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\begin{document}

\title{Increased dialysis symptom index burden in maintenance hemodialysis
patients during the COVID-19 lockdown period}



\author[1]{Wen-Man Zhao}%
\author[1]{Li Zhu}%
\author[1]{Yvyv Zhu}%
\author[1]{Xun-Liang Li}%
\author[1]{Rui Shi}%
\author[1]{Zhi-Juan Wang}%
\author[2]{Hai-Feng Pan}%
\author[1]{De-Guang Wang}%
\author[1]{Liang Yuan}%
\affil[1]{Second Affiliated Hospital of Anhui Medical University}%
\affil[2]{Anhui Medical University}%


\vspace{-1em}



  
  \date{May 26, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The high prevalence of dialysis-related symptoms in maintenance
hemodialysis (MHD) patients severely affect quality of life. Therefore,
in this study, we assessed the dialysis symptom index (DSI) of MHD
patients during the second wave of COVID-19, which triggered a health
crisis, resulting in many cities in China opting for social isolation. A
total of 106 MHD patients from our center were screened. DSI, sleep
quality, and fatigue scales were investigated separately before and
during lockdown. Demographic and laboratory data of MHD patients were
collected. A nomogram was used to predict high DSI by combining multiple
indicators. Additionally, internal validation was performed to reduce
overfitting bias. The mean age of patients was 56.0 years (SD 13.1). The
prevalence and severity of DSI were significantly higher during lockdown
than pre-lockdown. Notably, itching, trouble staying asleep, bone or
joint pain, muscle cramps, feeling irritability, difficulty
concentrating, headache, constipation, and feeling nervous were observed
( \emph{P}\textless{}0.05). Multivariate logistic regression analysis
identified longer dialysis vintage, lower albumin level, and lower Kt/V
as predictors of high DSI. Additionally, the nomogram showed good
accuracy in estimating high DSI with a C-index and bootstrap-corrected
index of 0.875 and 0.863, respectively. Moreover, calibration plots
showed optimal consistency with the actual presence of high DSI. We
found a higher prevalence of DSI in MHD patients during the COVID-19
lockdown. Furthermore, patients with longer dialysis vintage, lower
albumin levels and Kt/V had a risk of developing high DSI. Further
studies should identify targeted therapies for improving the symptom
burden of MHD patients.%
\end{abstract}%



\sloppy


\textbf{Increaseddialysis symptom index burden in maintenance
hemodialysis patients during the COVID-19 lockdown period}

Wen-Man Zhao\textsuperscript{1,2+}, Li Zhu\textsuperscript{1,2+}, Yvyv
Zhu\textsuperscript{1,2+}, Xun-Liang Li\textsuperscript{1,2}, Rui
Shi\textsuperscript{1,2}, Zhi-Juan Wang\textsuperscript{1,2}, Hai-Feng
Pan\textsuperscript{3,4}, De-Guang Wang\textsuperscript{1,2*}, Liang
Yuan\textsuperscript{1,2*}

\textsuperscript{1}\emph{Department of Nephrology, The Second Hospital
of Anhui MedicCal University, Hefei, China}

\textsuperscript{2}\emph{Institute of Kidney Disease, Inflammation \&
Immunity-mediated Diseases, The Second Hospital of Anhui Medical
University, Hefei, China}

\textsuperscript{3}\emph{Department of Epidemiology and Biostatistics,
School of Public Health, Anhui Medical University, Hefei, China}

\textsuperscript{4}\emph{Inflammation and Immune Mediated Diseases
Laboratory of Anhui Province, Hefei, China}

\textsuperscript{+} Wen-Man Zhao, Li Zhu and Yvyv Zhu contributed
equally to this work.

\textbf{* Correspondence:}

De-Guang Wang, Department of Nephrology, The Second Hospital of Anhui
Medical University, Hefei, China. Email: \emph{wangdeguang@ahmu.edu.cn}

Liang Yuan, Department of Nephrology, The Second Hospital of Anhui
Medical University, Hefei, China. Email: \emph{kevin8yuan@163.com}

\textbf{Running title} : Increased DSI burden in MHD patients during the
COVID-19 lockdown.

