This project is a case-control study conducted during the decline of the coronavirus disease (COVID-19) pandemic in Tunisia ( eg ; September 2020). The study was conducted in collaboration with the department of physiology at the faculty of medicine of Sousse (Sousse, Tunisia) and three departments from Farhat HACHED hospital in Sousse ( ie ; infectious diseases, biochemistry, and hematology). The study was conducted following the guidelines established by the STROBE statement. ²⁴

Each participant received comprehensive information about the study’s objectives, procedures, potential risks, and other pertinent details. After this thorough briefing, we obtained written informed consent from all participants, confirming their voluntary involvement in the study. Additionally, each participant was provided with a report of his/her individual evaluations.

Two groups of participants ( ie ; cases and controls) were recruited ( Figure 1).

Cases were selected from patients followed for VHB infection, who had undergone histological evaluation by liver biopsy (LB) or fibroscan within the last four years prior to inclusion in the study at the above infectious diseases department. Diagnosis of hepatitis B virus (HBV) infection was based on a positive result for hepatitis B surface antigen (HBsAg) for at least six months. Patients were eligible for inclusion if they were aged between 25 and 55 years, had an HBV-DNA viral load higher than 2000 IU/ml confirmed at least one year prior to inclusion, and showed no significant pathological fibrosis, as indicated by a fibroscan score less than 6 kPa and/or a “meta-analysis of histological data in viral hepatitis” score less than A2F2. Exclusion criteria were as follows: physical or mechanical impairments that could interfere with the 6MWT such as a history of orthopedic or rheumatologic diseases, contraindications for the 6MWT like signs of unstable angina or myocardial infarction within the previous month, resting heart-rate (HR) higher than 120 bpm, systolic blood pressure higher than 180 mmHg, or diastolic blood pressure hgher than 100 mmHg), ¹⁶ comorbidities such as respiratory or cardiovascular diseases, systemic conditions that could influence blood test results like diabetes mellitus or renal failure, consumption of alcohol, co-infection with other viruses, liver damage, or the requirement for CHB treatment during the study period.

Controls were “apparently” healthy participants, non-alcohol consumers, aged between 25 and 55 years, without any chronic disease, physical problems, COVID-19 infection, or 6MWT contraindications. ¹⁶

Participants from both groups with missing biological data were excluded from the final statistical analysis.

The sample size was calculated using this equation ²⁵ : N = ( ( r + 1 ) ( Z α / 2 + Z 1 − β ) 2 s 2 ) / ( rd 2 ) ; where •

“ N” is the the required number of participants ( N = n ₁ + n ₂, such as n ₁ and n ₂ are the sample sizes for the case and control groups);

Inserting these values into the predictive equation resulted in a total sample size of 54 participants (27 in each group). Assuming a 10% loss of biological data, a revised sample size of 60 participants was determined (60 = 54/(1-0.10)).

The explorations were conducted indoor between 8:00 AM and 12:00 PM, with four participants examined per day, and an average time of 60 minutes per participant. The study protocol included the following steps: •

Signing of consent and completion of medical questionnaires.

A questionnaire comprising three parts was administered by one qualified examiner ( JB in the authors’ list). The mean duration of the questionnaire was approximately 20 minutes.

The first part was a standard medical questionnaire (widely used in the infectious diseases and physiology departments) aiming at collecting clinical and socioeconomic data. Questions were asked in Arabic. Clinical histories, such as previous hospitalization, comorbidities, and viral co-infections were recorded. Cigarettes smoking was evaluated in pack-years, and participants were classified into two groups (non-smoker: <5 pack-years; smoker ³ : 5 pack-years). ⁶ Depending on alcohol consumption habits, participants were classified into two groups (consumer/non-consumer). ⁶ Socioeconomic-level was determined according to the participant’s profession, with two levels defined ( ie ; unfavorable and favorable). ⁶ Schooling level was arbitrarily defined as low and high. ⁶ Parity (the number of children born to a woman) was noted. Since the 2023 Tunisian global fertility rate was 2.09 children per woman, a parity greater than two was considered “high”. ^{26, 27}

The second part of the questionnaire was linked to the physical-activity level, which was estimated using the Voorrips questionnaire. ²⁸ This questionnaire is reproducible, and its score is positively related to the 24-hour measurement of the physical-activity as assessed by a pedometer. ²⁸ While the Arabic version is not validated, it has been widely used in previous studies. ^{29– 31} This questionnaire contains 51 items assessing various scores, which are divided into three categories of physical-activity ( ie ; daily, sports, and leisure activities). The sum of the three scores represents the total physical-activity score. According to the total score, participants were divided into two groups: sedentary (score <9.42) and active (score ≥9.42). ²⁸

The third part of the questionnaire is related to the evaluation of quality-of-life using the Chronic liver diseases questionnaire. ³² Data from this part will be analyzed in a subsequent study.

