Exploring Acute Kidney Injury Incidence in Hip Periprosthetic Joint Infection Treatment With Combined Intravenous and Intra-articular Antibiotic Infusion by Wenbo Mu, MD, PhD, Boyong Xu, MD, Fei Wang, MD, Wentao Guo, MD, PhD, Xiaogang Zhang, MD, Li Cao, MD

“…The median onset of AKI was on postoperative day 2, with stage I AKI being the most prevalent, accounting for 64.71% of cases. Diabetes and low baseline serum creatinine levels were identified as independent risk factors for AKI, with odds ratios of 9.69 and 1.09, respectively. …”
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Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning by Xiyu Cao, Jianli Ma, Xiaoyi He, Yufei Liu, Yang Yang, Yaqi Wang, Chuantao Zhang

“…Analysis included 12 variables: age, gender, race, PIR, education, smoking, alcohol, BMI, hyperlipidemia, hypertension, diabetes, and AO. Logistic regression analyzed the association between AO and CVD, with sensitivity and subgroup analyses. …”
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Skin Microbiota: Mediator of Interactions Between Metabolic Disorders and Cutaneous Health and Disease by Magdalini Kreouzi, Nikolaos Theodorakis, Maria Nikolaou, Georgios Feretzakis, Athanasios Anastasiou, Konstantinos Kalodanis, Aikaterini Sakagianni

“…Metabolic disorders, including type 2 diabetes mellitus (T2DM), obesity, and metabolic syndrome, are systemic conditions that profoundly impact the skin microbiota, a dynamic community of bacteria, fungi, viruses, and mites essential for cutaneous health. …”
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Higher systemic immune-inflammation index is associated with increased risk of Parkinson’s disease in adults: a nationwide population-based study by Jiayu Zhao, Zhipeng Wu, Zhipeng Wu, Fengyin Cai, Xuejv Yu, Zhenyu Song

“…Subgroup analysis showed that this association was more significant in women, younger than 60 years old, non-smokers, alcohol drinkers, non-obese, and without a history of stroke, diabetes, or coronary heart disease. In addition, there was a positive dose-response relationship between SII and PD, and SII had an acceptable diagnostic value for PD (AUC = 0.72).ConclusionSII is positively correlated with the prevalence of PD in the adult population, and SII can help differentiate between PD and non-PD cases.…”
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The effects of psychosocial and economic factors on the quality of life of patients with end-stage renal disease and their caregivers in Klang Valley, Malaysia: protocol for a mixe... by Norhayati Ibrahim, Sin Yee Chu, Ching Sin Siau, Noh Amit, Rozmi Ismail, Abdul Halim Abdul Gafor

“…Introduction The number of patients in Malaysia requiring dialysis is expected to rise substantially in the future due to the ageing population and increasing prevalence of diabetes mellitus and hypertension. Hence, more individuals will be expected to adopt the role of caregivers in the future. …”
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Assessing Associations of Nurse‐Managed Hypertension Care on Pharmacotherapy, Lifestyle Counseling, and Prevalence of Comorbid Cardiometabolic Diseases in All Patients With Hyperte... by Charlotte Ivarsson, Monica Bergqvist, Per Wändell, Sebastian Lindblom, Anders Norrman, Julia Eriksson, Jan Hasselström, Christina Sandlund, Axel C. Carlsson

“…Nurse‐managed hypertension care was not significantly associated with differences in pharmacotherapy or patients’ comorbidity, except for diabetes. Primary health care centers with nurse‐managed hypertension care had a 10% greater adherence to national guidelines for lifestyle counseling (33.5%) compared to those without nurse‐managed hypertension care (22.5%). …”
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Inflamación crónica y enfermedades degenerativas by Alvaro Paul Moina-Veloz, Patricio Gabriel Cargua-Inca, Darwin Bladimir Tinillo-Tapia, Bryan Alexander Cueva-Jara

