reduce their incidence and progression. Systemic diseases such as hypertension , 14 and In 2017, Burnett et al.  indicateThis study was carried out at the Madang Provincial Hospital Eye Clinic in Papua New Guinea. The facility is funded by The Fred Hollows Foundation New Zealand to provide free services and medications to all patients and is one of the main eye care centers in the country. All patients aged 30 years and above undergo diabetes and hypertension screenings as part of the standard procedures at the eye clinic at the time of this study. The facility also provides diabetic retinopathy screening services.This was a hospital-based retrospective study and involved a review of patients' records at the eye clinic from January to June 2021 to obtain data on patients' demographics and risk factors of retinal diseases.Purposive sampling was used in this study. The study involved all available records of patients on diabetes and hypertension screening register at the eye clinic.The study included data from all ophthalmic patients attending the clinic from January to June 2021. However, those below 30 years were excluded from the study since the clinic does not include them in diabetes and hypertension screenings.The following definitions were used for the purpose of this study –30:Normal vision: presenting visual acuity ≥6/12 in the better eye.Mild visual impairment: presenting visual acuity <6/12 to ≥6/18 in the better eye.Moderate visual impairment: presenting visual acuity <6/18 to ≥6/60 in the better eye.Severe visual impairment: presenting visual acuity <6/60 to ≥3/60 in the better eye.Blindness: presenting visual acuity <3/60 in the better eye.Normal blood pressure: systolic pressure of <120 mmHg or diastolic pressure of <80 mmHg.Prehypertension: systolic pressure of between 120 and 139 mmHg, or diastolic pressure between 80 and 89 mmHg.Hypertension: systolic blood pressure of ≥140 mmHg, or a diastolic pressure of ≥90 mmHg.Hypertensive crisis: systolic pressure of >180 mmHg, or a diastolic pressure of >120 mmHg.Hypoglycemia: fasting blood sugar level of <4.0 mmol/L or a random blood sugar of below 3.9 mmol/L.Normal blood sugar level: a fasting blood sugar level from 4.0 to 5.4 mmol/L or random blood sugar reading of 4.0 to <7.7 mmol/L.Prediabetes: fasting blood sugar level of 5.5–6.9 mmol/L or a random blood sugar of 7.7–11.0 mmol/L.Diabetes (hyperglycemia): fasting blood sugar ≥7.0 mmol/L or a random blood sugar level ≥11.1 mmol/L.Fasting blood sugar level was defined as the blood sugar reading taken at least eight hours after a meal. Random blood sugar level was defined as the blood sugar reading taken at any time of the day regardless of when a meal was had.2). It was further classified as follows:Very underweight: BMI of <17 kg/m2.Underweight: BMI >17 to 18.5 kg/m2.Healthy weight: BMI >18.5 to 25 kg/m2.Overweight: BMI >25 to 30 kg/m2.Obesity: BMI >30 to 35 kg/m2.2.Severe obesity: BMI >35 kg/mBody mass index (BMI) was defined as a measure of body fat indicated by the person's weight in kilograms per square meter of the person's height  to check the blood pressure and the blood glucose level was taken using ACCU-CHEK glucometer. The BMI was calculated and classified based on the Nutrition Australia BMI chart and guideline that is used at the eye clinic.p value of <0.05 was considered statistically significant.Data were manually entered, cleaned, and edited for inconsistencies. The data was then analyzed using the International Business Machines Corporation's Statistical Package for Social Sciences version 21 . Descriptive statistics were computed for all variables. Categorical data were presented as frequencies and percentages, and continuous data as mean ± standard deviation. The chi-square test for independence was used to determine associations between variables. A A total of 477 patients visited the eye clinic during the period under study out of which 255 patients (53.46%) were screened for diabetes and hypertension and thus, met the inclusion criteria for this study.p=0.007). The mean age of the patients was 53.14 ± 11.20 years and ranged from 30 to 90 years. Males who comprised the majority of the patients (56.86%) were significantly older than females (The occupation of most patients (61.2%) was not recorded but of those who did have occupation recorded, the greatest number were farmers (16.1%) and housewives (13.3%). Almost all patients (92.9%) were from the Madang province. A total of 208 (81.6%) patients were dwellers of Madang district which is the administrative capital of Madang province. Morobe province accounted for six patients (2.4%) and the remaining twelve patients (4.7%) were almost equally distributed among eight other provinces in PNG.More than three-quarters (84.7%) of the patients reported no prevailing or past medical conditions. The most commonly reported