Geigy Scientific Tables

The safe disposal of human excreta is of paramount importance for the health and welfare of populations living in low income countries as well as the prevention of pollution to the surrounding environment. On-site sanitation (OSS) systems are the most numerous means of treating excreta in low income countries, these facilities aim at treating human waste at source and can provide a hygienic and affordable method of waste disposal. However, current OSS systems need improvement and require further research and development. Development of OSS facilities that treat excreta at, or close to, its source require knowledge of the waste stream entering the system. Data regarding the generation rate and the chemical and physical composition of fresh feces and urine was collected from the medical literature as well as the treatability sector. The data were summarized and statistical analysis was used to quantify the major factors that were a significant cause of variability. The impact of this data on biological processes, thermal processes, physical separators, and chemical processes was then assessed. Results showed that the median fecal wet mass production was 128 g/cap/day, with a median dry mass of 29 g/cap/day. Fecal output in healthy individuals was 1.20 defecations per 24 hr period and the main factor affecting fecal mass was the fiber intake of the population. Fecal wet mass values were increased by a factor of 2 in low income countries (high fiber intakes) in comparison to values found in high income countries (low fiber intakes). Feces had a median pH of 6.64 and were composed of 74.6% water. Bacterial biomass is the major component (25-54% of dry solids) of the organic fraction of the feces. Undigested carbohydrate, fiber, protein, and fat comprise the remainder and the amounts depend on diet and diarrhea prevalence in the population. The inorganic component of the feces is primarily undigested dietary elements that also depend on dietary supply. Median urine generation rates were 1.42 L/cap/day with a dry solids content of 59 g/cap/day. Variation in the volume and composition of urine is caused by differences in physical exertion, environmental conditions, as well as water, salt, and high protein intakes. Urine has a pH 6.2 and contains the largest fractions of nitrogen, phosphorus, and potassium released from the body. The urinary excretion of nitrogen was significant (10.98 g/cap/day) with urea the most predominant constituent making up over 50% of total organic solids. The dietary intake of food and fluid is the major cause of variation in both the fecal and urine composition and these variables should always be considered if the generation rate, physical, and chemical composition of feces and urine is to be accurately predicted.

/pdf/the-characterization-of-feces-and-urine-a-review-of-the-48jlbpxv0z.pdf

The Characterization of Feces and Urine: A Review of the Literature to Inform Advanced Treatment Technology

https://www.kidney-international.org/article/S0085-2538(15)54564-X/pdf

Normalization of urinary biomarkers to creatinine during changes in glomerular filtration rate.

Background: Proteinuria is recognized as an independent risk factor for cardiovascular and renal disease and as a predictor of end organ damage. The reference test, a 24-h urine protein estimation, is known to be unreliable. A random urine protein:creatinine ratio has been shown to correlate with a 24-h estimation, but it is not clear whether it can be used to reliably predict the presence of significant proteinuria.

Methods: We performed a systematic review of the literature on measurement of the protein:creatinine ratio on a random urine compared with the respective 24-h protein excretion. Likelihood ratios were used to determine the ability of a random urine protein:creatinine ratio to predict the presence or absence of proteinuria.

Results: Data were extracted from 16 studies investigating proteinuria in several settings; patient groups studied were primarily those with preeclampsia or renal disease. Sensitivities and specificities for the tests ranged between 69% and 96% and 41% and 97%, respectively, whereas the positive and negative predictive values ranged between 46% and 95% and 45% and 98%, respectively. The positive likelihood ratios ranged between 1.8 and 16.5, and the negative likelihood ratios between 0.06 and 0.35. The cumulative negative likelihood ratio for 10 studies on proteinuria in preeclampsia was 0.14 (95% confidence interval, 0.09–0.24).

Conclusion: The protein:creatinine ratio on a random urine specimen provides evidence to “rule out” the presence of significant proteinuria as defined by a 24-h urine excretion measurement.

/pdf/use-of-protein-creatinine-ratio-measurements-on-random-urine-2mgj8a3n6k.pdf

Use of Protein:Creatinine Ratio Measurements on Random Urine Samples for Prediction of Significant Proteinuria: A Systematic Review

https://www.tera.org/Publications/Hays%20et%20al.%202008.pdf

Guidelines for the communication of Biomonitoring Equivalents: report from the Biomonitoring Equivalents Expert Workshop.

PROBLEM TO BE SOLVED: To enhance correctness of a semiquantitative method by correcting a concentration of a first analysis object in a humor with a concentration of a second analysis object related clinically to the first analysis object. SOLUTION: In the case of albumin in urine in an effective analysis range (30-300 mg/l), a concentration of creatine as a second analysis object is measured, a ratio of albumin/creatine is calculated and a correction concentration of albumin in a sample is obtained. Meanwhile, outside the effective analysis range, the concentration of creatine is not measured, and the ratio of albumin/ creatine is determined with the use of a value of creatine of general healthy people. Errors in estimated values are offset accordingly and a concentration of albumin is determined with more correctness.

Jane F. Wallace

Papers

Method for improving correctness of semiquantitative determination of analysis object in fluid sample