Sample of Our Bibliography for Reference Ranges

Reference Ranges Overview

Lab Reference Ranges

Lab reference ranges refer to the ranges found next to each marker on the bloodwork. Each lab across the country defines their own reference ranges. They are typically referred to as the “normal” or “healthy” ranges but in reality, they just represent 95% of the population tested at that lab and have no basis for defining optimal health. See optimal reference ranges section for more details.

Lab reference ranges used in LabSmarts are taken from two types of sources (in order of priority):

• Clinical research (with links to PubMed)
• National averages and/or ranges from labs and clinical textbooks
• LabCorp, Quest Diagnostics, Mayo Clinic Medical Laboratories, and Lab Tests Online (created by the American Association for Clinical Chemistry)
• McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017.
• Kaushansky K, Lichtman MA, Prchal J, et al. Williams Hematology. 9th ed. New York: McGraw-Hill; 2015.
• Wintrobe MM, Greer JG, Rodgers GM, et al. Wintrobe’s Clinical Hematology. 14th ed. Philadelphia: Wolters Kluwer; 2019.
• Pagana KD, Pagana TJ, Pagana TN. Mosby’s Diagnostic and Laboratory Test Reference. 15th ed. St. Louis, MO: Elsevier; 2021.
• Hillman RS, Ault KA, Leporrier M, Rinder HM. Hematology in Clinical Practice. 5th ed. New York: McGraw-Hill Medical; 2010.
• Hoffbrand AV, Steensma DP. Hoffbrand’s Essential Haematology. 8th ed. Hoboken, NJ: Wiley; 2020.

Optimal Reference Ranges

As mentioned, labs define their reference ranges based on 95% of the population they test. The majority of the population is unhealthy, values in the low and high ends of the lab range justifiably represent suboptimal health and indicate an imbalance in a body system function. Optimal body system function happens when values are within the “optimal” range, which is inside the low and high ends of the lab range, closer to the average (mean) population.

The optimal range for each marker is defined using validated clinical research correlating threshold values to imbalances in body system function. If evidence for the optimal range is not listed below, the optimal range minimum and maximum values are calculated using one standard deviation from the lab mean. This range covers 68% of the population, a much more realistic range for representing optimal body system function than the lab range which is two standard deviations from the lab mean representing 95% of the population. Learn more about the 68-95-99.7 rule here.

Alarm Reference Ranges

The alarm reference range minimum and maximum values used in the software are three standard deviations away from the mean, unless otherwise noted below. These values should be given serious consideration as they are a clear indication that the body system associated with that marker may not be functioning properly.

Age Ranges Supported

Reference ranges used in LabSmarts are for adults only, with one exception. References ranges for infants and children are defined for the seven red blood cell related makers on the CBC based on the study below. Use with infants and children at your own risk.

Red Blood Cells (RBC) Reference Ranges

Lab reference ranges adjusted based on gender and age

• LabSmarts uses the reference ranges for each gender and age group found in the study below as the lab reference ranges for the seven red blood cell related markers on the CBC.
• This study is a better representation of a slightly healthier population than the reference ranges found on your client’s bloodwork.
• This study used the values from 44K “healthy” people from a large nationally representative, population-based, cross-sectional NHANES database to determine “normal/healthy” reference ranges. They started with 65K people then excluded 21K who had 1 of over 15 different health conditions, such as heart disease, stroke, and cancer.
• The ranges from this study still do not represent optimal ranges. Optimal ranges are defined below as 1 standard deviation from the mean of the ranges in this study.

