\documentclass[twocolumn,twoside]{article}
\makeatletter\if@twocolumn\PassOptionsToPackage{switch}{lineno}\else\fi\makeatother

\usepackage{amsfonts,amssymb,amsbsy,latexsym,amsmath,tabulary,graphicx,times,xcolor}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Following additional macros are required to function some 
% functions which are not available in the class used.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\usepackage{url,multirow,morefloats,floatflt,cancel,tfrupee}
\makeatletter


\AtBeginDocument{\@ifpackageloaded{textcomp}{}{\usepackage{textcomp}}}
\makeatother
\usepackage{colortbl}
\usepackage{xcolor}
\usepackage{pifont}
\usepackage[nointegrals]{wasysym}
\urlstyle{rm}
\makeatletter

%%%For Table column width calculation.
\def\mcWidth#1{\csname TY@F#1\endcsname+\tabcolsep}

%%Hacking center and right align for table
\def\cAlignHack{\rightskip\@flushglue\leftskip\@flushglue\parindent\z@\parfillskip\z@skip}
\def\rAlignHack{\rightskip\z@skip\leftskip\@flushglue \parindent\z@\parfillskip\z@skip}

%Etal definition in references
\@ifundefined{etal}{\def\etal{\textit{et~al}}}{}


%\if@twocolumn\usepackage{dblfloatfix}\fi
\usepackage{ifxetex}
\ifxetex\else\if@twocolumn\@ifpackageloaded{stfloats}{}{\usepackage{dblfloatfix}}\fi\fi

\AtBeginDocument{
\expandafter\ifx\csname eqalign\endcsname\relax
\def\eqalign#1{\null\vcenter{\def\\{\cr}\openup\jot\m@th
  \ialign{\strut$\displaystyle{##}$\hfil&$\displaystyle{{}##}$\hfil
      \crcr#1\crcr}}\,}
\fi
}

%For fixing hardfail when unicode letters appear inside table with endfloat
\AtBeginDocument{%
  \@ifpackageloaded{endfloat}%
   {\renewcommand\efloat@iwrite[1]{\immediate\expandafter\protected@write\csname efloat@post#1\endcsname{}}}{\newif\ifefloat@tables}%
}%

\def\BreakURLText#1{\@tfor\brk@tempa:=#1\do{\brk@tempa\hskip0pt}}
\let\lt=<
\let\gt=>
\def\processVert{\ifmmode|\else\textbar\fi}
\let\processvert\processVert

\@ifundefined{subparagraph}{
\def\subparagraph{\@startsection{paragraph}{5}{2\parindent}{0ex plus 0.1ex minus 0.1ex}%
{0ex}{\normalfont\small\itshape}}%
}{}

% These are now gobbled, so won't appear in the PDF.
\newcommand\role[1]{\unskip}
\newcommand\aucollab[1]{\unskip}
  
\@ifundefined{tsGraphicsScaleX}{\gdef\tsGraphicsScaleX{1}}{}
\@ifundefined{tsGraphicsScaleY}{\gdef\tsGraphicsScaleY{.9}}{}
% To automatically resize figures to fit inside the text area
\def\checkGraphicsWidth{\ifdim\Gin@nat@width>\linewidth
	\tsGraphicsScaleX\linewidth\else\Gin@nat@width\fi}

\def\checkGraphicsHeight{\ifdim\Gin@nat@height>.9\textheight
	\tsGraphicsScaleY\textheight\else\Gin@nat@height\fi}

\def\fixFloatSize#1{}%\@ifundefined{processdelayedfloats}{\setbox0=\hbox{\includegraphics{#1}}\ifnum\wd0<\columnwidth\relax\renewenvironment{figure*}{\begin{figure}}{\end{figure}}\fi}{}}
\let\ts@includegraphics\includegraphics

\def\inlinegraphic[#1]#2{{\edef\@tempa{#1}\edef\baseline@shift{\ifx\@tempa\@empty0\else#1\fi}\edef\tempZ{\the\numexpr(\numexpr(\baseline@shift*\f@size/100))}\protect\raisebox{\tempZ pt}{\ts@includegraphics{#2}}}}

%\renewcommand{\includegraphics}[1]{\ts@includegraphics[width=\checkGraphicsWidth]{#1}}
\AtBeginDocument{\def\includegraphics{\@ifnextchar[{\ts@includegraphics}{\ts@includegraphics[width=\checkGraphicsWidth,height=\checkGraphicsHeight,keepaspectratio]}}}

\DeclareMathAlphabet{\mathpzc}{OT1}{pzc}{m}{it}

\def\URL#1#2{\@ifundefined{href}{#2}{\href{#1}{#2}}}

%%For url break
\def\UrlOrds{\do\*\do\-\do\~\do\'\do\"\do\-}%
\g@addto@macro{\UrlBreaks}{\UrlOrds}



\edef\fntEncoding{\f@encoding}
\def\EUoneEnc{EU1}
\makeatother
\def\floatpagefraction{0.8} 
\def\dblfloatpagefraction{0.8}
\def\style#1#2{#2}
\def\xxxguillemotleft{\fontencoding{T1}\selectfont\guillemotleft}
\def\xxxguillemotright{\fontencoding{T1}\selectfont\guillemotright}