conditions were diabetes (3.1%), kidney disease (2.0%), asthma (2.0%), tuberculosis (1.6%), trauma (1.6%), and anemia (1.2%). Similarly, 209 patients (82.0%) had no previous ocular problem but refractive error was commonly reported by 22 (8.6%). Eye injuries and previous cataract surgery were also reported .p=0.441) or between smoking habits and age group (p=0.258).Less than one-quarter (13.7%) of the patients were smokers. There was no significant association between smoking habits and gender (The mean (±SD) systolic blood pressure was 134.43 ± 22.34 mmHg and that of the diastolic blood pressure was 78.24 ± 12.88 mmHg. More than one-third (35.7%) of patients were prehypertensive and a third (33.3%) had hypertension. There was no significant association between blood pressure and the patient's demographics. Blood sugar levels were determined either as fasting blood sugar (FBS) or random blood sugar (RBS) depending on the time it was measured. The mean FBS was 6.66 ± 3.11 mmol/L, while RBS averaged 8.47 ± 3.91 mmol/L. Seventy-nine patients (31.0%) were prediabetics and a little over one-fifth had diabetes. There was no statistically significant association between blood sugar levels and patients' demographics. 2 (a range between 14 and 46 kg/m2). More than half of the patients had an unhealthy BMI. Overweight (22.4%) and underweight (21.2%) were the highest recorded categories of abnormal BMI. There was a statistically significant association between BMI and gender, age, blood sugar level, and blood pressure (see p=0.001). The highest rate of overweight and obesity was among patients aged 41 to 50 years (p=0.001).The mean BMI was 24.53 ± 5.54 kg/msure see . Female Almost one-fifth (18.4%) were diagnosed with refractive error. This was similar to the number of patients who had cataracts (17.6%). Only four patients (1.6%) were diagnosed with retinal diseases. Therefore, no associations were analyzed between retinal disorders and the patient's demographic characteristics or risk factors.Identifying people at high risk of retinal problems is an essential step for early detection and treatment of ocular and visual conditions before the onset of irreversible blindness. This study shines a light on the prevalence of risk factors of retinal diseases among patients seeking eye care services in Madang province of PNG. A study on retinal conditions was previously conducted in PNG but it focused mainly on diabetic retinopathy  and it aThe subjects in this current study were predominantly adults with an average age of 53.14 ± 11.20 years. Many previous studies have identified aging as a risk factor for AMD, DR, and hypertensive retinopathy . The BhaThe majority of the patients (84.7%) reported that they had no history of any medical condition. However, the majority of them (73.3%) were either prehypertensive or hypertensive when they were screened during their visits. The hospital-based prevalence of high blood pressure in this study 37.6%) was comparable to a hospital-based multicenter study in ophthalmic clinics in sub-Sahara Africa (37.3%) . Similar.6% was cA few of the patients reported a history of tuberculosis (1.6%), smoking (13.7%), and previous cataract surgery (2.0%). Tuberculosis is a known cause of posterior segment diseases such as uveitis and choroiditis –41 and aNearly one-third (31.1%) of the patients were either overweight, obese, or severely obese. Prediabetes was high in overweight, obese, and severely obese subjects . Diabetes was also high in patients who were overweight (33.3%). The findings support other studies which have reported that there is a high chance of developing diabetes in overweight and obese people , 42, 43 Almost half of the patients 43.6%) were either visually impaired or blind. This prevalence is higher than the prevalence reported in other hospital-based studies in developing countries –46. Howe3.6% wereIn summary, our study underlines the importance of eliminating barriers to health care and strengthening eye care services in PNG. Policymakers and stakeholders need to institute health promotion programs in the country and educate the public about the risk factors and consequences of retinal conditions as well as cardiovascular diseases. There is a need to educate the public on lifestyle modifications such as a healthy diet and regular exercise which could address the high rates of underweight, overweight, and obesity. Stronger advocacy for greater and improved diabetic retinopathy screening programs is also essential in PNG. The lack of information for certain variables of the patients is a limitation on our findings, and the outcome cannot be fully generalized for the entire country. We propose that a population-based study should be carried out to detect and treat diabetes and hypertension in Madang province to prevent complications such as retinopathies and blindness.