Age (in years) and sex and were documented for each participant. Height was measured in centimeters using a Siber Hegner ^® standing stadiometer, with participants standing upright, without shoes, heels together, and back straight. Weight (in kilograms), muscle mass (in percentage), and body fat (in percentage) were assessed using a Beurer BF-600 (Beurer GmbH, Germany) bioelectrical impedance analyzer in the morning after an overnight fast, with participants in a standing position. ³³ Body mass index (BMI, kg/m ²) was determined. Participants corpulence status was categorized based on BMI as follows: underweight (BMI < 18.5 kg/m ²), normal weight (BMI: 18.5–24.9 kg/m ²), overweight (BMI: 25–29.9 kg/m ²), and obesity (BMI ≥ 30 kg/m ²). All measurements were conducted by a single qualified examiner ( JB in the authors’ list).

Some biological data ( eg ; hemoglobin, erythrocyte-sedimentation-rate, C-reactive-protein, interleukin-6, alkaline-phosphatase, alanine-aminotransferase, aspartate-aminotransferase, gamma-glutamyl-transpeptidase, total-bilirubin, non-conjugated bilirubin, ( ie ; antioxidant stress marker), ³⁵ albumin ( ie ; antioxidant stress marker), ^{36, 37} and uric-acid ( ie ; oxidant-antioxidant balance marker) ³⁸ were collected by a nurse. Some of these biological data and their technical aspects were detailed elsewhere. ^{6, 7}

Handgrip-strength, the technique and findings of which were detailed elsewhere, ^{6, 7} was performed by one qualified examiner ( JB in the authors’ list). For this study, the highest absolute handgrip-strength value (kg) between the two hands of each participant was retained.

Sub-maximal aerobic capacity was evaluated using the 6MWT, supervised by one qualified examiner ( IL in the authors’ list). Participants were asked to wear comfortable clothing and appropriate footwear for walking, and to avoid strenuous exercise in the two hours preceding the 6MWT. ¹⁶ A single 6MWT was performed in a 40 m flat corridor indoor ( ie ; physiology department), which was marked every meter with start and end indicators. ³⁹ Instructions given before the 6MWT followed the most updated guidelines, ^{16, 39} which included “walk as far as possible for 6 minutes”. Participants were informed that they could slow down, stop, rest as needed, and resume walking when able. ^{16, 39} They were instructed not to run under any circumstances, and no encouragement or walking aids were provided during the 6MWT. ^{16, 39} The remaining time was announced every minute ( eg ; you have × minutes left). ^{16, 39} The examiner did not walk with the participants to avoid influencing their walking speed.

The following 6MWT data were recorded: HR [bpm, % of maximal predicted HR (MPHR (bmp) = 208-0.7×Age (year))], ⁴⁰ dyspnea (absolute value), blood-pressure (mmHg), oxy-hemoglobin saturation (SpO ₂, %), number of stops while walking, and 6MWD (m, %). Additional relative 6MWD indices, including the product between 6MWD and weight ( ie ; 6-min walk work (6MWW, m.kg)), ⁴¹ BMI (m.kg/m ²), muscle-mass (m.kg), body-fat (m.kg), and SpO _2End (%m) were calculated. HR, SpO ₂, blood-pressure, and dyspnea were measured while the participant was seated at rest ( _Rest) and immediately at the end ( _End) of the 6MWT. ^{16, 39} HR and SpO ₂ were measured using a handheld pulse oximeter (M700, Biolight CO., LTD. China), and blood-pressures were measured using a manual tensiometer and a stethoscope. Delta (∆) HR and SpO ₂ ( ie ; ∆HR (bpm) = HR _End – HR _Rest, ∆SpO ₂ = SpO _2End - SpO _2Rest) were calculated. Dyspnea was measured on a visual analog scale (VAS) ranging from 0 (no dyspnea) to 10 (maximum dyspnea). ⁴²