\newif\ifmultipleabstract\multipleabstractfalse%
\newenvironment{typesetAbstractGroup}{}{}%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\usepackage[authoryear]{natbib}



\newif\ifnokeywords\nokeywordsfalse

\makeatletter\input{size10-pointfive.clo}\makeatother%
\definecolor{kwdboxcolor}{RGB}{242,242,242}
\usepackage[hidelinks,colorlinks=true,allcolors=blue]{hyperref}
\linespread{1}                 
\def\floatpagefraction{0.8}

\usepackage[paperheight=11.69in,paperwidth=8.26in,top=1in,bottom=1in,left=1in,right=.75in,headsep=24pt]{geometry}

\usepackage{multirow-custom}

\makeatletter

\def\hlinewd#1{%
  \noalign{\ifnum0=`}\fi\hrule \@height #1%
  \futurelet\reserved@a\@xhline}
\def\tbltoprule{\hlinewd{1pt}\\[-14pt]}
\def\tblbottomrule{\noalign{\vspace*{6pt}}\hline\noalign{\vspace*{2pt}}}
\def\tblmidrule{\hline\noalign{\vspace*{2pt}}}



\let\@articleType\@empty
\let\@journalDoi\@empty
\let\@journalVolume\@empty
\let\@journalIssue\@empty
\let\@crossMarkLink\@empty
\let\@receivedDate\@empty
\let\@acceptedDate\@empty
\let\@revisedDate\@empty
\let\@publishedDate\@empty
\let\@copyrightYear\@empty
\let\@firstPage\@empty
\def\articleType#1{\gdef\@articleType{#1}}
\def\journalDoi#1{\gdef\@journalDoi{#1}}
\def\crossMarkLink#1{\gdef\@crossMarkLink{#1}}
\def\receivedDate#1{\gdef\@receivedDate{#1}}
\def\acceptedDate#1{\gdef\@acceptedDate{#1}}
\def\revisedDate#1{\gdef\@revisedDate{#1}}
\def\publishedDate#1{\gdef\@publishedDate{#1}}
\def\copyrightYear#1{\gdef\@copyrightYear{#1}}
\def\journalVolume#1{\gdef\@journalVolume{#1}}
\def\journalIssue#1{\gdef\@journalIssue{#1}}
\def\firstPage#1{\gdef\@firstPage{#1}}
\let\@issuelogo\@empty%
\let\@issuelogoex\@empty%
\def\issuelogo#1{\gdef\@issuelogo{#1}}
\def\issuelogoex#1{\gdef\@issuelogoex{#1}}


\def\author#1{%
  \gdef\@author{%
    \hskip-\dimexpr(\tabcolsep)\hskip5pt%
    \parbox{\dimexpr\textwidth-1pt}%
    {\fontsize{11}{13}\selectfont\raggedright #1}%
  }%
}


\usepackage{pharmascope-abs}
\usepackage{caption}
\usepackage{lastpage}
\usepackage{fancyhdr}
\usepackage[noindentafter,explicit]{titlesec}
\usepackage{fontspec}

\setmainfont[%
BoldFont=cambriab.ttf,%
ItalicFont=CAMBRIAI.TTF,%
BoldItalicFont=CAMBRIAZ.TTF]{Cambria.ttf}
\lefthyphenmin = 3

\def\title#1{%
  \gdef\@title{%
      \vspace*{-40pt}%
       \ifx\@articleType\@empty\else{\fontsize{10}{12}\scshape\selectfont\hspace{8pt}\@articleType\hfill\mbox{}\par\vspace{2pt}}\fi%
       \minipage{\linewidth}
         \hrulefill\\[-0.7pt]%%{\includegraphics[width=75pt,height=50pt]{ijrps_logo.png}}\hfill
         \mbox{~}\hspace{5pt}\parbox{.1\linewidth}{\IfFileExists{images/\@issuelogo.\@issuelogoex}{\includegraphics[width=79pt,height=61pt]{images/\@issuelogo.\@issuelogoex}}{\includegraphics[width=75pt,height=50pt]{ijrps_logo.png}}}\hfill
         \fcolorbox{kwdboxcolor}{kwdboxcolor}{\parbox{.792\linewidth}{%
          \begin{center}\fontsize{17}{17}\selectfont\scshape\vskip-7pt International Journal of Research in Pharmaceutical Sciences\hfill\end{center}%
          \vspace*{-10pt}\hspace*{4pt}{\fontsize{8}{9}\selectfont Published by JK Welfare \& Pharmascope Foundation\hfill  Journal Home Page: \href{https://ijrps.com}{\color{blue}\underline{\smash{https://ijrps.com}}}}\hspace*{4pt}\mbox{}}}%
       \par\vspace*{-1pt}\rule{\linewidth}{1.3pt}%
       \endminipage%
    \par\vspace*{9.2pt}\parbox{.98\linewidth}{\linespread{.9}\raggedright\fontsize{14}{17}\selectfont #1}%
    \vspace*{-8pt}%
  }
}


