Introduction5-oxoproline (pyroglutamic acid), an organic acid intermediate of the gamma-glutamyl cycle, is a rare cause of high anion gap metabolic acidosis. Acetaminophen and several other drugs have been implicated in the development of transient 5-oxoprolinemia in adults. We believe that reporting all cases of 5-oxoprolinemia will contribute to a better understanding of this disease. Here, we report the case of a patient who developed transient 5-oxoprolinemia following therapeutic acetaminophen use.Case presentationA 75-year-old Caucasian woman was initially admitted for treatment of an infected hip prosthesis and subsequently developed transient high anion gap metabolic acidosis. Our patient received 40g of acetaminophen over a 10-day period. After the more common causes of high anion gap metabolic acidosis were excluded, a urinary organic acid screen revealed a markedly increased level of 5-oxoproline. The acidosis resolved completely after discontinuation of the acetaminophen.Conclusion5-oxoproline acidosis is an uncommon cause of high anion gap metabolic acidosis; however, it is likely that it is under-diagnosed as awareness of the condition remains low and testing can only be performed at specialized laboratories. The diagnosis should be suspected in cases of anion gap metabolic acidosis, particularly in patients with recent acetaminophen use in combination with sepsis, malnutrition, liver disease, pregnancy or renal failure. This case has particular interest in medicine, especially for the specialties of nephrology and orthopedics. We hope that it will add more information to the literature about this rare condition.
BackgroundThe extent to which smoking contributes to adverse outcomes among men and women of all ages undergoing dialysis is uncertain. The objective of this study was to determine the differential impact of smoking on risks of mortality and kidney transplantation by age and by sex at dialysis initiation.MethodsWe conducted a population-based cohort of incident U.S dialysis patients (n = 1, 220, 000) from 1995–2010. Age- and sex-specific mortality and kidney transplantation rates were determined for patients with and without a history of cardiovascular disease. Multivariable Cox regression evaluated relative hazard ratios (HR) for death and kidney transplantation at 2 years stratified by atherosclerotic condition, smoking status and age. Analyses were adjusted for demographic characteristics, non-cardiovascular conditions, laboratory variables, socioeconomic and lifestyle factors.ResultsThe average age was 62.8 (±15) years old, 54 % were male, and the majority was white. During 2-year follow-up, 40.5 % died and 5.7 % were transplanted. Age- and sex-specific mortality rates were significantly higher while transplantation rates were significantly lower for smokers with atherosclerotic conditions than non-smokers (P < 0.01). The adjusted mortality hazards were significantly higher for smokers with pre-existing coronary disease (HR 1.15, 95 % CI (1.11–1.18), stroke (HR 1.21, 1.16–1.27) and peripheral vascular disease (HR = 1.21, 1.17–1.25) compared to non-smokers without these conditions (HR 1.00, referent group). The magnitude of effect was greatest for younger patients than older patients. Contrastingly, the adjusted risks of kidney transplantation were significantly lower for smokers with coronary disease: (HR 0.60, 0.52–0.69), stroke; (HR 0.47, 0.37–0.60), and peripheral arterial disease (HR 0.55, 0.46–0.66) respectively compared to non-smokers without these conditions.ConclusionsWe provide compelling evidence that smoking is associated with adverse clinical outcomes and reduced lifespans among dialysis patients of all ages and sexes. The adverse impact is greatest for younger men and women.Electronic supplementary materialThe online version of this article (doi:10.1186/s12882-016-0311-x) contains supplementary material, which is available to authorized users.
Aims In patients with HGG, we know that QoL and physical function decline with progressive disease (PD) and fatigue is a strong predictor of survival in recurrent disease. Despite notable technical advances in therapy for in the past decade, survival has not improved. The role of physical function as a predictor of QoL, treatment tolerance and as an early indicator of worsening morbidity (e.g. tumour recurrence) is an area of growing importance. Recent advancements in wearable technology allow us the opportunity to gather high-quality, continuous and objective data BrainWear is a feasibility study collecting longitudinal physical activity (PA) data from patients with primary and secondary brain tumours and we hypothesise changes in PA over time, are a potentially sensitive biomarker for PD both at diagnosis and relapse. Method Here we show early analysis of this novel dataset of 42 HGG patients and will present: 1) feasibility and acceptability 2) how digitally captured PA changes through treatment and at PD/hospitalization 3) the correlation between patient reported outcomes (PRO) and PA data 4) how PA in HGG patients compares with healthy UK Biobank participants. PA data is collected via a wrist-worn accelerometer. Raw accelerometer data is processed using the UK Biobank Accelerometer Analysis pipeline in python 3.7, and evaluated for good quality wear-time. Overall activity is represented as vector magnitude in milligravity units(mg) and a machine-learning classifier classifies daily activity into 5 separate groups (walking, tasks-light, moderate, sedentary and sleep). Descriptive statistics summarise baseline characteristics and unadjusted mean used to present vector magnitude and accelerometer-predicted functional behaviours (in h/day) by age, sex, radiotherapy and weekend days. Mixed effect models for repeated measures are used for longitudinal data evaluation of PA. Results Between October 2018 and March 2021, 42 patients with a suspected HGG were recruited; 16 females and 26 males with a median age of 59. 40 patients had surgery and 35 patients had adjuvant primary radiotherapy, 23 of whom had a 6-week course. They have provided 3458 days of accelerometer data, 80% of which has been classified as good quality wear-time. There are no statistical differences in mean activity between gender, patients >60 years show statistical difference in time spent doing moderate activity compared to those <60 years, and there are significant differences in mean vector magnitude and walking between radiotherapy and non-radiotherapy days. In patients having a 6-week RT course, time spent in daily moderate activity falls 4-fold between week 1 and the second week following RT completion (70 minutes to 16 minutes). HGG versus healthy UK Biobank participants shows significant differences in all measures of PA. Conclusion Here we present preliminary analysis of this highly novel dataset in adult high grade glioma patients, and show digital remote health monitoring is feasible and acceptable with 80% of data classified as high quality wear-time suggesting good patient adherence. We are able to objectively describe how PA changes through standard treatments and understand the inter and intra-patient variation in PA, and whether there are correlates with patient-centred measures, clinical measures and early indicators of worsening disease. We will present further data on changes in PA prior to hospitalisation and at disease progression, and discuss some of the challenges of running a digital health trial. The passive and objective nature of wearable activity monitors gives clinicians the opportunity to evaluate and monitor the patient in motion, rather than the episodic snapshot we currently see, and in turn has the potential to improve our clinical decision making and potentially outcomes.
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