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      Post-discharge persistent symptoms and health-related quality of life after hospitalization for COVID-19

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          Abstract

          Dear editor, In this journal, we recently reported a series of 279 hospitalized patients with novel coronavirus 2019 disease (COVID-19) and their short-term outcome. 1 However, only a few studies have assessed post-discharge persistent symptoms and health-related quality of life (HRQoL) after hospitalization for COVID-19. 2 , 3 Here, we describe a single-centre study assessing post-discharge persistent symptoms and HRQoL of patients hospitalized in our COVID-19 ward unit more than 100 days after their admission. COVID-19 diagnosis was based on positive SARS-CoV-2 real-time reverse transcriptase-polymerase chain reaction on nasal swabs, and/or typical abnormalities on chest computed tomography. Patients who were directly admitted to the ICU without being hospitalized in our COVID-19 unit were excluded. Demographic and clinical data at admission were extracted from electronic medical records. We designed a short phone questionnaire to collect post-discharge clinical symptoms, modified Medical Research Council (mMRC) dyspnoea scale scores, professional and physical activities, and attention, memory and/or sleep disorders. HRQoL was assessed using the EQ-5D-5L questionnaire, a widely used, validated European questionnaire 4 . Patients are asked to rate their health state from 1 to 5 in five domains (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and on a scale ranging from 0 (“the worst possible health”) to 100 (“the best possible health”) on a visual analogue scale (EQ-VAS). Based on the answers, an EQ-5D- index can be calculated, ranging from states worse than dead (<0) to 1 (full health). 5 All eligible patients were contacted by phone by trained physicians and were asked to answer to the questionnaire. Deceased, unreachable, demented, bedridden and non-French speaking patients were excluded. We compared patients managed in hospital ward without needing intensive care (“ward group”) with those who were transferred in intensive care units (ICU) for artificial ventilation, including non-invasive ventilation, high flow nasal cannula and/or mechanical ventilation (ICU group), with t-tests for quantitative variables and Chi-square tests for qualitative variables. All tests were two-sided, and a P-value <0.05 was considered statistically significant. All analyses were performed with R version 3.6.1. (R Foundation for Statistical Computing, Vienna, Austria). The study was approved by the local institutional review board (IRB 00006477). Of the 279 hospitalized patients between March 15th and April 14th, 2020 in our COVID-19 unit, 48 were admitted to ICU, and 57 patients died within the three months following admission (43 in the ward group and 14 in the ICU group) (Supplementary figure 1). After having excluded demented or bedridden (n=18), unreachable (n=69), non-French speaking patients (n=12), and those declining participation (n=2), 120 patients answered the phone questionnaire after a mean (±SD) of 110.9 (±11.1) days following admission: 96 in the ward group and 24 in the ICU group for artificial ventilation (mechanical ventilation for 14, CPAP for 10 and high flow nasal cannula for 7). After a mean of 110.9 days, the most frequently reported persistent symptoms were fatigue (55%), dyspnoea (42%), loss of memory (34%), concentration and sleep disorders (28% and 30.8%, respectively) (Table 1 ). Loss of hair was reported by 24 (20%) patients, including 20 women and 4 men. Comparisons between ward- and ICU patients led to no statistically significant differences regarding those symptoms. Thirty-five (29%) patients had a mMRC grade ≥2 (“Walks slower than people of the same age because of dyspnoea or has to stop for breath when walking at own pace”). Table 1 Post-discharge persistent symptoms and health-related quality of life of 120 patients after a mean of 110.9 days after their admission for COVID-19. Table 1 Overall Ward patients ICU patients P value N=120 N=96 N=24 Age, years 63.2 (15.7) 64.1 (16.1) 59.6 (13.7) 0.208 Sex, male 75 (62.5) 56 (58.3) 19 (79.2) 0.099 Comorbidities  Diabetes 26 (21.7) 22 (22.9) 4 (16.7) 0.698  Hypertension 56 (46.7) 45 (46.9) 11 (45.8) 1.000  Body mass index (kg/m²) <0.001  <25, n (%) 35 (29.2) 32 (33.3) 3 (12.5)  ≥25, n (%) 57 (47.5) 37 (38.5) 20 (83.3)  Missing, n (%) 28 (23.3) 27 (28.1) 1 (4.2) Clinical features at admission  Confusion 7 (5.8) 6 (6.2) 1 (4.2) 1.000  Cough 87 (72.5) 69 (71.9) 18 (75.0) 0.959  Dyspnoea 88 (73.3) 68 (70.8) 20 (83.3) 0.327  Myalgia 19 (15.8) 