\setlength{\parindent}{0pt}
\setlength{\parskip}{0.4pc plus 1pt minus 1pt}

\def\abbrvJournalTitle{Int. J. Res. Pharm. Sci.}

\fancypagestyle{headings}{%
  \renewcommand{\headrulewidth}{0pt}%
  \renewcommand{\footrulewidth}{0.3pt}
  \fancyhf{}%
  \fancyhead[R]{%
    \fontsize{9.12}{11}\selectfont\RunningAuthor,\ \abbrvJournalTitle,\ \ifx\@journalVolume\@empty X\else\@journalVolume\fi%
    \ifx\@journalIssue\@empty\else(\@journalIssue)\fi%
    ,\ \ifx\@firstPage\@empty 1\else\@firstPage\fi-\pageref*{LastPage}%
  }%
  \fancyfoot[LO,RE]{\fontsize{9.12}{11}\selectfont\textcopyright\ International Journal of Research in Pharmaceutical Sciences}%
  \fancyfoot[RO,LE]{\fontsize{9.12}{11}\selectfont\thepage}
}\pagestyle{headings}

                                                         
\fancypagestyle{plain}{%
  \renewcommand{\headrulewidth}{0pt}%
  \renewcommand{\footrulewidth}{0.3pt}%
  \fancyhf{}%
  \fancyhead[R]{%
    \fontsize{9.12}{11}\selectfont\RunningAuthor,\ \abbrvJournalTitle,\ \ifx\@journalVolume\@empty X\else\@journalVolume\fi%
    \ifx\@journalIssue\@empty\else(\@journalIssue)\fi%
    ,\ \ifx\@firstPage\@empty 1\else\@firstPage\fi-\pageref*{LastPage}%
  }%
  \fancyfoot[LO,RE]{\fontsize{9.12}{11}\selectfont\textcopyright\ International Journal of Research in Pharmaceutical Sciences}%
  \fancyfoot[RO,LE]{\fontsize{9.12}{11}\selectfont\thepage}
  \ifx\@firstPage\@empty\else\setcounter{page}{\@firstPage}\fi
}


\def\NormalBaseline{\def\baselinestretch{1.1}}
\usepackage{textcase}
\setcounter{secnumdepth}{0}

\titleformat{\section}[block]{\bfseries\boldmath\NormalBaseline\filright\fontsize{10.5}{13}\selectfont}
{\thesection}
{6pt}
{\MakeTextUppercase{#1}}
[]
\titleformat{\subsection}[block]{\bfseries\boldmath\NormalBaseline\filright\fontsize{10.5}{12}\selectfont}
{\thesubsection}
{6pt}
{#1}
[]
\titleformat{\subsubsection}[block]{\NormalBaseline\filright\fontsize{10.5}{12}\selectfont}
{\thesubsubsection}
{6pt}
{#1}
[]
\titleformat{\paragraph}[block]{\NormalBaseline\filright\fontsize{10.5}{10}\selectfont}
{\theparagraph}
{6pt}
{#1}
[]
\titleformat{\subparagraph}[block]{\NormalBaseline\filright\fontsize{10.5}{12}\selectfont}
{\thesubparagraph}
{6pt}
{#1}
[]

\titlespacing{\section}{0pt}{.5\baselineskip}{.5\baselineskip}  
\titlespacing{\subsection}{0pt}{.5\baselineskip}{.5\baselineskip}  
\titlespacing{\subsubsection}{0pt}{.5\baselineskip}{.5\baselineskip}  
\titlespacing{\paragraph}{0pt}{.5\baselineskip}{.5\baselineskip}  
\titlespacing{\subparagraph}{0pt}{.5\baselineskip}{.5\baselineskip}

\captionsetup[figure]{skip=1.4pt,font=bf,labelsep=colon,justification=raggedright,singlelinecheck=false}
\captionsetup[table]{skip=1.4pt,font=bf,labelsep=colon,justification=raggedright,singlelinecheck=false}

\def\bibyear#1{#1}
%\def\bibjtitle#1{#1}   %%Publisher request
\def\bibauand{}
\setlength\bibsep{3pt}
\setlength\bibhang{8pt}

\makeatother
\date{}


\usepackage[flushleft]{threeparttablex}

\begin{document}


\def\RunningAuthor{Sireen Shilbayeh et al.}
\firstPage{7747}
\articleType{Original Article}
\receivedDate{13 Jul 2020}
\acceptedDate{30 Sep 2020}
\revisedDate{25 Aug 2020}
\journalVolume{2020, 11}
\journalIssue{4}
\journalDoi{ijrps.v11i4.4210}
\copyrightYear{2020}
\def\authorCount{7}
\def\affCount{4}

