Urine osmolality is used as a measure of response to Vasopressin (ADH). Given that urine specific gravity is much easier to measure it would be helpful to establish a mapping between the two.
Some overview information from Wikipedia:
Urine specific gravity
Osmolality
Correlation of specific gravity and osmolality of urine in neonates and adults gives a regression equation for osmolality for both neonates and adults. They use a refractometer to measure urine SG.
I think the figure 1 caption is in error and the solid circles are adults.
Note that figure 2 indicates there is variation with age. I need to better understand this.
Note that this presentation indicates that a dipstick SG measurement is not as useful for this purpose as a refractometer measurement.
First look at the regression equation given.
osmolality = 33194 (specific gravity)-33247
SG2Osm <- function (SG)
{
osm <- 33194 * SG - 33247
}
SGgrid <- seq(1, 1.030, by=0.001)
#osm <- 33194 * SGgrid - 33247
osm <- SG2Osm(SGgrid)
plot(SGgrid, osm, xlab="Urine Specific Gravity",
ylab="Urine Osmolality (mosm/kg)", main="Regression of Osmolality on SG")
grid()
data.frame(SGgrid, osm) # Show as table
## SGgrid osm
## 1 1.000 -53.00
## 2 1.001 -19.81
## 3 1.002 13.39
## 4 1.003 46.58
## 5 1.004 79.78
## 6 1.005 112.97
## 7 1.006 146.16
## 8 1.007 179.36
## 9 1.008 212.55
## 10 1.009 245.75
## 11 1.010 278.94
## 12 1.011 312.13
## 13 1.012 345.33
## 14 1.013 378.52
## 15 1.014 411.72
## 16 1.015 444.91
## 17 1.016 478.10
## 18 1.017 511.30
## 19 1.018 544.49
## 20 1.019 577.69
## 21 1.020 610.88
## 22 1.021 644.07
## 23 1.022 677.27
## 24 1.023 710.46
## 25 1.024 743.66
## 26 1.025 776.85
## 27 1.026 810.04
## 28 1.027 843.24
## 29 1.028 876.43
## 30 1.029 909.63
## 31 1.030 942.82
Information to interpret readings. From this presentation
Typical values
500-800 mosm/kg (24 hour)
- 300-900 mosm/kg (random)
After 12 hours fasting >850 mosm/kg
A.m. specimen about 3 times serum osmolality
Increased: Dehydration, SIADH, Adrenal insufficiency, Glycosuria, Hypernatraemia, High protein diet
Decreased: Diabetes insipidus, Excess fluid intake, Renal insufficiency, glomerulon ephritis
Normal Urine Output
<50 mL/day anuria
<500 mL/day oligouria
>3L /day polyuria
Typical balance 900 mosm/1.5 L giving 600 mosm/L (remember 1L water is about 1kg)
Polyuria
<150 mosm/kg : Water diuresis
Diabetes Insipidus (P.Na high/normal)
Polydipsia (P.Na low/normal)
>300 mosm/kg Solute diuresis
See further about Water Deprivation (Miller) Test (details in water_deprivation_protocol_pdf.pdf)
See hyponatremia decision tree
This reference analyzes three methods of measuring urine SG (refractometry, hydrometry, and reagent strips) and states only refractometry is suitable for their purposes.
Comparison of 3 Methods to Assess Urine Specific Gravity in Collegiate Wrestlers
In particular note that they found refractometer measures to be consistently lower (by about 0.003)
They used the Schuco Clinical Refractometer (model 5711-2021) which appears to be veterinary. One disadvantage of this is it covers a range of 1.000-1.060 so the useful range is compressed on their scale).
Details for each method are below.
Refractometers are commonly used in beer and wine making so are easily available. Here is an example: Refractometer RF15 with Automatic Temperature Compensation (0-32 Brix)
Some things to be aware of when purchasing a refractometer:
1. Refractometers may be calibrated in either or both of Brix and specific gravity.
2. The correct range is important. For urine we need to cover 0-8 Brix or 1.000-1.030 SG
3. Temperature compensation is desirable
4. Scale markings are helpful. I have seen SG markings at intervals of 0.005, or 0.001
More possibilities:
Ade Advanced Optics® Tri-Scale Clinical Refractometer-Urine Specific Gravity, Urine Refractive Index and Blood Serum Protein - Veterinarian
Brix/SG conversion, roughly
SG = 1 + (0.004 x Brix)
more accurately
SG = 1.000019 + [0.003865613(Brix) + 0.00001296425(Brix) + 0.00000005701128(Brix)]
See https://byo.com/stories/item/1313-refractometer which also has usage information
Veterinary refractometers typically have scales for cats and dogs (small and large animals). Humans should be treated as large animals here.
See http://www.ncbi.nlm.nih.gov/pubmed/21187683
Decide on and purchase a refractometer (see some criteria above). The veterinary versions look best for my purposes, but look for readable scale.
Clinical usage & Veterinary Refractometer RHC-200ATC WMicro brand from sportswarehouse on Amazon, SG accuracy quoted as +-0.005
Other RHC-200ATC links: link1, AliExpress RHC-200ATC - Note there is an RHC-201ATC that claims SG accuracy of +-0.002 rather than +-0.005
Aquarium Refractometer has finer (0.001) markings and a range to 1.070. Some reviews complain about a small and hard to read scale.