Red Blood Cells (RBC)

• • Lab Min and Max (using gender and age specific ranges from this study): “The large sample size (44K) of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean

Hemoglobin (HGB)

• • Lab Min and Max (using gender and age specific ranges from this study): “The large sample size of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean
  1. “Hemoglobin values ≤12.0 g/dL (and possibly ≤13.0 g/dL) in females age 50+ (but not age <50) and hemoglobin values ≤13.0 g/dL in all males are associated with progressively increasing mortality risk independent of the contribution of other test values. Increased risk is also noted for hemoglobin values >15.0 g/dL (and possibly >14.0 g/dL) for all females and for hemoglobin values >16.0 g/dL for males.” Fulks M, Dolan VF, Stout RL. Hemoglobin Screening Independently Predicts All‐Cause Mortality. J Insur Med. 2015;45:75–80. [PubMed]
  2. “Our results provide evidence that low and high levels of hemoglobin are associated with increased risk of mortality in otherwise healthy women.” Kabat GC, Kim MY, Verma AK, Manson JE, Lessin LS, Kamensky V, Lin J, Wassertheil-Smoller S, Rohan TE. Association of Hemoglobin Concentration With Total and Cause‐Specific Mortality in a Cohort of Postmenopausal Women. Am J Epidemiol. 2016;183(10): 911–19. [PubMed]
  3. “An inverse J-shaped relationship between hemoglobin and all-cause mortality was observed; the lowest risk for mortality occurred at hemoglobin values between 130 to 150 g/L (13.0 to 15.0 g/dL) for women and 140 to 170 g/L (14.0 to 17.0 g/dL) for men.” Culleton BF, Manns BJ, Zhang J, Tonelli M, Scott Klarenbach S, Hemmelgarn BR. Impact of anemia on hospitalization and mortality in older adults. Blood. 2006; 107:3841-3846. [PubMed]
  4. “…subjects with hemoglobin < 14.0 g/dL showed higher mortality rate than those with hemoglobin 14.0-14.9 g/dL or ≥ 15.0 g/dL. The subjects with hemoglobin ≥ 15.0 g/dL showed a lower survival rate than those with 14.0-14.9 g/dL… “ The low number of red blood cells is an important risk factor for all-cause mortality in the general population. Kim YC, Koo HS, Ahn SY, Oh SW, Kim S, Na KY, Chae DW, Kim S, Chin HJ. Tohoku J Exp Med. 2012;227(2):149-59. [PubMed]

Hematocrit (HCT)

• • Lab Min and Max (using gender and age specific ranges from this study): “The large sample size (44K) of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean
  1. “The lowest risk for all-cause mortality was seen in quartile 2 for men (range, 0.421-0.440) and women (range, 0.381-0.400). In absolute Hct values, Hct >0.44 in either men or women is associated with increased risk of death. However, at the lower end of the scale, in men risk of death increases at approximate Hct <0.42, whereas in women the risk of death increases only at a lower threshold of Hct <0.38.” Paul L, Jeemon P, Hewitt J, McCallum L, Higgins P, Walters M, et al. Hematocrit Predicts Long‐Term Mortality in a Nonlinear and Sex‐Specific Manner in Hypertensive Adults. Hypertension. 2012;60:631–638. [PubMed]
  2. “Low and high levels of HCT are associated with increased mortality in the general population.” Boffetta P, Islami F, Vedanthan R, Pourshams A, Kamangar F, Khademi H, et al. A U‐shaped relationship between haematocrit and mortality in a large prospective cohort study. Int J Epidemiol. 2013;42(2):601–615. [PubMed]

