Health outcomes of COVID-19 patients from Wuhan, China 3-year after hospital discharge: a cohort study

Abstract

Objectives

To evaluate changes in health outcomes between years 2 and 3 after discharge following COVID-19 and to identify risk factors for poor health 3-year post-discharge.

Design

This is a multicentre observational cohort study.

Setting

This study was conducted in two centres from Wuhan, China.

Participants

Eligibility screening has been performed in 3988 discharged laboratory-confirmed adult COVID-19 patients. Exclusion criteria were refusal to participate, inability to contact and death before follow-up. The WHO COVID-19 guidelines on defining disease severity were adopted.

Results

1594 patients participated in the 1-year, 2-year and 3-year follow-ups, including 796 (49.9%) male patients, and 422 (26.5%) patients were classified in the severe disease group. 3 years after discharge, 182 (11.4%) patients still complained of at least one symptom. The most common symptoms were fatigue, myalgia, chest tightness, cough, anxiety, shortness of breath and expectoration. Fatigue or myalgia, the most common symptom cluster, frequently coexisted with chest symptoms and anxiety. Symptom persistence between years 2 and 3 was reported in 70 patients (4.4%) for which intensive care unit (ICU) admission was a risk factor (p=0.038). Of the 1586 patients who completed the chronic obstructive pulmonary disease assessment test (CAT), 97 (6.1%) scored ≥10, with older age being associated with CAT ≥10 (p=0.007).

Conclusions

Between years 2 and 3 after SARS-CoV-2 infection, most patients returned to an asymptomatic state, and only a few were still symptomatic. ICU admission was a risk factor for symptom persistence.

Correspondence to Dr Li Li; [email protected]

Strengths and limitations of this study

• Symptom dynamic analysis of long COVID-19 between year 2 and year 3 was performed.

• We performed symptom clustering to describe long COVID-19 in detail.

• Chronic obstructive pulmonary disease assessment test scoring was used to quantitatively assess the symptom burden of long COVID-19.

• Lacking of a control group without SARS-Cov-2 infection.

• A relatively high percentage of lost to follow-up may introduce bias.

Introduction

As of 5 April 2023, the worldwide pandemic of COVID-19 has caused at least 760 million infections and more than 6 million deaths. The data is still growing as variants of SARS-CoV-2 continue to emerge and spread.^{1 2} Although mortality rates following SARS-CoV-2 infection have decreased as a consequence of public health policies, vaccination and antiviral therapies,^3–5 many patients suffered from the emerging post-acute sequelae of COVID-19, or long COVID-19, leading to deterioration in quality of life, and persistent disabilities.^6–8 Continuous follow-up is necessary for understanding the long-term health outcomes of COVID-19.

Previous studies reported that various health-related problems may persist after recovery from the acute phase of SARS-CoV-2 infection. A longitudinal cohort study involving 1192 survivors showed improvement in health status 2 years after hospital discharge, but the burden of symptomatic sequelae remained high.⁹ Recently, it was reported that the incidence of long COVID-19 is 10%–30% of non-hospitalised cases and 50%–70% of hospitalised cases, respectively.^{10 11} In 2022, another meta-analysis involving 41 studies indicated that the global pooled long COVID-19 prevalence was estimated to be 43%.¹² In a national cohort study involving more than 5 million COVID-19 patients, a higher risk of developing mental health disorders was found 2 years after infection.¹³ We have previously also reported symptoms of COVID-19 survivors at 1 year and 2-year follow-ups, and the most common symptoms were fatigue, chest tightness, anxiety, dyspnoea and myalgia.^{14 15} In the current study, we investigated the trajectory of symptom status in COVID-19 survivors 3 years after discharge and analysed risk factors associated with the persistence of symptoms.