RHC-300ATC veterinary, another source has finer (0.001) markings and a range to 1.060.
I have not seen a definitive statement of suitability for osmolality calculation. I believe a urinometer is appropriate for this purpose (perhaps not, see above).
Usage instructions
Manual
Note that temperature compensation is necessary. Be aware of both the sample and calibration temperature.
Calibration temperature 60F. Add .001 for every 5.4F (3C) sample is above calibration temp.
A typical temperature for an immediate reading is 90F which gives an adjustment of (90-60)/5.4 = 5.6. Round down to 5 since I am not always so prompt.
Test strips are not recommended for measuring specific gravity as a proxy for osmolality due to the inferior correlation discussed in references above.
These examples demonstrate the collection and use of urine data. They should include:
1. Measurement of data - tools and procedures
2. Collection of data - what and how to record
3. Calculations - conversion of data into useful information
Collecting all urine output for 24 hours is a good way to examine trends and reduce noise from individual measurements.
These measurements were done with a urinometer and pH strips. I am concerned that the urinometer measurements may be biased low.
Measurements are collected in a CSV file. This provides an easy way to view and edit all the data.
urine24hr <- read.csv("24HourUrine.csv")
# Convert volume to liters
# May want to see http://stackoverflow.com/questions/7214781/converting-units-in-r
urine24hr$Vol <- urine24hr$Volume..oz. * 0.0295735
# Temperature compensation (not in early data, be careful about whether necessary)
urine24hr$SG = urine24hr$SG + 0.005
# Convert SG to osmolality (mosm/kg)
urine24hr$Osmolality <- SG2Osm(urine24hr$SG)
# Assuming 1L is 1kg calculate mosm
urine24hr$Mosm <- urine24hr$Vol * urine24hr$Osmolality
urine24hr
## Date Time Volume..oz. SG UpH SpH Vol Osmolality Mosm
## 1 8/8/2011 6:30AM 19 1.015 5.7 6.8 0.5619 444.9 249.99
## 2 8/8/2011 10AM 9 1.013 5.8 7.2 0.2662 378.5 100.75
## 3 8/8/2011 12:45PM 9 1.016 7.3 6.7 0.2662 478.1 127.25
## 4 8/8/2011 1:55PM 6 1.009 5.8 6.6 0.1774 245.7 43.61
## 5 8/8/2011 3:50PM 14 1.009 5.6 6.8 0.4140 245.7 101.75
## 6 8/8/2011 6:55PM 13 1.015 5.7 6.7 0.3845 444.9 171.05
## 7 8/8/2011 9:40PM 10 1.016 6.4 6.5 0.2957 478.1 141.39
# Calculate 24 hour values
urine24hrtotal <- data.frame(
Vol = sum(urine24hr$Vol),
Mosm = sum(urine24hr$Mosm))
urine24hrtotal$Osmolality <- urine24hrtotal$Mosm / urine24hrtotal$Vol
urine24hrtotal
## Vol Mosm Osmolality
## 1 2.366 935.8 395.5
# Some metrics: 24 hr frequency, Mean volume/void, Maximum volume/void
Some metrics (see FMUV below):
24 hour volume (mL): 2366
24 hour frequency: 7
Mean volume/void (mL): 338
Maximum volume/void (mL): 562
Observations.
Volume is clearly on the high side at 2.4L.
Mosm for one day appears low at 543 mosm.
Average osmolality for one day is low at 230 mosm/kg.
As noted above, I suspect my SG readings may be low (measurement error), but even so there appears to be a definite trend to high volume and low osmolality.
Especially interesting is the first morning osmolality of 279 mosm/kg when the presentation gave an estimate of 3 times serum osmolality (my 6/11 and 9/11 blood tests gave an estimated serum osmolality of 295-299).
Also note that my 6/11 and 9/11 blood NA results were 144 and 142 which would tend to indicate that polydipsia was not the issue.
I think the most likely explanation is a tendency towards diabetes insipidus (but not enough so to qualify diagnostically).
After adding temperature compensation results appear more reasonable (but still on the low SG side).
Similar to the 24 hour collection above except done while abstaining from both food and drink.
urineWaterDep <- read.csv("WaterDeprivationTest.csv")
# Convert volume to liters
# May want to see http://stackoverflow.com/questions/7214781/converting-units-in-r
urineWaterDep$Vol <- urineWaterDep$Volume..oz. * 0.0295735
# Temperature compensation (not in early data, be careful about whether necessary)
urineWaterDep$SG = urineWaterDep$SG + 0.005
# Convert SG to osmolality (mosm/kg)
urineWaterDep$Osmolality <- SG2Osm(urineWaterDep$SG)
# Assuming 1L is 1kg calculate mosm
urineWaterDep$Mosm <- urineWaterDep$Vol * urineWaterDep$Osmolality
urineWaterDep
## Date Time Volume..oz. SG Vol Osmolality Mosm
## 1 8/11/2011 6:50AM 16 1.020 0.4732 610.9 289.1
## 2 8/11/2011 1:40PM 11 1.023 0.3253 710.5 231.1
## 3 8/11/2011 10:50PM 8 1.029 0.2366 909.6 215.2
# Calculate 24 hour values
urineWaterDeptotal <- data.frame(
Vol = sum(urineWaterDep$Vol),
Mosm = sum(urineWaterDep$Mosm))
urineWaterDeptotal$Osmolality <- urineWaterDeptotal$Mosm / urineWaterDeptotal$Vol
urineWaterDeptotal
## Vol Mosm Osmolality
## 1 1.035 735.4 710.5
This demonstrates that I can concentrate urine effectively. However, I think my response is less than typical. Need more data on others to check this.