High Elevation (Altitude) Adjustments to RBC, HGB, and HCT Reference Ranges

• • Find the elevation of your client’s city HERE
  • The barometric pressure of the atmosphere decreases with each incremental increase in elevation or altitude causing oxygen molecules in the air to get further apart. As a result, the oxygen content of each breath is reduced incrementally the higher up one lives from sea-level.
  • Because people living at higher elevations take in less oxygen with each breath, their bodies have to overcompensate by generating more red blood cells to capture more of the oxygen they take in. This means their normal levels of RBC, HGB, and HCT are higher than those living closer to sea-level.
  • If the ranges for these markers are not adjusted upward, you may miss out on identifying suboptimal blood oxygen delivery as a possible root cause of your client’s fatigue or incorrectly identify dehydration as a condition your client should address.
  • This is why LabSmarts adjusts these ranges for clients living at elevations above 3,280 feet using correction factors recommended by the World Health Organization at elevation increments based on the study from Sullivan and others.
  1. WHO. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin and Mineral Nutrition Information System. Geneva, World Health Organization, 2011 (WHO/NMH/NHD/MNM/11.1). Website or PDF. Accessed February 19, 2020.
  2. Sullivan KM, Mei Z, Grummer-Strawn L, Parvanta I. Haemoglobin adjustments to define anaemia. Trop Med Int Health. 2008;13(10):1267-1271. [PubMed]
  • If vacationing in a higher elevation location, wait at least 3 days before getting blood drawn.

WHO. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin and Mineral Nutrition Information System. Geneva, World Health Organization, 2011 (WHO/NMH/NHD/MNM/11.1). Website or PDF.

Pregnancy Adjustments to RBC, HGB, and HCT Reference Ranges

• • Normal physiological changes in pregnancy result in a reduction of hemoglobin concentration.
  • “Red cell mass (driven by an increase in maternal erythropoietin production) also increases, but relatively less, compared with the increase in plasma volume, the net result being a dip in hemoglobin concentration. Thus, there is dilutional anemia.” Chandra S, Tripathi AK, Mishra S, Amzarul M, Vaish AK. Physiological changes in hematological parameters during pregnancy. Indian J Hematol Blood Transfus. 2012;28(3):144-146. [PubMed]
  • LabSmarts adjusts the reference ranges for these three markers based on the correction factors in the study from Sullivan et al. See the table from this study above.
  1. Sullivan KM, Mei Z, Grummer-Strawn L, Parvanta I. Haemoglobin adjustments to define anaemia. Trop Med Int Health. 2008;13(10):1267-1271. [PubMed]

Mean Corpuscular Volume (MCV)

• • Reference ranges adjusted automatically for the following criteria:
  1. Male ages: 1-2, 3-8, 9-12, 13, 14-15, 16-19, 20-50, 51+
  2. Females ages: 1-2, 3-4, 5-11, 12-16, 17-19, 20-40, 41-55, 56+ with pregnancy ranges for age groups 12-16, 17-19, 20-40, and 41-55
  3. Trimester of pregnancy (if unknown is selected, ranges for trimester 1 are used)
  1. Lab ranges for each trimester from: Abbassi-Ghanavati M, Greer LG, Cunningham FG. Pregnancy and laboratory studies: a reference table for clinicians. Obstet Gynecol. 2009;114(6):1326-1331. [PubMed]
  • Lab Min and Max (using gender and age specific ranges from this study): “The large sample size (44K) of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean
  1. “Patients with PAD (peripheral arterial disease) displayed a significantly higher mean corpuscular volume level (94.5 fl) than control subjects (90.9 fl, p<0.001).” Mueller T, Haidinger D, Luft C, Horvath W, Poelz W, Haltmayer M. Association between erythrocyte mean corpuscular volume and peripheral arterial disease in male subjects: a case control study. Angiology. 2001;52(9):605–613. [PubMed]
  2. “…elevated MCV level in non-anemic cancer-free individuals was associated with increased all-cause mortality in both men and women, and with cancer mortality, in particular liver cancer mortality in men.” Yoon, Hyung‐Jin, Kyaehyung Kim, You‐Seon Nam, Jae‐Moon Yun, and Minseon Park. Mean Corpuscular Volume Levels and All‐Cause and Liver Cancer Mortality. Clinical Chemistry and Laboratory Medicine. 2016;54(7):1247–57. [PubMed]
  3. “…larger erythrocytes in older adults are associated with poorer cognitive function.” Gamaldo, Alyssa A., Luigi Ferrucci, Joseph Rifkind, Dan L. Longo, and Alan B. Zonderman. The Relationship between Mean Corpuscular Volume and Cognitive Performance in Older Adults. Journal of the American Geriatrics Society. 2013;61(1):84–89. [PubMed]
  4. Anderson JL, Ronnow BS, Horne BD, Carlquist JF, May HT, Bair TL, et al. Usefulness of a complete blood count‐derived risk score to predict incident mortality in patients with suspected cardiovascular disease. Am J Cardiol. 2007;99:169–174. [PubMed]