\def\journalTitle{International Journal of Research in Pharmaceutical Sciences}

\title{\textbf{Prevalence of anemia} \textbf{and its impact on the quality of life of renal transplant recipients in a Saudi setting}}
\author{Sireen~Shilbayeh\textsuperscript{*}\textsuperscript{1},  
            Rawan~ALBalawi\textsuperscript{2},  
            Munirah~Alhajri\textsuperscript{2},  
            Hawazan~Alkhammash\textsuperscript{2},  
            Maha~Almarhoum\textsuperscript{2},  
            Muhammed~Alwaily\textsuperscript{3}, 
            Rafat~Zahid\textsuperscript{4}~\\[5pt]{\textsuperscript{1}Department of Pharmaceutical Practice, College of Pharmacy, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi Arabia}~\\{\textsuperscript{2}College of Pharmacy, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi Arabia}~\\{\textsuperscript{3}Department of Pharmacy, Prince Sultan Military Medical City, Riyadh 11671, Saudi Arabia}~\\{\textsuperscript{4}Multi organ transplant center and kidney transplant unit, Prince Sultan Military Medical City, Riyadh 11671, Saudi Arabia}}

\begin{abstract}
Renal transplant patients show a high incidence of anemia, which is often \mbox{}\protect\newline responsible for cardiovascular morbidity and graft rejection. Anemia reportedly impacts the health-related quality of life (HRQoL); however, only a limited number of related studies have been conducted on renal transplant recipients. In this study, we estimated the prevalence of anemia and its effects on QoL of renal transplant patients in Saudi Arabia. Seventy-four patients were recruited in this study. They were asked to fill a self-reported EuroQoL instrument (EQ-5D-5L). Anemia and severe anemia were defined as Hgb \textless\ 12 g/dL and Hgb \textless\ 10 g/dL, respectively. Of the 74 recruited patients, 53 patients (71.6\%) were anemic. Around 33.7\% patients were reported to be completely healthy, with a 5-digit of 11111. With respect to EQ-5D-5L, the responses of anemic and non-anemic patients did not differ significantly. However, the response to anxiety-related questions for patients belonging to severe and mild-to-moderate anemia groups differed significantly. The final multivariate logistic model analysis revealed that the female gender of patient was significantly associated with incidence of anemia postoperatively [OR: 6.72, 95\% CI: 1.7 - 25.6, P-value = 0.000]. Interestingly, our findings revealed a higher prevalence of anemia among the Saudi kidney patients compared to those of other nations. Furthermore, multicentric prospective studies are warranted to elucidate other clinical factors and the underlying pathophysiological mechanisms.
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}Anemia,\newline post-transplant,\newline quality of life,\newline renal,\newline Saudi
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Sireen~Shilbayeh~\\ Phone:\ 009661182239450~\\  Email:\ sirraz\_6@hotmail.com
        \par}\vspace*{-11pt}\hrulefill\par{\fontsize{12}{14}\selectfont ISSN: 0975-7538}\par% 
        \textsc{DOI:}\ \href{https://doi.org/10.26452/\@journalDoi}{\textcolor{blue}{\underline{\smash{https://doi.org/10.26452/\@journalDoi}}}}\par%
        \vspace*{-11pt}\hrulefill\\{\fontsize{9.12}{10.12}\selectfont Production and Hosted by}\par{IJRPS |~\href{https://ijrps.com}{https://ijrps.com}}\par%
        \vspace*{-2pt}{\fontsize{9.12}{10.12}\selectfont\textcopyright\ \@copyrightYear\ $|$ All rights reserved.}\par%
        \vspace*{-11pt}\rule{\linewidth}{1.2pt}
        \makeatother
        
    
\section{Introduction}
In Saudi Arabia, renal replacement therapy is administered via three methods: hemodialysis, peritoneal dialysis, and renal transplantation. The first renal transplantation in the country was done in 1979 at Riyadh Military Hospital. By 2017, 11509 kidney transplantations had been conducted, among which 7838, 563, and 3108 procedures involved related, unrelated, and deceased donors, respectively \unskip~\citep{911043:20570746}.

Anaemia is commonly found in patients with end-stage renal disease, who harbour damaged kidneys that produce an inadequate amount of erythropoietin, which leads to fewer red blood cells in the bone marrow, thus, reducing the oxygen-carrying capacity of the blood \unskip~\citep{911043:20570743}. Anaemic males and females are defined as haemoglobin level (Hgb) \textless\ 13.5 g/dL and 12 g/dL, respectively \unskip~\citep{911043:20570744}. Renal transplant patients showed a high incidence of anaemia, which, in turn, is associated with cardiovascular morbidity and graft rejection. Post-renal transplant anaemia exhibited multi-factorial pathogenesis, including graft rejection, iron deficiency, chronic infection, and immunosuppressive therapy \unskip~\citep{911043:20570736}. Previous studies have reported that anaemia impacts the HRQoL of patients. A previous study in the USA was conducted with the primary objective of determining the impact of anaemia management on improving the HRQoL domains, regardless of the disease type. 

Interestingly, the study showed that efficient treatment of anaemia significantly improved the selected HRQoL subdomains in patients with renal insufficiency and cancer. Their findings indicated that erythropoiesis-stimulating protein-mediated anaemia management could improve the overall HRQoL of patients \unskip~\citep{911043:20570742}. Another study in Japan conducted on pre-menopausal women with iron-deficiency anaemia showed that iron-supplementation helped in haemoglobin recovery in patients, which, in turn, improved the overall HRQoL scores \unskip~\citep{911043:20570735}. In 2018, another study revealed that anaemia not only reduced HRQoL but also deteriorated the clinical conditions of patients, impaired their work productivity, and gave rise to other comorbidities \unskip~\citep{911043:20570740}. However, a limited number of investigators have investigated the effect of anaemia on HRQoL of post-renal transplant patients. A study conducted at Istanbul University on post-renal transplant patients reported 19\% of patients suffered from anaemia, and 4.5\% of patients suffered from severe anaemia. As expected, anaemic patients showed lower QoL than that of non-anaemic patients \unskip~\citep{911043:20570744}. Univariate regression analyses employed in another study showed a significant association of positive proteinuria and low Hgb with low HRQoL and anaemia incidence. After adjustment for other parameters, low Hgb was still significantly associated with both the abovementioned outcomes \unskip~\citep{911043:20570738}. In another study, 887 renal transplant recipients were retrospectively analyzed. This study showed a significant association between anaemia and postoperative outcomes, such as death-censored graft survival, patient survival, or graft function \unskip~\citep{911043:20570741}.  

