Method for predicting salivary secretion volume

Abstract

To provide a method for quantitatively predicting a saliva secretion quantity.SOLUTION: Saliva pH of a subject 15 is acquired. The salvia pH of the subject 15 is applied to a regression model 10 acquired in advance with the salvia pH as an explanatory variable and with a saliva secretion quantity as an objective variable. This quantitatively predicts the salvia secretion quantity of the subject 15. Biological information 11 of the subject 15 is acquired in other manners. The biological information 11 of the subject 15 is applied to the regression model 10 acquired in advance with the biological information 11 of the same kind of this as an explanatory variable and the saliva secretion quantity as an objective variable. This quantitatively predicts the saliva secretion quantity of the subject. The biological information 11 is any of the salvia pH, salvia occult blood concentration and a salvia white blood cell count.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a method for predicting salivary secretion volume.

Background Art

[0002] Evaluating oral dryness, that is, measuring the amount of moisture in the oral cavity, is equivalent to measuring the amount of saliva in the oral cavity. The amount of saliva in the oral cavity varies depending on the supply amount, that is, the secretion amount, and the excretion amount. Since the excretion of saliva occurs due to evaporation by mouth breathing and various physiological phenomena such as bolus formation and swallowing during chewing, it is difficult to analyze the factors in evaluating oral dryness. Therefore, measuring the salivary secretion volume is the gold standard in evaluating oral dryness.

[0003] Oral dryness means that either a subjective feeling of oral dryness or an objective finding of oral dryness is recognized. Objective findings include a quantitative decrease and qualitative changes in saliva. In particular, the objective finding of a quantitative decrease in saliva is referred to as decreased salivary secretion.

[0004] As described in Non-Patent Document 1, the measurement of salivary secretion volume is classified into two types: measurement of resting salivary secretion volume and measurement of stimulated salivary secretion volume. The resting salivary secretion volume can be measured by the expectoration method. In the expectoration method, the amount of saliva secreted within a unit time is measured. The stimulated salivary secretion volume can be measured by the gum method or the Saxon method. In the Saxon method, the amount of saliva absorbed by chewing a standard gauze is measured. In the gum method, the saliva secreted by chewing gum is weighed. The Saxon method, the gum method, and the expectoration method are also adopted in the diagnostic criteria for Sjogren's syndrome.

[0005] As new evaluation methods for salivary secretion volume, a salivary wetness test, the Watt method, and clinical diagnostic criteria are used. Also, Patent Document 1 discloses a paper chromatography method. In the paper chromatography method, the salivary secretion volume is determined by the penetration rate of saliva into strip pieces made of paper or other materials.

Prior Art Documents

Patent Documents

[0006] [Patent Document 1] Japanese Patent No. 4141048 [Patent Document 2] Japanese Patent No. 5981350 [Patent Document 3] Japanese Patent No. 6117499 [Patent Document 4] Japanese Patent No. 4417841 [Non-Patent Document]

[0007] [Non-Patent Document 1] Yasuaki Kakinoki, “Disease Condition and Treatment of Dry Mouth.”, Annals of Japan Prosthodontic Society, Japan Prosthodontic Society, 2015, 7, p.136-141. [Non-Patent Document 2] Anne Marie Lynge Pedersen, Allan Bardow and Birgitte Nauntofte, “Salivary changes and dental caries as potential oral markers of autoimmune salivary gland dysfunction in primary Sjogren's syndrome.”, [online], 2005-03-01, BMC Clinical Pathology, [retrieved on 2020-10-28], 5, 4. Retrieved from <https: / / doi.org / 10.1186 / 1472-6890-5-4> [Non-Patent Document 3] Masae Kitakawa, Toshiyoshi Yanagisawa, Tomonori Shintani, Ikuko Ogawa, Hideaki Kurihara, “Examination of salivary secretion volume during stimulation, caries risk test items, and oral candidal count”, Journal of the Japanese Society for Oral Examination, Japanese Society for Oral Examination, 2013-03-30, 5, 1, p.31-37. [Non-Patent Document 4] Yoshio Nomura, Jiro Kita, Yukio Iwasan, Yozo Kobayashi, Tadashi Mihara, Shoji Uchida, Hiroo Hayashi, Hirohiro Kashiwada, Yoji Murayama, Ichiro Yokomizo, "Results of Applying Clinical Test pH Test Paper (Hema-Combistix) for Early Detection of Periodontal Diseases in Mass Examinations", Journal of the Japanese Society of Periodontology, 1973, 15, 2, pp. 106-111.

Summary of the Invention

Problems to be Solved by the Invention

[0008] In measuring either the resting salivary flow rate or the stimulated salivary flow rate, it takes time to collect saliva. Measuring the resting salivary flow rate by the expectoration method takes 15 minutes. Measuring the stimulated salivary flow rate by the Saxon method takes 2 minutes. And during these measurement times, it is necessary to have the subject himself / herself perform the exact examination procedure. Also, the mental state during saliva collection, for example, being nervous, affects the measured value. Therefore, it is not suitable for use in mass health examinations or as a test commonly used in the clinical setting.

[0009] Therefore, the inventors considered that it was necessary to indirectly predict these salivary flow rates from an index that could obtain a measured value simply and in a short time. The inventors focused on pH.

[0010] Patent Document 2 discloses a method for measuring salivary pH with a pH indicator. Patent Document 3 discloses a method for measuring salivary pH with a pH meter. As described in these documents, the measurement of salivary pH, unlike the measurement of salivary flow rate, can be easily performed in a short time using chemical means or mechanical means. In addition, a pH indicator is added to the paper or other materials for measuring the penetration rate of saliva described in Patent Document 1. However, no particular correlation between the penetration rate and pH is claimed.

[0011] Turning to the relationship with diseases, Table 4 on page 6 of Non-Patent Document 2 discloses that the salivary pH is lower in patients with Sjögren's syndrome compared to healthy subjects. The salivary secretion volume is low in patients with Sjögren's syndrome. As described in Non-Patent Document 2, if the population is pre-divided into healthy subjects and patients with Sjögren's syndrome, it can be qualitatively predicted that the salivary pH and the salivary secretion volume will decrease in patients with Sjögren's syndrome.

[0012] The abstract of Non-Patent Document 3 discloses that a correlation is found between the salivary secretion volume during stimulation and the salivary pH in a population of patients who underwent caries examination and oral Candida (OC) examination. The population includes patients with Sjögren's syndrome. As described in Non-Patent Document 3, when the patients to be examined orally are used as the population, a qualitative correlation is found between the decrease in salivary pH and the decrease in salivary secretion volume.