It is interesting to see that the estimated total mosm is very close (within 4%) to the non-fasting result despite the 2.3x difference in volume.
After adding TC results have changed and look more reasonable.
Emanual Revici (in Research in Physiopathology as Basis of Guided Chemotherapy: With Special Application to Cancer). Also see
discusses urine SG in a number of places:
According to Table XXII 1.016 is an average SG value. Lower values indicate Anaerobic while higher values indicate Dysaerobic.
(This is very odd given that I seem Dysaerobic in some ways–e.g. tissue cholesterol of 150–but anaerobic here. I suspect this can be explained as a separate issue with my posterior pituitary function–e.g. Melvin Page’s work indicates I have a problem here–which is not captured by Revici’s work.)
Page 579 has a discussion of the relation of urine SG and ST.
Page 86 has an overview of the measurements Revici used.
Table XXIV on page 536 describes tests and agents for different levels (Cellular, Tissue, and Organ/Organism). Note that urine SG (along with ST and body temperature) is at the organ/organism level.
See pp. 89-90 for some interesting comments about SG and urine substance concentrations (normalization).
Harold Kristal (page 233 of The Nutrition Solution: A Guide to Your Metabolic Type) uses SG < 1.011 as an anabolic marker and SG > 1.020 as a catabolic marker.
Look at osmolality of these SGs: 312, 478, 611
Guy Schenker (in An Analytical System of Clinical Nutrition) uses SG in his system. The way he uses it is complicated though. One interesting subtlety is that he uses SG to adjust urine pH and saliva pH measurements (see page A-7).
FMUV here. Seems like it might be useful as a metric. For example, track estimated bladder capacity over time to look for prostate enlargement.
Note that the convention (which I am not following) is to consider the first urine to be part of the previous day.
I think the first step is to try to find typical values. Perhaps look for bladder capacity estimates by age?
Urodynamic testing looks like a good starting point.
It looks like the continence literature might be helpful.
For example: http://www.continence.org.nz/pages/bladder-retraining/48/
The 24-h frequency-volume chart in adults reporting no voiding complaints: defining reference values and analysing variables (downloaded full text)
This gives 24 hour urine volume for males 40-49 as 1765 (839) mL (mean/SD).
Maximum void volume (should plot this, see other plots in paper):
Male 20-29: 491 (152) mL
Male 30-39: 510 (201) mL
Male 40-49: 503 (184) mL
Male 50-59: 465 (196) mL
Male 60-69: 414 (156) mL
Male >= 70: 349 (131) mL
NHANES 2009-2010 has urine flow rate data.
Concentrations versus amounts of biomarkers in urine: a comparison of approaches to assess pyrethroid exposure has some useful information.
I was unable to find information about variation of bladder/void volume by weight.
maxVol <- data.frame(age = factor(c("20-29", "30-39", "40-49", "50-59", "60-69", "70+"), ordered=TRUE),
mean = c(491, 510, 503, 465, 414, 349),
sd = c(152, 201, 184, 196, 156, 131))
# See http://www.cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2)/
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.0.3
ggplot(maxVol, aes(x=age, y=mean)) +
geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), width=.1) +
# geom_line() +
geom_point() +
xlab("Age") +
ylab("Volume (mL)") +
ggtitle("Maximum Urine Void Volume by Age for Males")
Trying to get a sense for typical values.
Urine osmolality and conductivity as indices of hydration status in athletes in the heat - 675 (+/- 232) mosmol.kg-1 (mean +/- SD) (increasing to 924 +/- 99 if hyphohydrated)
Interesting that this is not a good preictor for Desmopressin response: Is Early Morning Urine Osmolality a Good Predictor of Response to Oral Desmopressin in Children with Primary Monosymptomatic Nocturnal Enuresis?
This looks like an interesting book (UCSC has a copy): Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
Try looking in physiology textbooks.
From Interpretation of Diagnostic Tests, 3e by Jacques Wallach, M.D.
Note this review comparing to more recent edition.
8e: 0781730554 , 7e: 0781716594
Pages 93-94 list the following tests:
Urine Concentration Test
Vasopressin (Pitressin) Concentration Test
Urine Osmolality
Urine Dilution Test
From old physical exams:
Date | SG | pH |
---|---|---|
11/21/06 | 1.021 | 6.5 |
9/10/09 | 1.015 | 7.0 |
12/9/09 | 1.020 | 7.5 |