Background: Evidence suggests that non-motor symptoms (NMS) are the most important predictors of decreased health-related quality of life (HR-QoL) in patients with cervical dystonia (CD). In this study, we evaluate an NMS screening list and examine the influence of motor symptoms and NMS on HR-QoL.
Methods: In 40 patients with CD, the frequency of NMS was evaluated using an extended NMS questionnaire. Furthermore, patients composed a list of their 5 most burdensome motor symptoms and NMS and scored the severity of predefined symptoms. HR-QoL was examined with the RAND 36-item Health Survey.
Results: Of 40 patients, 38 experienced NMS (median number of NMS, 6.5; range, 0-13; maximum, 15). The self-perceived most burdensome symptoms were tremor/jerks, pain, sleep disturbances, daily-life limitations, and fatigue. Also, of the predefined symptom list, tremor and fatigue were identified as the most disturbing. Several domains of HR-QoL were significantly influenced by NMS, whereas motor symptoms had only a small influence on the physical functioning domain of HR-QoL.
Conclusion: Our findings highlight the impact of NMS on HR-QoL and emphasize the importance of a standardized, validated NMS questionnaire for patients with dystonia. This would enable us to monitor the effect of treatment for motor symptoms and NMS on an individual basis and improve treatment options.
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http://dx.doi.org/10.1002/mdc3.12510 | DOI Listing |
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Department of Neurology, Mayo Clinic Rochester, Rochester, MN, USA.
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ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal.
Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high mortality persisted even after the state of emergency ended. Current mortality prediction methods remain limited, especially for critically ill ICU patients, due to their dynamic metabolic changes and heterogeneous pathophysiological processes. This study evaluated how the serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support mortality prediction models in COVID-19 ICU patients.
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High-Risk Pregnancy Center, Hospital da Luz Lisboa, 1500-650 Lisboa, Portugal.
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