[0013] The Abstract of Non-Patent Document 4 discloses that there is a correlation between the salivary pH at rest and the complaint of dry mouth (feels dry mouth) in a population of the elderly in a long-term care facility. 76.5% of the elderly in the population are receiving medication. As described in Non-Patent Document 4, when the elderly who are likely to be receiving medication are used as the population, a correlation is found between the decrease in salivary pH and the increase in the complaint of dry mouth.

[0014] Based on the above, an object of the present invention is to provide a method for quantitatively predicting the salivary secretion volume.

Means for Solving the Problems

[0015] <1> Obtaining the salivary pH of a subject, By fitting the salivary pH of the subject into a regression model previously obtained with the salivary pH as an explanatory variable and the salivary secretion volume as an objective variable, quantitatively predicting the salivary secretion volume of the subject, Method.

[0016] <2>The regression model is obtained in advance by multiple regression analysis including at least one of the items of salivary occult blood concentration, number of salivary white blood cells, salivary ammonia concentration, age, gender, current number of teeth, presence or absence of disease, complaint of dry mouth, complaint of sticky mouth, complaint of chewing difficulty, complaint of periodontal disease symptoms, complaint of dry skin, and salivary weight as the explanatory variables. Further obtain the same additional items as the items of the explanatory variables from the subject, and fit the salivary pH and the additional items of the subject to the regression model to predict the salivary secretion volume of the subject. The method according to <1>.

[0017] <3>In the regression model, the salivary secretion volume is the resting salivary secretion volume. The regression model is obtained in advance by multiple regression analysis including the stimulated salivary secretion volume as the explanatory variable. Further obtain the stimulated salivary secretion volume of the subject, and fit the salivary pH and the stimulated salivary secretion volume of the subject to the regression model to predict the resting salivary secretion volume of the subject. The method according to <1> or <2>.

[0018] <4>In the regression model, the salivary pH is the pH of the rinsing saliva. Fit the pH of the rinsing saliva of the subject as the salivary pH of the subject to the regression model to predict the salivary secretion volume of the subject. The method according to <1>.

[0019] <5>A system for providing information necessary for determining decreased salivary secretion, Performing at least one of receiving test information consisting of the salivary pH of the patient itself and receiving test information reflecting the salivary pH of the patient and calculating the salivary pH of the patient from the test information. Quantitatively predict the salivary secretion volume of the patient by fitting the salivary pH of the patient to a regression model obtained in advance with the salivary pH as the explanatory variable and the salivary secretion volume as the objective variable. The result information is presented to at least one of the examining doctor of the examinee, the examinee or his / her assistant (hereinafter referred to as the examinee, etc.). The result information is at least one of the predicted value of the saliva secretion amount itself and the qualitative determination indicating whether or not the predicted value of the saliva secretion amount is below the threshold of decreased saliva secretion. System.

[0020] <6> Receive the color information of the color development of the pH test paper wetted with the saliva or mouthwash spit of the examinee as the inspection information from the terminal of the examinee, etc. via the network. Send the result information to at least one of the terminal of the examining doctor, the terminal of the examinee, etc. and other terminals via the network. Present the result information by displaying it on the terminal that has received the result information. The system according to <5>.

[0021] <7> Cause the terminal to receive the result information from the server via the network. Further cause the terminal to display the result information. Yes. An application, The predicted value of the saliva secretion amount of the examinee is predicted by the server by fitting the saliva pH of the examinee to a regression model that was previously obtained with the saliva pH as the explanatory variable and the saliva secretion amount as the objective variable and that the server has. The saliva pH of the examinee is calculated by the server from the color information. Application.

[0022] <8> Obtain any biological information of the saliva occult blood concentration and the saliva white blood cell count of the subject. Quantitatively predict the saliva secretion amount of the subject by fitting the biological information of the subject to a regression model that was previously obtained with the same type of biological information as the explanatory variable and the saliva secretion amount as the objective variable. Method.

Advantages of the Invention

[0023] The present invention can provide a method for quantitatively predicting the saliva secretion amount.

Brief Description of the Drawings

[0024]

Figure 1

Figure 2

Figure 3

Modes for Carrying Out the Invention

[0025] <Prediction of Saliva Secretion Amount>

[0026] As shown in FIG. 1, by fitting the saliva pH information 12 of the subject 15 to the regression model 10, a quantitative prediction 13 of the saliva secretion amount of the subject 15 is obtained. In one aspect, the subject 15 is a patient who undergoes measurement of the saliva secretion amount. In one aspect, although there is no limitation on whether the subject 15 takes medicine, it is preferably not taking medicine. In one aspect, the prediction 13 of the saliva secretion amount is the resting saliva secretion amount or the stimulated saliva secretion amount.

[0027] In one aspect shown in FIG. 1, the fitting of the information 12 to the regression model 10 is performed by automatic calculation, that is, by a computer. In one aspect, the computer consists of a dedicated LSI, and in other aspects, it consists of a programmable circuit or a general-purpose CPU. Also, a quick reference table consisting of a series of saliva pH and a series of saliva secretion amounts may be created from the regression model 10, and the prediction 13 may be obtained by fitting the information 12 to such a quick reference table.

[0028] In obtaining prediction 13 as shown in FIG. 1, information 12 on the saliva pH of subject 15 is acquired. In one aspect, the acquisition of information 12 on the saliva pH is performed by measuring the pH of saliva specimen 11 collected from subject 15. The collection of saliva specimen 11 is performed by having subject 15 rinse their mouth with a mouthwash and then spit out the mouthwash spit containing saliva. The mouthwash is not particularly limited as long as it does not stimulate the salivary glands during mouth rinsing and is unlikely to affect the pH of saliva. Water is preferred as the mouthwash. In one aspect, the volume of the mouthwash when having subject 15 rinse their mouth is 1 to 10 mL, preferably 1.5 to 6 mL, and more preferably 2 to 4 mL.

[0029] In another aspect shown in FIG. 1, the acquisition of information 12 is performed by receiving information 12 that has been obtained in advance. Information 12 may be obtained by listening, received in writing, or received electronically.

[0030] One aspect of measuring the saliva pH is the pH colorimetric method. In one aspect, the pH colorimetric method is the pH test paper method. A pH test paper is a material in which a pH indicator is impregnated on a carrier. In one aspect, the carrier is a stick-shaped piece of paper. The pH test paper is wetted with the mouthwash spit. The pH test paper may also be wetted directly with saliva. The pH indicator reacts with saliva or the mouthwash spit to produce a color change. In one aspect, the color change of the pH test paper is measured by the two-wavelength reflectance photometry method described in Patent Document 2.

[0031] In one aspect, a pH indicator having a color change range in the pH range of 2 - 9 is used. One aspect of the pH indicator is any one of bromocresol green, bromocresol blue, bromoxylenol blue, methyl red, and bromothymol blue.

[0032] According to JIS K8001 2009, the color change range of bromocresol green is pH 3.8 - 5.4. The color change range of bromocresol blue is pH 3.0 - 4.6. The color change range of methyl red is pH 4.2 - 6.2. The color change range of bromothymol blue is pH 6.0 - 7.6.

