Calibration of the Periotron 8000® and 6000® by polynomial regression
This paper reports the detailed calibration of the new Periotron 8000® with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order poly...
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| Vydáno v: | Journal of periodontal research Ročník 34; číslo 2; s. 79 - 86 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Oxford, UK
Blackwell Publishing Ltd
01.02.1999
Blackwell |
| Témata: | |
| ISSN: | 0022-3484, 1600-0765 |
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| Abstract | This paper reports the detailed calibration of the new Periotron 8000® with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order polynomial regression equation (recommended by the manufacturer) provided better coefficients of determination (R2: 0.999) and root mean square errors (RMSE = 1.6) than either linear regression (R2: 0.986, RMSE = 10.9) or quadratic models (R2: 0.998, RMSE = 3.2). Data derived using the manufacturer's MLCONVERT software program lacked accuracy and incurred large errors for volumes > 0.5 μl. Calibrations performed on one day could be used with accuracy to derive volumes >0.1 μl collected on subsequent days, when using the same machine (s.d. for residuals plot=2.49 Periotron units), but this was not the case for different machines (s.d. = 9.57 Periotron units). Varying serum protein concentration by up to 500% had a negligible effect on calculated volumes above 0.1 μl. We conclude that the Periotron 8000® is at least as reliable a machine as the Periotron 6000®, and that the calibration lines for both machines are best described using 4th order polynomial regression equations and “look‐up” tables, rather than quadratic (Periotron 6000®) or the manufacturer's software (Periotron 8000®). Serum seems to be an acceptable GCF substitute for calibrations, which can be performed 1 day, and used on subsequent days for a given machine and for volumes above 0.1 μl. |
|---|---|
| AbstractList | This paper reports the detailed calibration of the new Periotron 8000® with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order polynomial regression equation (recommended by the manufacturer) provided better coefficients of determination (
R
2
: 0.999) and root mean square errors (RMSE = 1.6) than either linear regression (
R
2
: 0.986, RMSE = 10.9) or quadratic models (
R
2
: 0.998, RMSE = 3.2). Data derived using the manufacturer's MLCONVERT software program lacked accuracy and incurred large errors for volumes > 0.5 μl. Calibrations performed on one day could be used with accuracy to derive volumes >0.1 μl collected on subsequent days, when using the same machine (s.d. for residuals plot=2.49 Periotron units), but this was not the case for different machines (s.d. = 9.57 Periotron units). Varying serum protein concentration by up to 500% had a negligible effect on calculated volumes above 0.1 μl. We conclude that the Periotron 8000® is at least as reliable a machine as the Periotron 6000®, and that the calibration lines for both machines are best described using 4th order polynomial regression equations and “look‐up” tables, rather than quadratic (Periotron 6000®) or the manufacturer's software (Periotron 8000®). Serum seems to be an acceptable GCF substitute for calibrations, which can be performed 1 day, and used on subsequent days for a given machine and for volumes above 0.1 μl. This paper reports the detailed calibration of the new Periotron 8000 with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order polynomial regression equation (recommended by the manufacturer) provided better coefficients of determination (R2: 0.999) and root mean square errors (RMSE = 1.6) than either linear regression (R2: 0.986, RMSE = 10.9) or quadratic models (R2: 0.998, RMSE = 3.2). Data derived using the manufacturer's MLCONVERT software program lacked accuracy and incurred large errors for volumes > 0.5 microliter. Calibrations performed on one day could be used with accuracy to derive volumes > 0.1 microliter collected on subsequent days, when using the same machine (s.d. for residuals plot = 2.49 Periotron units), but this was not the case for different machines (s.d. = 9.57 Periotron units). Varying serum protein concentration by up to 500% had a negligible effect on calculated volumes above 0.1 microliter. We conclude that the Periotron 8000 is at least as reliable a machine as the Periotron 6000, and that the calibration lines for both machines are best described using 4th order polynomial regression equations and "look-up" tables, rather than quadratic (Periotron 6000) or the manufacturer's software (Periotron 8000). Serum seems to be an acceptable GCF substitute for calibrations, which can be performed 1 day, and used on subsequent days for a given machine and for volumes above 0.1 microliter.This paper reports the detailed calibration of the new Periotron 8000 with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order polynomial regression equation (recommended by the manufacturer) provided better coefficients of determination (R2: 0.999) and root mean square errors (RMSE = 1.6) than either linear regression (R2: 0.986, RMSE = 10.9) or quadratic models (R2: 0.998, RMSE = 3.2). Data derived using the manufacturer's MLCONVERT