Investigate pulse wave velocity and central systolic blood pressure among pediatric population with chronic kidney disease.Ⓡ algorithm and were compared with previously established percentiles. In this cross-sectional study, 57 patients  aged 6.2 to 17.5 years old, 44 with nondialysis chronic kidney disease and 13 on chronic dialysis, were included in the analysis. The pulse wave velocity and the central systolic blood pressure were measured with an oscillometric device with an inbuilt ARC Solver The prevalence of elevated pulse wave velocity was 21.1% (95%Cl: 11.4-33.9) and elevated central systolic blood pressure was 28.1% (95%CI: 17.0-41.5). According to the generalized linear model, there was a higher risk of elevated pulse wave velocity in patients undergoing chronic dialysis treatment than nondialysis chronic kidney disease patients . Hypertensive patients (stage 2) had a higher risk of elevated pulse wave velocity than normotensive ones , as did patients younger than 12 years than the older patients . Hypertensive patients had a higher risk of elevated central systolic blood pressure than normotensives , as did patients undergoing chronic dialysis treatment when comparing to nondialysis chronic kidney disease patients . Younger age, dialysis, and hypertension in children are independently associated with higher pulse wave velocity. Hypertension and dialysis are independently associated with higher central systolic blood pressure. In the pediatric age group, CKD is rare, with a prevalence between 18 and 100 cases per million, though it has been increasing in recent decades. In these patients, mortality is up to 30 times higher than that in the general pediatric population, and cardiovascular disease (CVD) is the most common cause.,5 Clinical and epidemiological studies show that although cardiovascular complications manifest especially in more advanced stages of the disease, and such changes begin early in patients with CKD.,7Chronic kidney disease (CKD), which is characterized by injury and progressive loss of renal function, is an important public health problem in Brazile.g., hypertension and dyslipidemia) and nontraditional risk factors for CVD .,8 Early markers of heart disease, such as hypertrophy and dysfunction of the left ventricle, and early markers of atherosclerosis, such as increased carotid intima-media thickness and arterial stiffening, are frequent findings in adults with CKD, especially in patients undergoing dialysis treatment.Pediatric patients with CKD have a high prevalence of traditional  reflects arterial changes more accurately than peripheral blood pressure and has predictive value for cardiovascular events. In recent years, PWV and cSBP have been widely studied and become accepted as a simple, noninvasive, reliable, and reproducible method for determining arterial stiffness. In pediatric CKD, data on arterial stiffening are still scarce, so further studies in this population are necessary.Pulse wave velocity (PWV) is a well-established predictor of cardiovascular events in adultsPulse wave velocity and cSBP were measured in pediatric patients with CKD, and the associations of clinical, anthropometric, and laboratory parameters with PWV and cSBP were assessed.Investigate pulse wave velocity and central systolic blood pressure among pediatric population with chronic kidney disease.Escola Paulista de Medicina da Universidade Federal de São Paulo (EPM/UNIFESP) in São Paulo. The convenience sample consisted of all patients followed up at the outpatient clinic who met the inclusion and exclusion criteria. A total of 62 patients were selected, of whom three refused to participate and two did not perform the exams, making up 57 patients in the study. The inclusion criteria were age between 6 and 18 years old, creatinine clearance <90mL/min/1.73m2 associated with kidney injury, i.e., stage 2, 3a, 3b, 4, or 5 CKD according to the kidney disease improving global outcomes (KDIGO) 2012. The exclusion criteria were age younger than 6 or older than 18 years old and neoplastic, infectious, or inflammatory diseases. Data were collected between May 2015 and March 2016. The study was approved by the Research Ethics Committee of UNIFESP (2130/11). The informed consent form and the consent form were obtained from all study participants and guardians.This was an observational, cross-sectional study that included 57 patients with CKD, who were followed up at the pediatric nephrology outpatient clinic of the Ⓡ algorithm. The device used was previously validated by direct measurements and/or tonometry, with good reproducibility in previous studies.,14 The patients remained in the dorsal decubitus position and rested for 10 minutes before the beginning of the examination. Two measurements were taken at a 5-minute interval, and the arithmetic mean between these two measurements was used as the final measurement for analysis.Pulse wave velocity and cSBP were measured with the automated Oscillometric Apparatus Mobil -O- Graph 24 hours PWA monitor , which uses the ARC Solver Values of PWV and cSBP above the 95th percentiles were classified as elevated.For the classification of PWV and cSBP, the percentile tables for height and sex proposed by Elmenhorst were used, which were prepared for children and adolescents using the same device. and glomerular filtration rate (GFR) was estimated using the Schwartz equation. The etiology of the baseline disease, the duration of CKD, the type of treatment, and the time of dialysis were collected from the medical records of the service. Blood pressure (BP) was assessed by an oscillometric measurement using a digital device  in the same week as the PWV and cSBP measurements. The patient remained at rest for 3 to 5 minutes, and a cuff adequate to the circumference of the arm (width and length) was used at the midpoint between the olecranon and the