[0033] The color change range of bromoxylenol blue is pH 6.0 - 7.6 (“Bromoxylenol Blue”, [online], Reagents - FUJIFILM Wako Pure Chemical Corporation (fujifilm.com), [searched on December 8, 2020], Internet <URL:https: / / labchem - wako.fujifilm.com / jp / product / detail / W01W0232 - 3812.html>).

[0034] In one aspect, a plurality of pH indicators are mixed with each other to form a composite reagent. One aspect of the composite reagent is a combination of bromocresol green and bromoxylenol blue. The concentration of bromocresol green in the pH indicator for immersing the carrier is preferably 0.1 - 0.6 mM, more preferably 0.1 - 0.4 mM. The concentration of bromoxylenol blue is preferably 0.6 - 2 mM, more preferably 0.8 - 1.8 mM. The time required for the color reaction is 30 seconds to 5 minutes in one aspect. In one example, with a reaction time of 60 seconds, the color development is measured with a measurement wavelength of 635 nm and a reference wavelength of 760 nm. Another aspect of the composite reagent is a combination of methyl red and bromothymol blue described in Non - Patent Document 4. The color change range of methyl red is pH 4.2 - 6.2. The color change range of bromothymol blue is pH 6.0 - 7.6.

[0035] The pH of saliva at rest is 5.7 - 7.1, and the pH of saliva during stimulation is 7.8 or less (Saliva, Teeth and Oral Health, 3rd Edition, Medical, Dental and Pharmaceutical Publishing, June 2008). In one aspect, by combining pH indicators, the range of saliva pH can be covered without limit.

[0036] Another aspect of measuring saliva pH is the electrode method. In one aspect, the pH measurement method of Japanese Industrial Standard JIS Z8802 is used. In this pH measurement method, a pH meter consisting of a detection unit equipped with a glass electrode, a reference electrode, and a temperature - compensating temperature - sensing element is used. The pH is obtained from the electromotive force measured by the glass electrode. In another aspect of the electrode method, pH is measured with an ion - sensitive field - effect transistor (ISFET) electrode.

[0037] In obtaining the prediction 13 as shown in FIG. 1, a regression model 10 is prepared in advance. In one aspect, a simple regression analysis is performed with the salivary pH as an explanatory variable and further with the salivary secretion volume as an objective variable. In other aspects, a multiple regression analysis is performed with the salivary pH and other items as explanatory variables and further with the salivary secretion volume as an objective variable. A method that does not use the salivary pH will be described later.

[0038] As shown in FIG. 1, the regression model 10 is obtained from the specimens 17 included in the set population 16 that has been set. Although not limited to whether the persons included in the population 16 are taking medicine or not, it is preferable that they are not taking medicine. In one aspect, the population 16 includes persons who are not taking medicine. That is, the specimens 17 include persons who are not taking medicine when obtaining the salivary pH and the salivary secretion volume. It is not necessary to exclude persons who are taking medicine when obtaining these from the specimens 17.

[0039] In one aspect shown in FIG. 1, the population 16 consists of persons who are not taking medicine. That is, the specimens 17 included in the population 16 consist of persons who are not taking medicine when obtaining the salivary pH and the salivary secretion volume. Persons who are taking medicine when obtaining these are excluded from the specimens 17. The subjects 15 included in the population 16 are not taking medicine during the test.

[0040] In one aspect shown in FIG. 1, the salivary pH as an explanatory variable is the pH of the mouthwash spit. The saliva specimen 11 is in the form of mouthwash spit. The pH information 12 of the mouthwash spit of the subject 15 is fitted into the regression model 10.

[0041] In one aspect shown in FIG. 1, the specimens 17 are persons other than the subject 15 who is to receive the prediction. The regression model 10 is obtained using the specimens 17 that do not include the subject 15. Then, the prediction 13 of the salivary secretion volume of the subject 15 is calculated by applying the regression model 10 to the salivary pH information 12 of the subject 15.

[0042] In an embodiment different from the embodiment shown in FIG. 1, the specimen 17 overlaps with the subject 15 to be predicted. The regression model 10 is obtained using the specimen 17 that includes the subject 15. Then, the prediction 13 of the saliva secretion amount of the subject 15 is calculated by applying the regression model 10 to the information 12 of the saliva pH of the subject 15.

[0043] <Multiple regression analysis and prediction>

[0044] In one embodiment, the saliva secretion amount is predicted from the saliva pH and other items. In one embodiment, as other items, at least one of the items of saliva occult blood concentration, saliva white blood cell count, saliva ammonia concentration, age, gender, current number of teeth, presence or absence of disease, oral dryness complaint, oral stickiness complaint, chewing difficulty complaint, periodontal disease symptom complaint, and skin dryness complaint is used.

[0045] In one embodiment, the "disease" related to the "presence or absence of disease" is a disease being treated in the subject or specimen. In one embodiment, the "presence or absence of disease being treated" represents the presence or absence of treatment being applied to the disease at that time. In one embodiment, the "disease" is a chronic disease. In one embodiment, the "disease" is at least one of a brain disease, a heart disease, a gastrointestinal disease (excluding temporary gastroenteritis and diarrhea), a liver disease, a kidney disease, a bone and joint disease (including osteoporosis and fractures), a nasal disease (including chronic rhinitis and hay fever), atopic dermatitis, Sjogren's syndrome, bronchial asthma, diabetes, hypertension, dyslipidemia (including cholesterol abnormalities and triglyceride abnormalities), urinary tract stones (including kidney stones and ureteral stones), dementia, and other chronic diseases. In one embodiment, the "treatment" is the application of medicine to the disease. In one embodiment, the "medicine" is a prescription drug or an OTC (Over The Counter) drug. In one embodiment, the "disease" is a disease that is receiving medicine application after undergoing surgical treatment for the disease site. In one embodiment, the "presence or absence of disease" does not include the presence or absence of "oral dryness complaint, oral stickiness complaint, chewing difficulty complaint, periodontal disease symptom complaint, and skin dryness complaint".

[0046] In one aspect, the "disease" related to "presence or absence of disease" is a disease that requires treatment but is before the start of treatment or during follow-up observation. In one aspect, the "disease" related to "presence or absence of disease" does not include a disease that has already completed treatment and been cured. In one aspect, the "disease" related to "presence or absence of disease" includes a disease that has already completed treatment and been cured but is applying medicine to prevent recurrence. In other embodiments, "presence or absence of disease" is interpreted in the same manner as above.

[0047] Note that the above uses salivary pH as an item necessary for prediction. Methods that do not use salivary pH according to other aspects will be described later.

