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\def\RunningAuthor{Pritha L et al.}
\firstPage{2081}
\articleType{Original Article}
\receivedDate{10.03.2019}
\acceptedDate{13.06.2019}
\revisedDate{08.06.2019}
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\journalDoi{ijrps.v10i3.1427}
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\title{Effectiveness of acupressure on bio-physiological parameters in mediosternotomy patients}
\author{Pritha~L\textsuperscript{*}\textsuperscript{1},  
            Valliammal~S\textsuperscript{2},  
            Sai~sailesh~Kumar~Goothy\textsuperscript{3}, 
            Vijayaraghavan~R\textsuperscript{4}~\\[5pt]{\textsuperscript{1}Sri SathyaSai Institute of Higher Medical Sciences, College of Nursing, EPIP Area, Bangalore, India}~\\{\textsuperscript{2}NIMHANS College of Nursing, NIMHANS, Bangalore, India}~\\{\textsuperscript{3}Department of Physiology\unskip, Vishnu Dental College, Bhimavaram, Andhra Pradesh, India}~\\{\textsuperscript{4}Saveetha Institute of Medical and Technical Sciences, Chennai , Tamil Nadu, India}}

\begin{abstract}
 Acupressure is one of the emerging alternative therapies for the management of the pain, anxiety and other physiological indexes. The present study was conducted at Sri Sathya Sai Institute of Higher Medical Sciences, Whitefield, Bangalore. A total of twenty male and female patients those who undergo open-heart surgery via median sternotomy were part of the study after obtaining the written informed consent. After recording the demographic data, the participants were randomly grouped into control and intervention groups using random numbers generated by computer with 10 participants in each group. The intervention will be provided at PC6 acupressure point, situated on the inner side of the forearm, three fingers below the wrist joint, three times a day (6 am, 12 noon, 6 pm). There was a significant decrease in the heart rate and blood pressure and a significant increase in the partial pressure of oxygen. Further, there was a decrease in the serum troponin T levels. The study support implementation of the acupressure. 
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}Acupressure,\newline Pain management,\newline Bio-Physiological parameters,\newline Alternative therapy
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Pritha~L~\\ Phone:\ ~\\  Email:\ prithashashu@gmail.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%
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        \makeatother
        
    
\section{Introduction}
Management of pain is a very essential part of medical history. Though there are several effective drugs are available, they are associated with significant side effects. Hence, the long term use of these medications is not advisable. Currently, there is an increase in the trend to the alternative therapies which are cost-effective and also not associated with side effects. Acupressure is one of the emerging alternative therapies for the management of the pain, anxiety and other physiological indexes. As it is cost-effective and non-invasive, the majority of practitioners prefer the application of acupressure in the management of pain \unskip~\citep{540985:12333525}. 

Further, majority of the patients prefer complementary medicine as it has no side effects. Interestingly, acupressure was reported to be effective in the management of the pain effectively in severe conditions like cancer and leukemia patients also \unskip~\citep{540985:12333526}. It was reported that the acupressure not only relieves the pain but also speed up the recovery of the patients after the surgery\unskip~\citep{540985:12333527}. Though the acupressure is an effective method in the management of pain, the studies supporting the scientific evidence are sparse. Hence, the present study was undertaken to observe the effect of acupressure on bio-physiological parameters in mediosternotomy patients.
    
\section{Materials and Methods}
\textbf{Study Design}

\textbf{\space }Experimental study with pre and post with control design.

\textbf{Study Setting}

\textbf{\space }The present study was conducted at Sri Sathya Sai Institute of Higher Medical Sciences, Whitefield, Bangalore.

\textbf{Study Population}

\textbf{\space }A total of twenty male and female patients those who undergo open-heart surgery via median sternotomy were part of the study after obtaining the written informed consent. After recording the demographic data, the participants were randomly grouped into control and intervention groups using random numbers generated by computer with 10 participants in each group. 

Group Control (= 10): No intervention applied

Group Experimental (= 10): Acupressure was applied

The participants were recruited using the following criteria.

\textbf{Inclusion criteria}


  
  \begin{enumerate}
  \item \relax Male and female participants between the age group of 19 and 60 years.
  \item \relax Patients those who report pain during deep inspiration with an intensity of at least 3 on a 0{\textendash}10 rating scale under standard analgesia. 
  \end{enumerate}
  

\begin{itemize}
  \item \relax Patients those who are extubated.
  \item \relax Patients on the first operative day and conscious.
  \item \relax Patients who can communicate through English, Tamil, Hindi and kannada.
  \item \relax Patients those who are willing to participate in a study.
\end{itemize}
  \textbf{Exclusion criteria}



\begin{itemize}
  \item \relax Patients who are having post-operative complications.
  \item \relax Patients with the emergency operation, chronic pain and hemodynamically unstable.
  \item \relax Patients who underwent graft donor site from hands for CABG.
\end{itemize}
  \textbf{Accupressure}

\textbf{\space }The intervention will be provided at PC6 acupressure point, situated on the inner side of the forearm, three fingers below the wrist joint, three times a day. 

