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Borghese G, Doglioli M, Orsini B, Raffone A, Neola D, Travaglino A, Rovero G, Del Forno S, de Meis L, Locci M, Guida M, Lenzi J, Seracchioli R, Raimondo D. Progression of adenomyosis: Rate and associated factors. Int J Gynaecol Obstet 2024. [PMID: 38738458 DOI: 10.1002/ijgo.15572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 04/13/2024] [Accepted: 04/20/2024] [Indexed: 05/14/2024]
Abstract
OBJECTIVE To evaluate the rate of disease progression and the factors associated with such progression in patients with an ultrasound diagnosis of adenomyosis. METHODS This was a single center, prospective, observational, cohort study performed at a tertiary referral center. Patients who obtained an ultrasound diagnosis of adenomyosis from May 2022 to August 2022 were recruited. Demographic, clinical and ultrasound data were recorded at the first visit (T0) and after 12 months (T1) for enrolled patients and compared between T0 and T1. The study population was divided in two groups according to progression (increase in uterine volume >20%) or stability/regression (decrease or increase in uterine volume ≤20%) of adenomyosis at T1. Primary study outcome was the rate of adenomyosis progression, while secondary study outcome was the association of adenomyosis progression with demographic and clinical factors. Post hoc subgroups analyses for primary and secondary study outcomes were performed based on hormonal therapy (untreated and treated). RESULTS A total of 221 patients were enrolled in the study, with no significant difference in terms of baseline data among the two study groups and no patients were lost to follow-up. The overall rate of adenomyosis progression was 21.3% (47/221 patients). The rate was 30.77% in hormonally untreated women, and 18.34% in hormonally treated women. Progression was associated with the presence of focal adenomyosis of the outer myometrium (P = 0.037), moderate to severe dysmenorrhea (P = 0.001), chronic pelvic pain (P = 0.05), dyschezia (P = 0.05), and worsening of chronic pelvic pain (P = 0.04) at T1. CONCLUSION Adenomyosis showed a rate of disease progression of 21.3% at the 12-month follow-up (30.77% in hormonally untreated women, and 18.34% in hormonally treated women). The presence and/or worsening of painful symptoms, such as severe dysmenorrhea, dyschezia and chronic pelvic pain, as well as the presence focal adenomyosis of the outer myometrium, might help identify patients at higher risk of disease progression and tailor their follow-up.
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Affiliation(s)
- Giulia Borghese
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
| | - Marisol Doglioli
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
- Department of Medical and Surgical Sciences, DIMEC, University of Bologna, Bologna, Italy
| | - Benedetta Orsini
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
- Department of Medical and Surgical Sciences, DIMEC, University of Bologna, Bologna, Italy
| | - Antonio Raffone
- Department of Medical and Surgical Sciences, DIMEC, University of Bologna, Bologna, Italy
- Gynecology and Obstetrics Unit, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy
| | - Daniele Neola
- Gynecology and Obstetrics Unit, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy
| | - Antonio Travaglino
- Unit of Pathology, Department of Medicine and Technological Innovation, University of Insubria, Varese, Italy
| | - Giulia Rovero
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
- Department of Medical and Surgical Sciences, DIMEC, University of Bologna, Bologna, Italy
| | - Simona Del Forno
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
| | - Lucia de Meis
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
| | - Mariavittoria Locci
- Gynecology and Obstetrics Unit, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy
| | - Maurizio Guida
- Gynecology and Obstetrics Unit, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy
| | - Jacopo Lenzi
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Renato Seracchioli
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
- Department of Medical and Surgical Sciences, DIMEC, University of Bologna, Bologna, Italy
| | - Diego Raimondo
- Division of Gynecology and Human Reproduction Physiopathology, IRCCS Azienza Ospedaliero Universitaria, Bologna, Italy
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Edgley K, Horne AW, Saunders PTK, Tsanas A. Symptom tracking in endometriosis using digital technologies: Knowns, unknowns, and future prospects. Cell Rep Med 2023; 4:101192. [PMID: 37729869 PMCID: PMC10518625 DOI: 10.1016/j.xcrm.2023.101192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 06/12/2023] [Accepted: 08/18/2023] [Indexed: 09/22/2023]
Abstract
Endometriosis is a common chronic pain condition with no known cure and limited treatment options. Digital technologies, ranging from smartphone apps to wearable sensors, have shown potential toward facilitating chronic pain assessment and management; however, to date, many of these tools have not been specifically deployed or evaluated in patients with endometriosis-associated pain. Informed by previous studies in related chronic pain conditions, we discuss how digital technologies may be used in endometriosis to facilitate objective, continuous, and holistic symptom tracking. We postulate that these pervasive and increasingly affordable technologies present promising opportunities toward developing decision-support tools assisting healthcare professionals and empowering patients with endometriosis to make better-informed choices about symptom management.
