Understanding the Female Physical Examination in Patients with Chronic Pelvic and Perineal Pain.
Augusto Pereira SánchezLucia FuentesBelen AlmogueraPilar ChavesGema VaqueroTirso Pérez MedinaPublished in: Journal of clinical medicine (2022)
(1) Background: The objective was to compare the exploration of chronic pelvic pain syndrome (CPPS) patients in different locations and establish the role of physical examination in CPPS patients. (2) Methods: We reviewed clinical data from 107 female patients with CPPS unresponsive to conventional therapies at Puerta de Hierro University Hospital Madrid, Spain, from May 2018 to June 2022. Patients were classified into three groups: (a) pelvic pain; (b) anorectal pain; or (c) vulvar/perineal pain. (3) Results: Although the demographics of patients with CPPS were different, their physical examinations were strikingly similar. Our study observed a comorbidity rate of 36% and 79% of central sensitization of pain. Seventy-one percent of patients had vulvar allodynia/hyperalgesia. Pain on examination was identified in any pelvic floor muscle, in any pelvic girdle structure, and neuropathic pain in 98%, 96%, and 89%, respectively. Patients with vulvar and perineal pain were more different from the other groups; these patients were younger and had fewer comorbidities and less central sensitization, less anorectal pain, more pain during intercourse, and greater nulliparity ( p = 0.022; p = 0.040; p = 0.048; p = 0.000; p = 0.006; p = 0.005). (4) Conclusions: The findings of this study are related to the understanding of the pathophysiology of CPPS. The physical examination confirms the central sensitization of female patients with CPPS, helps us to determine the therapeutic management of the patient, and can be considered as a prognostic factor of the disease.
Keyphrases
- neuropathic pain
- chronic pain
- end stage renal disease
- prognostic factors
- pain management
- chronic kidney disease
- ejection fraction
- newly diagnosed
- spinal cord injury
- spinal cord
- skeletal muscle
- mental health
- radiation therapy
- early stage
- deep learning
- machine learning
- case report
- men who have sex with men
- patient reported
- artificial intelligence