[0048] Values representing the characteristics related to the selected items are obtained from the specimen. In one aspect, when obtaining these items, those who are taking medicine are excluded from the specimen. Multiple regression analysis is performed by including the values obtained in addition to the salivary pH as explanatory variables. Furthermore, the values of other items may be included as explanatory variables.

[0049] Based on the obtained regression model, the salivary secretion volume of the subject is predicted. Values representing the characteristics related to the same items as those selected as the above explanatory variables are obtained from the subject. For the regression model obtained as described above, the salivary pH and other characteristics of the subject are fitted. Methods that do not use salivary pH will be described later.

[0050] In one aspect, the acquisition of values from the specimen and the acquisition of values from the subject are performed as follows. In one aspect, at least any one of the salivary occult blood concentration, the number of salivary white blood cells, and the salivary ammonia concentration is measured. In one aspect, at least any one of the age, gender, current number of teeth, and presence or absence of disease of the specimen is obtained. In one aspect, the intensity or presence or absence of at least any one of the main complaints of dry mouth, sticky mouth, difficulty chewing, periodontal disease symptoms, and dry skin is obtained.

[0051] In one aspect, the measurement of at least any one of the salivary occult blood concentration, the number of salivary white blood cells, and the salivary ammonia concentration is performed by the test paper method. In one aspect, in the test paper method, the measurement is performed by two-wavelength reflectance photometry.

[0052] In one aspect of measuring the salivary occult blood concentration, the test strip method is an enzymatic method. In one aspect, the enzymatic method is a hemoglobin contact activity method. It may be carried out as described in Patent Document 2. Another aspect of measuring the salivary occult blood concentration is a method using an immune reaction. One aspect thereof is a method using an antigen-antibody reaction between hemoglobin and an anti-human hemoglobin antibody. One aspect thereof is any one of radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescence immunoassay, immunoturbidimetry, latex agglutination method, hemagglutination method, and immunochromatography method.

[0053] In one aspect of measuring the salivary white blood cell count, the test strip method is an enzymatic method. In one aspect, the enzymatic method utilizes the color development of an alcohol component generated by the hydrolysis of an ester compound by leukocyte esterase. It may be carried out as described in Patent Document 2. Another aspect of measuring the white blood cell count is immunonephelometry. One aspect of immunonephelometry is a latex agglutination immunoassay using an antibody against leukocyte elastase.

[0054] In one aspect of measuring the salivary ammonia concentration, the test strip method is a pH color development method. In one aspect, the pH color development method utilizes the microdiffusion method. In one aspect, in the microdiffusion method, ammonia is volatilized under alkaline conditions, and the volatilized ammonia is trapped by a carrier containing a pH indicator, and detected by the color change of the pH indicator that has reacted with ammonia. It may be carried out as described in Patent Document 2. Another aspect of measuring the salivary ammonia concentration is an enzymatic method. One aspect of the enzymatic method is either a method using glutamic acid synthase or a method using various dehydrogenases.

[0055] In one aspect, the intensity or presence of at least any one of the main complaints of oral dryness, mouth stickiness, chewing difficulty, periodontal disease symptoms, and skin dryness is obtained by a questionnaire to the test participants who constitute the sample. In one aspect, the intensity or presence of periodontal disease symptoms is investigated based on the observation of the state of gingival crevicular fluid.

[0056] In one aspect, the intensity or presence of the complaint of oral dryness is obtained by the VAS (Visual Analog Scale) method.

[0057] In other aspects, the resting salivary secretion volume is predicted from the salivary pH and the salivary secretion volume during stimulation. The regression model used for this is obtained in advance by multiple regression analysis. The salivary pH, the salivary secretion volume during stimulation, and the resting salivary secretion volume are obtained from a specimen. Multiple regression analysis is performed with the salivary pH and the salivary secretion volume during stimulation included as explanatory variables. Other items may also be included as explanatory variables. The salivary secretion volume as the objective variable is the resting salivary secretion volume.

[0058] Based on the regression model, the salivary secretion volume of the subject is predicted. The salivary pH and the salivary secretion volume during stimulation of the subject are measured. By fitting these measured values of the subject to the regression model obtained as described above, a predicted value of the resting salivary secretion volume is obtained.

[0059] In one aspect, the acquisition of values from a specimen and the acquisition of values from a subject are performed as follows. In one aspect of measuring the salivary weight during stimulation, the Saxon method, that is, the gauze method, is used. In other aspects, the gum method is used.

Example

[0060] <Specimen and Measurement>

[0061] A group of 68 people including 55 people who were not taking prescription drugs and 13 people who were taking prescription drugs was used as a specimen. Hereinafter, these people are referred to as participants.

[0062] Each participant was asked to fill out a questionnaire in advance. The questionnaire sought answers regarding age, gender, and the current number of teeth. It also sought the presence or absence of diseases during treatment, oral dryness, sticky mouth, chewing difficulty, periodontal disease symptoms, and the presence or absence of complaints of skin dryness.

[0063] Next, the Visual Analog Scale (VAS) method was used to measure the intensity of the participants' complaints of oral dryness. A 10-cm straight line with a scale of 0 to 100 scores was used as the VAS scale. The left end of the scale represented a state where no dryness was felt at all, and the right end represented a state where dryness was felt very strongly. It was assumed that the higher the score, the higher the dryness level.

[0064] Next, the participants were acclimated by having them spend 10 minutes under the conditions of a temperature of 23 ± 3°C and a humidity of 40 ± 10%.

[0065] Next, the oral moisture content of the participants was measured 5 times using the oral moisture meter Mukas (trademark, Life Co., Ltd.). This device is equipped with a capacitance-type sensor described in Patent Document 4.

[0066] Next, the mouthwash discharge fluid of the participants was collected. The participants rinsed their mouths with 3 ml of sterilized distilled water for 10 seconds and then spat it out into a dedicated container. Using the multi-item and short-time saliva test system SMT (Salivary Multi Test, trademark, Lion Dental Materials) with the discharged fluid as the specimen, the pH, occult blood concentration, white blood cell count, and ammonia concentration of the saliva were measured. One drop of the discharged fluid was dropped onto each individual test paper for acidity, occult blood, white blood cells, and ammonia using a dropper. The pH test paper for acidity is a type of pH test paper. The individual test papers were mechanically measured using the SMT.

[0067] Furthermore, using the mouthwash discharge fluid as the specimen, its pH was measured using a pH electrode, LAQUATwin pH-33B (trademark, Horiba, Ltd.). The tests using the SMT and the pH electrode were each performed twice, and the average value of each was obtained. Regression analysis was performed based on each average value.

[0068] Next, the resting saliva secretion volume was measured by the spitting method. The participants were in a resting state for 15 minutes. During this period, the participants spat the saliva into a conical tube without swallowing it. By measuring the weight of the conical tube and subtracting the weight of the empty conical tube measured in advance, the resting saliva secretion volume was obtained.