This aim of this study was to estimate anaemia prevalence and its impact on the QoL of renal transplant patients in Saudi Arabia.
    
\section{Materials and Methods}
\textbf{Patient Recruitment}

In this cross-sectional, retrospective study, the individuals who underwent renal transplant from April 2014 to April 2019 were recruited. The inclusion criteria included mentally stable patients, age \ensuremath{\geq } 18 years, and registered at Transplantation Outpatient Clinic of Prince Sultan Military Medical City, Riyadh, Saudi Arabia. The exclusion criteria were as follows: suffering from hematologic disorders, dementia, impaired cognitive function, solid organ malignancy, and/or no consent for the study. All the included patients agreed to participate and signed a consent form.


\begin{table*}[!htbp]
\caption{\boldmath {Population characteristics} }
\label{tw-bdea3d14c3b3}
\centering 
\begin{threeparttable}

\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.34300000000000004\linewidth-2\tabcolsep}p{\dimexpr.32366666666666674\linewidth-2\tabcolsep}p{\dimexpr.3333333333333333\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Continuous data & \cAlignHack Mean (SD) & \cAlignHack Range\\
\tblmidrule 
\cAlignHack Age (y) &
  \cAlignHack 49 (14.9) &
  \cAlignHack 21-78\\
\cAlignHack Weight (kg) &
  \cAlignHack 74.7 (12) &
  \cAlignHack 44-103\\
\cAlignHack Height (cm) &
  \cAlignHack 160 (20) &
  \cAlignHack 1.6-177\\
\cAlignHack BMI &
  \cAlignHack 28 (4.8) &
  \cAlignHack 19-44.5\\
 &
   &
  \\
\cAlignHack \textbf{Categorical data} &
  \cAlignHack \textbf{Frequency (n)} &
  \cAlignHack \textbf{Percent (\%)}\\
\cAlignHack Gender  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Male &
  \cAlignHack 43 &
  \cAlignHack 58\\
\cAlignHack Female &
  \cAlignHack 31 &
  \cAlignHack 41.9\\
\cAlignHack Kidney donor state &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Living &
  \cAlignHack 68 &
  \cAlignHack 91.9\\
\cAlignHack Deceased &
  \cAlignHack 6 &
  \cAlignHack 8\\
\cAlignHack Type of living donor  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Related &
  \cAlignHack 49 &
  \cAlignHack 66\\
\cAlignHack Unrelated &
  \cAlignHack 25 &
  \cAlignHack 33.8\\
\cAlignHack Hypertension &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 14 &
  \cAlignHack 18.9\\
\cAlignHack Yes &
  \cAlignHack 60 &
  \cAlignHack 81\\
\cAlignHack Dyslipidemia &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 64 &
  \cAlignHack 86.5\\
\cAlignHack Yes &
  \cAlignHack 9 &
  \cAlignHack 12\\
\cAlignHack Cardiovascular &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 68 &
  \cAlignHack 91.9\\
\cAlignHack Yes &
  \cAlignHack 6 &
  \cAlignHack 8\\
\cAlignHack Diabetes &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 43 &
  \cAlignHack 58\\
\cAlignHack Yes &
  \cAlignHack 31 &
  \cAlignHack 41.9\\
\cAlignHack ESA use &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 35 &
  \cAlignHack 47\\
\cAlignHack Yes &
  \cAlignHack 39 &
  \cAlignHack 52.7\\
\cAlignHack Induction phase &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 41 &
  \cAlignHack 55\\
\cAlignHack Yes &
  \cAlignHack 33 &
  \cAlignHack 44.6\\
\cAlignHack IV immunoglobulin &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack No &
  \cAlignHack 67 &
  \cAlignHack 90.5\\
\cAlignHack Yes &
  \cAlignHack 7 &
  \cAlignHack 9.5\\
\cAlignHack Dialysis &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Yes &
  \cAlignHack 52 &
  \cAlignHack 70\\
\cAlignHack Type of dialysis &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Hemodialysis &
  \cAlignHack 42 &
  \cAlignHack 56.8\\
\cAlignHack Peritoneal dialysis &
  \cAlignHack 10 &
  \cAlignHack 13.5\\
\tblbottomrule 
\end{tabulary}\par 
\begin{tablenotes}\footnotesize 
    
\item{Abbreviations: ESA, erythropoiesis-stimulating agent. Inductionphase: use of either basiliximab or thymoglobulin. Continuous data was presentedas mean (SD) and range. Categorical data was presented as frequencies (n) and percentage (\%).}
\end{tablenotes}
\end{threeparttable}