16 (16.7) 3 (12.5) 0.851  Diarrhoea 29 (24.2) 25 (26.0) 4 (16.7) 0.488 Admission data  Length of stay in hospital, days 11.2 (13.4) 7.4 (5.4) 26.5 (22.3) <0.001  Length of stay in ICU, days - - 17.1 (15.7) - Persistent symptoms  Cough 20 (16.7) 14 (14.6) 6 (25.0) 0.358  Chest pain 13 (10.8) 11 (11.5) 2 (8.3) 0.941  Fatigue 66 (55.0) 52 (54.2) 14 (58.3) 0.891  Dyspnoea 50 (41.7) 38 (39.6) 12 (50.0) 0.487  Ageusia 13 (10.8) 9 (9.4) 4 (16.7) 0.509  Anosmia 16 (13.3) 14 (14.6) 2 (8.3) 0.638  Hair loss 24 (20.0) 18 (18.8) 6 (25.0) 0.690  Attention disorder 32 (26.7) 28 (29.2) 4 (16.7) 0.327  Memory loss 41 (34.2) 36 (37.5) 5 (20.8) 0.194  Sleep disorder 37 (30.8) 29 (30.2) 8 (33.3) 0.535 mMRC dyspnoea scale 0.438  Grade 0 56 (46.7) 47 (49.0) 9 (37.5)  Grade 1 29 (24.2) 22 (22.9) 7 (29.2)  Grade 2 or more 35 (29.2) 27 (28.1) 8 (33.3) Professional and physical activities  Returned to work/worked before hospitalization 38/56 (67.9) 31/41 (75.6) 7/15 (46.7) 0.061  Resumed sport/practiced sport regularly before hospitalization 28/39 (71.8) 23/31 (74.2) 5/8 (62.5) 0.937 EQ-5D-5L  EQ-VAS (%) 70.3 (21.5) 69.9 (21.4) 71.7 (22.2) 0.711  EQ-5D index 0.86 (0.20) 0.86 (0.19) 0.82 (0.21) 0.306 Results are expressed as count (%) for categorical variables and as mean (standard deviation) for quantitative variables. ICU: intensive care unit; mMRC: modified Medical Research Council; Before COVID-19 infection, 56 (46.7%) were active workers. Among them, 38 (69.1%) had gone back to work at the time of the phone interview. Among the 39 patients who had regular sports activity before their hospitalizations for COVID-19, 28 (71.8%) have been able to resume physical activity, but at a lower level for 18 (46%). There was no statistically significant difference between ward and ICU groups, but there was a non-significant trend towards a reduced proportion of patients returning to work among ICU patients (46.7% versus 77.5%, P=0.061). In both group, dimensions of the EQ-5D (mobility, self-care, pain, anxiety or depression, usual activity) were altered with a slight difference in pain in the ICU group, but no statistically significant difference in the other groups (Figure 1 ). Mean EQ-VAS was 70.3% and mean EQ-5D index 0.86, with no difference between ICU and ward patients (Table 1). Figure 1 Health-related quality of life after hospitalization for COVID-19 assessed by the EQ-5D 5L in the ward and the ICU groups. 1A: Distribution of the EQ-5D index (0: death to 1: full health). 1B: EQ-5D 5L scores in the ward and in the ICU groups on each domain. Each domain is scored on a 5-point scale: 1 no problem, 2 slight problem, 3 moderate problem, 4 severe problem, 5 unable to do. *: P=0.032. Figure 1 The present study shows that most patients requiring hospitalization for COVID-19 still have persistent symptoms, even 110 days after being discharged, especially fatigue and dyspnoea. These results highlight the need for a long-term follow-up of those patients and rehabilitation programs. Surprisingly, many patients (mainly women) spontaneously reported significant hair loss, which may correspond to a telogen effluvium, secondary to viral infection and/or a stress generated by the hospitalization and the disease. 6 Nevertheless, HRQoL was quite satisfactory, as most patients who had a professional activity before the infection went back to work. Except pain or discomfort, we found no significant difference regarding persistent symptoms and HRQoL between ward patients versus ICU patients. This clearly supports the interest of a full resuscitation for COVID patients despite heaviness of cares. However, patients from our “ICU group” were relatively non-severe, as those who were directly admitted to ICU (thus corresponding to the most severe forms) were not included in our study. Other limitations of our study include the limited number of patients, the single-centre nature of our series, and the high rate of unreachable patients, which could lead to differential bias. In conclusion, many symptoms persist several months after hospitalization for COVID-19. While there were few differences between HRQoL between ward and ICU patients, our findings must be confirmed in larger cohorts, including more severe ICU patients. AUTHOR CONTRIBUTIONS All authors have made substantial contributions to this work and have approved the final version of the manuscript. Concept and design: EG, BF, YN. Acquisition of data: all authors. Statistical analysis: YN. Interpretation of data: EG, BF, YN. Writing original draft: EG, YN. Writing review and editing: all authors. FINANCIAL SUPPORT None Declaration of Competing Interest None of the authors declared any competing interest in link with the present study.