\textbf{Assessment of Bio-Physiological parameters}

Blood pressure was recorded by using Diamond digital sphygmomanometers (BPDG024) and P02, pulse rate was recorded by using pulse oximeter (EDAN H100B) respiratory rate was measured manually \unskip~\citep{540985:12333529,540985:12333528}.\textbf{\space }

\textbf{Ethical consideration}

The study was approved by the Institutional Ethics Committee. A written, informed consent was obtained from all the participants. The study was performed in accordance with the "Ethical Guidelines for Biomedical Research on Human Participants, 2006" by the Indian Council of Medical Research and the Declaration of Helsinki, 2008.

\textbf{Data analysis}

Data was analyzed using SPSS 20.0. Data were expressed as frequency and percentage. Pain scores were expressed as mean and SD. A probability value of less than 0.05 was considered significant.
    
\section{Results and Discussion}
Table~\ref{tw-bc69d3829094}  presents the comparison of post values of heart rate among control and experimental groups. Table~\ref{tw-8cb68bf97074} presents the comparison of post values of respiratory rate among control and experimental groups. Table~\ref{tw-d3a2e8b01b29} presents the comparison of post values of systolic blood pressure among control and experimental groups.\textbf{\space }Table~\ref{tw-cda25bbdef0b} presents the comparison of post values of Diastolic blood pressure among control and experimental groups. Table~\ref{tw-1bd71e469e59} presents the comparison of post values of partial pressure of oxygen (\%) among control and experimental groups. Table~\ref{tw-189317fe0e0a} presents the comparison of post values of Serum Troponin T among control and experimental groups.

\textbf{Discussion}

The present study was undertaken to observe the effect of acupressure on bio-physiological parameters in mediosternotomy patients. There was a significant decrease in the heart rate, blood pressure and significant improvement in the partial pressure of oxygen followed by the acupressure. The serum troponin T levels also significantly decreased followed by the acupressure. It was reported that the pain levels were reduced significantly followed by the acupressure in conditions like after the childbirth and after the surgery. 