\textbf{Abstract}

The high prevalence of dialysis-related symptoms in maintenance
hemodialysis (MHD) patients severely affect quality of life. Therefore,
in this study, we assessed the dialysis symptom index (DSI) of MHD
patients during the second wave of COVID-19, which triggered a health
crisis, resulting in many cities in China opting for social isolation. A
total of 106 MHD patients from our center were screened. DSI, sleep
quality, and fatigue scales were investigated separately before and
during lockdown. Demographic and laboratory data of MHD patients were
collected. A nomogram was used to predict high DSI by combining multiple
indicators. Additionally, internal validation was performed to reduce
overfitting bias. The mean age of patients was 56.0 years (SD 13.1). The
prevalence and severity of DSI were significantly higher during lockdown
than pre-lockdown. Notably, itching, trouble staying asleep, bone or
joint pain, muscle cramps, feeling irritability, difficulty
concentrating, headache, constipation, and feeling nervous were observed
(\emph{P} \textless{}0.05). Multivariate logistic regression analysis
identified longer dialysis vintage, lower albumin level, and lower Kt/V
as predictors of high DSI. Additionally, the nomogram showed good
accuracy in estimating high DSI with a C-index and bootstrap-corrected
index of 0.875 and 0.863, respectively. Moreover, calibration plots
showed optimal consistency with the actual presence of high DSI. We
found a higher prevalence of DSI in MHD patients during the COVID-19
lockdown. Furthermore, patients with longer dialysis vintage, lower
albumin levels and Kt/V had a risk of developing high DSI. Further
studies should identify targeted therapies for improving the symptom
burden of MHD patients.

\textbf{KEYWORDS} :

COVID-19, dialysis system index, lockdown, nomogram, predictive model

\textbf{INTRODUCTION}

Maintenance hemodialysis (MHD) patients have a high prevalence of
physical and emotional illness-related symptoms\textsuperscript{1-3}. A
high symptom burden is associated with a high mortality risk in MHD
patients\textsuperscript{4}. In a Thai study, 98.7\% of MHD patients
reported one or more symptom burdens, with the most common ones being
itchy skin, dryness, muscle ache, dry mouth, muscle cramps, and
insomnia\textsuperscript{5}. A Korean study revealed that 97.4\% of all
MHD patients reported one or more symptoms, with fatigue and dry skin
being the most common physical symptoms and worry, tension, and anxiety
as the most common emotional symptoms\textsuperscript{6}. These symptoms
cause distress and affect the overall well-being of patients, leading to
a reduced quality of life, and may increase patient
mortality\textsuperscript{1,7}. Therefore, a symptom study of end-stage
renal disease (ESRD) patients on hemodialysis would contribute to
effective symptom management and maximize patient benefits.

Studies have shown that the isolation and containment of patients with
COVID-19 have far-reaching effects on different groups, including
insomnia, depression, anxiety, and post-traumatic stress disorder
(PTSD)\textsuperscript{8-11}. A study conducted among isolated college
students confirmed the dramatic impact of the COVID-19 pandemic on their
mental health\textsuperscript{12}. Psychiatric symptoms were strikingly
prevalent: 67.05\% reported traumatic stress, 46.55\% reported
depressive symptoms, and 34.73\% reported anxiety symptoms. In a study
conducted in a Chinese isolation ward with infected
patients\textsuperscript{13}, the prevalence of generalized anxiety
symptoms was 51.3\%; depressive symptoms, 41.2\%; and post-traumatic
stress symptoms (PTSS)/PTSD symptoms, 33.6\%. A longitudinal study
conducted in France revealed the impact of the pandemic on the mental
health status of the French population\textsuperscript{14}. The study
included participants who had undergone a mental health study in
2014--2019. The results showed that isolation led to higher
psychological stress and that those with poorer physical health showed
more severe anxiety symptoms.