Methods

Study design and patients

This is an observational prospective cohort study. The participants in the study are COVID-19 survivors discharged from Huoshenshan Hospital and Taikang Tongji Hospital in Wuhan, China, between 12 February and 10 April 2020. All discharged patients were included in the screening. Exclusion criteria were refusal to participate, inability to contact and death before follow-up. Follow-up was done by telephone contact using information recorded in their medical records. The patients were followed up at years 1, 2 and 3 after hospital discharge. The 3-year follow-up study was conducted between 1 March and 1 April 2023, and the data were analysed from 2 April to 20 April. This study was reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

Procedures and data acquisition

We contacted all patients in the order of their discharge dates as recorded in the medical records, and two additional contacts were attempted for patients who did not respond to the first telephone interview. Each patient received a standardised telephone interview and completed a self-reported symptom questionnaire and the chronic obstructive pulmonary disease assessment test (CAT). CAT is an appropriate questionnaire to evaluate COPD patients’ life quality, which has good measurement properties.^{16 17} In 2020, Daynes et al used CAT to evaluate the symptom burden of COVID-19 patients and used 10 as the cut-off score, and concluded that the CAT is a useful tool to assess symptoms of COVID-19 recovery.¹⁶ In our previous studies,^{14 15} we described the symptoms reported by patients during hospitalisation and presenting at 1 year and 2-year follow-ups, which were used as the basis for designing the questionnaire for the current study (online supplemental table S1). Symptoms included in the questionnaire were graded using a Likert scale into four levels: no problem, mild problem, moderate problem and severe problem. The presence of symptoms was defined as at least one problem being rated as moderate or severe. The questionnaire was based on the WHO’s definition of long COVID-19, which states that if the presence of one or more respiratory or systemic symptoms, or organ dysfunction persists for at least 2 months after the initial 12 weeks post-SARS-CoV-2 infection, and cannot be explained by other known aetiologies, it is classified as long COVID-19. Patients were classified into four categories based on the change in symptom status between year 2 and year 3 as¹ Symptom persistence: at least one symptom at years 2 and 3.² Symptom relief: symptomatic at year 2 but asymptomatic at year 3.³ New-onset symptom: asymptomatic at year 2 but symptomatic at year 3, or mild symptoms at year 2 worsened to moderate or severe at year 3.⁴ No symptom: asymptomatic at years 2 and 3.

Our previous studies described how clinical data were collected from patients’ electronic medical records, including self-reported demographic characteristics (age, sex and cigarette smoking) and clinical characteristics (comorbidities and symptoms).^{14 15} The WHO COVID-19 guidelines on the definition of the severity of the disease were adopted. A person with fever or suspected respiratory infection was defined as having severe pneumonia if one of the following conditions was presented: respiratory rate greater than 30 breaths per minute, severe respiratory distress or oxygen saturation as measured by pulse oximetry (SpO₂) less than or equal to 93% on room air.¹⁸ We double-entered and validated all data using EpiData software V.3.1 (EpiData Association).

Statistical analysis

Continuous variables were first tested for conformity to a normal distribution. Depending on the distribution, the mean (SD) or median (quartile 1–3) was chosen to represent them, and comparisons between groups were made using the Student t-test or the Mann-Whitney U test. Categorical variables were expressed as absolute values with percentages and then subjected to the Pearson χ2 test or Fisher exact test where appropriate. We compared baseline characteristics of enrolled patients with the lost to follow-up population and those who dropped since year 2, and a 1:1 propensity score matching (PSM) was applied between enrolled patients and all lost to follow-up population based on age, sex, disease severity and coexisting diseases. Symptom clustering, examined to further characterise the symptoms, was implemented in a two-step process as described previously.¹⁹ Briefly, after identifying strongly correlated self-reported symptoms using exploratory multivariable factor analysis (using oblimin rotation) and determining the ideal number of factors using ‘parallel’ analysis, each symptom was included in the cluster with the highest factor loadings, with some adjustment for certain clusters based on their clinical characteristics. To explore risk factors associated with presenting symptoms, symptom persistence and CAT ≥10, we did a two-step analysis. First, we used univariable logistic regression models to identify factors with p<0.10. Second, we performed multivariable logistic regression analysis by a stepwise (forward likelihood ratio) selection process, whereas age, sex and disease severity were forced into the model because of their importance. All tests were two-sided, and p<0.05 was considered significant. SPSS statistical package 26.0 for Windows (IBM SPSS Statistics) and R statistical software V.4.1.1 were used for all statistical analyses.