The 6MWD was expressed both in absolute value (m) and as a percentage of the predicted 6MWD. ^{22, 43} For participants under 40 years of age, the following predictive equation for 6MWD specific to the North African population was applied: 6MWD (m) = 800.05-64.71 × Sex (0: Man; 1: Woman) - 10.23 × BMI (kg/m ²) - 1.63 × Age (years) + 2.05 × Weight (kg). ⁴³ For this group, the lower limit of normal (LLN) was calculated by subtracting 74.31 m from the predicted 6MWD value. ⁴³ For participants older than 40 years of age, the following predictive equation for 6MWD specific to the North African population was applied: 6MWD (m) = 720.50-160.27 × Sex (0: Man; 1: Woman) - 5.14 × Age (years) - 2.23 × Weight (kg) + 271.98 × Height (m). ²² For this group, the LLN was calculated by subtracting 89 m from the predicted 6MWD value. ²²

Since the 6MWT assesses the integrated response of the CRMC, ^{39, 44} its estimated age (ECRMC) was calculated using the following formulas: ECRMC (years) = 184.25-0.36 × measured 6MWD (m) + 44.39 × Height (m) - 13.87 × Sex (0: Man; 1: Woman); for participants under 40 years of age ⁴⁵ ; and ECRMC (years) = 140.17-0.19 × measured 6MWD (m) - 31.18 × Sex (0: Man; 1: Woman) - 0.43 × Weight (kg) + 52.91 × Height (m); for participants aged 40 years and more. ⁴⁵

The following definitions were applied based on previous studies ^{22, 46, 47} : i)

Signs of walking intolerance: abnormal 6MWD ( ie ; 6MWD < lower limit of normal), stopping while walking, high dyspnea ( ie ; dyspnea _End >5/10);

The distribution of quantitative data was analyzed using the Shapiro-Wilk W test. Data were expressed as means±SD (and 95% confidence intervals) when the normality test was met. If not, data were presented as medians (interquartile range). The Wilcoxon matched-pairs test was used to compare chronological and ECRMC ages within each group. Two significant approaches were applied: i) Quantitative (statistical) approach: The Mann-Whitney U and Chi-2 tests were used to compare quantitative and categorical data, respectively, between the two groups; and ii) Qualitative (clinical) approach: The percentages of participants with walking intolerance signs, desaturation, chronotropic insufficiency were compared using the 2-sided Chi-2 test. Hedge’s unbiased d value was used to measure the effect size of the main outcome (6MWD). ⁴⁸ The effect size was described as small (≤0.2), medium (around 0.5), large (around 0.8), or very large ( ³1.30). ⁴⁸

All statistical procedures were performed using. STATISTICA (data analysis software system, version 12. www.statsoft.com, RRID: SCR_014213). The significance level was set at p<0.05.

The CHB-group had a lower 6MWD by approximately 61 m compared to the control-group, aligning with the Saudi study, ¹¹ which reported a difference of about 41 m. Additionally, the CHB-group exhibited an approximately 8% lower 6MWD expressed as a percent of predicted value (Appendix 1). No previous study have expressed the 6MWD as a percent of a predicted value. Relative 6MWD indices in CHB patients have not been previously evaluated. Compared to the control group, the CHB group had lower 6MWW by ≈5266 m.kg, “6MWDxBMI” by ≈1498 m.kg/m ², and “6MWDxSpO _2End” by ≈5650 %m, while “6MWDxmuscle-mass” and “6MWDxbody-fat” values were comparable between the groups. There are no prior case-control studies evaluating these indices in chronic disease patients. The 6MWW, reflecting the work done during the 6MWT, has been assessed in conditions such as HIV infection and chronic obstructive pulmonary disease, which reported lower 6MWWs in chronic patient. ^{49– 51}