From the beginning of October till the end of November 2022, the
COVID-19 epidemic in Hefei became increasingly severe. An epidemic is
characterized by multi-point distribution, localized aggregation, and
gradual spillover. Therefore, multiple regions of our city were under
lockdown and static management during this period. With static
management, residents cannot leave their houses and engage in outdoor
activities. Concerns about daily life and disease treatment caused great
psychological and physical distress to MHD patients. However, the
dialysis symptom index (DSI) of MHD patients during the lockdown remains
unclear. Therefore, to fully evaluate the psychological and mental
status of MHD patients, we investigated the DSI of MHD patients during
the COVID-19 lockdown period, so as to provide a reference for the
development of comprehensive management programs for MHD patients.

\textbf{METHODS}

\textbf{2.1 Study population}

The study population included a cohort of adult MHD patients at the
Second Hospital of Anhui Medical University who had completed their
first DSI assessment 6 months earlier (March 2022). Exclusion criteria
were 1) inability to comprehend with the questionnaire content, 2)
presence of comorbid malignancies and infections (including COVID-19)
based on clinical/laboratory findings, and 3) inability to provide
consent without a proxy. A second DSI assessment was performed for
screened patients during lockdown(between October and November 2022).
This study was approved by the Ethics Review Committee of the Second
Affiliated Hospital of the Anhui Medical University (No. pj - yx2020 -
006). Before participation, all patients were required to read and sign
an informed consent form.

\textbf{2.2 Baseline information}

At the beginning of the study (March 2022), demographic and laboratory
data were collected for all patients. General information included sex,
age, and dialysis vintage. Laboratory parameters included creatinine,
blood urea nitrogen, hemoglobin, albumin, blood calcium, blood
phosphorus, alkaline phosphatase (ALP), intact parathyroid hormone
(iPTH), and total Kt/V(dialysis effectiveness index).

\textbf{2.3 Assessment of dialysis symptom index}

The DSI is a validated instrument consisting of 30 questions to assess
the severity of discomfort and unpleasant emotions in patients on MHD,
with each question addressing a specific physical or emotional
symptom\textsuperscript{7,15}. The 30 questions can be summarized into
eight groups of symptoms: 1) gastrointestinal, 2) musculoskeletal and
fluid volume, 3) neurological symptoms, 4) irritation of the mucous
membranes and skin, 5) depression, 6) sleep disturbance, 7) sexual
symptoms, and 8) anemia. Patients were asked to report symptoms that
occurred in the last week, answering ``yes'' or ``no'' to each symptom.
Severity was assessed on a five-point Likert scale, with scores ranging
from 0 to 4 for each answer (i.e., a response of ''0'' means ''no,''
whereas a response of ''4'' means ''yes: very much''). The total DSI
score represents the sum of individual scores (ranging from 0 to 120),
with higher total scores indicating higher overall symptom severity.

\textbf{2.4 Assessment of fatigue}

The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F)
scale was used to assess fatigue in MHD patients. The 13-item
questionnaire examined self-reported fatigue and its impact on daily
activities and function. The scale consists of five points (0 = not at
all, 1 = a little bit, 2 = somewhat, 3 = quite a bit, and 4 = very
much). All items contributed equally to the total score. The scale
ranged from 0 to 52, with 0 representing the worst possible score and 52
representing no fatigue. Previously, a FACIT-F score [?] 34 was considered
indicative of fatigue\textsuperscript{16}.

\textbf{2.5 Assessment of sleep quality}

The Pittsburgh Sleep Quality Index (PSQI) is an effective indicator of
sleep quality and patterns. Subjective sleep quality, sleep latency,
sleep length, habitual sleep efficiency, sleep disruptions, use of sleep
medications, and daytime dysfunction were evaluated. Each factor was
weighted from 0 to 3, resulting in a global score between 0 and 21. Poor
sleep quality was defined as a global PSQI score of
\textgreater{}5\textsuperscript{17}.