software program lacked accuracy and incurred large errors for volumes > 0.5 microliter. Calibrations performed on one day could be used with accuracy to derive volumes > 0.1 microliter collected on subsequent days, when using the same machine (s.d. for residuals plot = 2.49 Periotron units), but this was not the case for different machines (s.d. = 9.57 Periotron units). Varying serum protein concentration by up to 500% had a negligible effect on calculated volumes above 0.1 microliter. We conclude that the Periotron 8000 is at least as reliable a machine as the Periotron 6000, and that the calibration lines for both machines are best described using 4th order polynomial regression equations and "look-up" tables, rather than quadratic (Periotron 6000) or the manufacturer's software (Periotron 8000). Serum seems to be an acceptable GCF substitute for calibrations, which can be performed 1 day, and used on subsequent days for a given machine and for volumes above 0.1 microliter. This paper reports the detailed calibration of the new Periotron 8000® with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order polynomial regression equation (recommended by the manufacturer) provided better coefficients of determination (R2: 0.999) and root mean square errors (RMSE = 1.6) than either linear regression (R2: 0.986, RMSE = 10.9) or quadratic models (R2: 0.998, RMSE = 3.2). Data derived using the manufacturer's MLCONVERT software program lacked accuracy and incurred large errors for volumes > 0.5 μl. Calibrations performed on one day could be used with accuracy to derive volumes >0.1 μl collected on subsequent days, when using the same machine (s.d. for residuals plot=2.49 Periotron units), but this was not the case for different machines (s.d. = 9.57 Periotron units). Varying serum protein concentration by up to 500% had a negligible effect on calculated volumes above 0.1 μl. We conclude that the Periotron 8000® is at least as reliable a machine as the Periotron 6000®, and that the calibration lines for both machines are best described using 4th order polynomial regression equations and “look‐up” tables, rather than quadratic (Periotron 6000®) or the manufacturer's software (Periotron 8000®). Serum seems to be an acceptable GCF substitute for calibrations, which can be performed 1 day, and used on subsequent days for a given machine and for volumes above 0.1 μl. This paper reports the detailed calibration of the new Periotron 8000 with different fluids and uses the method of least squares to derive polynomial regression equations up to the 6th order, to investigate the most accurate descriptor of the resulting calibration lines. The use of a 4th order polynomial regression equation (recommended by the manufacturer) provided better coefficients of determination (R2: 0.999) and root mean square errors (RMSE = 1.6) than either linear regression (R2: 0.986, RMSE = 10.9) or quadratic models (R2: 0.998, RMSE = 3.2). Data derived using the manufacturer's MLCONVERT software program lacked accuracy and incurred large errors for volumes > 0.5 microliter. Calibrations performed on one day could be used with accuracy to derive volumes > 0.1 microliter collected on subsequent days, when using the same machine (s.d. for residuals plot = 2.49 Periotron units), but this was not the case for different machines (s.d. = 9.57 Periotron units). Varying serum protein concentration by up to 500% had a negligible effect on calculated volumes above 0.1 microliter. We conclude that the Periotron 8000 is at least as reliable a machine as the Periotron 6000, and that the calibration lines for both machines are best described using 4th order polynomial regression equations and "look-up" tables, rather than quadratic (Periotron 6000) or the manufacturer's software (Periotron 8000). Serum seems to be an acceptable GCF substitute for calibrations, which can be performed 1 day, and used on subsequent days for a given machine and for volumes above 0.1 microliter. |
| Author | Landini, G. Patel, N. C. Chapple, I. L. C. Ward, R. S. N. Griffiths, G. S. |
| Author_xml | – sequence: 1 givenname: I. L. C. surname: Chapple fullname: Chapple, I. L. C. organization: Oral Diseases Research Group, The University of Birmingham, School of Dentistry – sequence: 2 givenname: G. surname: Landini fullname: Landini, G. organization: Oral Diseases Research Group, The University of Birmingham, School of Dentistry – sequence: 3 givenname: G. S. surname: Griffiths fullname: Griffiths, G. S. organization: Department of Periodontology, The Eastman Dental institute, London, UK – sequence: 4 givenname: N. C. surname: Patel fullname: Patel, N. C. organization: Oral Diseases Research Group, The University of Birmingham, School of Dentistry – sequence: 5 givenname: R. S. N. surname: Ward fullname: Ward, R. S. N. organization: Department of Periodontology, The Eastman Dental institute, London, UK |
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| Cites_doi | 10.1111/j.1600-0765.1996.tb00513.x 10.1902/jop.1990.61.11.670 10.1111/j.1600-0765.1988.tb01024.x 10.1902/jop.1984.55.5.294 10.1111/j.1600-0765.1995.tb01255.x 10.1111/j.1600-0765.1984.tb00822.x 10.1111/j.1600-0765.1995.tb01264.x 10.1111/j.1600-051X.1984.tb01313.x 10.1111/j.1600-0765.1986.tb01436.x 10.1016/S0140-6736(86)90837-8 |