No previous studies have compared HR, SpO ₂, blood-pressure, and dyspnea data between CHB and control groups. Compared to the control-group, the CHB-group had lower HR _End (bpm and %PMHR) by ≈26 and ≈12, respectively, and ΔHR by ≈26 bpm, with a higher percentage of patients exhibiting chronotropic insufficiency (4% vs. 23%) (Appendix 1). Despite being “apparently” free from cardiovascular diseases, chronotropic insufficiency in CHB patients could be a preclinical sign of incipient cardiovascular pathology, as 3% of CHB patients are reported to develop cardiovascular diseases. ¹²

Compared to the control-group, the CHB-group had a higher ΔSpO ₂, but comparable SpO _2Rest and SpO _2End (Appendix 1). The higher ΔSpO ₂ observed in our CHB-group lacks clinical significance as both groups had comparable SpO ₂ values, and no participant experienced “clinically significant desaturation”. This suggests that the alveolo-capillary membrane remains intact.

Both groups had comparable blood-pressure and VAS dyspnea (Appendix 1), indicating that CHB does not significantly affect blood-pressure or dyspnea.

Compared to the control-group, the CHB-group had a higher ECRMC’ age by ≈23 years ( Table 1). The ECRMC age for the CHB and control groups was higher by ≈11 years and lower by ≈12 years compared to chronological age, respectively. This indicates accelerated CRMC aging, similar to findings reported in diabetic patients. ⁵²

Factors explaining the decline in 6MWD and acceleration of CRMC aging in NC-CHB patients

Several factors may explain the decline in 6MWD and the acceleration of CRMC aging in NC-CHB patients, including comorbidities ( eg ; cardiac, respiratory, and/or muscular diseases), patient characteristics ( eg ; age, corpulence status, schooling-level, socioeconomic-level, sedentarily lifestyle), parity, and smoking habits.

Chronotropic insufficiency may partly explain the 6MWD decrease, as seen in previous studies involving obstructive sleep apnea-hypopnea-syndrome (OSAHS) patients, ⁴⁵ diabetic patients, ⁵² or narghile-smokers. ³¹ Although the impact of CHB on sinus node activity during walking was not documented, it affects sinoatrial node function. ⁵³ Concerning the respiratory system, possible explanations for the 6MWD decrease include alterations in the alveolo-capillary membrane, bronchial airway, and respiratory muscle strength. The absence of SpO ₂ alterations suggests that the alveolo-capillary membrane is intact ( Table 4). However, lung function data alteration and respiratory muscle weakness indicate that these factors may contribute to the 6MWD decrease. ⁸ Muscle function was not a factor in our study, as both groups had comparable muscle-mass and handgrip-strength ( Table 1). Previous studies have reported no impairment in muscle strength in CHB patients, ^{54, 55} but handgrip-strength is a strong predictor of 6MWD, ⁵⁶ and CHB can cause muscle injuries. ^{5, 13}

The 5-year age gap between the CHB and control groups is unlikely to account for the differences in 6MWD and HR, as adjustments were made for age. Literature presents conflicting results regarding the effect of age on 6MWD. ^{22, 31, 45, 52} While age has been identified as an independent predictor of 6MWD in diabetic patients, ⁵² it is a non-independent predictor in OSAHS patients ⁴⁵ and narghile-smokers. ³¹ In healthy adults, age is a dependent predictor of 6MWD. ²²

The corpulence status was not a factor in our study, as the two groups had comparable BMI values and comparable corpulence statuses ( Table 1). Literature also provides conflicting conclusions about the effect of BMI and corpulence status on 6MWD. ^{22, 31, 45, 52} While some studies consider BMI an independent predictor of 6MWD in OSAHS patients, ⁴⁵ narghile-smokers, ³¹ and healthy adults, ²² others do not. ⁵² While some studies consider corpulence status an independent 6MWD predictor in diabetic patients, ⁵² others do not in OSAHS patients, ⁴⁵ narghile-smokers, ³¹ and healthy adults. ²²

In our study, the CHB-group encompassed higher percentages of participants with lower schooling-level and unfavorable socioeconomic-level ( Table 1). The effect of schooling-level and socioeconomic-level on 6MWD is also controversial in literature. ^{22, 31, 52, 56, 57} Schooling-level was an independent predictor in some studies of healthy adults, ⁵⁷ but not in others. ^{22, 31, 45, 52, 56} Socioeconomic-level was an independent predictor in healthy adults ²² and diabetic patients, ⁵² but not in others including OSAHS patients ⁴⁵ or narghile-smokers. ³¹ In, the socioeconomic-level was identified as a dependent 6MWD predictor.