\textbf{2.6 Statistical analyses}

Categorical variables are expressed as percentages, and continuous
variables are expressed as mean (SD) or median (IQR). Differences in
baseline characteristics, and laboratory measures between groups were
assessed using Chi square test, or Mann-Whitney U test, as appropriate.
In the univariate logistic regression analysis, variables associated
with a high risk of high DSI (\emph{P} \textless{}0.05) were introduced
into the multivariate model. The collinearity between the final model
variables was evaluated using the variance inflation factor (VIF). VIF [?]
5 signified the absence of collinearity between the final model
variables. Nomogram were generated based on the results of multivariate
logistic regression on the dependent variable using the 'rms' package in
R software (version 4.2.1). In addition, we used the bootstrapping
method with 1000 resamples to conduct internal validation. The
discriminative power of the model was assessed using the consistency
index (C-index), and the goodness of fit is shown in the calibration
plot. Statistical analyses were performed using R software (version
4.2.1). \emph{P} value of \textless{}0.05 was considered statistically
significant.

\textbf{RESULTS}

\textbf{3.1 Effect of COVID-19 lockdown on DSI in MHD patients}

A total of 130 patients had their first assessment before the lockdown.
During the lockdown period, only 106 of the 130 cases participated in
the second evaluation. Finally, 106 patients who were assessed twice
were included in the trial. 60.4\% of the patients were male (n = 64).
The mean age of patients was 56.0 (SD = 13.1) years. We observed that
DSI severity in MHD patients during lockdown was higher than that before
lockdown (Table 1). In particular, itching, trouble staying asleep, bone
or joint pain, muscle cramps, feeling irritable, difficulty
concentrating, headache, constipation, and feeling nervous were observed
(\emph{P} \textless{}0.05, Table 1). Moreover, the prevalence of fatigue
(PSQI\textgreater{}5) and poor sleep (FACIT-F[?]34) was higher during
lockdown than before lockdown (\emph{P} \textless{}0.05).

\textbf{3.2 Overall severity of DSI in the MHD cohort}

We compared differences in the distribution of DSI in MHD patients
before and during lockdown (Figure 1, Figure 2.). The overall pattern of
patients was similar in both groups. The most common symptoms reported
by patients in Figure 1 included feeling tired or lacking energy
(81.1\%), dry skin (76.5\%), trouble falling asleep (74.5\%), feeling
sad (66.0\%), and dry mouth (63.2\%). In contrast, most of the symptoms
reported by patients in Figure 2 included itching (84.9\%), trouble
falling asleep (84.9\%), dry skin (84.0\%), feeling tired or lacking
energy (80.2\%), and dry mouth (73.6\%).

\textbf{3.3 Relationship between baseline data and DSI in MHD patients
during lockdown}

Based on the mean of the median DSI (40) from both surveys, patients
were divided into a low DSI (DSI\textless{}40) and a high DSI (DSI[?]40)
group in the second evaluation. We found that patients in the high DSI
group had a longer dialysis vintage and lower albumin and Kt/V levels
than those in the low DSI group (Table 2). There were no significant
differences between the two groups in the percentage of women, age,
Kt/V, and hemoglobin, blood urea nitrogen, alkaline phosphatase, serum
Ca, serum P, iPTH, ferroprotein, and transferrin levels.

\textbf{3.4 Univariate and multivariate logistic regression analysis}

The univariate logistic regression analysis showed that dialysis
vintage, albumin and Kt/V were associated with the development of high
DSI in MHD patients during lockdown period. The multivariate logistic
model's mean VIF of 1.22 indicates the direct absence of
multicollinearity among variables. Multivariate logistic regression
revealed that dialysis vintage (OR 1.031, 95\%CI 1.013-1.050;\emph{P}
=0.001), albumin (OR 0.782, 95\%CI 0.627-0.975; \emph{P} =0.029) and
Kt/V (OR 0.028, 95\%CI 0.001-0.556; \emph{P} =0.019) were significant
risk variables for hige DSI (Table 3).

\textbf{3.5 Nomogram construction and validation}

The results of multivariate logistic regression were applied to
construct a nomogram of hige DSI in MHD patients, and scores were
assigned to the screened variables based on their regression
coefficients (Figure 3). As shown in nomogram, patients with longer
dialysis vintage, lower albumin levels and Kt/V had a higher risk of
developing high DSI. By summing the scores and locating them on the
total score scale, it was possible to predict the occurrence of high DSI
in individuals during lockdown period.