\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Post-transplant follow-up} }
\label{tw-fd45555f3e00}
\centering 
\begin{threeparttable}

\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.3404\linewidth-2\tabcolsep}p{\dimexpr.3217\linewidth-2\tabcolsep}p{\dimexpr.3379\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Test & \cAlignHack Mean (SD) & \cAlignHack Range\\
\tblmidrule 
\cAlignHack  &
  \cAlignHack \textbf{V1} &
  \cAlignHack \textbf{V2}\\
\cAlignHack Leukocyte (\ensuremath{\times}10\ensuremath{^{3}}) &
  \cAlignHack 8.6 (3.4), 2.2-20 &
  \cAlignHack 7.5 (2.8), 3.1-17\\
\cAlignHack Hgb (g/dL) &
  \cAlignHack 10.7 (2.2), 6.9-19 &
  \cAlignHack 13 (1.9), 9-16\\
\cAlignHack Hct (\%) &
  \cAlignHack .33 (.067), .21-.49 &
  \cAlignHack .41 (.060), .27-.54\\
\cAlignHack MCH (pg) &
  \cAlignHack 28.7 (2.8), 19-39 &
  \cAlignHack 27 (3), 19-36\\
\cAlignHack Platelet (\ensuremath{\times}10\ensuremath{^{3}}) &
  \cAlignHack 249 (101), 71-497 &
  \cAlignHack 263 (69), 112-439\\
\cAlignHack \textbf{Diagnosis of anemia} &
  \cAlignHack \textbf{Frequency (n)} &
  \cAlignHack \textbf{Percent (\%)}\\
\cAlignHack Early anemia &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Mild-to-moderate &
  \cAlignHack 23 &
  \cAlignHack 31\\
\cAlignHack Severe &
  \cAlignHack 29 &
  \cAlignHack 39\\
\cAlignHack Late anemia &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Mild-to-moderate &
  \cAlignHack 16 &
  \cAlignHack 21.6\\
\cAlignHack Severe &
  \cAlignHack 4 &
  \cAlignHack 5.4\\
\cAlignHack Total &
  \cAlignHack 53 &
  \cAlignHack 71.6\\
\tblbottomrule 
\end{tabulary}\par 
\begin{tablenotes}\footnotesize 
    
\item{Abbreviations: Hgb, hemoglobin; Hct, hematocrit; MCH, mean corpuscular hemoglobin. V1; measurement at clinic visit within 1-3 months post renal transplant, V2; measurement at last clinic visit.}
\end{tablenotes}
\end{threeparttable}

