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Lactation mastitis: Promising alternative indicators for early diagnosis.
Huang, Qian; Zheng, Xue-Mei; Zhang, Mao-Lin; Ning, Ping; Wu, Meng-Jun.
Afiliação
  • Huang Q; School of Medicine, University of Electronic Science and Technology of China, Chengdu 610000, Sichuan Province, China.
  • Zheng XM; School of Medicine, University of Electronic Science and Technology of China, Chengdu 610000, Sichuan Province, China.
  • Zhang ML; Department of Anesthesiology, Chongqing Medical University, Chongqing 400016, Sichuan Province, China.
  • Ning P; Department of Breast, Chengdu Women's and Children's Central Hospital, Chengdu 610000, Sichuan Province, China. nping11@163.com.
  • Wu MJ; Department of Anesthesiology, Chengdu Women's and Children's Central Hospital, Chengdu 610000, Sichuan Province, China.
World J Clin Cases ; 10(31): 11252-11259, 2022 Nov 06.
Article em En | MEDLINE | ID: mdl-36387788
Although lactation mastitis (LM) has been extensively researched, the incidence rate of LM remains a salient clinical problem. To reduce this incidence rate and achieve a better prognosis, early and specific quantitative indicators are particularly important. It has been found that milk electrolyte concentrations (chloride, potassium, and sodium) and electrical conductivity (EC) significantly change in the early stages of LM in an animal model. Several studies have evaluated EC for the detection of subclinical mastitis in cows. EC, chloride, and sodium content of milk were more accurate for predicting infection status than were other variables. In the early stages of LM, lactic sodium, chloride, and EC increase, but potassium decreases. However, these indicators have not been reported in the diagnosis of LM in humans. This review summarizes the pathogenesis and the mechanism of LM in terms of milk electrolyte concentration and EC, and aim to provide new ideas for the detection of sub-clinical mastitis in humans.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article