Since the two groups were matched for physical-activity ( Table 1), physical-activity levels cannot explain the 6MWD decrease. Literature on physical-activity’s effect on 6MWD is mixed. ^{22, 31, 45, 52} While one study considered physical-activity an independent 6MWD predictor in diabetic patients, ⁵² two others considered it a non-independent 6MWD predictor in OSAHS patients ⁴⁵ or narghile-smokers. ³¹ In healthy adults, ²² the physical-activity level was identified as a dependent 6MWD predictor.

Since the women of both groups were matched for parity data ( Table 1), the latter cannot explain the 6MWD decrease. In literature, parity is recognized as a 6MWD influencing factor in healthy adults, ^{22, 58} and patients with chronic conditions. ^{45, 52}

The matched smoking status ( Table 1), also eliminates smoking as a cause for the 6MWD decrease, with conflicting literature results, ^{45, 52} While one study considered it an independent 6MWD predictor in diabetic patients, ⁵² but not in others including OSAHS patients. ⁴⁵

Pathophysiological mechanisms explaining 6MWD decline and CRMC aging acceleration

Several mechanisms may explain the 6MWD decline and CRMC aging acceleration in NC-CHB patients, including anemia, inflammation, liver dysfunction, oxidative stress, and apoptosis. ^{59– 69}

Anemia, ⁵⁹ inflammation, ^{60, 61} and certain liver function markers (aspartate-aminotransferase, alkaline-phosphatase, and bilirubin) ^{62, 63} are associated with exercise capacity. Nonetheless, since both groups were matched for hemoglobin, inflammation, and liver function data, these factors alone do not fully explain the 6MWD decline.

CHB interferes with apoptosis signaling pathways, ^{64, 65} and oxidative stress may contribute to liver disease progression in CHB patients. ^{66– 68} Similar to chronic obstructive pulmonary disease, apoptosis in the quadriceps of CHB patients might impair muscle function, ⁶⁹ while oxidative stress could affect functional capacity. ^{30, 60} Although albumin, non-conjugated bilirubin, and uric-acid values were comparable between groups, suggesting maintained oxidant-antioxidant balance, the oxidative stress factor cannot be completely ruled out in explaining the 6MWD decline.

Several methodological points including, which may influence our results, require discussion. The following paragraphs will discuss the sample and effect sizes, participants’ characteristics, statistical analysis approaches, recruitment methods, 6MWT practice, and data collection.

Sample and effect sizes

In contrast to the Saudi study, ¹¹ we calculated both sample and effect sizes. Determining an adequate sample size is crucial for ensuring sufficient power to detect statistical effects. ⁷⁰ The effect size provides a quantitative measure of the strength and magnitude of the observed association between exposure and outcome variables. ⁴⁸ Unlike p-values, which indicate only whether an association is statistically significant, the effect size offers a more comprehensive understanding of the practical significance of the relationship. ⁴⁸ Our calculated sample size ( ie ; CHB-group = 26, control-group = 28) was smaller than that of the Saudi study ( ie ; CHB-group = 49, control-group = 45), ¹¹ and the effect size for the 6MWD was small.

Participants’ characteristics

Several factors can influence the 6MWD, including anthropometric data ( eg ; age, height, weight, BMI, corpulence status, and muscle-mass), sex, biological data ( eg ; hematological, inflammatory, and biochemical data), parity, schooling-level, socioeconomic-level, physical-activity level, and muscle strength. The influence of these factors will be discussed below.

Age, height, weight, BMI, corpulence status, muscle-mass, and sex are known independent predictors of 6MWD. ^{71– 74} Compared to our study, the Saudi study ¹¹ included participants with a broader age range (25-55 vs. 18-80 years), which could introduce confusion, as 6MWD is negatively correlated with age. ^{71– 73} In our study, the control-group was younger than the CHB-group by ≈5 years. To account for this, we applied two corrective actions. We used North African 6MWD reference equations to standardize 6MWD by age, ^{22, 43} and we expressed HR as a percentage of MPHR, accounting for age. ⁴⁰ Anthropometric data ( ie ; height, weight, BMI, corpulence status, and muscle-mass), and sex were comparable between our two groups. The Saudi study ¹¹ reported comparable age, height, and weight but did not compare BMI or corpulence status (Appendix 1). This omission could lead to misinterpretation, as high BMI is associated with reduced functional capacity ⁷⁵ and 6MWD. ²² Additionally, muscle-mass, an important factor influencing 6MWD ⁷⁴ was comparable between groups. As done by Alameri et al., ¹¹ comparable percentages of men and women were included in our study. Sex also influences 6MWT results, with women generally showing lower 6MWD than men. ⁷⁶