Results

Patient characteristics

Of 3988 discharged COVID-19 survivors, 1594 patients participated in all three interviews and were included in the final analysis (figure 1), among whom, 796 (49.9%) were male and 422 (26.5%) were categorised as having severe disease (table 1). The median (quartile 1–3) age was 58.0 (49.0–67.0) years and the median (quartile 1–3) duration of hospital stay was 14^9–20 days (table 1). The mean (SD) time from discharge to follow-up was 34.9 (0.7) months at year 3 (table 1). During hospitalisation, 11 (0.7%) patients received mechanical ventilation and 26 (1.6%) patients were admitted to intensive care unit (ICU) (table 1). The 2394 lost to follow-up patients were older and had a higher rate of severe disease, more coexisting disorders and a higher percentage receiving mechanical ventilation and ICU admission. However, no statistical differences were found between enrolled and lost to follow-up patients in terms of sex, smoking or duration of hospital stay (table 1). 270 patients were lost to follow-up between years 2 and 3, who were older, had a higher percentage of ICU admission in 2020 (online supplemental table S2) and a higher rate of at least one symptom at year 2 (lost to follow-up vs enrolled, 90 [33.3%] vs 289 [18.1%], p<0.0001, online supplemental table 1).

Figure 1. Study flowchart.

Table 1

Characteristics of enrolled patients

Characteristic	Patients, no. (%)				P value
	Enrolled patients (n=1594)	Severe (n=422)	Non-severe (n=1172)	Lost to follow-up (n=2394)	Enrolled patients vs lost to follow-up	Severe vs non-severe
Age, median (quartile 1–3), years*	58.0 (49.0–67.0)	63.0 (54.0–71.0)	57.0 (46.0–65.0)	63.0 (52.0–71.0)	<0.0001	<0.0001
Sex
Male	796 (49.9%)	225 (53.3%)	571 (48.7%)	1184 (49.5%)	0.79	0.12
Female	798 (50.1%)	197 (46.7%)	601 (51.3%)	1210 (50.5%)
Severe disease	422 (26.5%)			719 (30.0%)	0.02
Cigarette smoking					0.50	0.52
Never	1464 (91.8%)	393 (93.1%)	1071 (91.4%)	2216 (92.6%)
Former	29 (1.8%)	6 (1.4%)	23 (2.0%)	33 (1.4%)
Active	101 (6.3%)	23 (5.5%)	78 (6.6%)	145 (6.0%)
Coexisting disorders					<0.0001	<0.0001
0	922 (57.8%)	192 (45.5%)	730 (62.3%)	1223 (51.1%)
1	400 (25.1%)	120 (28.4%)	280 (23.9%)	653 (27.3%)
≥2	272 (17.1%)	110 (26.1%)	162 (13.8%)	518 (21.6%)
Hypertension	450 (28.2%)	167 (39.6%)	283 (24.1%)	790 (33.0%)	0.002	<0.0001
Diabetes mellitus	220 (13.8%)	81 (19.2%)	139 (11.9%)	347 (14.5%)	0.56	0.0002
Cardiovascular diseases	144 (9.0%)	58 (13.7%)	86 (7.3%)	267 (11.2%)	0.04	<0.0001
Chronic liver diseases	87 (5.5%)	22 (5.2%)	65 (5.5%)	125 (5.2%)	0.80	0.89
Cerebrovascular diseases	27 (1.7%)	10 (2.4%)	17 (1.5%)	148 (6.2%)	<0.0001	0.30
Chronic kidney diseases	35 (2.2%)	12 (2.8%)	23 (2.0%)	71 (3.0%)	0.17	0.39
Tumour	28 (1.8%)	11 (2.6%)	17 (1.5%)	59 (2.5%)	0.17	0.18
Tracheitis	24 (1.5%)	10 (2.4%)	14 (1.2%)	54 (2.3%)	0.12	0.14
COPD	12 (0.8%)	6 (1.4%)	6 (0.5%)	39 (1.6%)	0.02	0.13†
Length of hospital stay, days*	14.0 (9.0–20.0)	15.0 (9.0–23.0)	14.0 (9.0–19.0)	14.0 (9.0–20.0)	0.91	<0.0001
Follow-up time, months	34.9 (0.7)	34.7 (0.6)	34.9 (0.7)	NA	NA	<0.0001
ICU admission	26 (1.6%)	22 (5.2%)	4 (0.3%)	82 (3.4%)	0.001	<0.0001
Oxygen therapy	1150 (72.1%)	374 (88.6%)	776 (66.2%)	1750 (73.1%)	0.53	<0.0001
Mechanical ventilation	11 (0.7%)	10 (2.4%)	1 (0.1%)	36 (1.5%)	0.02	<0.0001†

*Mann-Whitney U test.