[0069] Next, the amount of saliva secreted during stimulation was measured by the Saxon method. The participants chewed medical gauze and sequentially spat out saliva into a conical tube. After 2 minutes, the gauze together with the saliva accumulated in the oral cavity was spat out into the conical tube. The weight of the conical tube was measured, and the weight of the gauze before chewing was subtracted from that weight to obtain the amount of saliva secreted during stimulation.

[0070] <Regression analysis of resting saliva secretion volume>

[0071] Regression analysis was performed based on the measured values of 68 participants. Also, regression analysis was performed based on the measured values of 55 participants who were not taking prescription drugs. Only the results of the regression analysis for the 68 participants, including both those not taking prescription drugs and those taking prescription drugs, are shown below. Note that for both the regression analysis results of all 68 participants and the regression analysis results of the 55 participants not taking prescription drugs, the correlation between the explanatory variables centered on saliva pH and the objective variable consisting of the saliva secretion volume was significant.

[0072] The analysis was carried out using the software "R" (version 3.5.2, CRAN). The prediction accuracy of the regression analysis was represented by the multiple correlation coefficient R. The significance level was 5% two-sided, and the confidence interval was 95% two-sided. The resting saliva secretion volume was set as the common objective variable. The explanatory variables were classified into the following groups (A) to (C). Since gender is a qualitative variable, it was treated as a dummy variable.

[0073] (M) Oral moisture content (A) Saliva pH measured by the pH test paper method (E) Saliva pH measured by the electrode method (B) Saliva occult blood concentration · Saliva white blood cell count (C) Ammonia concentration (D) Questionnaire results (S) Amount of saliva secreted during stimulation

[0074] Simple regression analysis was performed using each item included in (M), (A), (E), and (B) as explanatory variables. It is shown in Table 1.

[0075]

Table 1

[0076] The regression model obtained by simple regression analysis using any one of salivary pH, salivary occult blood concentration, and the number of salivary white blood cells as an explanatory variable was found to be useful for predicting the resting salivary secretion volume. It was found that both the pH test paper method and the electrode method for measuring salivary pH were useful for predicting the resting salivary secretion volume. The correlation between salivary pH and the resting salivary secretion volume was stronger than the correlation between oral moisture content and the resting salivary secretion volume.

[0077] Multiple regression analysis was performed by further adding each item included in (B) and (C) as an explanatory variable to the explanatory variable (A). Multiple regression analysis was performed by further adding all three items included in (B) and (C) as an explanatory variable to the explanatory variable (A). As shown in Table 2.

[0078]

Table 2

[0079] The regression model obtained by multiple regression analysis using salivary pH and at least any one of salivary occult blood concentration, the number of salivary white blood cells, and salivary ammonia concentration as explanatory variables was found to be useful for predicting the resting salivary secretion volume.

[0080] Multiple regression analysis was performed with each item included in the explanatory variable (B) as the following explanatory variable 1 and explanatory variable 2. As shown in Table 3.

[0081]

Table 3

[0082] The regression model obtained by multiple regression analysis using the two of salivary occult blood concentration and the number of salivary white blood cells as explanatory variables was found to be useful for predicting the resting salivary secretion volume.

[0083] For the explanatory variable (A), each item included in (D) and (S) was further added as an explanatory variable, and multiple regression analysis was performed. Also, for the explanatory variable (A), all 13 items included in (B), (C), (D) and (S) were further added as explanatory variables, and multiple regression analysis was performed. Also, for the explanatory variable (A), all 12 items included in (B), (C) and (D) were further added as explanatory variables, and multiple regression analysis was performed. Shown in Table 4.

[0084]

Table 4

[0085] The regression model obtained by multiple regression analysis with salivary pH, age, gender, current number of teeth, presence or absence of disease under treatment, oral dryness complaint, mouth stickiness complaint, chewing difficulty complaint, periodontal disease symptom complaint, skin dryness complaint, and at least one of the low salivary secretion volume during stimulation as explanatory variables was found to be useful for predicting the resting salivary secretion volume. Also, when salivary occult blood concentration, salivary white blood cell count, and salivary ammonia concentration were added as explanatory variables, and when salivary secretion volume during stimulation was further added as an explanatory variable, the obtained regression models were both found to be useful for predicting the resting salivary secretion volume.

[0086] <Regression analysis of salivary secretion volume during stimulation>

[0087] Regression analysis was performed in the same manner as the regression analysis of the resting salivary secretion volume, with the salivary secretion volume during stimulation as the common objective variable.

[0088] (M), (A), (E) and each item included in (B) were used as explanatory variables for simple regression analysis. Also, all 13 items included in (A), (B), (C) and (D) were used as explanatory variables for multiple regression analysis. Shown in Table 5.

[0089]

Table 5

[0090] The regression model obtained by simple regression analysis using any one of the salivary pH, salivary occult blood concentration, and the number of salivary white blood cells as an explanatory variable was found to be useful for predicting the salivary secretion volume during stimulation. The measurement methods of salivary pH, both the pH test paper method and the electrode method, were found to be useful for predicting the salivary secretion volume during stimulation. The correlation between salivary pH and the salivary secretion volume during stimulation was stronger than the correlation between the oral moisture content and the salivary secretion volume during stimulation.

[0091] The regression model obtained by multiple regression analysis with 13 items added to the salivary pH, namely the salivary occult blood concentration, the number of salivary white blood cells, the salivary ammonia concentration, age, gender, the number of current teeth, the presence or absence of diseases under treatment, the complaint of oral dryness, the complaint of sticky mouth, the complaint of chewing difficulty, the complaint of periodontal disease symptoms, and the complaint of skin dryness, as explanatory variables was found to be useful for predicting the salivary secretion volume during stimulation.

[0092] <Application Example: Determination of Reduced Salivary Secretion>

[0093] In one aspect, a qualitative determination is made as to whether or not the predicted value of the salivary secretion volume is below the oral dryness threshold. When the resting salivary secretion volume predicted based on the salivary pH and / or other items of the subject is less than 1.5 g / 15 minutes, it is determined that the subject is highly likely to actually suffer from reduced salivary secretion. In another aspect, when the predicted value of the salivary weight during stimulation (Saxon method) predicted based on the salivary pH of the subject is less than 2.0 g / 2 minutes, it is determined that the subject is highly likely to actually suffer from reduced salivary secretion. In another aspect, when the predicted value of the salivary weight during stimulation (gum method) predicted based on the salivary pH of the subject is less than 10 mL / 10 minutes, it is determined that the subject is highly likely to actually suffer from reduced salivary secretion. Thus, it is possible to determine the possibility of actually suffering from reduced salivary secretion based on the prediction of the salivary secretion volume. The determination result is useful in the form of medical treatment centered on the treatment for the restoration of tooth morphology.