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          Applicability of the CURB-65 pneumonia severity score for outpatient treatment of COVID-19

          Dear editor, Tomlins and colleagues recently reported in this journal the clinical features of 95 sequential hospitalised patients with novel coronavirus 2019 disease (COVID-19) in the first UK cohort. 1 Interestingly, consistent with evidence supporting the use of CURB-65 as a predictor of mortality secondary to community acquired pneumonia (CAP), non-survivors had a significantly higher median CURB-65 score versus survivors (2.5 versus 1 respectively). The CURB-65 is a severity score for CAP, comprising 5 variables, attributing 1 point for each item: new onset confusion; urea >7 mmol/L; respiratory rate ≥30/minute, systolic blood pressure 7 mmol/L 103 (36.9) 10 (5.8) 52 (78.8) 41 (97.6) 30/min 59 (21.1) 25 (14.6) 9 (13.6) 25 (59.5) 65 years 145 (52.0) 47 (27.5) 57 (86.4) 41 (97.6) 38°C 110 (39.4) 71 (41.5) 23 (34.8) 16 (38.1) 0.630  Cough 190 (68.1) 129 (73.7) 39 (59.1) 22 (52.4) 0.003  Dyspnoea 198 (71.0) 126 (37.7) 39 (59.1) 33 (78.6) 0.043  Myalgia 58 (20.8) 43 (25.1) 8 (12.1) 7 (16.7) 0.067  Diarrhoea 55 (19.7) 41 (24.0) 9 (13.6) 5 (11.9) 0.077 Biological features  Lymphocytes count (G/L) 1.2 (1.0) 0.7 (2.5) 1.0 (0.6) 1.0 (0.7) 0.038  C-reactive protein (mg/L) 126.3 (91.11) 117.0 (86.1) 126.1 (94.2) 164.2 (98.1) 0.013  Creatinine level (µmol/L) 108.2 (75.7) 84.1 (41.6) 134.7 (105.2) 164.1 (95.1) <0.001  SGOT (U/L) 71.2 (101.9) 65.6 (49.4) 58.7 (38.6) 108.4 (224.5) 0.033  SPOT (U/L) 45.8 (59.1) 47.0 (43.5) 32.79 (24.6) 59.73 (114.1) 0.078  D-dimers (mg/L) 3421.5 (7303.8) 3229.8 (7209.2) 3662.21 (7544.5) 3737.0 (7639.4) 0.945  Us Troponin I (ng/L) 72.7 (421.9) 21.5 (43.8) 46.3 (63.1) 301.3 (1016.1) 0.009  Ferritin (mg/L) 1465.3 (1584.2) 1485.8 (1836.6) 1309.3 (1115.2) 1585.3 (1303.5) 0.824 Outcome  Favourable 191 (68.5) 135 (78.9) 42 (63.6) 14 (33.3) <0.001  Unfavourable 88 (31.5) 36 (21.1) 24 (36.4) 28 (66.7) <0.001   HFNC or NVI 28 (10.0) 13 (11.4) 10 (29.4) 5 (26.3) 0.024   Mechanical ventilation 27 (39.1) 19 (16.2) 5 (14.7) 3 (15.8) 0.977   Deceased 51 (18.3) 15 (8.9) 15 (24.2) 21 (53.8) <0.001 Results are expressed as count (%) for categorical variables and as mean (standard deviation) for quantitative variables. *SGOT and SPOT were available for 244 (87.5%), us troponin I levels for 157 (56.3%) patients, and ferritin for 112 (29.6%) patients. Abbreviations: AST: aspartate aminotransferase; ALT: alanine aminotransferase; HFNC: high flow nasal cannula; NVI: non-invasive ventilation. In the Cox proportional hazard model, the CURB-65 was strongly associated with a poor outcome (HR 1.84, 95%CI 1.10–3.09, P=0.020 for a CURB-65 of 2 compared to 0–1; and HR 4.18, 95% CI 2.54–6.86, p<0.001 for a CURB-65 of 3–5 compared to 0–1; P for linear trend <0.001). However, among patients with a CURB-65 of 0–1, thus considered at low risk, 36/171 (21.1%) had a poor outcome: 27 (15.8%) were transferred for ICU for HFNC and/or NIV (N=13), and/or invasive mechanical ventilation (N=19), and 15 (8.8%) patients died within the 14 days following admission (Figure 1 ). Figure 1 Description of the outcome according to the CURB-65 (N=279). Figure 1 Our results showed that the CURB-65 is associated with an unfavourable outcome, and thus its application as a severity score for COVID-19 might be promising. However, while the majority of our patients would have been considered at low risk of 30-day mortality according to this severity score, more than 20% of them had a poor outcome. Our study suggests that the applicability of CURB-65 to guide the decision of inpatient or outpatient care is scarce, as it does not safely identify patients who could be managed as outpatients. In studies of CURB-65 in the clinical practice of CAP, many patients with low CURB-65 scores are not suitable for outpatient treatment because many factors are not incorporated in the score, including hypoxemia requiring oxygen therapy, unmet social needs 6 . In addition, this score also appears to underestimate severity in young patients with CAP. Those limitations might also apply to COVID-19, whose epidemiology and severity also differ from CAP. COVID-19 is a systemic disease, and its severity might be due to virus-activated “cytokine storm syndrome”, exacerbated inflammatory responses. 7 Many known risk factors, such as cardiovascular history, D-dimers, Interleukin-6, but also the myocardial involvement of COVID-19 might not be captured by the CURB-65 8, 9, 10. Thus, we express our concerns regarding the use of the CURB-65 to guide the decision of inpatient or outpatient care for COVID-19. There is an unmet need to have easy-to-use scores to detect COVID-19 patients at risk, and to guide this decision. Declaration of Competing Interest None of the authors declared any competing interest in link with the present study.
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            A French Value Set for the EQ-5D-5L