Internal validation was conducted to evaluate the model's discrimination
and reduce overfitting bias. The results demonstrated a C-Index of 0.875
for the primary cohort and 0.863 for the internal validation cohort. The
calibration plots showed excellent agreement between the nomogram
predictions and the actual observation of high DSI (Figure 4).

\textbf{DISCUSSION}

Patients on MHD have a heavy burden of DSI symptoms, but they are often
underestimated or even ignored, and thus
undertreated\textsuperscript{18}. COVID-19 has been a challenge to all
humanity, both on physical and psychological level. Its impact is
diverse and it has caused varying degrees of distress to everyone.
Lockdowns increase MHD patients' anxiety and worry about the treatment
of their disease. In this study, we used validated tools to assess the
presence and severity of patient complaints\textsuperscript{19}. The DSI
is the most common tool used to assess the prevalence and severity of
dialysis-related discomfort in patients with ESRD. A growing number of
epidemiological studies have attempted to use DSI to reveal the
prevalence of physical and emotional symptoms in MHD
patients\textsuperscript{4,20,21}.

In this single-center cohort study, we investigated DSI in patients on
MHD before and during lockdown. We found a significant increase in the
prevalence of individual symptoms and overall symptom severity scores
during the lockdown. Notably, the prevalence of itching, trouble staying
asleep, bone or joint pain, muscle cramps, feeling irritability,
difficulty concentrating, headache, constipation, and feeling nervous
increased compared with pre-lockdown. Examination of symptoms across the
cohort revealed that the most commonly reported symptoms were those
related to fatigue, skin disorders (i.e., dry skin, pruritus), and sleep
disturbances.

These symptoms can be mainly summarized in terms of physical and
psychological aspects. We speculate that there may be the following
reasons for the above changes. First, the lockdown caused inconvenience
to the daily treatment of MHD patients, which may have led to
insufficient treatment of some patients. Second, the concern of exposure
to the virus may directly increase the psychological burden on MHD
patients. Third, patients may not have received timely and adequate
attention from physicians because physicians were overburdened with the
care of the influx of COVID-19 patients. Given the high prevalence of
these unpleasant symptoms and their dominance in the cluster, future
studies to identify therapies that effectively target these symptoms may
substantially improve the health and well-being of a large proportion of
dialysis patients.

According to the nomogram, longer dialysis vintage is a risk factor of
high DSI. However, patients with high albumin levels and Kt/V had a
lower risk of developing high DSI. The Kt/V value, which represents the
adequacy of dialysis, may decrease as dialysis vintage increases.
Studies have shown that MHD patients are more prone to urinary
toxin-related discomfort and vital organ dysfunction when dialysis is
inadequate\textsuperscript{19,22}. Therefore, it is important to reduce
DSI severity by improving dialysis adequacy in patients on MHD. In
addition, we found that low albumin level was a risk factor of high DSI.
Albumin level is an important index for evaluating the nutritional
status of the body. Studies have found that low albumin level is one of
the main causes of serious complications in dialysis
patients\textsuperscript{23,24}. However, we also observed that
nutritional parameters defined by albumin level were associated with a
wider range of symptoms, including decreased energy (feeling tired or
lacking energy), restless legs, muscle discomfort (muscle cramps, muscle
aches), impaired cognition (difficulty concentrating), and overall
symptom burden. Improving the nutritional status of patients on MHD may
be beneficial for reducing discomfort symptoms.

The strengths of our study include the first-time assessment of DSI in
MHD patients during COVID-19 lockdown, rigorous use of a symptom
assessment tool (DSI) that has been validated in the dialysis population
for symptom assessment in MHD patients, and the comprehensive
availability of detailed patient data collected. However, our study has
several limitations. First, the research subjects in this study is not
representative of all HD population; patients who agreed to participate
in the study may have been healthier than those who were not recruited
and, therefore, may have had lower symptom scores than the broader
hemodialysis population. Second, the limited sample size may not have
allowed the detection of significant subgroup analysis-based
interactions. Third, uncomfortable symptoms during dialysis can be
exacerbated by comorbidities, medications, lifestyle and dietary
regimens, renal replacement therapy, and aging. Due to data limitations,
we were unable to examine the relationship between certain dialysis
treatment features (i.e., hemodialysis membranes and medications on
dialysis) and symptom burden.