\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {EQ-5D-5L frequencies and proportions among post-transplant patients} }
\label{tw-e32bf9bb2c04}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.1687285714285714\linewidth-2\tabcolsep}p{\dimexpr.14242857142857142\linewidth-2\tabcolsep}p{\dimexpr.13691428571428576\linewidth-2\tabcolsep}p{\dimexpr.12161428571428571\linewidth-2\tabcolsep}p{\dimexpr.19430000000000003\linewidth-2\tabcolsep}p{\dimexpr.2360142857142857\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack Mobility & \cAlignHack Self-care & \cAlignHack Activities & \cAlignHack Pain / discomfort & \cAlignHack Anxiety/ depression\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack n (\%) & \cAlignHack n (\%) & \cAlignHack n (\%) & \cAlignHack n (\%) & \cAlignHack n (\%)\\
\tblmidrule 
\cAlignHack No problem &
  \cAlignHack 44 (59.5) &
  \cAlignHack 64 (86.5) &
  \cAlignHack 55 (74) &
  \cAlignHack 36 (48.6) &
  \cAlignHack 46 (62)\\
\cAlignHack Slight problem &
  \cAlignHack 11 (14.9) &
  \cAlignHack 4 (5.4) &
  \cAlignHack 9 (12) &
  \cAlignHack 15 (20) &
  \cAlignHack 18 (24)\\
\cAlignHack Moderate problem &
  \cAlignHack 12 (16.2) &
  \cAlignHack 3 (4.1) &
  \cAlignHack 5 (6.8) &
  \cAlignHack 19 (25.7) &
  \cAlignHack 6 (8)\\
\cAlignHack Severe problem &
  \cAlignHack 6 (8.1) &
  \cAlignHack 2 (2.7) &
  \cAlignHack 3 (4) &
  \cAlignHack 3 (4) &
  \cAlignHack 3 (4)\\
\cAlignHack Extreme problem/ unable to do daily activities &
  \cAlignHack 1 (1.4) &
  \cAlignHack 1 (1.4) &
  \cAlignHack 2 (2.7) &
  \cAlignHack 1 (1.4) &
  \cAlignHack 1 (1.4)\\
\cAlignHack Total &
  \cAlignHack 74 (100) &
  \cAlignHack 74 (100) &
  \cAlignHack 74 (100) &
  \cAlignHack 74 (100) &
  \cAlignHack 74 (100)\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {EQ-5D-5L frequencies and proportion according to incidence of anemia} }
\label{tw-052704a161ae}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.34949999999999996\linewidth-2\tabcolsep}p{\dimexpr.24810000000000002\linewidth-2\tabcolsep}p{\dimexpr.26439999999999998\linewidth-2\tabcolsep}p{\dimexpr.138\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Dimension & \cAlignHack Anemia n (\%) & \cAlignHack Without anemia n (\%) & \cAlignHack P value \\
\tblmidrule 
\cAlignHack  &
  \multicolumn{2}{p{\dimexpr(.5125\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Mobility}} &
  \cAlignHack \\
\cAlignHack No problem &
  \cAlignHack 34 (64.2) &
  \cAlignHack 10 (47.6) &
  \cAlignHack .416\\
\cAlignHack Slight problem &
  \cAlignHack 8 (15.1) &
  \cAlignHack 3 (14.3) &
  \cAlignHack \\
\cAlignHack Moderate problem &
  \cAlignHack 6 (11.3) &
  \cAlignHack 6 (28.6) &
  \cAlignHack \\
\cAlignHack Severe problem &
  \cAlignHack 4 (7.5) &
  \cAlignHack 2 (9.5) &
  \cAlignHack \\
\cAlignHack Extreme problems/unable to move &
  \cAlignHack 1 (1.9) &
  \cAlignHack 0 (0.0) &
  \cAlignHack \\
\cAlignHack  &
  \multicolumn{2}{p{\dimexpr(.5125\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Self-care}} &
  \cAlignHack \\
\cAlignHack No problem &
  \cAlignHack 47 (88.7) &
  \cAlignHack 17 (81.0) &
  \cAlignHack .534\\
\cAlignHack Slight problem &
  \cAlignHack 3 (5.7) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack Moderate problem &
  \cAlignHack 1 (1.9) &
  \cAlignHack 2 (9.5) &
  \cAlignHack \\
\cAlignHack Severe problem &
  \cAlignHack 1 (1.9) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack Extreme problems/unable to do self-care &
  \cAlignHack 1 (1.9) &
  \cAlignHack 0 (0.0) &
  \cAlignHack \\
\cAlignHack  &
  \multicolumn{2}{p{\dimexpr(.5125\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Usual activities}} &
  \cAlignHack \\
\cAlignHack No problem &
  \cAlignHack 39 (73.6) &
  \cAlignHack 16 (76.2) &
  \cAlignHack .706\\
\cAlignHack Slight problem &
  \cAlignHack 8 (15.1) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack Moderate problem &
  \cAlignHack 3 (5.7) &
  \cAlignHack 2 (9.5) &
  \cAlignHack \\
\cAlignHack Severe problem &
  \cAlignHack 2 (3.8) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack Extreme problem/ unable to do daily activities &
  \cAlignHack 1 (1.9) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack  &
  \multicolumn{2}{p{\dimexpr(.5125\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Pain /discomfort}} &
  \cAlignHack \\
\cAlignHack No pain /discomfort &
  \cAlignHack 25 (47.2) &
  \cAlignHack 11 (52.4) &
  \cAlignHack .889\\
\cAlignHack Slight pain /discomfort &
  \cAlignHack 12 (22.6) &
  \cAlignHack 3 (14.3) &
  \cAlignHack \\
\cAlignHack Moderate pain /discomfort &
  \cAlignHack 13 (24.5) &
  \cAlignHack 6 (28.6) &
  \cAlignHack \\
\cAlignHack Severe pain /discomfort &
  \cAlignHack 2 (3.8) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack Extreme pain /discomfort &
  \cAlignHack 1 (1.9) &
  \cAlignHack 0 (0.0) &
  \cAlignHack \\
\cAlignHack  &
  \multicolumn{2}{p{\dimexpr(.5125\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Anxiety/depression}} &
  \cAlignHack \\
\cAlignHack Not anxious/depressed &
  \cAlignHack 32 (60.4) &
  \cAlignHack 14 (66.7) &
  \cAlignHack .378\\
\cAlignHack Slightly anxious /depressed &
  \cAlignHack 13 (24.5) &
  \cAlignHack 5 (23.8) &
  \cAlignHack \\
\cAlignHack Moderately anxious /depressed &
  \cAlignHack 5 (9.4) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\cAlignHack Severely anxious /depressed &
  \cAlignHack 3 (5.7) &
  \cAlignHack 0 (0.0) &
  \cAlignHack \\
\cAlignHack Extremely anxious /depressed &
  \cAlignHack 0 (0.0) &
  \cAlignHack 1 (4.8) &
  \cAlignHack \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
\textbf{Data Collection}

The electronic medical records of the patients were used to obtain the following data: age, body mass index, gender, duration since transplant, living/dead status, relation to the donor, Hbg, platelets, use of iron, use of immunosuppression therapy, including induction phase therapy (basiliximab vs thymoglobulin), maintenance phase therapy (tacrolimus-based vs cyclosporin-based), intravenous (IV) immunoglobulin, supportive therapies (antiviral, antibiotic, and diabetes medications), and vitamin supplements (ferrous, B12, folate, etc.). Dialysis status and type before transplantation were also recorded. At three months postoperatively and last clinical visit, other haematological parameters were recorded, such as Hbg, mean cell volume (MCV), hematocrit (Hct), platelets, and leucocyte counts. Mild-to-moderate and severe anemia were defined by Hbg \textless\ 12 g/dL and Hbg \textless\ 10 g/dL, respectively. 