[0094] Regarding the prediction of the above-mentioned saliva secretion volume, the test itself that the subject undergoes is simple, and the work of the subject himself / herself is completed in a short time. Therefore, it is easy to operate as a test commonly used in mass health examinations and at the medical treatment site. For this reason, the method of this embodiment is also useful in the form of medical treatment for maintaining, recovering, and coordinating oral functions. That is, it is useful for a large number of people other than those at risk such as those undergoing head and neck cancer treatment, smokers, diabetes patients, Sjogren's syndrome patients, dental caries patients, and oral candidiasis patients.

[0095] <Application Example: System>

[0096] Figure 2 is a block diagram showing a system that provides information necessary for determining a decrease in saliva secretion. The system mainly consists of a terminal 20 in a medical institution 19. In one aspect, the medical institution 19 is a dental hospital. The terminal 20 is connected to a server 30 in an information institution 29 via a network.

[0097] When using the system, test information is obtained in the test 21 performed in the medical institution 19 shown in Figure 2. In the test 21, the rinsing spit 22 of the examinee Pt is collected. Saliva may be collected instead of the rinsing spit 22. The pH of the rinsing spit 22 is obtained by the pH test paper method or the electrode method. The pH of the rinsing spit 22 reflects the saliva pH. For convenience, the pH of the rinsing spit 22 is hereinafter referred to as the saliva pH. The pH of the rinsing spit 22 reflects the saliva pH. The saliva pH is input into the terminal 20 as test information.

[0098] In an aspect different from the aspect shown in Figure 2, the terminal 20 is connected to a measuring device. The measuring device may be the device described in Patent Document 2. The measuring device automatically inputs the saliva pH as test information into the terminal 20 according to the request of the terminal 20. In other aspects, the measuring device is an integrated device with the terminal 20. In one aspect, the measuring device reads the change in the color tone of the pH test paper. In other aspects, the measuring device performs pH measurement by the electrode method described later. In other aspects, the measuring device performs both reading the change in the color tone of the pH test paper and pH measurement by the electrode method.

[0099] In inspection 21 shown in FIG. 2, instead of the mouthwash discharge 22, the pH on the oral mucosa 23 may be directly measured. As a method of direct measurement, there are a method of placing pH test paper directly on the mucosa, a method of measuring with a portable pH meter in contact with the mucosa as one aspect of the electrode method, and the like. In one aspect, the portable pH meter is LAQUAtwin (trademark, manufactured by Horiba).

[0100] As shown in FIG. 2, the terminal 20 receives inspection information. The terminal 20 includes a processing unit 25. The processing unit 25 substitutes the inspection information, that is, the saliva pH, into the regression model. The regression model has the saliva pH and, if necessary, other items as explanatory variables, and the saliva secretion amount as the target variable, which has been obtained in advance. A system that uses a regression model that does not have the saliva pH as an explanatory variable will be described later. The processing unit 25 stores the regression model in advance. The processing unit 25 loads the regression model into the memory. The server 30 may provide the regression model to the terminal 20. The processing unit 25 quantitatively predicts the saliva secretion amount of the examinee Pt.

[0101] Those who manage the regression model may improve the regression model by further collecting data including the saliva pH. The server 30 stores the improved regression model as a new version or overwrites the past version. The terminal 20 receives the updated version of the regression model from the server 30.

[0102] The terminal 20 shown in FIG. 2 calculates the test result of saliva secretion reduction from the predicted value of the saliva secretion amount in accordance with the above-described method for determining saliva secretion reduction. The terminal 20 presents the result information 26 including the test result of saliva secretion reduction to the diagnosing doctor Dc. In another aspect, the result information 26 includes the predicted value of the saliva secretion amount itself. In one aspect, the diagnosing doctor Dc is a dentist. The diagnosing doctor Dc diagnoses the examinee Pt based on the test result of saliva secretion reduction. The diagnosing doctor Dc treats or provides health guidance to the examinee Pt based on the diagnosis. In another aspect, the terminal 20 presents the result information 26 to the examinee Pt or his / her assistant.

[0103] The examinee Pt, or his / her assistant or the diagnostician Dc inputs the answers to the above-mentioned questionnaire into the terminal 20. The processing unit 25 receives the answers to the questionnaire. The processing unit 25 performs multiple regression analysis by fitting the saliva pH and the answers to the questionnaire into the regression model.

[0104] As shown in FIG. 2, the terminal 20 sends a maintenance request for the consumables 27 required for the examination 21 to the information institution 29 via the network. The information institution 29 sends the consumables 27 to the medical institution 19 in response to the maintenance request.

[0105] <Application Example: Program>

[0106] The terminal 20 shown in FIG. 2 is a computer that operates according to a program. The program provides information necessary for the determination of decreased saliva secretion. The program causes the terminal 20 to receive examination information including the saliva pH. In another aspect, the program causes the terminal 20 to receive examination information reflecting the saliva pH and calculates the actual value of the saliva pH from the examination information. One aspect of the examination information reflecting the saliva pH is the color development of the pH test paper using the mouthwash spit.

[0107] In the aspect shown in FIG. 2, the program causes the terminal 20 to quantitatively predict the saliva secretion amount of the examinee Pt. At this time, the program causes the terminal 20 to fit the saliva pH received as examination information into the regression model. As described above, the saliva pH may be the saliva pH calculated by the terminal 20 itself. The program causes the terminal 20 to present the result information 26 consisting of the saliva secretion decrease test results. In one aspect, at least one of the diagnostician Dc, the examinee Pt, and the assistant of the examinee Pt receives the presentation.

[0108] Either the server 30 shown in FIG. 2 or any other server stores the program. The program is stored in a disk, tape, flash memory, and other non-volatile storage media. The server 30 and other servers upload the program to the terminal 20 via the network. In another aspect, the server 30 and other servers bear part of the operation of the terminal 20.

[0109] <Application Example: Integrated Device>

[0110] One aspect described in FIG. 2 is an integrated device including the functions of the terminal 20 and a salivary pH measurement device. In one aspect, the integrated device further includes a display for presenting result information. In one aspect, the integrated device is composed of a compact housing suitable for installation beside a dental treatment chair. In one aspect, the integrated device includes a camera as a measurement device and is provided as a tablet or smartphone installed with an app.

[0111] In other aspects, the integrated device includes a storage device that functions as the server 30 and incorporates the above-described system. Regardless of whether it is connected to the outside through a network or not, the integrated device performs from pH measurement to prediction of salivary secretion volume. Therefore, it is suitable not only for installation in medical institutions but also for installation in each household where home medical treatment is carried out. The integrated device includes an interface for updating the regression model stored in the storage device.

[0112] <Application Example: Service Provision>

[0113] FIG. 3 shows another aspect of a system that provides information necessary for determination of reduced salivary secretion. The information institution 39 includes a server 40. The terminal 35 is connected to the server 40 via a network. The system is composed of the terminal 35 and the server 40.