\textbf{CONCLUSION}

DSI prevalence and severity were higher in MHD patients during lockdown
period than before. The novel predictive nomogram achieved a good
prediction of high DSI in patients on MHD. Using this model, the risk of
high DSI in patients with MHD can be determined earlier.

\textbf{AUTHOR CONTRIBUTIONS}

The authors who conceived the study: Wen-Man Zhao and Liang Yuan.
Authors who designed the study: Wen-Man Zhao and Li Zhu. Authors who
performed the experiments: Wen-Man Zhao, Rui Shi and Yvyv Zhu. Authors
who performed statistical analyses: Xun-Liang Li and Zhi-Juan Wang.
Authors who wrote and edited the manuscript: Wen-Man Zhao, Hai-Feng Pan,
De-Guang Wang. All authors read and approved the final version.

\textbf{ACKNOWLEDGMENTS}

This work was supported by grants from the Natural Science Foundation of
the Anhui Province (number 2008085MH244), National Natural Science
Foundation Incubation Programof the Second Hospital of Anhui Medical
University(2020GMFY04), Clinical Research Incubation Program of the
Second Hospital of Anhui Medical University (2020LCZD01), Anhui Medical
University 2021 Clinical and Pre-disciplinary Co-Construction
(2021lcxk032),

Joint Research on Prevention and Control of Chronic Diseases in the
Second Hospital of Anhui Medical University (MBLHJJ202008).

\textbf{CONFLICTS OF INTEREST}

The authors declare no conflicts of interest.

\textbf{DATA AVAILABILITY STATEMENT}

The data that support the findings of this study are available from the
corresponding open accessed websites.

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24. Miyasato Y, Hanna RM, Morinaga J, Mukoyama M, Kalantar-Zadeh K.
Prognostic Nutritional Index as a Predictor of Mortality in 101,616
Patients Undergoing Hemodialysis. \emph{Nutrients.} 2023; 15(2).