acromion. The BP measurement was confirmed by auscultatory measurement and was classified according to the Guideline for Screening and Management of High Blood Pressure in Children and Adolescents 2017.Chronic kidney disease was classified according to KDIGO 2012,®, SP, Brazil) and physicians using a vertical wall-mounted stadiometer. Weight and height measurements were used to calculate the body mass index for age (BMI/A) z-score and height for age (H/A) z-score, according to the World Health Organization’s (WHO) reference standard.The patients were evaluated by a single nutritionist using an electronic scale , total calcium (8.6-10.2mg/dL), ionic calcium (1.20-1.37mmol/L), hemoglobin (12-15.5g/dL), alkaline phosphatase , phosphorus (2.5-4.5mg/dL), albumin (4 days to 14 years old 3.8-5.4g/dL and 14 to 18 years old 3.2-4.5g/dL), magnesium (1.8-2.5mg/dL), C-reactive protein (up to 1.00mg/L), 25OH-vitamin D (>30ng/dL), and sodium bicarbonate (23-27mmol/L). The Brazilian Guidelines for Clinical Practice for Mineral and Bone Disorders in Chronic Kidney Disease of Children were used for the classification of parathyroid hormone (PTH) values.For total cholesterol, LDL, HDL, and triglycerides (TG), the I Guidelines for the Prevention of Atherosclerosis in Childhood and Adolescence were used as reference. In this case, the increase in PWV or in cSBP were considered the dependent variable, and the various exposure factors were considered independent variables. The variables that showed a p value of 20% or lower in the univariate analysis were selected to compose the multivariate model. It was decided to calculate the PR instead of calculating the odds ratio because the events evaluated (elevated PWV and elevated cSBP) were frequent (≥20%).The prevalence of children and adolescents with CKD who had changes in PWV and cSBP, and their respective 95% confidence intervals (95%CI) were estimated. The qualitative variables were written as number (n) and percentage (%). Pearson’s correlation test was used to assess the association with PWV and cSBP. To estimate the strengths of the associations between PWV alteration or cSBP alteration and risk factors, the prevalence ratio (PR) and its 95% CI were calculated using the generalized linear model (GLM) with a binomial distribution and the log link function.All analyses were performed in Stata version 14.2 for Windows. Results with p<0.05 were considered significant.The age of the studied patients (n=57) ranged from 6.2 to 17.5 years old, with median of 11.9 years old, and 61.4% of them were male. A total of 44 (77.2%) patients underwent conservative treatment, 5 (8.8%) patients underwent peritoneal dialysis, and 8 (14%) hemodialysis. The prevalence of elevated PWV and cSBP found in the study population were 21.1% (95%CI: 11.4-33.9) and 28.1% (95%CI: 17.0-41.5), respectively.According to i.e., no patient with elevated PWV was observed among the 15 patients with PTH within the reference range. However, 12 of the patients with out-of-reference PTH values (≤9 or ≥33) had elevated PWV. Despite the significant association, from a statistical point of view, it was not possible to estimate PR in this case because no patient with altered PWV was observed among those who had PTH values within the reference.No significant association between laboratory parameters in altered PWV were found, except for PTH (p=0.044) and LDL-C (p=0.048), For LDL, there was a higher percentage of patients with altered PWV among those with elevated LDL-C (41.7%) than those presenting normal LDL-C levels (15.9%).The prevalence of elevated PWV among patients younger than 12 years old was 2.9 times that observed among patients older than 12 years old (95%CI: 1.05-8.40) . PatientAccording to There was no significant association between elevated cSBP and laboratory tests (p>0.05). The variables independently associated with abnormal cSBP found through the multivariate model were type of treatment and BP. The prevalence of elevated cSBP among patients on dialysis was approximately 2.1 times that observed among those under conservative treatment . Patients classified with stage 1 or 2 of hypertension had a prevalence of elevated cSBP 3.3 times that observed among patients classified as normotensive .This study analyzed PWV and cSBP and their associations with clinical, anthropometric, and laboratory data of children and adolescents at different stages of CKD. Patients under dialysis treatment had a higher prevalence of elevated PWV and elevated cSBP than patients under conservative treatment. Regarding BP, patients on stages 1 and 2 of hypertension had higher prevalence of elevated PWV and cSBP. Children younger than 12 years old had higher prevalence of elevated PWV than those aged 12 years or older, but did not predict higher cSBP. The analysis of PWV and cSBP is already well established for evaluating arterial stiffness, and the use of the indirect oscillometric method has advanced in the literature.Cardiovascular disease is the main cause of mortality in patients with CKD, and its manifestation is subclinical in most cases. In recent years, the number of studies describing cardiovascular changes in children and adolescents has increased, and the need to include cardiovascular assessment in the clinical routine of care for patients with CKD has led to the search for rapid assessment methods validated for the pediatric population and independent operators.Although there are different methods for assessing PWV, many have not been standardized for children. Tonometry, which is considered the “gold standard”, is a method that is difficult to apply in pediatrics. Even with the child cooperating during the test, the signal may be not adequately detected in the arteries of young children. The oscillometric methods of PWV analysis, which use pressure cuffs, have the advantage of being rapid, consistent, and