†Fisher’s exact test. The rest of the statistical tests were calculated with the Pearson χ² test.

COPD, chronic obstructive pulmonary disease; ICU, intensive care unit; NA, not applicable.

Characteristics of long-term symptoms at 3 year follow-up

The detailed symptoms of enrolled patients are listed in online supplemental table S4. Overall, there was a decreasing trend in the percentages of patients with symptoms: 692 (43.4%) at year 1, 289 (18.1%) at year 2 and 182 (11.4%) at year 3 (figure 2A and online supplemental table S4). The most common symptoms (incidence ≥1%) were fatigue (85 [5.3%]), myalgia (33 [2.1%]), chest tightness (32 [2.0%]), cough (24 [1.5%]), anxiety (22 [1.4%]), shortness of breath (19 [1.2%]) and expectoration (17 [1.1%]) (figure 2A and online supplemental table S4). Compared with the 2394 who were lost to follow-up, during hospitalisation in 2020, the enrolled patients reported a higher percentage of fatigue (p=0.03) and shortness of breath (p=0.03) (online supplemental table S5). After PSM, 1498 enrolled patients (94.0%) were successfully matched to those lost to follow-up, and no significant differences were found in baseline characteristics (online supplemental table S6). The most common symptoms in the PSM population were similar to enrolled patients (online supplemental table S7). Based on the correlation between them, the 20 symptoms included in this study could be combined into 10 symptom clusters, with fatigue or myalgia being the most common symptom cluster, which co-occurred with chest symptoms, upper respiratory symptoms and anxiety (figure 2B).

Figure 2. Symptoms of COVID-19 survivors during 3-year follow-up. (A) Percentage of patients presenting with COVID-19-related symptoms at 1-year, 2-year and 3-year follow-up. (B) Co-occurrence network of symptom clusters 3 years after hospital discharge. Outer circles represent individual symptoms. The outer circle area represents the proportion of participants with that symptom. These are linked to inner circles, which represent symptom clusters. The width of the link lines also represents the proportion of patients with that symptom. The circle area for clusters represents the proportion of participants with at least one symptom from that cluster. Central link lines between symptom clusters represent the co-occurrence of symptom clusters. Line width represents the degree of co-occurrence. (C, D) Proportion of different symptoms in the symptoms persist group and new-onset symptoms group at 3-year follow-up. (E) Factors associated with sequelae at 3-year follow-up. (F) Factors associated with sequelae of respiratory system at 3-year follow-up.

Changes in symptoms between years 2 and 3

Symptom persistence between years 2 and 3 was reported by 70 (4.4%) patients, and the rate was higher in the severe disease group (severe vs non-severe, 26 [6.2%] vs 44 [3.7%], p=0.04, table 2). No significant differences were found between the severe and non-severe groups in patients who presented symptom relief, new-onset symptom or no symptom (table 2). The five most common symptoms in patients with symptom persistence and new-onset symptom were fatigue, myalgia, chest tightness, cough and anxiety (figure 2C and D). Of the PSM population, a non-significant higher incidence of symptom persistence was found between severe and non-severe groups (online supplemental table S8).

Table 2

Symptom dynamics of COVID-19 survivors according to disease severity

Categories	Number of symptoms		Patients, no. (%)			P value Severe vs non-severe
	2 years	3 years	Enrolled patients	Severe	Non-severe
Total			1594 (100.0)	422 (100.0)	1172 (100.0)
Symptom persist	≥1	≥1	70 (4.4)	26 (6.2)	44 (3.7)	0.04
Symptom relief	≥1	0	219 (13.7)	66 (15.6)	153 (13.1)	0.19
New-onset symptom	0	≥1	112 (7.0)	24 (5.7)	88 (7.5)	0.21
No symptom	0	0	1193 (74.9)	306 (72.5)	887 (75.7)	0.20

‘Symptom persist’ refers to patients with at least one symptom at both 2-year and 3-year follow-up.