\textbf{Tables}

\textbf{TABLE 1} Comparison of DSI scores of MHD cohort in different
periods (n = 106).\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Individual Symptoms} & \textbf{Pre-lockdown} & \textbf{Lockdown}
& \emph{P}\textbf{-value}\tabularnewline
\textbf{DSI}, M (Q1, Q3) & 36 (28, 42) & 54 (32, 65) &
\textbf{\textless{}0.001}\tabularnewline
\textbf{Itching}, n (\%) & 61 (57.5) & 90 (84.9) &
\textbf{\textless{}0.001}\tabularnewline
Dry skin, n (\%) & 81 (76.4) & 89 (84.0) & 0.168\tabularnewline
Trouble falling asleep, n (\%) & 79 (74.5) & 90 (84.9) &
0.060\tabularnewline
\textbf{Trouble staying asleep}, n (\%) & 56 (52.8) & 72 (67.9) &
\textbf{0.025}\tabularnewline
Numbness or tingling in feet, n (\%) & 45 (42.5) & 52 (49.1) &
0.335\tabularnewline
Muscle cramps, n (\%) & 66 (62.3) & 60 (56.6) & 0.401\tabularnewline
Swelling in legs, n (\%) & 51 (48.1) & 53 (50.0) & 0.783\tabularnewline
Restless legs or difficulty keeping legs still, n (\%) & 42 (39.6) & 50
(47.2) & 0.268\tabularnewline
\textbf{Bone or joint pain}, n (\%) & 32 (30.2) & 60 (56.6) &
\textbf{\textless{}0.001}\tabularnewline
Shortness of breath, n (\%) & 54 (50.9) & 63 (59.4) &
0.214\tabularnewline
Cough, n (\%) & 41 (38.7) & 44 (41.5) & 0.674\tabularnewline
\textbf{Muscle soreness}, n (\%) & 49 (46.2) & 76 (71.7) &
\textbf{\textless{}0.001}\tabularnewline
Feeling tired or lacking energy, n (\%) & 86 (81.1) & 85 (80.2) &
0.862\tabularnewline
Feeling anxious, n (\%) & 59 (55.7) & 71 (67.0) & 0.091\tabularnewline
\textbf{Feeling irritable}, n (\%) & 47 (44.3) & 67 (63.2) &
\textbf{0.006}\tabularnewline
Feeling sad, n (\%) & 70 (66.0) & 69 (65.1) & 0.885\tabularnewline
\textbf{Difficulty concentrating}, n (\%) & 46 (43.4) & 65 (61.3) &
\textbf{0.009}\tabularnewline
\textbf{Headache}, n (\%) & 39 (36.8) & 63 (59.4) &
\textbf{0.001}\tabularnewline
Decreased appetite, n (\%) & 49 (46.2) & 57 (53.8) &
0.272\tabularnewline
Diarrhea, n (\%) & 44 (41.5) & 40 (37.7) & 0.574\tabularnewline
Nausea, n (\%) & 56 (52.8) & 55 (51.9) & 0.891\tabularnewline
Vomiting, n (\%) & 37 (34.9) & 47 (44.3) & 0.160\tabularnewline
Dry mouth, n (\%) & 67 (63.2) & 78 (73.6) & 0.104\tabularnewline
\textbf{Constipation}, n (\%) & 42 (39.6) & 61 (57.5) &
\textbf{0.009}\tabularnewline
Chest pain, n (\%) & 39 (36.8) & 43 (40.6) & 0.573\tabularnewline
Lightheadedness or dizziness, n (\%) & 42 (39.6) & 55 (51.9) &
0.073\tabularnewline
Worrying, n (\%) & 62 (58.5) & 73 (68.9) & 0.116\tabularnewline
\textbf{Feeling nervous}, n (\%) & 52 (49.1) & 73 (68.9) &
\textbf{0.003}\tabularnewline
Decreased interest in sex, n (\%) & 56 (52.8) & 57 (53.8) &
0.891\tabularnewline
Difficulty becoming sexually aroused, n (\%) & 60 (56.6) & 57 (53.8) &
0.679\tabularnewline
\textbf{PSQI}\textgreater{}5, n (\%) & 75(70.8) & 88(83.0) &
\textbf{0.034}\tabularnewline
\textbf{FACIT-F}[?]34, n (\%) & 48(45.3) & 65(61.3) &
\textbf{0.019}\tabularnewline
\bottomrule
\end{longtable}

DSI, dialysis symptom index; MHD, maintenance hemodialysis; PSQI,
Pittsburgh Sleep Quality Index; FACIT-F, Functional Assessment of
Chronic Illness Therapy-Fatigue Scale.

\textbf{TABLE 2} Baseline characteristics of MHD patients with high DSI
scores during lockdown.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Variables}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Overall} (n = 106)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{DSI\textless{}}40 (n = 39)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{DSI}[?]40 (n = 67)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{P}\textbf{-value}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Female, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
42(39.6)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
12(30.8)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
30(44.8)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.155\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Age (years), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
56.0(13.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
53.9(13.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
57.2(13.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.216\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Dialysis vintage (months), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
64.8(36.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
41.1(27.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
78.6(33.7)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{\textless{}0.001}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Hemoglobin (g/L), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
114.8(13.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
117.6(12.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
113.1(13.4)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.079\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Albumin (g/L), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
38.5(3.4)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
40.1(2.5)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
37.8(3.5)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{\textless{}0.001}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
BUN (mmol/L), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
22.2(8.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
23.2(8.4)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
22.2(7.4)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.275\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
ALP (U/L), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
100.3(37.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
95.1(33.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
103.4(39.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.245\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Serum Ca (mmol/L), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.2(0.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.2(0.3)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.2(0.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.605\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Serum P (mmol/L), mean (SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.8(0.5)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.8(0.5)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.9(0.6)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.169\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
iPTH (pg/mL), median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
330.5(352.8)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
331.0(335)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
330.0(432)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.171\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Ferroprotein (ug/L), median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
100.1(150.7)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
125.0(147)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
99.0(151.8)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.987\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Transferrin (g/L), median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.0(0.7)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.9(0.6)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.0(0.6)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.816\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Kt/V, median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.8(0.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.9(0.3)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.7(0.3)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{\textless{}0.001}\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