Mean Corpuscular Hemoglobin (MCH)

• • Reference ranges adjusted automatically for the following criteria:
  1. Male ages: 1-2, 3-6, 7-13, 14, 15, 16-19, 20-35, 36-50, 51-75, 76+
  2. Females ages: 1-2, 3, 4-11, 12-19, 20-40, 41+ with pregnancy ranges for age groups 12-19, 20-40, and 41+
  3. Trimester of pregnancy (if unknown is selected, ranges for trimester 1 are used)
  1. Lab ranges for each trimester from: Abbassi-Ghanavati M, Greer LG, Cunningham FG. Pregnancy and laboratory studies: a reference table for clinicians. Obstet Gynecol. 2009;114(6):1326-1331. [PubMed]
  • Lab Min and Max (using gender and age specific ranges from this study): “The large sample size (44K) of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean
  1. Anderson JL, Ronnow BS, Horne BD, Carlquist JF, May HT, Bair TL, et al. Usefulness of a complete blood count‐derived risk score to predict incident mortality in patients with suspected cardiovascular disease. Am J Cardiol. 2007;99:169–174. [PubMed]

Mean Corpuscular Hemoglobin Concentration (MCHC)

• • Reference ranges adjusted automatically for the following criteria:
  1. Male ages: 1-12, 13-19, 20-55, 56+
  2. Females ages: 1-19, 20-60, 61+ with pregnancy ranges for age groups 1-19, 20-60, and 61+
  3. Trimester of pregnancy (if unknown is selected, ranges for trimester 1 are used)
  1. Lockitch G. Handbook of Diagnostic Biochemistry and Hematology in Normal Pregnancy. Boca Raton:CRC, 1993.
  • Lab Min and Max (using gender and age specific ranges from this study): “The large sample size (44K) of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean
  1. Anderson JL, Ronnow BS, Horne BD, Carlquist JF, May HT, Bair TL, et al. Usefulness of a complete blood count‐derived risk score to predict incident mortality in patients with suspected cardiovascular disease. Am J Cardiol. 2007;99:169–174. [PubMed]

Red (Blood) Cell Distribution Width (RDW)

