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American Diabetes Association (ADA), Diabetes Canada (DC) published updates to the management of Diabetic peripheral neuropathy (DPN) in 2017 and 2018. National Institute of Healthcare and excellence (NICE) also updated their guidelines for management of neuropathic pain in 2018. This article aims to review the topic given those updates and to highlight similarities as well as differences in management. The authors will focus on implications and their clinical application in everyday practice.

Centres for Disease Control and prevention (CDC) reports that there are limited data and information about the impact of underlying medical conditions and the risk of infection. To date, there are no studies that report on the risk of infection among patients with haematological diseases or abnormalities. This cross-sectional study reports on the baseline complete blood count in patients attending publicly funded primary care settings with a diagnosis of suspected COVID-19 infections in the state of Qatar. The study will report on the descriptive characteristics of the population, including gender, age and prior abnormalities to their blood test results. We will compare the results of those with positive and negative PCR test results, where appropriate. Nine hundred sixty-two adult patients attended publicly funded primary health care settings in the state of Qatar between February the 10th and April the 30th 2020 with a diagnosis of suspected COVID-19 infections had prior recorded blood investigations in the last six months and were included in this study. The population was young, mean of age is 38.8±11.6. (Median: 36 [Min: 19 - Max: 85]). Complete blood count of the sample had minimal missing data points. Females were more presented in our samples, Female (n=560, 58.21%) and Male (n=402, 41.79%). Most of our sample had a documented PCR test result, negative (n=831, 86.38%); positive (n=123, 12.79%) and missing (n=8, 0.83%). Low haemoglobin values (n=265, 27.5%) and low red blood cell count (n =170, 17.7%) were the most prevalent complete blood count abnormality in the population. Leukopenia was less common (n=50, 8.2%). Most of the population had normal platelet count (n=895, 93%). Gender was the most influential factor in our sample to increase the odds of having a positive PCR t results; males were more likely to be affected (P<0.001, Chi-square test) (OR 2.56, 95% CI 1.73-3.77). Categories for haematological abnormalities were not associated with increased risk of having a positive PCT test result. In a population attending primary healthcare settings with early presentation of symptoms of COVID-19 infection, the risk of infection among our cohort was not affected by the prior haematological values of those patients. Gender was the most influential parameter in the risk of infection in our population. Analysis of the results using gender-specific categories for different haematological parameters suggested that patients with abnormal haematological values were not at increased risk of having a positive COVID-19 infection.

Background This study aimed to evaluate the efficacy of ChatGPT, an advanced natural language processing model, in adapting and synthesizing clinical guidelines for diabetic ketoacidosis (DKA) by comparing and contrasting different guideline sources. Methodology We employed a comprehensive comparison approach and examined three reputable guideline sources: Diabetes Canada Clinical Practice Guidelines Expert Committee (2018), Emergency Management of Hyperglycaemia in Primary Care, and Joint British Diabetes Societies (JBDS) 02 The Management of Diabetic Ketoacidosis in Adults. Data extraction focused on diagnostic criteria, risk factors, signs and symptoms, investigations, and treatment recommendations. We compared the synthesized guidelines generated by ChatGPT and identified any misreporting or non-reporting errors. Results ChatGPT was capable of generating a comprehensive table comparing the guidelines. However, multiple recurrent errors, including misreporting and non-reporting errors, were identified, rendering the results unreliable. Additionally, inconsistencies were observed in the repeated reporting of data. The study highlights the limitations of using ChatGPT for the adaptation of clinical guidelines without expert human intervention. Conclusions Although ChatGPT demonstrates the potential for the synthesis of clinical guidelines, the presence of multiple recurrent errors and inconsistencies underscores the need for expert human intervention and validation. Future research should focus on improving the accuracy and reliability of ChatGPT, as well as exploring its potential applications in other areas of clinical practice and guideline development.