operator independent. This finding was also observed in transplanted patients: Briese et al. analyzed 36 transplanted children and compared them with a Control Group; they also found elevated PWV in the transplant group, and systolic pressure showed significant association with elevated PWV in the multivariate analysis. Kis et al. included 11 patients with a mean age of 14 years old (standard deviation = 4.1 years) who were compared with a control population of 133 healthy children. There was no difference in PWV between patients on dialysis and the normal population when matched by age; however, when matched by height, the PWV of patients on dialysis was significantly higher. This finding indicates that PWV is directly related to body size.The first studies describing vascular changes in the pediatric population mainly focused on patients with terminal CKD, especially those on dialysis and post-transplantation. In 2006, Covic et al. analyzed 14 children on hemodialysis and compared them with a control group; they found a higher PWV in hemodialysis patients.thpercentile of the reference population by sex and height. The prevalence of elevated PWV was 21.1%. In a multicenter European study (The 4C Study) which included 12 countries and 688 pediatric patients under conservative treatment, PWV was also evaluated using reference values for height and age. Elevated PWV, defined as above the 95th percentile, was observed in 20.1% of patients.In this study, we used a reference population validated with the device utilized, and PWV was considered elevated when above the 95The interest in studying early cardiovascular changes in pediatric patients with CKD has grown in recent years. The demonstration of PWV changes and their incorporation in the evaluation and long-term follow-up of children and adolescents with terminal CKD may help in the development of strategies to decrease cardiovascular morbidity after the onset of kidney disease. The long-term consequences of vascular injury are particularly important in the pediatric population because these children and adolescents will be under renal replacement therapy for a long time.2), Sinha et al. observed a higher PWV than in the Control Group; however, there was no association of elevated PWV with the stage of the disease, only with hypertension, which suggests that vascular injury begins early.In 2016, Taşdemir et al. published a study with 25 pediatric patients with stage 2 CKD and elevated PWV compared to the control group. The elevation in PWV was independently associated with arterial hypertension, which was also found in our study. In another study with 188 children with CKD under conservative treatment . The studies in which older age was associated with elevated PWV The CAFE study, with 2,199 adult patients, observed that antihypertensive drugs had different effects on central aortic pressure despite having similar effects on peripheral pressure.In their 2015 study, Sinha et al., also observed that children with CKD and peripheral BP above the 75th percentile had higher central blood pressure than the Control Group. The measurement of central arterial pressure can help in the diagnosis of hypertension and in the therapeutic management of children, and there are already tables with reference values per height, age, and sex for cSBP, such as the one used in this study.Central blood pressure is not well studied in pediatrics, but some studies in adults suggest that it is more related to cardiovascular risk, such as carotid intima-media thickness and left ventricular hypertrophy, than peripheral  pressure.Some limitations of the current study deserve comment. The number of children included could be considered relatively small, but it is comparable to previous studies. The analysis of patients undergoing conservative treatment and dialysis was combined to increase the statistical power. However, in the multivariate analysis, the dialysis variable was independently associated, thus controlling for possible clinical differences in relation to conservative treatment. Finally, as it was a cross-sectional study, the analysis was not done over time, and further prospective studies are needed to confirm our findings in this cross-sectional analysis.In the studied pediatric patients with chronic kidney disease, the prevalence of elevated pulse wave velocity and elevated central systolic blood pressure is common. Among several associations observed in the univariate analysis, younger age, dialysis, and hypertension were independently associated with elevated pulse wave velocity. Dialysis and hypertension were independently associated with elevated central systolic blood pressure.


Endothelial dysfunction commonly occurs in chronic kidney disease (CKD) patients and increases the risk for cardiovascular disease. Among CKD patients, biomarkers involved in the pathogenesis of CKD-mineral bone disorder (CKD-MBD), such as phosphorus, parathyroid hormone, and fibroblast growth factor 23, are associated with endothelial dysfunction. We investigated whether these biomarkers induce endothelial dysfunction in CKD patients with normal phosphorus levels.This cross-sectional study examined CKD patients with normal phosphorus levels; patients with an estimated glomerular filtration rate (eGFR) <15 or who were under dialysis were excluded. Iontophoresis with laser doppler flowmetry (ILDF) and peripheral arterial tonometry were performed to assess endothelial function in 85 patients. Pearson's correlation coefficient, multiple regression, and mediation analyses were performed to examine the association between CKD-MBD biomarkers and endothelial dysfunction.r = 0.22, P = 0.04), intact parathyroid hormone , and VCAM-1 . The reactive hyperemia index (RHI) was significantly related to phosphorus levels  and iPTH . After adjusting for eGFR, iPTH and VCAM-1 remained independent