“…Las consecuencias clínicas de un daño por inflamacion puede llegar a ser grave e incluir un mayor riesgo de síndrome metabólico, diabetes tipo 2; hepatopatías, hipertensión, enfermedades cardiovasculares, enfermedad renal crónica o varios tipos de cáncer. …”
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COVID-19's impact on hospital stays, mortality, and readmissions for poverty-related diseases, noncommunicable diseases, and injury groups in Thailand. by Satiti Palupi, Kyaw Ko Ko Htet, Vorthunju Nakhonsri, Chumpol Ngamphiw, Peerapat Khunkham, Sanya Vasoppakarn, Narumol Atthakul, Sissades Tongsima, Chantisa Keeratipusana, Watcharapot Janpoung, Virasakdi Chongsuvivatwong

“…Most poverty-related and noncommunicable diseases indicate increased resource requirements and associated costs, except for HIV/AIDS and diabetes mellitus, showing mixed trends. In injuries, road traffic accidents consistently decrease resource needs and costs, but suicide cases show mixed trends.…”
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Associations of reverse triiodothyronine serum levels with anxiety, depression, and health related quality of life after experiencing acute ischemic stroke by Saulius Taroza, Helene Plamondon, Aurelija Podlipskyte, Nijole Kazukauskiene, Nicolas Francisco Narvaez Linares, Marilou Poitras, Julius Burkauskas, Narseta Mickuviene

“…After adjustment for age, sex, National Institutes of Health Stroke Scale scores, previous stroke, modified Rankin Scale before AIS ≤ 2, and diabetes mellitus, multivariable linear regression revealed negative associations of rT3 with HADS total score (β = −0.163; p = 0.046) and HADS-D subscale score (β = −0.187; p = 0.019). …”
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Propensity score matched cohort study on magnesium supplementation and mortality in critically ill patients with HFpEF by Lijun Song, Jianjun Ying, Min Li, Lan Ying, Chenliang Zhao

“…The results showed that magnesium intake significantly contributed to a decrease in the 28-day all-cause mortality rate (hazard ratio [HR], 0.682; 95% confidence interval [CI], 0.539–0.863), particularly in subgroups such as older patients (HR, 0.65; 95% CI 0.52–0.81), females (HR, 0.55; 95% CI 0.41–0.73), and those with hypertension (HR, 0.62; 95% CI 0.48–0.79) or without diabetes (HR, 0.54; 95% CI 0.41–0.71). Although magnesium treatment improved both ICU and one-year mortality rates, it concurrently resulted in extended ICU and hospital stays. …”
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Unveiling risk factors: a prognostic model of frequent peritonitis in peritoneal dialysis patients by Qi-jiang Xu, Qi-jiang Xu, Zhi-yun Zang, Xue-li Zhou, Xue-li Zhou, Ni-ya Ma, Li Pu, Li Pu, Zi Li

“…In the training set, we found several independent risk factors significantly associated with frequent episodes in PDAP patients, including diabetes mellitus (DM), hemoglobin (HB), serum albumin (ALB), lactatic dehydrogenase (LDH), serum potassium (K), N-terminal pro-brain natriuretic peptide (NT-proBNP) and peritoneal dialysate white cell counts on day 1. …”
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Impact of gas flaring on acute respiratory distress among pregnant women and newborn babies in Delta State Central Senatorial District, Nigeria by Omatseye Alero Akuirene, John Esimaje Moyegbone, Charity Omoikhekpen Chukumah, Mercy Ebiyemi Kalaroo, Josiah Obaghwerhievwo Adjene, Emmanuel Agbonomhen Agege, Joseph Onyedenyifa Odoko, Ezekiel Uba Nwose

“…RDS contributes more to cardiovascular disease and diabetes, hence it is important to address this public health issue …”
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Coffee, including caffeinated and decaffeinated coffee, and the risk of hepatocellular carcinoma: a systematic review and dose–response meta-analysis by Paul Roderick, Peter Clive Hayes, Julie Parkes, Ryan Buchanan, Oliver John Kennedy, Jonathan Andrew Fallowfield