\textbf{EQ-5D-5L questionnaire and QoL assessment}

Patient QoL was assessed using the EQ-5D-5L questionnaire \unskip~\citep{911043:20570745}. The questionnaire consisted of five domains: self-care, anxiety/depression, mobility, usual activities, and pain/discomfort. For every question, five responses were available: no, slight, moderate, severe, and extreme problem. All the responses were coded based on the user manual. Based on the patient responses, a five-digit code was derived, with each digit about each domain. A code of 11111 represented no problem in any domain and completely healthy patient. The questionnaire also included a visual analogue scale (VAS) that recorded the opinion of the patients regarding their current health on a visual equivalent scale ranging from a score of 0 (least QoL) to 100 (highest QoL). Thus, EQ-VAS essentially provided a quantitative measure of patients' health based on their perception \unskip~\citep{911043:20570745}. 
    
\section{\textbf{STATISTICAL ANALYSIS}}
SPSS (version 27) was used to conduct all statistical analyses. Initially, the data distribution was examined for normality using the Smirnov Test. Univariate analyses were used to assess the association between patient variables and anaemia prevalence. The variables that were found to be significantly associated with anaemia prevalence were fitted into a multivariate logistic regression model to assess their final significance using forward and backward selection methods. Intervariable differences were assessed using Pearson's Chi-square test. P-value \textless\ 0.05 represented statistically significant differences. 
    
\section{Results and Discussion}
Table~\ref{tw-bdea3d14c3b3} shows the clinical, laboratory, and demographic data of all patients. Most of the patients were middle-aged (median age: 49 years; range: 21-78 years) with 58.1\% male and 41.9\% female patients. 

Of all patients, 53 (71.6\%) patients were anaemic. During the induction phase, 55.4\% of patients received basiliximab, and 44.6\% of patients received thymoglobulin. Moreover, during the maintenance phase, 91.9\% of patients received a tacrolimus-based regimen, while 8.1\% of patients received cyclosporin-based regimen. Around 9.5\% of patients received IV immunoglobulin. Among supportive therapies, antiviral, antibiotic, and diabetes medications were administered in 8.1\%, 39.3\%, and 2.7\% patients, respectively. 

\textbf{Anaemia prevalence according to patient variables}

The correlation between anaemia prevalence and patient's variables was examined using the univariate and multivariate analyses (Table~\ref{tw-fd45555f3e00}). Final model findings revealed that prevalence of anemia was most significantly associated with female gender [OR: 6.72, 95\% CI: 1.7- 25.6, P-value = 0.000; (25 males, 47.2\%) vs. (28 females, 52.9\%)]. None of the other demographic variables showed any significant association with anaemia prevalence. Furthermore, the use of IV immunoglobulin was also significantly associated with the incidence of late anaemia [P-value = 0.012; (57\% in females vs 23\% in males)]. This finding was consistent with those of previous studies \unskip~\citep{911043:20570739,911043:20570737}. None of the used therapies was associated with anaemia prevalence (all P-values \ensuremath{\geq } 0.05). Surprisingly, prior use of and/or type of dialysis used preoperatively did not significantly affect anaemia prevalence (P-value = 0.4).  

\textbf{QoL assessment by EQ-5D-5L }

Table~\ref{tw-e32bf9bb2c04} shows the EQ-5D-5L scores of all patients. Around 33.7\% of patients corresponded to a 5-digit score of 11111 that represented a full state of health. Table~\ref{tw-052704a161ae} shows no significant difference in EQ-5D-5L scores of patients in anaemic and non-anaemic groups. However, the response related to the anxiety domain of EQ-5Q-5L differed significantly between the patients of early severe and mild-to-moderate anaemia groups (P-value = 0.02). Furthermore, the responses of the patients in the late anaemia group and those of other groups were not significantly different. 

\textbf{Study limitations}

The study was conducted at only one centre. Thus, our results could not be extrapolated or generalized to all Saudi renal transplant settings. Furthermore, the anaemia status of the patients was defined by their Hbg levels that were obtained in a retrospective manner, which might be prone to error due to inaccurate entry in the patients' medical files. Therefore, larger-scale, prospective-design, cohort studies are needed to elucidate further anaemia incidence and its underlying pathophysiological mechanisms and sub-classifications.
    
\section{Conclusion }
To the best of our knowledge, this is the first study to determine anaemia prevalence in post-renal transplant patients in Saudi Arabia. Interestingly, in this study, the anaemia prevalence in Saudi patients was observed to be higher than that in patients of other countries. Around 31.1\% and 40.5\% of our patients suffered from mild-to-moderate and severe anaemia, respectively. However, anaemia incidence was not observed to affect the QoL of patients. The most significant predictors of anaemia among Saudi renal transplant patients were female gender and IV immunoglobulin use. Further studies need to focus on other patient parameters as potential predictors of anaemia prevalence and their impact on the QoL of post-renal and non-renal transplant patients. 

\textbf{Conflict of Interest} \textbf{\space }

The authors declare that they have no conflict of interest.\textbf{\space }

\textbf{Funding Support} \textbf{\space }

This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program.
    

\bibliographystyle{pharmascope_apa-custom}

\bibliography{\jobname}
\end{document}