‘Symptom relief’ refers to patients with at least one symptom at 2-year follow-up but without any symptom at 3-year follow-up.

‘New-onset symptom’ refers to patients without any symptoms at 2-year follow-up but reported at least one symptom at 3-year follow-up.

‘No symptom’ refers to patients with no symptom at any follow-up.

To explore the risk factors associated with symptoms at year 3, we performed a logistic regression model analysis. Using a univariable analysis, ICU admission (OR, 2.93; 95% CI, 1.13 to 6.78; p=0.017) and mechanical ventilation during hospitalisation (OR, 5.27; 95% CI, 1.34 to 18.61; p=0.011) were associated with presence of at least one symptom; however, multivariable analysis showed that only mechanical ventilation (OR, 5.30; 95% CI, 1.44 to 19.51; p=0.012) was a risk factor (figure 2E and online supplemental table S9). For respiratory system sequelae, ICU admission was identified as a risk factor in both univariable (OR, 4.42; 95% CI, 1.26 to 11.97; p=0.008) and multivariable analysis (OR, 5.07; 95% CI, 1.59 to 16.21; p=0.006) (figure 2F and online supplemental table S10). ICU admission was also associated with higher risk of fatigue (OR, 3.34; 95% CI, 0.96 to 8.97; p=0.03) and symptom persistence (OR, 4.14; 95% CI, 1.07 to 17.13; p=0.038) in univariable analysis (online supplemental table S11 and S12).

CAT scores at Year 3

At year 3, 8 of the 1594 enrolled patients did not complete the CAT. The median (quartile 1–3) CAT score of the remaining 1586 COVID-19 patients was 0 (0–3) and no significant difference was found between severe and non-severe groups (figure 3A and online supplemental table S13). 97 (6.1%) patients had CAT scores ≥10, with a higher percentage in the severe group (severe vs non-severe, 31 [7.5%] vs 66 [5.6%]) (figure 3B and online supplemental table S14). After analysing each item of the CAT score, sleep disorder and energy lacking were the most common disorders (figure 3C and online supplemental table S15). Only age (OR, 1.02; 95% CI, 1.01 to 1.04; p=0.007) was associated with increased risks for CAT ≥10 using univariable analysis (online supplemental table S16), while the p values of other factors were not significant.

Figure 3. Total and item chronic obstructive pulmonary disease (COPD) assessment test (CAT) scores in patients at 3-year follow-up. (A) Total CAT score at 3 years after patient discharge; lines within bars denote means, and error bars denote 95% CIs. (B) Percentage of patients with CAT score 10 or higher and less than 10. (C) Histogram of responses to individual CAT items; confidence refers to a CAT item concerning confidence leaving the home.

Discussion

The current study found that of 1594 discharged COVID-19 patients at 3-year follow-up, 11.4% were still symptomatic, and the most common symptoms were fatigue, myalgia, chest tightness, cough, anxiety, shortness of breath and expectoration. During the period from year 2 to year 3, only 4.4% of patients showed symptom persistence, for which, ICU admission was a risk factor. The majority of patients had very low CAT scores and only 6.1% had a score ≥10.

Fatigue or myalgia was the most common symptom cluster. In a systematic review and meta-analysis involving 52 studies, the two most frequent symptoms within 1 year after SARS-CoV-2 infection were fatigue and dyspnoea/breathlessness.²⁰ A further systematic review and meta-analysis reporting 1 year follow-up data on 8591 COVID-19 patients found that fatigue, dyspnoea and arthralgia/myalgia were the most common symptoms.²¹ This suggests that while respiratory symptoms gradually resolve over time, motor system symptoms such as fatigue/myalgia recover more slowly. ICU admission was associated with symptom persistence in univariable analysis but not significant in multivariable regression analysis. Weihe and colleagues found that long-term cognitive functional impairment was found in up to one in four of COVID-19 patients who had been admitted to ICU at both 6 and 12 months.²² Similarly, in a systematic review and meta-analysis that included 12 studies involving 1 289 044 participants from 11 countries, it was reported that patients with severe COVID-19 disease (admitted to the ICU or requiring mechanical ventilation) were at greater risk for long-term sequelae.²³ In the current study, the lack of statistical significance for ICU admission under multivariable regression analysis may be due to the small sample size or the effect of ICU admission waning over time.