[0114] In the test 31 shown in FIG. 3, the pH test paper 32 is colored by wetting it with the mouthwash discharge fluid 22. The coloration reflects the salivary pH. The pH test paper 32 is wetted with saliva instead of the mouthwash discharge fluid 22. In other aspects of the test 31, the pH test paper 32 is wetted with saliva on the oral mucosa. The examinee Pt or his / her assistant wets the pH test paper 32.

[0115] As shown in FIG. 3, the examinee Pt or his / her assistant causes the terminal 35 to read the color development of the pH test paper 32. The terminal 35 acquires the color development of the pH test paper 32 as color information using the camera it is equipped with. In one aspect, the terminal 35 is a smartphone, tablet, personal computer, and other terminals. In one aspect, the color information is a color image of the wet pH test paper. The camera photographs the surface of the pH test paper 32. In other aspects, a scanner is used instead of the camera. The scanner scans the surface of the pH test paper 32 and converts the color development into color information.

[0116] In one aspect shown in FIG. 3, a color chart for color correction is attached to the pH test paper 32. In one aspect, the camera and the scanner acquire an image in which the color chart is reflected in addition to the wet surface. In other aspects, the camera and the scanner further acquire an image in which the color chart is reflected in addition to the image of the wet surface. In one aspect, the terminal 35 reads the color development of the color chart in addition to the color development of the pH test paper 32. The terminal 35 corrects the color information of the color development of the pH test paper 32 based on the color development of the color chart.

[0117] In an aspect different from the aspect shown in FIG. 3, the camera is independent of the terminal 35. The camera acquires the color development of the pH test paper as color information and sends the color information to the terminal 35.

[0118] As shown in FIG. 3, the terminal 35 sends the inspection information including the color information to the server 40. The server 40 receives the inspection information. The server 40 calculates the saliva pH of the examinee Pt from the inspection information. The server 40 substitutes the calculated saliva pH into the regression model stored in the server 40. The server 40 quantitatively predicts the saliva secretion amount of the examinee Pt. In other aspects, after receiving the inspection information from the terminal 35, the server 40 receives the regression model from another server via the network and stores it.

[0119] The server 40 shown in FIG. 3 calculates a salivary secretion reduction test result from a predicted value of the salivary secretion amount in accordance with the above-described method for determining the possibility of actually suffering from a decrease in salivary secretion. The server 40 sends result information including the salivary secretion reduction test result to the terminal 35. In an embodiment different from the embodiment shown in the figure, the server 40 sends result information including the salivary secretion reduction test result to the terminal 35. The terminal 35 that has received the result information displays the result information. The examinee Pt knows the salivary secretion reduction test result through the terminal 35. In other embodiments, the result information is sent to a terminal different from the terminal 35. Such a terminal presents the result information to the diagnosing doctor of the examinee Pt.

[0120] The color development of the pH test paper shown in FIG. 3 is also applicable to the system shown in FIG. 2. The examinee or his / her assistant inputs the color development of the pH test paper wetted with the mouthwash discharge 22 or saliva as inspection information to the terminal 20. The terminal 20 receives the inspection information. The processing unit 25 calculates the salivary pH of the examinee from the inspection information. The processing unit 25 substitutes the calculated salivary pH into the regression model stored in the processing unit 25. The processing unit 25 quantitatively predicts the salivary secretion amount of the examinee Pt.

[0121] <Application Example: Application Distributed to the Terminal>

[0122] In one embodiment shown in FIG. 3, the terminal 35 operates based on an application program, hereinafter referred to as an app. The app installed on the terminal 35 causes the terminal 35 to execute the generation of the color information of the color development of the above-described wetted pH test paper. In other embodiments, the app causes the terminal 35 to receive the color information.

[0123] The app installed on the terminal 35 shown in FIG. 3 causes the terminal 35 to send the color information towards the server 40. The app further sends a request to the server 40 to generate the above-described result information from the color information. The app further causes the terminal 35 to receive the result information sent from the server 40. The app further causes the terminal 35 to display the result information.

[0124] Either the server 40 shown in FIG. 2 or another server stores the application. The application is stored in a disk, tape, flash memory, and other non-volatile storage media. The server 30 and other servers upload the application to the terminal 35 via a network. In other embodiments, part of the operation of the server 40 is borne by other servers.

[0125] The present invention is not limited to the above embodiments and can be appropriately changed without departing from the spirit.

[0126] <Method for Predicting Salivary Secretion Volume from Salivary Occult Blood Concentration>

[0127] In one embodiment, the salivary secretion volume is predicted from the salivary occult blood concentration. The prediction does not rely on the measurement of salivary pH. First, a regression model is obtained in advance with the salivary occult blood concentration as the explanatory variable and the salivary secretion volume as the objective variable. Next, the salivary occult blood concentration of the subject is obtained. Next, the salivary occult blood concentration of the subject is fitted into the regression model. The salivary secretion volume of the subject is quantitatively predicted by a computer.

[0128] In other embodiments, multiple regression analysis is performed with the salivary occult blood concentration and other items as explanatory variables and the salivary secretion volume as the objective variable. In one embodiment, as other items, at least one of the items of the number of salivary white blood cells, salivary ammonia concentration, age, gender, current number of teeth, presence or absence of disease, oral dryness complaint, oral stickiness complaint, chewing difficulty complaint, periodontal disease symptom complaint, and skin dryness complaint is used. Values representing the characteristics related to the same items as those selected as the above explanatory variables are obtained from the subject. The salivary occult blood concentration and other characteristics of the subject are fitted into the regression model obtained as described above.

[0129] As shown in Tables 1 and 5, it was found that the regression model obtained by simple regression analysis with the salivary occult blood concentration as the explanatory variable is useful for predicting the resting salivary secretion volume. As shown in Table 3, it was found that the regression model obtained by multiple regression analysis with the salivary occult blood concentration and the number of salivary white blood cells as the explanatory variables is useful for predicting the resting salivary secretion volume.

[0130] <Method for Predicting Salivary Secretion Volume from Salivary White Blood Cell Count>

[0131] In one aspect, the salivary secretion volume is predicted from the salivary white blood cell count. This prediction does not rely on the measurement of salivary pH. First, a regression model is obtained in advance with the salivary white blood cell count as the explanatory variable and the salivary secretion volume as the objective variable. Next, the salivary white blood cell count of the subject is acquired. Then, the salivary white blood cell count of the subject is fitted into the regression model. The salivary secretion volume of the subject is quantitatively predicted by a computer.