factors for predicting endothelial dysfunction measured using Ach-induced ILDF. In addition, iPTH and phosphorus levels were independent predictors for endothelial dysfunction measured using RHI in the eGFR-adjusted model. Mediation analyses showed that the individual indirect effects of iPTH were significantly affected ILDF and RHI.Endothelial dysfunction was observed in all subjects with a low response to ILDF and 27% of subjects according to peripheral arterial tonometry. Acetylcholine (Ach)-induced ILDF was significantly associated with eGFR (Serum levels of phosphorus and iPTH are associated with endothelial dysfunction, even in CKD patients with normal phosphorus levels. Endothelial dysfunction is a multifactorial and complex disorder that contributes to the development of cardiovascular disease, and it is the leading cause of death in chronic kidney disease (CKD) patients . ResearcOver the past half a century, researchers have focused on the relationship between conventional cardiovascular risk factors and cardiovascular events in CKD patients. However, CKD patients present with unique cardiovascular challenges, and thus the need to explore non-traditional risk factors in this patient population has emerged. It has recently been reported that hyperphosphatemia, such as that occurring in CKD-mineral bone disease (CKD-MBD), may be a risk factor for the accelerated onset of cardiovascular disease in CKD patients –7.in vitro experiment, high phosphorus levels inhibited nitric oxide (NO) production, resulting in increased reactive oxygen species release and endothelial NO synthase inactivation via conventional protein kinase C, ultimately leading to impaired vasodilation. Based on these results, most advanced CKD patients are prescribed oral phosphate binders to lower their serum level of phosphorus; nonetheless, cardiovascular mortality in CKD patients remains high  for assessing the endothelial function of peripheral vessels , 11. PerTherefore, we investigated whether a normal phosphorus level can cause endothelial dysfunction and how the major factors involved in mineral metabolism, including serum phosphorus, parathyroid hormone (PTH), and fibroblast growth factor 23 (FGF23) levels, affect endothelial dysfunction in CKD patients, using EndoPAT and iontophoresis with LDF.This was a single-center, cross-sectional study. From January 2018 to December 2020, 85 patients with non-dialysis CKD were recruited from the outpatient clinic at the Ewha Womans University Mokdong hospital in Seoul, Korea. To be included in the study, patients were required to be aged between 18 and 65 years, have CKD stage 1–4, and have a normal reference serum level of phosphorus (2.3–4.5 mg/dL) for at least 3 months prior to enrollment. Patients with New York Heart Association class III/IV heart failure, acute myocardial infarction, severe peripheral arterial disease, decompensation in the past 3 months, malignancy in the past 5 years, hepatic insufficiency, acute infectious disease in the last 30 days, or who were pregnant or breastfeeding were excluded. Enrollment information and past medical history data were obtained from patient medical records. To evaluate endothelial function, iontophoresis with laser doppler flowmetry (ILDF) and EndoPAT-2000  analysis were performed after the patients had fasted for at least 8 h. Each subject was instructed to avoid food, drugs, tobacco, alcohol, coffee, and tea 10 h prior to the test. The study protocol was approved by the hospital's ethics committee (IRB no. ECT12–02A-28) and written informed consent was obtained from all subjects prior to participation in the study. All clinical investigations were conducted in accordance with the 2013 Declaration of Helsinki.Laser-doppler flowmetry is a non-invasive method used to determine endothelial dysfunction according to skin microvasculature function , and it The EndoPAT-2000 is a non-operator-dependent, non-invasive device used to assess microvascular function. It records post-ischemic reactive hyperemia, known as the peripheral arterial tone signal, using plethysmographic probes placed on the index finger of each hand. Prior to taking measurements, the patients were instructed to rest in a supine position for a minimum of 20 min in the same room where ILDF was performed. Each recording consisted of 5 min of baseline measurements, 5 min of occlusion measurements, and 5 min of post-occlusion measurements (hyperemic period). The occlusion pressure was at least 60 mmHg above the patient's systolic blood pressure (200–230 mmHg). Occlusion of the brachial artery was performed on the non-dominant upper arm. After 5 min of inflation the cuff was deflated, which induced reactive hyperemia. During this hyperemic period, flow measurements were recorded and the response to reactive hyperemia was calculated automatically by the software system. A reactive hyperemia index (RHI) was created using the post- and pre-occlusion values and normalized to measurements from the contralateral arm, which served as a control for non-endothelial-dependent systemic effects . An RHI Venous blood samples were collected from each patient prior to measuring endothelial function after overnight fasting (at least 8 h). Standard laboratory tests included complete blood cell counts and routine blood chemistry, including serum albumin, creatinine, triglycerides, total cholesterol, low density lipoprotein (LDL) cholesterol, and uric acid, activated vitamin D were collected using automated techniques. Values of estimated GFR (eGFR) were calculated with a new equation proposed by investigators at the Chronic Kidney Disease Epidemiology (CKD-EPI) Collaboration. Baseline phosphate levels were measured with an ammonium molybdate assay on the Olympus AU1000 auto-analyzer . Intact PTH (iPTH) was measured using a radioimmunometric assay . Serum VCAM-1 levels were