“…There was evidence that the association was not significantly altered by stage of liver disease or the presence/absence of high alcohol consumption, high body mass index, type 2 diabetes mellitus, smoking, or hepatitis B and C viruses. …”
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Navigating next-gen nutrition care using artificial intelligence-assisted dietary assessment tools—a scoping review of potential applications by Anuja Phalle, Devaki Gokhale

“…Dietary assessment tools integrated with AI and ML could estimate real-time energy and macronutrient intake in patients with chronic conditions such as obesity, diabetes, and dementia. Additionally, these tools are non-laborious, time-efficient, user-friendly, and provide fairly accurate data free from recall/reporting bias enabling clinicians to offer personalized nutrition.ConclusionTherefore, integrating AI-based dietary assessment tools will help improve the quality of nutrition care and navigate next-gen nutrition care practices. …”
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PSYCHOSOCIAL ILLNESS IN CHILDREN WITH THALASSEMIA: A CASE-CONTROL STUDY by Erum Afzal, Muhammad Aslam Sheikh, Sajjad Hussain Bhaba, Tanveer Ahmed, Imran Iqbal, Muhammad Khalid Iqbal

“…Regarding characteristics of thalassemia 74 %( n=37) patients were diagnosed within 1st year of life, while 26 %( n=13) after 1st year.64 %( n=32) had well controlled and 36 %( n=18) poor controlled disease. 20%(n=10) had developed Diabetes mellitus,2%(n=1) heart failure,74%(37) growth failure,76%(n=38) hemolytic facial features and 72%(n=36)skin discoloration. …”
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Association between intraoperative fluid management and postoperative outcomes in living kidney donors: a retrospective cohort study by Ja Eun Lee, Chisong Chung, Sunghae Park, Kyo Won Lee, Gaab Soo Kim

“…The following covariates were used: age, sex, body weight, height, diabetes mellitus, hypertension, preoperative estimated glomerular filtration rate, operation duration, surgeon, nephrectomy side, and estimated blood loss. …”
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Clinical Features and Predictors of Lethal Outcome in Tick-Borne Encephalitis: A Retrospective Study from Lithuania by G. Rynkevič, E. Žilinskas, D. Streckytė, D. Radzišauskienė, R. Mameniškienė

“…Patients with the meningoencephalomyelitic form of TBE less often had headache on admission, more often had diabetes, and had fewer lymphocytes in the CSF (all p<0.05). …”
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Kleinia (Asteraceae): comprehensive review of ethnomedicinal uses, phytochemical profiles, ethnopharmacological applications, and toxicological insights by Bantayehu Addis Tegegne, Tesfa Begashaw, Wubetu Yihunie Belay, Mengistie Kassahun Tariku, Tirsit Ketsela Zeleke, Mohammed Jemal, Mamaru Getinet, Agumas Alemu Alehegn, Abebe Dagne

“…Literature highlights numerous Kleinia taxa used in traditional medicine for conditions like intestinal parasites, measles, smallpox, diabetes, edema, nerve disorders, sexual dysfunction, gastrointestinal issues, cancer and more. …”
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Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches by Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, Mostafa Sabzekar, Gordon A. Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…Abstract Background The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM). Method A dataset derived from the Mashhad Stroke and heart atherosclerotic disorders (MASHAD) study comprising 9354 subject aged 65 − 35. 25% (2336 people) of subjects were diabetic and 75% (7018 people) where non-diabetic was used for the analysis of 10 anthropometric factors and age that were measured in all patients. …”
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Adenylate cyclase 10 promotes brown adipose tissue thermogenesis by Anupam Das, Christine Mund, Eman Hagag, Ruben Garcia-Martin, Eleftheria Karadima, Anke Witt, Mirko Peitzsch, Andreas Deussen, Triantafyllos Chavakis, Thomas Noll, Vasileia Ismini Alexaki

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