• • “The sizes (volumes) of red cells vary within a certain range in which the number of cells of particular volumes form a bell-shaped or Gaussian distribution; the standard deviation of the cell volumes divided by the mean cell volume gives what is called the red cell distribution width, or RDW, measured as a percent. As it happens, the RDW is a parameter that helps to further classify an anemia because it reflects the variation of red blood cell size. It can be helpful in differentiating causes of microcytosis, because moderate to severe iron deficiency anemia is associated with an increased RDW, whereas thalassemia and anemia of chronic disease (ACD) are associated with a normal RDW.” McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017. p. 85.
  • Lab Max (using gender and age specific ranges from this study): “The large sample size (44K) of NHANES provided a high degree of statistical power in determining age- and sex-specific partitions in reference intervals.  A major strength of our study is the use of a large nationally representative population-based sample (NHANES), use of numerous variables to help define a “healthy” population, and the use of piecewise regression to develop objectively/statistically defined breakpoints. While other procedures for curve fitting may provide a better overall fit of the raw data, piecewise regression was chosen for this study because it objectively identifies breakpoints and, as a result, provides greater specificity.” Fulgoni VL, Agarwal S, Kellogg MD, Lieberman HR. Establishing Pediatric and Adult RBC Reference Intervals With NHANES Data Using Piecewise Regression. Am J Clin Pathol. 2019;151(2):128-142. [PubMed]
  • Alarm Max = 3 standard deviations from lab mean
  • Optimal Max – anything below this value is considered optimal as low RDW has no clinical significance
  1. “For every 1-unit increase of RDW, there is an increased risk of occurrence of ACM (all-cause mortality) and MACEs (major adverse cardiac events). This study indicates RDW may be a prognostic indicator for CVD outcomes.” Hou H, Sun T, Li C, et al. An overall and dose-response meta-analysis of red blood cell distribution width and CVD outcomes. Sci Rep. 2017;7:43420. Published 2017 Feb 24. [PubMed]
  2. “High RDW (≥15% variation, n = 6,050) compared to low (<12.5% n = 20,844) was strongly associated with mortality. Higher RDW was also associated with incident CAD, heart failure, peripheral vascular disease, atrial fibrillation, stroke, cancer, colorectal cancer, and especially leukemia.“ Pilling LC, Atkins JL, Kuchel GA, Ferrucci L, Melzer D. Red cell distribution width and common disease onsets in 240,477 healthy volunteers followed for up to 9 years. PLoS One. 2018;13(9):e0203504. Published 2018 Sep 13. [PubMed]
  3. “Median RDW values varied across studies from 13.2% to 14.6%. During 68,822 person-years of follow-up of 11,827 older adults with RDW measured, there was a graded increased risk of death associated with higher RDW values (p < .001).” Patel KV, Semba RD, Ferrucci L, et al. Red cell distribution width and mortality in older adults: a meta-analysis. J Gerontol A Biol Sci Med Sci. 2010;65(3):258–265. [PubMed]
  4. “…a strong, graded association of RDW with hsCRP and ESR independent of numerous confounding factors.” Lippi G, Targher G, Montagnana M, Salvagno GL, Zoppini G, Guidi GC. Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients. Arch Pathol Lab Med 2009;133:628–32. [PubMed]
  5. “RDW, which is recently considered as an inflammatory marker with a significant predictive value of mortality in diseased and healthy populations, is significantly higher in diabetic patients than healthy subjects and is particularly higher in uncontrolled glycemia.” Nada AM. Red cell distribution width in type 2 diabetic patients. Diabetes Metab Syndr Obes. 2015;8:525–533. Published 2015 Oct 30. [PubMed]
  6. “Even when analyses were restricted to nonanemic participants or to those in the reference range of RDW (11%-15%) without iron, folate, or vitamin B(12) deficiency, RDW remained strongly associated with mortality. Red blood cell distribution width is a widely available test that is a strong predictor of mortality in the general population of adults 45 years or older.” Patel KV, Ferrucci L, Ershler WB, Longo DL, Guralnik JM. Red blood cell distribution width and the risk of death in middle-aged and older adults. Arch Intern Med. 2009;169(5):515–523. [PubMed]
  7. Titcomb CP. Red Cell Distribution Width (RDW): An Underappreciated Marker for Increased Mortality. ON THE RISK Journal of The Academy of Life Underwriting. 2017;33(1):30-46. [Article] [Full Issue]

Corrected Reticulocyte Count (CRC)