quantified using an ELISA kit designed to quantitatively measure the human soluble VCAM-1 concentration in serum . Plasma FGF23 concentrations were measured using an ELISA assay (concentration detection range: 3–800 pg/mL) with a commercial reagent . The serum VCAM-1 and plasma FGF23 concentrations were measured twice and then averaged.P-value of < 0.05 was considered statistically significant.Because FGF23, VCAM-1, and the values from vascular measurements were not normally distributed, these variables were logarithmically transformed before further analysis. Variables correlated with endothelial dysfunction were evaluated by a univariate linear regression analysis and variables found to be significant, including eGFR, sex, albumin, and hemoglobin, were further analyzed with a multivariate stepwise linear regression analysis. The SPSS statistical package for Windows was used for all analyses . A Mediation analyses were performed, when appropriate, based on the multivariate regression results to assess the hypothesized associations between PTH and endothelial dysfunction. Specifically, the mediation analysis was performed when the exposure was significantly correlated to the mediator or endothelial dysfunction, or when mediator was significantly related to endothelial dysfunction. Indirect effects and confidence intervals were estimated by bootstrapping with 5,000 resamples using the PROCESS Statistical Package for SPSS . Statistically significant mediation was considered established when the indirect effect was significantly different from zero.n = 49) were males. The mean age was 49.5 years and the mean body mass index was 24.5 kg/m2. The etiology of CKD in this study included hypertension (18.8%), diabetes mellitus (12.9%), and glomerulonephritis (40.0%). Hypertension was the most common comorbidity during the CKD management follow-up period (56.5%), followed by dyslipidemia (32.9%), and diabetes mellitus (17.5%). Most patients were taking either angiotensin-converting enzyme inhibitors (15.3%) or angiotensin receptor blockers (63.5%) without concurrent use of angiotensin blockade. Approximately half of the patients were taking a statin (44.7%) and a calcium carbonate was prescribed for three patients for calcium supplement.Characteristics of the CKD patients are listed in 2, ranging from 15.6 to 120.9 mL/min/1.73 m2. The average of intact PTH, log transformed FGF 23, and log transformed VCAM-1 were 62.1 ± 40.8 pg/mL, 4.7 ± 1.7, 5.9 ± 0.3, respectively.The biochemical and vascular assessments are presented in On the day of vascular assessment, the average systolic blood pressure and diastolic pressure were 122.8 ± 14.4 and 74.2 ± 9.9 mmHg, respectively. For the endothelial function test, endothelial dysfunction was observed in all subjects as the ratio of their response PU to baseline PU value measured according to Ach-induced ILDF <100. The log-transformed responses to Ach- and SNP-induced iontophoresis and RHI values were 13.2 ± 9.1, 11.5 ± 6.2, and 2.2 ± 0.6, respectively. Endothelial dysfunction, defined as an RHI value <1.67, was detected in 23 patients (27%).r = −0.32, P = 0.003) and iPTH  significantly increased, although serum phosphorus levels were within normal limits , while the change in FGF 23 was not significant.A scatter plot of the relationship between eGFR and PTH, serum phosphorus, log FGF 23, and log VCAM-1 is shown in l limits . Log VCAP = 0.043), iPTH , and log-transformed VCAM-1  were correlated with log-transformed Ach-induced iontophoresis. NSP-induced iontophoresis was not significantly correlated with serum phosphorus, iPTH, FGF23, or VCAM-1, however, serum phosphorus  and iPTH  were correlated with RHI.In the crude model, eGFR  and serum phosphorus  were significant predictors for RHI. Potential cofounders such as age, hypertension, diabetes, and covariants including, sex, serum albumin level, and hemoglobin, significant in the univariate analysis (P = 0.017).When adjusted for eGFR, iPTH  and VCAM-1  remained significant predictors for Ach-induced iontophoresis in model 1. After adjusting for potential cofounders  and covariants, including eGFR, history of hypertension and dyslipidemia, use of beta blockers, and hemoglobulin level, that were significant in the univariate analyses (P = 0.039).Similarly, when adjusted by eGFR, iPTH , 10 patients with CKD 5 without SHPT, and 15 healthy volunteers (In agreement with previous studies in which CKD and PTH implicated impaired NO-mediated vasodilation, our results indicate that eGFR and elevated iPTH and VCAM-1 are related to a decrease in Ach-induced vasodilation . Endotheidectomy . Anotherlunteers . The stuVCAM-1 is considered an endothelial-specific biomarker and an important adhesion molecule that is upregulated during endothelial activation . BecauseThe digital vascular response to reactive hyperemia is predominantly dependent on NO-mediated vasodilation in healthy subjects  and is aTaken together, our data suggest that ILDF and EndoPAT-2000 measurements appear to analyze different aspects of vascular function in selected vascular beds and vessel sizes. Thus, we suggest cautiously that biomarkers of mineral metabolism, such as serum phosphorus and iPTH, involve impaired vasodilation based on different vascular beds and vessel sizes. Finally, our data confirm that endothelial dysfunction is a multifactorial and complex disorder that occurs in CKD patients with an arbitrarily set normal range of serum phosphorus levels.Our study had some limitations that should be considered. Given its small patient population and cross-sectional design, the causal relationships in the present study cannot be determined. In addition, the assessments were only performed once and were not based on a time series. Furthermore, regarding the calcium-PTH-vitamin D axis, vitamin D deficiency is a pivotal change in CKD-MBD, in which vitamin D receptors are expressed in the vascular endothelium. Vitamin D deficiency in CKD patients has been suggested to be independently associated with impaired FMD  and vitaIn conclusion, a normal reference range of serum phosphorus levels and corresponding elevated PTH values is associated with endothelial dysfunction in non-dialysis CKD patients. Further studies are needed to determine whether adjusting phosphorus levels is necessary in CKD patients.