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| Keywords | Human Periodontal disease Equipment Stomatology Pathogenesis Technology Calibration equipment Exploration Early Diagnosis |
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| References | Van Der Bijl P, Dreyer WP, Grobler SR. The Periotron gingival crevicular fluid meter: an assessment of three different instruments. J Periodont Res 1986; 21: 39-44. Preshaw PM, Kelly PJ, Heasman PA. Quadratic calibration curves for the Periotron 6000®. J Periodont Res 1996; 31: 441-443. Bickel M, Cimasoni G. Reliability of volume measurements with the new Periotron® 6000. J Periodont Res 1984; 19: 313-316. Hinrichs JE, Bandt CL, Smith JA. Relative error (variability) associated with an improved instrument for measuring gingivai crevicular fluid. J Periodontol 1984; 2: 294-298. Medlicott NJ, Tucker IG, Rathbone MJ, Holborow DW. Determination of small sample volumes in the analysis of drugs at specific sites in the oral cavity. J Periodont Res 1995; 30: 144-146. Griffiths GS, Curtis MA, Wilton JMA. Selection of a filter paper with optimum properties for the collection of gingival crevicular fluid. J Periodont Res 1988; 23: 33-38. Hinrichs JE, Bandt CL, Smith JA, Golub LM. Comparisons of 3 systems for quantifying gingival crevicular fluid with respect to linearity and the effects of qualitative differences of the fluids. J Clin Periodontol 1984; 11: 652-661. Chapple ILC, Garner I, Moscrop H, Saxby MS, Matthews JB. Prediction and diagnosis of attachment loss by enhanced chemiluminescent assay of crevicular fluid alkaline phosphatase levels. J Clin Periodontol 1999; 3:(in press). Chapple ILC, Cross IA, Glenwright HD, Matthews JB. Calibration and reliability of the Periotron 6000® for individual gingival crevicular fluid samples. J Periodont Res 1995; 30: 73-79. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 8: 307-310. Stoller NH, Karras DC, Johnson LR. Reliability of crevicular fluid measurements taken in the presence of supragingival plaque. J Periodontol 1990; 61: 670-673. 1995; 30 1988; 23 1984; 19 1999; 3 1986; 8 1984; 2 1986; 21 1996; 31 1984; 11 1990; 61 e_1_2_1_6_2 e_1_2_1_7_2 e_1_2_1_4_2 e_1_2_1_5_2 e_1_2_1_2_2 e_1_2_1_11_2 e_1_2_1_3_2 Chapple ILC (e_1_2_1_12_2) 1999; 3 e_1_2_1_10_2 e_1_2_1_8_2 e_1_2_1_9_2 |
| References_xml | – reference: Preshaw PM, Kelly PJ, Heasman PA. Quadratic calibration curves for the Periotron 6000®. J Periodont Res 1996; 31: 441-443. – reference: Chapple ILC, Cross IA, Glenwright HD, Matthews JB. Calibration and reliability of the Periotron 6000® for individual gingival crevicular fluid samples. J Periodont Res 1995; 30: 73-79. – reference: Hinrichs JE, Bandt CL, Smith JA. Relative error (variability) associated with an improved instrument for measuring gingivai crevicular fluid. J Periodontol 1984; 2: 294-298. – reference: Van Der Bijl P, Dreyer WP, Grobler SR. The Periotron gingival crevicular fluid meter: an assessment of three different instruments. J Periodont Res 1986; 21: 39-44. – reference: Hinrichs JE, Bandt CL, Smith JA, Golub LM. Comparisons of 3 systems for quantifying gingival crevicular fluid with respect to linearity and the effects of qualitative differences of the fluids. J Clin Periodontol 1984; 11: 652-661. – reference: Chapple ILC, Garner I, Moscrop H, Saxby MS, Matthews JB. Prediction and diagnosis of attachment loss by enhanced chemiluminescent assay of crevicular fluid alkaline phosphatase levels. J Clin Periodontol 1999; 3:(in press). – reference: Stoller NH, Karras DC, Johnson LR. Reliability of crevicular fluid measurements taken in the presence of supragingival plaque. J Periodontol 1990; 61: 670-673. – reference: Griffiths GS, Curtis MA, Wilton JMA. Selection of a filter paper with optimum properties for the collection of gingival crevicular fluid. J Periodont Res 1988; 23: 33-38. – reference: Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 8: 307-310. – reference: Medlicott NJ, Tucker IG, Rathbone MJ, Holborow DW. Determination of small sample volumes in the analysis of drugs at specific sites in the oral cavity. J Periodont Res 1995; 30: 144-146. – reference: Bickel M, Cimasoni G. Reliability of volume measurements with the new Periotron® 6000. 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| Snippet | This paper reports the detailed calibration of the new Periotron 8000® with different fluids and uses the method of least squares to derive polynomial... This paper reports the detailed calibration of the new Periotron 8000 with different fluids and uses the method of least squares to derive polynomial... |
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| SubjectTerms | Biological and medical sciences Calibration Dental Equipment - standards Equipment Design GCF volume Gingival Crevicular Fluid Humans Investigative techniques, diagnostic techniques (general aspects) Least-Squares Analysis Medical sciences Miscellaneous. Technology Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques Periodontics - instrumentation Periotron 6000 Periotron 8000 polynomial regression reliability Reproducibility of Results |
| Title | Calibration of the Periotron 8000® and 6000® by polynomial regression |
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