The two groups were matched for all biological data. Our sample of CHB patients represents a real-life cohort. For instance, the mean hemoglobin value in our study (14.51±1.92 g/dL) is similar to that reported by Alameri et al. ¹¹ (12.87±4.41 g/dL).

We reported data on parity, which was comparable between the two groups, with no women having high parity. Parity negatively correlates with 6MWD, with multiparous women showing lower 6MWD compared to nulliparous women. ²² This effect may be due to hormonal changes, biochemical modifications, or respiratory muscle impairment. ²²

We reported schooling-level and socioeconomic-level data for our participants ( Table 1). The unfavorable socioeconomic-level among our NC-CHB patients reflects findings in African CHB patient. ⁷⁷

We assessed physical-activity level and handgrip-strength, finding comparable data between the two groups. In our study 96% of the CHB-group had a sedentarily status ( Table 1), which aligns with a study reporting 60% of CHB patients as sedentary. ⁷⁸ Reduced physical-activity often leads to altered muscle metabolism, decreased muscle-mass, and reduced physical capacity. ⁷⁴ Handgrip-strength is a strong, independent predictor of 6MWD. ⁵⁶

While the Saudi study. ¹¹ employed only a quantitative approach to compare measured data, our study utilized both quantitative and qualitative approaches. The qualitative approach, such as comparing percentages of patients with abnormal 6MWD, is recommended in medical exercise research. ²³

Recruitment methods of the two groups

Like what has been done by Alameri et al., ¹¹ our CHB patients were recruited from those followed at outpatient clinics. The main limitation of such method is the potential for selection bias. ⁷⁹ Outpatient clinics typically serve individuals with less severe or milder forms of illness compared to those admitted to hospitals. ⁸⁰ This bias may affect the generalizability of the results to the broader population, including those not seeking regular medical care or those treated in other healthcare settings. ⁷⁹

Contrary to the Saudi study, ¹¹ where healthy participants were recruited from hospital employees and medical students, in our study, the “apparently” healthy participants were recruited from relatives of CHB patient and from the announcement on social media account. On the one hand, the method applied by Alameri et al. ¹¹ may consist of more highly educated individuals with a higher socioeconomic-levels, which are more likely to come from the broader general population. On the other hand, some relatives of CHB patients could be unknowingly carrying HBV.

6MWT practice

Since the information about 6MWT practice and data collection during the test allow better interpretation and comparison of results among different studies, many details such as applied guidelines, corridor length, place, number of tests, day-time, encouragement and walking aids during the 6MWT, and number of investigators need to be discussed. First, as done in Saudi study, ¹¹ we applied the most updated available guidelines ( ie ; 2002, ³⁹ and 2014 guidelines, respectively). ^{15, 16} Using updated guidelines in medical research lies in the promotion of scientific rigor, patient safety, relevance, consistency, regulatory compliance, and improved clinical decision-making. Second, as done in Saudi study, ¹¹ we reported the corridor’ length ( ie ; 30 and 40 m, respectively). The corridor length is essential for precise comparisons of 6MWT results ⁸¹ and can influence performance. ^{15, 39} Although it was recommended that the walking course must be 30 m in length, ³⁹ research has shown that there are no significant differences in outcomes when tracks of lengths ranging from 15 to 50 m are used. ⁸¹ Third, unlike the Saudi study, ¹¹ we reported the 6MWT practice place ( ie ; indoor as recommended). ³⁹ Research has indicated that there is little difference in 6MWD ( ie ; mean difference 4 m) between indoor and outdoor courses. ⁸² Fourth, as done by Alameri et al. ¹¹ we performed only one 6MWT. Although repeated testing is recommended to account for the familiarization effect on 6MWD, ^{22, 71, 73, 83– 86} the 6MWT is more appropriate for clinical settings, where the test is typically performed once. ⁸⁷ Fifth, contrary to the Saudi study, ¹¹ we reported the day-time of the 6MWT ( ie ; between 8 and 11 am). ^{22, 84} This period is characterized by a stable ambient temperature and humidity which can minimize the intraday effects. ⁸⁸ Intraday variability can be a source of biased data. ³⁹ Sixth, contrary to the Saudi study, ¹¹ we mentioned that no encouragement or walking aids during the 6MWT was given to participants. The latter can influence the 6MWD. ^{15, 16, 89, 90} Finally, contrarily to the Saudi study, ¹¹ where 6MWT was supervised by several investigators, only one investigator was implicated in our study. In patients with chronic conditions, the 6MWT data can be compared when conducted by different investigators. ⁹¹