BUN, blood urea nitrogen; ALP, Alkaline phosphatase; Kt/V, dialysis
effectiveness index, DSI, dialysis effectiveness index; iPTH, intact
parathyroid hormone; MHD, maintenance hemodialysis.

\textbf{TABLE 3} Logistic regression analysis of predictors for high DSI
of MHD patients during lockdown.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Variables} & \textbf{Univariate} & \textbf{Univariate} &
\textbf{Univariate} & \textbf{Multivariate} & \textbf{Multivariate} &
\textbf{Multivariate}\tabularnewline
& \textbf{OR} & \textbf{95\%CI} & P & \textbf{OR} & \textbf{95\%CI} &
P\tabularnewline
Female, n (\%) & 0.548 & 0.238-1.261 & 0.157 & & &\tabularnewline
Age (years) & 1.020 & 0.989-1.051 & 0.215 & & &\tabularnewline
dialysis vintage (months) & 1.038 & 1.022-1.055 & \textless{}0.001 &
1.031 & 1.013-1.050 & 0.001\tabularnewline
Hemoglobin (g/L) & 0.972 & 0.941-1.004 & 0.090 & & &\tabularnewline
Albumin (g/L) & 0.718 & 0.604-0.854 & \textless{}0.001 & 0.782 &
0.627-0.975 & 0.029\tabularnewline
BUN (mmol/L) & 0.996 & 0.968-1.024 & 0.759 & & &\tabularnewline
ALP (U/L) & 1.006 & 0.995-1.018 & 0.265 & & &\tabularnewline
Serum Ca (mmol/L) & 1.628 & 0.301-8.798 & 0.572 & & &\tabularnewline
Serum P (mmol/L) & 1.676 & 0.790-3.556 & 0.179 & & &\tabularnewline
iPTH (pg/mL) & 1.001 & 1.000-1.003 & 0.102 & & &\tabularnewline
Ferroprotein (ug/L) & 1.000 & 0.997-1.002 & 0.835 & & &\tabularnewline
Transferrin (g/L) & 0.874 & 0.336-2.271 & 0.782 & & &\tabularnewline
Kt/V & 0.004 & 0.000-0.069 & \textless{}0.001 & 0.028 & 0.001-0.556 &
0.019\tabularnewline
\bottomrule
\end{longtable}

BUN, blood urea nitrogen; ALP, Alkaline phosphatase; Kt/V, dialysis
effectiveness index, DSI, dialysis effectiveness index; iPTH, intact
parathyroid hormone; MHD, maintenance hemodialysis.

\textbf{Figures}

\textbf{FIGURE 1}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{FIGURE 2}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{FIGURE 3}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{FIGURE 4}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure legends}

\textbf{FIGURE 1} Prevalence of individual symptoms in the maintenance
hemodialysis patient cohort before lockdown.

\textbf{FIGURE 2} Prevalence of individual symptoms in the maintenance
hemodialysis patient cohort during lockdown.

\textbf{FIGURE 3} Nomogram of predictors based on multivariate
regression analysis for predicting DSI\textgreater{}40.

\textbf{FIGURE 4} Calibration plots of internal validation.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/FIGURE-3/FIGURE-3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/FIGURE-4/FIGURE-4}

\end{center}
\end{figure}

\textbf{Hosted file}

\verb`TABLES.docx`  available at \url{https://authorea.com/users/589197/articles/626138-increased-dialysis-symptom-index-burden-in-maintenance-hemodialysis-patients-during-the-covid-19-lockdown-period}

\selectlanguage{english}
\FloatBarrier
\end{document}