• • Reticulocytes are immature red cells that lose their RNA a day or so after reaching the blood from the marrow.
  • A reticulocyte count provides an estimate of the rate of red blood cell production.
  • LabSmarts corrects the value entered for reticulocyte count and plots a corrected reticulocyte count (CRC) on a bar graph in the RBC Analysis section.
  • CRC = reticulocytes % x (HCT %/mean HCT %), mean HCT % is determined based on gender and age.
  1. “A very useful measurement in determining the cause of normocytic anemia is the reticulocyte count. Reticulocytes are newly formed red blood cells that have recently lost their nuclei but retain high levels of cytosolic mRNA dedicated to the synthesis of hemoglobin. In cases, prominently in hemolytic anemia, where there is a loss of red blood cells due to peripheral destruction of these cells, there is an increased synthesis in bone marrow of red blood cells and an early release of red blood cell precursors, especially reticulocytes.” McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017. p. 86.
  2. “Reticulocytes should rise in anaemia because of erythropoietin increase, and be higher the more severe the anaemia. This is particularly so when there has been time for erythroid hyperplasia to develop in the marrow as in chronic haemolysis. After an acute major haemorrhage there is an erythropoietin response in 6 hours, and the reticulocyte count rises within 2-3 days, reaches a maxiumum in 6-10 days and remains raised until the haemoglobin returns to the normal level. If the reticulocyte count is not raised in an anaemic patient, this suggests impaired marrow function or lack of erythropoietin stimulus.” Hoffbrand AV, Steensma DP. Hoffbrand’s Essential Haematology. 8th ed. Hoboken, NJ: Wiley; 2020.
  • Lab Min and Max
  1. “The normal percentage is 0.5-2.5%.” Hoffbrand AV, Steensma DP. Hoffbrand’s Essential Haematology. 8th ed. Hoboken, NJ: Wiley; 2020.
  2. “The normal reticulocyte count at birth ranges from 3% to 7% during the first 48 hours, during which time it rises slightly. After the second day, it falls rather rapidly to 1% to 3% by the seventh day of life.” McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017.
  3. “Typical Reference Interval: 0.5% – 1.5%“ McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017. p. e22.
  4. “The normal reticulocyte count for both the automated and new methylene blue methods is 1% with a range of 0.6%–2.0%.” Hillman RS, Ault KA, Leporrier M, Rinder HM. Hematology in Clinical Practice. 5th ed. New York: McGraw-Hill Medical; 2010.
  • Alarm Min and Max = 3 standard deviations from lab mean
  • Optimal Min and Max = 1 standard deviation from lab mean

Reticulocyte Production Index (RPI)

• • RPI corrects the CRC with respect to the proportion of reticulocytes present in a patient without anemia and the premature release of reticulocytes into the peripheral circulation. Therefore, RPI is a more meaningful expression of erythropoiesis.
  • LabSmarts uses RPI to help distinguish between iron insufficiency and blood loss as a possible root cause of suboptimal blood oxygen delivery.
  • The RPI is calculated by dividing the corrected reticulocyte count (CRC) by a correction factor that’s based on an estimated maturation time of reticulocytes in the blood.
  • See Reticulocyte production index in Wikipedia for the RPI formula and maturation correction table used in the formula.
  • Lab Min and Max
  1. “Bone marrow response to anemia may be appropriate (hyperproliferative), with an RPI over 3 generally indicating marrow red cell hyperproliferation; however, the anemia may be due to defective red blood cell production or marrow failure (hypoproliferative), which is generally indicated by an RPI less than 2.” McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017.
  2. “Optimal Marrow Response: Reticulocyte Production Index Greater Than Two: If the output of reticulocytes has exceeded two times normal, as determined by the absolute reticulocyte count, or RPI, it can be assumed that the marrow has reached an optimal response. The cause for the anemia is then acute blood loss or hemolysis. If blood loss cannot be proved, evidence that hemolysis is in fact present must be sought.” McPherson RA, Pincus MR. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 23rd ed. St. Louis, MO: Elsevier; 2017. p. 600.
  3. “Bone marrow response to anemia may be appropriate (hyperproliferative), with an RPI over 3 generally indicating marrow red cell hyperproliferation; however, the anemia may be due to defective red blood cell production or marrow failure (hypoproliferative), which is generally indicated by an RPI less than 2.” Hillman RS, Ault KA, Leporrier M, Rinder HM. Hematology in Clinical Practice. 5th ed. New York: McGraw-Hill Medical; 2010.