Long-term health outcomes of Q-fever fatigue syndrome patients.

This study determined long-term health outcomes (≥10 years) of Q-fever fatigue syndrome (QFS). Long-term complaints, health-related quality of life (HRQL), health status, energy level, fatigue, post-exertional malaise, anxiety, and depression were assessed. Outcomes and determinants were studied for the total sample and compared among age subgroups: young (<40years), middle-aged (≥40-<65years), and older (≥65years) patients. 368 QFS patients were included. Participants reported a median number of 12.0 long-term complaints. Their HRQL (median EQ-5D-5L index: 0.63) and health status (median EQ-VAS: 50.0) were low, their level of fatigue was high, and many experienced post-exertional malaise complaints (98.9%). Young and middle-aged patients reported worse health outcomes compared with older patients, with both groups reporting a significantly worse health status, higher fatigue levels and anxiety, and more post-exertional malaise complaints and middle-aged patients having a lower HRQL and a higher depression risk. Multivariate regression analyses confirmed that older age is associated with better outcomes, except for the number of health complaints. QFS has thus a considerable impact on patients' health more than 10 years after infection. Young and middle-aged patients experience more long-term health consequences compared with older patients. Tailored health care is recommended to provide optimalcare for each QFS patient.

Prerequisites, barriers and opportunities in care for Q-fever patients: a Delphi study among healthcare workers.

BACKGROUND: Q-fever is a zoonotic disease that can lead to illness, disability and death. This study aimed to provide insight into the perspectives of healthcare workers (HCWs) on prerequisites, barriers and opportunities in care for Q-fever patients. METHODS: A two-round online Delphi study was conducted among 94 Dutch HCWs involved in care for Q-fever patients. The questionnaires contained questions on prerequisites for high quality, barriers and facilitators in care, knowledge of Q-fever, and optimization of care. For multiple choice, ranking and Likert scale questions, frequencies were reported, while for rating and numerical questions, the median and interquartile range (IQR) were reported. RESULTS: The panel rated the care for Q-fever patients at a median score of 6/10 (IQR = 2). Sufficient knowledge of Q-fever among HCWs (36%), financial compensation of care (30%) and recognition of the disease by HCWs (26%) were considered the most important prerequisites for high quality care. A lack of knowledge was identified as the most important barrier (76%) and continuing medical education as the primary method for improving HCWs' knowledge (76%). HCWs rated their own knowledge at a median score of 8/10 (IQR = 1) and the general knowledge of other HCWs at a 5/10 (IQR = 2). According to HCWs, a median of eight healthcare providers (IQR = 4) should be involved in the care for Q-fever fatigue syndrome (QFS) and a median of seven (IQR = 5) in chronic Q-fever care. CONCLUSIONS: Ten years after the Dutch Q-fever epidemic, HCWs indicate that the long-term care for Q-fever patients leaves much room for improvement. Facilitation of reported prerequisites for high quality care, improved knowledge among HCWs, clearly defined roles and responsibilities, and guidance on how to support patients could possibly improve quality of care. These prerequisites may also improve care for patients with persisting symptoms due to other infectious diseases, such as COVID-19.

Sensitivity of the EQ-5D-5L for fatigue and cognitive problems and their added value in Q-fever patients.

PURPOSE: Measuring health-related quality of life (HRQoL) with the EQ-5D-5L might lack sensitivity for disease-specific health complaints. This cross-sectional study analyzed whether fatigue and cognitive problems are captured by the EQ-5D-5L in a Q-fever patient population with persistent fatigue/cognitive problems, and whether addition of fatigue/cognition improved the explained variance for HRQoL. METHODS: A Dutch sample of Q-fever patients filled out the EQ-5D-5L and EQ VAS, the fatigue subscale of the Checklist Individual Strength, and a cognition dimension in the EQ-5D-5L format. The extent to which fatigue and cognition were captured by the EQ-5D-5L was determined based on distributional effects, head-to-head comparisons, Spearman rank correlation coefficients, and regression analyses. Explanatory power was determined of the EQ-5D-5L for the EQ VAS with and without a fatigue and cognition dimension. RESULTS: Out of 432 respondents, 373(86%) reported severe fatigue, 387(90%) cognitive problems. EQ-5D-5L utility and EQ VAS scores of respondents reporting severe fatigue/cognitive problems were significantly lower. Fatigue was strongly correlated with EQ-5D-5L dimensions usual activities and pain/discomfort (r = 0.602 and r = 0.510) and moderately with other EQ-5D-5L dimensions (r = 0.305-0.476). Cognition was strongly correlated with usual activities (r = 0.554) and moderately with other dimensions (r = 0.291-0.451). Adding fatigue to the EQ-5D-5L increased explanatory power for the EQ VAS with 6%. CONCLUSION: Fatigue and cognitive problems in Q-fever patients were partially captured by the EQ-5D-5L dimensions. The addition of fatigue to the EQ-5D-5L slightly improved explained variance for the EQ VAS. This potentially also accounts for patients who experience sequelae of other infectious diseases, such as COVID-19.

Long-term impact of a Q-fever outbreak: An evaluation of health symptoms, health-related quality of life, participation and health care satisfaction after ten years.

OBJECTIVE: To assess health symptoms, health-related quality of life, participation, and health care satisfaction in Q-fever patients up to 10 years after infection. METHODS: Cross-sectional questionnaire survey in the Netherlands. Data on health symptoms, fatigue (CIS), health-related quality of life (EQ-5D), social/work participation, health care providers and health care satisfaction were collected in patients with chronic Q-fever (CQ), Q-fever fatigue syndrome (QFS), and patients who experience QFS-like disease without a post-infection diagnosis (QLD). RESULTS: A vast majority of the 478 Q-fever patients (response rate 54.3%) face several health problems 10 years after infection. Fatigue was the most prevalent symptom in all groups (91.2%). The median EQ-5D index value differed significantly between the three diagnostic groups (CQ: 0.67; QFS: 0.55; QLD:0.70; p < 0.001). Approximately 50% of all patients had serious problems with work and physical activities, and more than 25% experienced difficulties with leisure time, household and social contacts. Also, more than one third stopped working permanently. Furthermore, GP's, internists, and physical therapists were the most often consulted health care providers. Patients gave low ratings for the overall quality of care for Q-fever, with 75% scoring a 5.0 or lower on a 10-point scale. CONCLUSION: Long-term health consequences are considerable for Q-fever patients, especially for those with QFS. The majority of the patients was unsatisfied with the quality of care for Q-fever. Awareness of the long-term impact of zoonotic diseases like Q-fever is needed to offer optimal health care for these patients.