Similar to the Saudi study, ¹¹ we reported the main outcome of the 6MWT ( ie ; 6MWD) (Appendix 1). Contrary to the Saudi study, we reported additional 6MWT data (Appendix 1).

The 6MWT main outcome, which is the 6MWD, is reported frequently in meters, ^{15, 16} which could be a source of misinterpretation. ^{8, 10, 11} In our study, 6MWD was expressed as percentage of predicted 6MWD, and the LLN was calculated from predicted values. Comparing measured 6MWD to predicted values derived from norms is an important point since norms are essential to guide the diagnostic and prognostic use of the 6MWT and the success in medical decision-making depends as much on selecting and properly using norms and their limits. ^{15, 39}

In our study, we reported some 6MWT secondary outcomes, including HR, SpO ₂, BP, dyspnea, ECRMC’ age, and 6MWD relative indices. The following sentences will discuss their clinical importance. First, HR was reported in pbm and as % of MPHR in order to avoid the age effect, and ΔHR was calculated. Expressing HR as % of MPHR accommodates individual variations in fitness levels and age, allowing for personalized exercise intensity assessment. ⁴¹ ΔHR calculation is essential since it correlated with 6MWD. ^{86, 92, 93} Second, SpO ₂ and ΔSpO ₂ were reported. Oxygen desaturation during a 6MWT provides information regarding exercise-induced desaturation, disease severity and disease progress. ^{15, 16} Third, BP was mentioned. Measuring BP during the 6MWT is valuable for assessing cardiovascular health, exercise responses, and overall patient safety. ^{22, 45, 94} It can aid in diagnosis, risk assessment, exercise prescription, and patient care in cardiovascular conditions. ^{22, 45, 94} Fourth, dyspnea was evaluated. On the one hand, dyspnea is a clinical sign of walking intolerance. ^{22, 46, 47} On the other hand, it reflects both the physiology of exercise limitation, and the impact of exercise limitation on daily life. ^{15, 16} Fifth, we estimated the ECRMC’ age, which reflects acceleration of ageing. ^{39, 44} Finally, we calculated some 6MWD relative indices ( eg ; 6MWW, “6MWDxBMI”, “6MWDxmuscle-mass”, “6MWDxbody-fat” and “6MWDxSpO _2End”) in order to better estimate the work required to perform the 6MWT than 6MWD alone. ⁴¹ For example, since weight directly affects the energy required to complete the 6MWT, the 6MWW can offer valuable insights into patients’ functional capacity. ^{15, 16} The 6MWW correlates strongly with V ̇ O 2 peak and is suggested as a parameter of patients’ fitness evaluation when gas exchange measurements are unavailable. ⁹⁵ In addition, as weight is not the only and best tool reflecting the body composition, and as the adiposity has a key position in the beginning of inability, ⁷⁵ we had multiplied the 6MWD by BMI, muscle-mass and body-fat. Moreover, since a positive and significant correlation was observed between 6MWD and SpO _2End, ⁹⁶ we had multiplied the 6MWD by the SpO _2End.

Study limitations

This study has two major limitations. First, the “apparently” healthy group did not undergo HBV-DNA testing or fibroscan to confirm the absence of HBV infection and hepatic fibrosis, respectively. These tests were challenging to perform due to economic constraints and ethical considerations. Second, the study did not include spirometry testing, despite its known predictive value for 6MWD. ^{22, 39, 56, 83, 84, 93} Spirometry tests were not feasible due to the COVID-19 pandemic and the associated restrictions. ⁹⁷