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Institutional Review Board of Ewha. The patients/participants provided their written informed consent to participate in this study.SL contributed to the conception or design of the work and drafted the manuscript. S-JK and SL contributed to the acquisition, analysis, or interpretation of data for the work. S-JK critically revised the manuscript. All gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


A 2003 SJPHC opinion paper on Frontline Ideas titled ‘Joining the mobile revolution’  promotedThe SJPHC paper of the year 2019 – ‘Having to learn this so late in our lives…’ Swedish elderly patients’ beliefs, experiences, attitudes, and expectations of e-health in primary health care’  shows thp = .61). The proportion of participants who reached SBP targets in the intervention and control groups were 28% and 31%, respectively (p = .52). Medication changes, number of antihypertensives and health care utilisation were also similar in both groups. Yet, results of blood pressure measurements presented in a box-plot-diagram in the paper showed a possible positive effect of the intervention regarding home SBP. Also, checklist and text message support were considered useful and important by most participants.To improve antihypertensive drug treatment, SMS was tested in the Check and Support study, a cluster randomised control trial (RCT) of 111 patients 30–75 years old with newly diagnosed hypertension in Finland . The intA Swedish six month RCT pilot study of SMS-messages for treatment of hypertension included 60 primary care patients aged 40–80 years with hypertension . Four liA main difference between the interventions were the number of messages delivered to the patients which were higher in the Swedish study. The Finnish patients were younger and newly diagnosed with hypertension whilst the Swedish patients had hypertension since before and thus a much lower baseline blood pressure value than the Finnish patients. These two recent Nordic RCTs of SMS to improve outcome in hypertension treatment in primary care did not give clear evidence for SMS being a useful tool even if especially the Swedish study showed promising results. Why? We believe that this is probably explained by underpowered design preventing the detection of small benefits of the interventions and the Swedish study indeed being a pilot intervention.Another explanation may be a low motivation to lifestyle modifications in patients without manifest cardiovascular disease which makes primary prevention a difficult challenge. The Australian RCT TEXTME studied lifestyle-focused SMS in patients with previous coronary heart disease and found significant improvement in several cardiovascular risk factors including reduced low density lipoprotein cholesterol and systolic blood pressure . HoweverAs most conclusions we also conclude that more evidence is needed in this field of support for hypertension treatment by using the SMS text function of the ever-present personal cell phone as a convenient digital telemedicine tool.


Dear Editors,Kidney transplant recipients are high-risk cardiovascular patients and cardiovascular events are the most common cause of death after kidney transplantation . ManagemTherefore, novel and highly efficient therapies such as inclisiran  may contribute to better LDLC management in this patient population. Inclisiran is a small interference-RNA against protein convertase subtilisin/kexin type 9 (PCSK9), preventing LDL receptor degradation . It is iTo our knowledge, there is no data about the use of inclisiran in kidney transplant recipients yet. Therefore, we present for the first time a case of a patient treated with inclisiran after renal transplantation.2 . The patient has a distinct cardiovascular risk profile. In addition to male sex and older age, he suffers from metabolic syndrome  with hyperuricemia and has a history of smoking (approximately 13 pack years). This has led to progressive peripheral artery disease (Fontaine IIB) and coronary artery disease.Our 79-year-old male patient received a deceased donor kidney transplant 12 years prior to the first inclisiran administration. End-stage renal disease was caused by right-sided nephrectomy due to renal cell carcinoma and unspecified nephrosclerosis of the left kidney. The immunosuppressive regimen at the time reported consisted of everolimus and prednisolone, due to a history of CMV disease. Serum creatinine was 2.44 mg/dL with an estimated GFR of 24 mL/min/mSerum lipids were inadequately controlled during therapy with atorvastatin 80 mg and ezetimibe 10 mg daily . For our very high-risk patient, the 2019 ESC/EAS guidelines on the treatment of dyslipidaemia recommend a target LDLC of < 1.4 mmol/L and an LDLC reduction >50% from baseline values [Inclisiran (284 mg s.c.) was administered at 0 and 3 months and then every 6 months while continuing atorvastatin and ezetimibe. LDLC was significantly lowered to 1.03, 1.14, and 1.32 mmol/L after 6, 9 and 12 months, respectively .2; During the 1-year follow-up, renal function was stable after 12 months (serum creatinine 2.39 mg/dL, eGFR 25 mL/min/mThe case presented demonstrates that inclisiran can be safely and conveniently administered with a profound effect on LDLC levels after renal transplantation. Further research needs to be conducted to demonstrate efficacy on cardiovascular death in transplanted patients.