The most common disorders in the CAT items were sleep disorder and energy lacking. In univariable analysis, only age was associated with risk factors for CAT ≥10. This may be due to declining lung function in patients with increasing age since a progressive decline in physical function and a gradual increase in the incidence of chronic age-related diseases in older adults has been reported.²⁴ Other studies found that older adults are at higher risk for the harmful health effects of SARS-CoV-2.^{25 26} But, Subramanian and colleagues reported that the risk of developing long COVID-19 increased along a gradient of decreasing age.²⁷ Clearly, more studies are needed to explore the relationship between age and long COVID-19, and the older population requires more attention.

There are several limitations to this study. First, 60.0% of discharged patients were lost to follow-up, who differed from enrolled patients regarding several baseline characteristics, which may introduce bias. Second, data was collected using telephone follow-ups, which may lead to errors or omissions in information collection compared with face-to-face interviews. Also, enrolled patients completed a self-reported symptom questionnaire, which may lead to subjective bias. Third, since China implemented a new COVID-19 management policy starting in December 2022, some patients were reinfected after that time. Although we asked patients at follow-up to give feedback only on the sequelae that existed after the infection in 2020, infection of SARS-CoV-2 again or other respiratory diseases may lead to changes in symptom status, which may have biased symptom reporting. What is more, patients who are complicated with pre-existing disease may progress, so the lack of a control group without SARS-CoV-2 infection became another limitation. In addition, the current cohort is only a subpopulation of all COVID-19 patients, and different subpopulations may have different incidence of long COVID-19, especially, at 3 years after discharge. For example, in 2021, Michael and colleagues found that 20%–30% of outpatient COVID-19 individuals and up to 80% of hospitalised COVID-19 patients had persistent long COVID-19 symptoms.²⁸ Therefore, the results of this study represent only the 3-year follow-up of hospitalised COVID-19 patients after discharge, and studies with larger sample sizes are needed to comprehensively explore the characteristics of long COVID-19, which requires a worldwide effort. Finally, variants of SARS-Cov-2 virus continue to emerge and spread, and the impact of new variants on the pattern and extent of recovery may differ.

Conclusions

In the current prospective cohort study, 88.6% of COVID-19 patients were no longer symptomatic 3 years after discharge, but a small number of patients still had persistent symptoms. ICU admission was associated with symptom persistence.

Thanks to all the patients and their families. Thanks to all staff at Wuhan Huoshenshan Hospital and Wuhan Taikang Tongji Hospital during the COVID-19 pandemic.

Data availability statement

Data are available upon reasonable request. The raw data supporting the conclusions of this article will be made available upon reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

This study involves human participants and was approved by Ethics Committee of the Daping Hospital, Third Military Medical University (Army Medical University); 2021-53. Participants gave informed consent to participate in the study before taking part.

Footnote

YD, YW, XYY, QHW, BMH and MW contributed equally.

Contributors LL is responsible for the overall content as guarantor. QXM, PWJ, LZ, GC, JJ, YH and CB critically reviewed the study proposal. YD, BMH, MW, JJ, LXC, FYZ, TQ and MYZ collected data. LL, YD, YW, XYY, QHW, YHL, QXM, PWJ and CB did the analysis or interpretation of data. LL, YD, YW, XYY and JJ drafted the paper. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Funding This work was supported by the National Natural Science Foundation of China (82272908, U23A20393), the Natural Science Foundation of Chongqing (CSTB2023NSCQ-JQX0033,CSTB2022NSCQ-JQX0017,CTSC2020jcyjjqX0014) and Science-Health Joint Medical Scientific Research Project of Chongqing (2023MSXM127).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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