[0132] In another aspect, multiple regression analysis is performed with the salivary white blood cell count and other items as explanatory variables and the salivary secretion volume as the objective variable. In one aspect, as other items, at least one of the items of salivary occult blood concentration, salivary ammonia concentration, age, gender, current number of teeth, presence or absence of disease, complaint of oral dryness, complaint of sticky mouth, complaint of chewing difficulty, complaint of periodontal disease symptoms, and complaint of skin dryness is used. Values representing the characteristics related to the same items as those selected as the above explanatory variables are acquired from the subject. The salivary white blood cell count and other characteristics of the subject are fitted into the regression model obtained as described above.

[0133] As shown in Table 1 and Table 5, it was found that the regression model obtained by simple regression analysis with the salivary white blood cell count as the explanatory variable is useful for predicting the resting salivary secretion volume. As shown in Table 3, it was found that the regression model obtained by multiple regression analysis with the salivary white blood cell count and the salivary occult blood concentration as the explanatory variables is useful for predicting the resting salivary secretion volume.

[0134] <Application Example: System for Analyzing Items Other than Salivary pH>

[0135] In another aspect, the system shown in FIG. 2 analyzes items other than salivary pH. The differences from the system for analyzing salivary pH described above are shown below. The terminal 20 acquires at least one of the salivary occult blood concentration and the salivary white blood cell count.

[0136] In one aspect of the inspection 21 shown in FIG. 2, at least one of the occult blood concentration and the white blood cell count of the mouthwash discharge 22 is obtained. The occult blood concentration and the white blood cell count of the mouthwash discharge 22 respectively reflect the occult blood concentration and the white blood cell count of saliva. For convenience, the occult blood concentration and the white blood cell count of the mouthwash discharge 22 are hereinafter referred to as the saliva occult blood concentration and the saliva white blood cell count. At least one of the saliva occult blood concentration and the saliva white blood cell count is input into the terminal 20 as inspection information.

[0137] In an aspect different from the aspect shown in FIG. 2, the terminal 20 is connected to a measuring device. The measuring device may be the device described in Patent Document 2. The measuring device automatically inputs the saliva pH as inspection information into the terminal 20 according to the request of the terminal 20. In another aspect, the measuring device is an integrated device with the terminal 20. In one aspect, the measuring device reads the change in the color tone of the test paper.

[0138] As shown in FIG. 2, the terminal 20 receives inspection information. The terminal 20 includes a processing unit 25. The processing unit 25 substitutes at least one of the inspection information, that is, the saliva occult blood concentration and the saliva white blood cell count, into the regression model. The regression model uses at least one of the saliva occult blood concentration and the saliva white blood cell count and other items as explanatory variables as required, and the saliva secretion amount as the target variable, which has been obtained in advance. The processing unit 25 performs multiple regression analysis by fitting at least one of the saliva occult blood concentration and the saliva white blood cell count and the answers to the questionnaire into the regression model.

Explanation of Signs

[0139] 10 Regression model, 11 Saliva specimen, 12 Saliva pH information, 13 Prediction of saliva secretion amount, 15 Subject, 16 Population, 17 Sample, 19 Medical institution, 20 Terminal, 21 Inspection, 22 Mouthwash discharge, 23 Oral mucosa, 25 Processing unit, 26 Result information, 27 Consumables, 29 Information institution, 30 Server, 31 Inspection, 32 Test paper, 35 Terminal, 39 Information institution, 40 Server, Dc Diagnostic doctor, Pt Patient

Claims

1. Obtaining, as acquisition information, at least any other item information selected from the group consisting of the salivary pH information of a subject, the salivary occult blood concentration, the salivary white blood cell count, and the salivary ammonia concentration, Using, as explanatory variables, the salivary pH corresponding to the salivary pH information of the subject included in the acquisition information and the other items corresponding to the other item information included in the acquisition information, and fitting the acquisition information of the subject to an analysis model obtained by using the salivary secretion volume as the objective variable, to qualitatively predict the salivary secretion volume of the subject. Method.

2. The analysis model is previously obtained by an analysis in which at least any item of age, gender, current number of teeth, presence or absence of disease, oral dryness complaint, oral stickiness complaint, chewing difficulty complaint, periodontal disease symptom complaint, and skin dryness complaint is added to the explanatory variables, Further obtaining information on the same items as the items added to the explanatory variables as additional acquisition information from the subject, and further fitting the additional acquisition information of the subject to the analysis model to qualitatively predict the salivary secretion volume of the subject. The method according to claim 1.

3. In the analysis model, the salivary secretion volume is the resting salivary secretion volume, The analysis model is obtained by an analysis further including the stimulated salivary secretion volume in the explanatory variables, Further obtaining the stimulated salivary secretion volume of the subject, and further fitting the stimulated salivary secretion volume of the subject to the analysis model to qualitatively predict the resting salivary secretion volume of the subject. The method according to claim 1 or 2.

4. In the analysis model, the explanatory variables are items corresponding to information based on mouthwash discharge fluid, Fitting each item information based on the mouthwash discharge fluid of the subject to the salivary pH information and the other item information of the subject in the analysis model to qualitatively predict the salivary secretion volume of the subject. The method according to claim 1.

5. A system for providing information necessary for determining reduced salivary secretion, receiving test information consisting of the salivary pH of the subject and at least any one other item selected from the group consisting of salivary occult blood concentration, salivary white blood cell count, and salivary ammonia concentration, and receiving test information reflecting the salivary pH and other items of the subject and calculating at least any one of the salivary pH and the other items of the subject from the test information, predicting the salivary secretion volume of the subject by fitting the salivary pH and the other items of the subject to an analysis model obtained by using the salivary pH and the other items as explanatory variables and the salivary secretion volume as the objective variable, presenting the result information to at least any one of the subject's diagnosing doctor and the subject or his / her assistant, wherein the result information is a qualitative determination indicating whether or not the predicted value of the salivary secretion volume is below the threshold of reduced salivary secretion. System.

6. receiving, as the test information, color information of the color development of a pH test paper wetted with the saliva or mouthwash spit of the subject and information on at least any one other item selected from the group consisting of salivary occult blood concentration, salivary white blood cell count, and salivary ammonia concentration, from at least any one of the terminals of the subject or his / her assistant via a network, sending, via the network, the result information to at least any one of the terminals of the diagnosing doctor, at least any one of the terminals of the subject or his / her assistant, and other terminals, presenting the result information by causing the terminal that has received the result information to display the result information. The system according to claim 5.

7. causing a terminal to receive result information from a server via a network, and further, an application for causing the terminal to display the result information, An analysis model in which the saliva secretion amount of a subject is an explanatory variable and the saliva secretion amount is an objective variable, where the explanatory variables are the saliva pH and at least one other item selected from the group consisting of the salivary occult blood concentration, the salivary white blood cell count, and the salivary ammonia concentration, and which is possessed by a server. By fitting the saliva pH and other items of the subject, the server qualitatively predicts it. Application.

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