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Affiliation(s)
- Katherine Edgley
- EXPPECT and MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4UU, Scotland, UK.
| | - Andrew W Horne
- EXPPECT and MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4UU, Scotland, UK
| | - Philippa T K Saunders
- Centre for Inflammation Research, University of Edinburgh, Edinburgh EH16 4UU, Scotland, UK
| | - Athanasios Tsanas
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh EH16 4UX, Scotland, UK; Alan Turing Institute, London NW1 2DB, UK
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Liu Y, Zhang G, Tarolli CG, Hristov R, Jensen-Roberts S, Waddell EM, Myers TL, Pawlik ME, Soto JM, Wilson RM, Yang Y, Nordahl T, Lizarraga KJ, Adams JL, Schneider RB, Kieburtz K, Ellis T, Dorsey ER, Katabi D. Monitoring gait at home with radio waves in Parkinson's disease: A marker of severity, progression, and medication response. Sci Transl Med 2022; 14:eadc9669. [PMID: 36130014 DOI: 10.1126/scitranslmed.adc9669] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Parkinson's disease (PD) is the fastest-growing neurological disease in the world. A key challenge in PD is tracking disease severity, progression, and medication response. Existing methods are semisubjective and require visiting the clinic. In this work, we demonstrate an effective approach for assessing PD severity, progression, and medication response at home, in an objective manner. We used a radio device located in the background of the home. The device detected and analyzed the radio waves that bounce off people's bodies and inferred their movements and gait speed. We continuously monitored 50 participants, with and without PD, in their homes for up to 1 year. We collected over 200,000 gait speed measurements. Cross-sectional analysis of the data shows that at-home gait speed strongly correlates with gold-standard PD assessments, as evaluated by the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III subscore and total score. At-home gait speed also provides a more sensitive marker for tracking disease progression over time than the widely used MDS-UPDRS. Further, the monitored gait speed was able to capture symptom fluctuations in response to medications and their impact on patients' daily functioning. Our study shows the feasibility of continuous, objective, sensitive, and passive assessment of PD at home and hence has the potential of improving clinical care and drug clinical trials.
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Affiliation(s)
- Yingcheng Liu
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guo Zhang
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Christopher G Tarolli
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | | | - Stella Jensen-Roberts
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Emma M Waddell
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Taylor L Myers
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Meghan E Pawlik
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Julia M Soto
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Renee M Wilson
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Yuzhe Yang
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Timothy Nordahl
- Department of Physical Therapy & Athletic Training, Center for Neurorehabilitation, Boston University College of Health and Rehabilitation: Sargent College, Boston, MA 02215, USA
| | - Karlo J Lizarraga
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Jamie L Adams
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Ruth B Schneider
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Karl Kieburtz
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Terry Ellis
- Department of Physical Therapy & Athletic Training, Center for Neurorehabilitation, Boston University College of Health and Rehabilitation: Sargent College, Boston, MA 02215, USA
| | - E Ray Dorsey
- Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.,Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Dina Katabi
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Emerald Innovations Inc., Cambridge, MA 02142, USA
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