            Objective The objective of this study was to develop a French value set for the EQ-5D-5L, for academic and clinical research, and for regulatory requirements for price-setting of drugs and medical devices. Method This study used the standardized valuation protocol developed by EuroQol, using computer-assisted personal interview software. A representative sample of 1048 French residents were interviewed by a market research company, under the supervision of the research team. Health states were valued using composite time trade-off and a discrete choice experiment. Modeling was used to create values for the 3125 possible health states. The composite time trade-off data were modeled using a Tobit model with censored observations at −1 and correcting for heteroscedasticity. A conditional logit model was used for the discrete choice results, and both models were combined using a hybrid model. An adjusted hybrid model was tested to correct for imbalance in the sample on age and sex compared with the general population. A comparison with the 3-level (3L) value set was performed. Results The adjusted model was preferred to comply with the representativeness of the general population. It provided a value set for which all coefficients were logically consistent. Values ranged from − 0.525 to 1. The distribution of values presented a shift towards higher values versus the 3L value set. Ranking of dimensions changed. Pain and discomfort and mobility were the dimensions with the highest potential for disutility compared with mobility and self-care for the 3L instrument. Conclusions This study provides a value set based on societal preferences of the French population, using an improved descriptive instrument of health-related quality-of-life health states. It will contribute to improve the quality of cost-effectiveness analysis in the French context and help stimulate disease-specific quality-of-life references for academic-, institutional-, and industry-promoted studies. Electronic supplementary material The online version of this article (10.1007/s40273-019-00876-4) contains supplementary material, which is available to authorized users.
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              Author and article information

              Contributors
              Journal
              J Infect
              J. Infect
              The Journal of Infection
              Published by Elsevier Ltd on behalf of The British Infection Association.
              0163-4453
              1532-2742
              25 August 2020
              25 August 2020
              Affiliations
              [1 ]Departement of Internal Medicine, AP-HP.Nord, Beaujon Hospital, University of Paris, Clichy, France
              [2 ]Department of Radiology, AP-HP.Nord, Beaujon Hospital, University of Paris, Clichy, France
              [3 ]Department of Anaesthesiology and Intensive Care, AP-HP.Nord, Beaujon Hospital, University of Paris, Clichy, France
              [4 ]Centre for Epidemiology and Population Health, INSERM U1018, Villejuif, France
              Author notes
              [* ]Corresponding author. yann.nguyen2@ 123456aphp.fr
              Article
              S0163-4453(20)30562-4
              10.1016/j.jinf.2020.08.029
              7445491
              © 2020 Published by Elsevier Ltd on behalf of The British Infection Association.

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