A Case of ‘Sweet’ Hydrothorax in a Patient on Peritoneal Dialysis

Non-infectious complications are an important cause of peritoneal dialysis failure. Increased intra-abdominal pressure resulting from dialysate inflow into the peritoneal cavity can cause leaks, including hydrothorax due to pleuroperitoneal communication. The authors describe a patient on peritoneal dialysis with a newly discovered pleural effusion with a high glucose level. The patient was treated conservatively with peritoneal dialysis cessation and switched to haemodialysis with complete resolution of the pleural effusion. After 5 weeks, the patient successfully restarted peritoneal dialysis without recurrence of the hydrothorax

Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies

Serum cystatin C - a new marker of glomerular filtration rate

Glomerulna filtracija (GF) je najpomembnejši pokazatelj ledvične funkcije. Ocena GF je pomembna za obravnavo in spremljanje bolnika z ledvično boleznijo. V vsakdanji klinični praksi se za oceno GF najpogosteje uporabljata koncentracija serumskega kreatinina in očistek kreatinina, kot standardna referenčna metoda za določanje GF pa očistek radioizotopnega označevalca. V zadnjem času se kot eden novih označevalcev glomerulne filtracije pojavlja serumski cistatin C, inhibitor proteaz, ki v telesu nastaja stalno v vseh jedrnih celicah in se zaradi svoje majhnosti prosto filtrira v glomerulu. Za razliko od kreatinina koncentracija cistatina C ni odvisna od mišične mase, starosti, spola in načina ter vrste prehrane. Številne raziskave so potrdile, da je serumski cistatin C dober označevalec GF. V določenih populacijah bolnikov z ledvično boleznijo se je koncentracija serumskega cistatina C pokazala kot boljši pokazatelj GF od koncentracije serumskega kreatinina.The glomerular filtration rate (GFR) is the main indicator of kidney function and GFR estimation is essential for the evaluation of patients with chronic kidney disease. In clinical practice, serum creatinine levels and creatinine clearance are the most commonly used markers to estimate GFR. The standard GFR estimation method is based on the clearance of a radionuclide-labelled marker. Recently, serum cystatin C has been proposed as a new endogenous GFR marker. This protease inhibitor with a low molecular weight is produced at a constant rate by all nucleated cells and is freely filtered across the glomerular membrane. Contrary to serum creatinine, serum cystatin C does not depend on muscle mass, sex, age or dietary protein intake. This study confirmed that serum cystatin C is a reliable marker of GFR. Serum cystatin C had a higher diagnostic accuracy than serum creatinine and also creatinine clearance in well-defined patients with chronic kidney disease

Cystatin C - a marker of kidney function and predictor of cardiovascular disease and mortality

Cistatin C v serumu je bil že pred desetletjem predlagan za označevalca ledvičnega delovanja. Trdni dokazi potrjujejo, da je ocena glomerulne filtracije s pomočjo cistatina C izboljšala prepoznavanje bolnikov s kronično ledvično boleznijo pri določenih populacijah. Enačbe za oceno ledvične funkcije, ki vključujejo standardizirano vrednost cistatina C v serumu so postale "state- of-the-art" določanja ledvične funkcije. Zadnje smernice za obravnavo bolnikov s kronično ledvično boleznijo tako vključujejo navodila in priporočila za uporabo cistatina C v klinični praksi. Rezultati raziskav kažejo, da je cistatin C več kot le označevalec ledvičnega delovanja, saj poda celostno informacijo o ogroženosti bolnikov, še posebej tistih z visoko stopnjo tveganja za razvoj sržnožilnih bolezni in dogodkov. Raziskave so pokazale tudi povezavo cistatina C z napredovanjem srčnožilnih bolezni