Aerobic bacterial vaginitis risk prediction model, method and system based on gram staining smear

A technique for Gram staining and vaginitis, which is applied in the field of biomedical diagnosis, can solve the problems of saline wet slides cannot be preserved, wet slide media flow, and cannot be read repeatedly, achieving high homogeneity, easy quality control, and reliability good sex effect

Pending Publication Date: 2022-07-19
薛凤霞
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, normal saline wet slides cannot be preserved and cannot be read repeatedly, and the medium of wet slides is fluid, making it difficult to observe. Microscopic examination to identify bacterial forms requires high requirements for inspectors and equipment (phase contrast microscope)

Method used

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  • Aerobic bacterial vaginitis risk prediction model, method and system based on gram staining smear
  • Aerobic bacterial vaginitis risk prediction model, method and system based on gram staining smear
  • Aerobic bacterial vaginitis risk prediction model, method and system based on gram staining smear

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0104] Example 1 Identification of related factors in Gram-stained smears of vaginal secretions

[0105] The relevant data of women with aerobic vaginitis and control women who were treated in the gynecological outpatient department of Tianjin Medical University General Hospital were extracted to construct a training data set. The cases in this part of the data set need to have vaginal secretions Gram-stained smears and saline wet smears at the same time. And the corresponding clinical information, the difference between the image-related data of the Gram-stained smear and the saline wet-film microscope was compared.

[0106] The first data came from the data of aerobic vaginitis women and control women in the microecology room of the gynecological outpatient clinic of Tianjin Medical University General Hospital (n=325vs.n=325). The general information of the 650 cases is shown in Table 1.

[0107] Table 1 Training dataset case information

[0108]

[0109]

[0110] E...

Embodiment 2

[0118] Example 2 Identification of correlative factors in clinical information

[0119] The second data comes from the clinical information database of the microecology room of the gynecological outpatient clinic of Tianjin Medical University General Hospital. The clinical information of the first data corresponding to the case is extracted, including pH value, itching, increased vaginal discharge, vulvovaginal burning sensation, pain during intercourse, and gynecological examination. Results, etc., including vaginal mucosal congestion, vaginal secretions (color, character, amount, smell), etc.

[0120] Furthermore, Logistic univariate and multivariate regression analysis was used to screen the clinical characteristics of aerobic vaginitis, and the factors finally included in the model included vaginal secretion pH value>4.5, yellow secretion, and vaginal mucosal congestion (Table 3).

[0121] Table 3 Logistic regression analysis of clinical characteristics of aerobic vagini...

Embodiment 3

[0127] Example 3 model building

[0128] The image characteristic factors under the Gram stained smear microscope selected in Example 1 and the clinical characteristic factors selected in Example 2 were incorporated into the model pool and compared to establish the prediction model of the present invention.

[0129] First, assign values ​​to the determined factors:

[0130] Gram-stained smear under 1000x microscope, gram-positive large bacilli, no spores, slender, curved or spherical rod-shaped, rod-shaped, single, and double are Lactobacillus-like bacteria; Gram-negative bacilli, no spores, single Or arranged in pairs as small Enterobacteriaceae; coccus-like or chain is the microscopic morphology of Gram-negative or positive monococci, diplococci or streptococci. Gram stained smear under 400 magnification, the cells are large, flat and polymorphic, with centered, small, round, and dense nuclei, which are vaginal exfoliated surface epithelial cells; small in size, round, de...

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Abstract

The invention provides a system and a grouping method for carrying out risk assessment on aerobic bacterial vaginitis by using gram staining smears and an establishment method of a prediction model adopted by the system and the grouping method. The systems and methods are based on the combination of vaginal secretion gram staining smears and clinical characteristics, can quickly and conveniently perform aerobic bacterial vaginitis risk assessment, and can provide a homogenized and standardized data basis for artificial intelligence reading of genital tract infection.

Description

technical field [0001] The invention belongs to the field of biomedical diagnosis, in particular, the invention relates to a risk prediction model of aerobic bacterial vaginitis. Background technique [0002] Vaginal infection is the most common infectious disease in women of reproductive age. Worldwide, more than 300 million women suffer from vaginal infections every year. A national multi-center epidemiological survey found that reproductive tract infections accounted for 55% of outpatients in gynecology and family planning, of which vaginal infections accounted for 30%-35%, and the proportion was even higher in primary medical institutions, reaching 50%-60%. [0003] Aerobic vaginitis is a new type of vaginal infection officially reported by Belgian scholars Donders et al. in 2002. It is characterized by vaginal inflammation caused by the reduction or absence of the dominant bacteria Lactobacillus in the vagina and the increase of aerobic bacteria. 5.0%-23.7% of symptom...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H10/20G16H10/40
CPCG16H50/30G16H10/20G16H10/40
Inventor 薛凤霞闫晔王辰韩姹李会阳范爱萍齐文慧董梦婷王颖梅田文艳孟珂
Owner 薛凤霞
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