\begin{table*}[!htbp]
\caption{\boldmath {Comparison of post values of heart rate amongcontrol and experimental groups (Data was expressed as mean and SD). (Exp-experimentalgroup, Con- control group)} }
\label{tw-bc69d3829094}
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\begin{tabulary}{\linewidth}{p{\dimexpr.2416\linewidth-2\tabcolsep}p{\dimexpr.0702\linewidth-2\tabcolsep}p{\dimexpr.20520000000000003\linewidth-2\tabcolsep}p{\dimexpr.283\linewidth-2\tabcolsep}p{\dimexpr.20\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Day-1}\\
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\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
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\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00 am} &
  112.3\ensuremath{\pm}14.47 &
  108.8\ensuremath{\pm}12.66 &
  0.5719\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{12-1:00 pm} &
  107.2\ensuremath{\pm}13.83 &
  104.2\ensuremath{\pm}12.77 &
  0.6204\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00pm} &
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  98.4\ensuremath{\pm}11.62 &
  0.5133\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00 am} &
  109.6\ensuremath{\pm}5.64 &
  109.6\ensuremath{\pm}5.64 &
  1\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{12-1:00pm} &
  106.2\ensuremath{\pm}4.85 &
  106.4\ensuremath{\pm}5.06 &
  0.9291\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00 pm} &
  100.8\ensuremath{\pm}4.92 &
  100.8\ensuremath{\pm}4.92 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-2}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00am} &
  95\ensuremath{\pm}11.60 &
  92.6\ensuremath{\pm}11.51 &
  0.6478\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{12-1:00pm} &
  91\ensuremath{\pm}8.81 &
  88\ensuremath{\pm}8.16 &
  0.4398\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00pm} &
  86.80\ensuremath{\pm}5.18 &
  84.80\ensuremath{\pm}5.18 &
  0.3994\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00am} &
  96.4\ensuremath{\pm}1.84 &
  96.4\ensuremath{\pm}1.84 &
  1\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{12-1:00pm} &
  93.20\ensuremath{\pm}2.70 &
  93.20\ensuremath{\pm}2.70 &
  1\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00pm} &
  90.2\ensuremath{\pm}1.48 &
  90.20\ensuremath{\pm}1.48 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-3}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
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  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00am} &
  86.4\ensuremath{\pm}4.70 &
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\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{12-1:00pm} &
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\multicolumn{2}{p{\dimexpr(.3118\linewidth-2\tabcolsep)}}{5-6:00pm} &
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  79.8\ensuremath{\pm}4.57 &
  0.3772\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Control group}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{88.60\ensuremath{\pm}1.65} &
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  1\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{88.60\ensuremath{\pm}2.67} &
  88.60\ensuremath{\pm}2.67 &
  1\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{86.60\ensuremath{\pm}2.50} &
  86.60\ensuremath{\pm}2.50 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-4}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\textbf{Test time} &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{\textbf{Pre}} &
  \textbf{Post} &
  \textbf{p-value}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{81\ensuremath{\pm}5.60} &
  78.8\ensuremath{\pm}4.64 &
  0.3512\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{80.8\ensuremath{\pm}3.16} &
  78.6\ensuremath{\pm}4.01 &
  0.1893\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{78.8\ensuremath{\pm}3.01} &
  76.4\ensuremath{\pm}3.37 &
  0.1105\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{84.4\ensuremath{\pm}2.46} &
  84.4\ensuremath{\pm}2.46 &
  1\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{82.4\ensuremath{\pm}2.27} &
  82.4\ensuremath{\pm}2.27 &
  1\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.27540000000000003\linewidth-2\tabcolsep)}}{80.60\ensuremath{\pm}1.65} &
  80.60\ensuremath{\pm}1.65 &
  1\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Comparison of post values of respiratory rate among control and experimental groups (Data was expressed as mean and SD). (Exp-experimental group, Con- control group)} }
\label{tw-8cb68bf97074}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.27060000000000002\linewidth-2\tabcolsep}p{\dimexpr.04219999999999997\linewidth-2\tabcolsep}p{\dimexpr.2221\linewidth-2\tabcolsep}p{\dimexpr.26509999999999998\linewidth-2\tabcolsep}p{\dimexpr.20\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Day-1}\\
\rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Experiment group}\\
\tblmidrule 
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00 am} &
  25.80\ensuremath{\pm}1.99 &
  24.20\ensuremath{\pm}1.99 &
  0.0888\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{12-1:00 pm} &
  24.60\ensuremath{\pm}2.32 &
  22.60\ensuremath{\pm}2.32 &
  0.0697\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00pm} &
  23.60\ensuremath{\pm}2.46 &
  21.80\ensuremath{\pm}2.39 &
  0.1145\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00 am} &
  25.8\ensuremath{\pm}0.63 &
  25.8\ensuremath{\pm}0.63 &
  1\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{12-1:00pm} &
  25.20\ensuremath{\pm}1.03 &
  25.20\ensuremath{\pm}1.03 &
  1\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00 pm} &
  23.60\ensuremath{\pm}0.84 &
  23.60\ensuremath{\pm}0.84 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-2}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00am} &
  22.60\ensuremath{\pm}1.90 &
  21\ensuremath{\pm}1.70 &
  0.0624\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{12-1:00pm} &
  21.80\ensuremath{\pm}1.75 &
  20.20\ensuremath{\pm}1.14 &
  0.0261*\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00pm} &
  21.40\ensuremath{\pm}0.97 &
  20.60\ensuremath{\pm}1.90 &
  0.2502\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-3}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  p-value\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00am} &
  21.60\ensuremath{\pm}0.84 &
  20\ensuremath{\pm}0.94 &
  0.0008***\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{12-1:00pm} &
  20.60\ensuremath{\pm}0.97 &
  19.60\ensuremath{\pm}0.84 &
  0.0239*\\
\multicolumn{2}{p{\dimexpr(.3128\linewidth-2\tabcolsep)}}{5-6:00pm} &
  21.40\ensuremath{\pm}0.97 &
  19.60\ensuremath{\pm}0.84 &
  0.0003***\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.2643\linewidth-2\tabcolsep)}}{21.60\ensuremath{\pm}0.84} &
  21.60\ensuremath{\pm}0.84 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-4}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\textbf{Test time} &
  \multicolumn{2}{p{\dimexpr(.2643\linewidth-2\tabcolsep)}}{\textbf{Pre}} &
  \textbf{Post} &
  \textbf{p-value}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.2643\linewidth-2\tabcolsep)}}{21\ensuremath{\pm}1.05} &
  19.6\ensuremath{\pm}0.84 &
  0.0042*\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.2643\linewidth-2\tabcolsep)}}{20\ensuremath{\pm}0.94} &
  18.4\ensuremath{\pm}1.26 &
  0.0049*\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.2643\linewidth-2\tabcolsep)}}{20\ensuremath{\pm}0.94} &
  18.2\ensuremath{\pm}0.63 &
  0.0001***\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{}\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Comparison of post values of systolic blood pressure among control and experimental groups(Data was expressed as mean and SD). (Exp-experimental group, Con- control group)} }
\label{tw-d3a2e8b01b29}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.20\linewidth-2\tabcolsep}p{\dimexpr.04339999999999999\linewidth-2\tabcolsep}p{\dimexpr.23740000000000002\linewidth-2\tabcolsep}p{\dimexpr.26799999999999997\linewidth-2\tabcolsep}p{\dimexpr.2512\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Day-1}\\
\rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Experiment group}\\
\tblmidrule 
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00 am} &
  139.2\ensuremath{\pm}6.94 &
  135.6\ensuremath{\pm}6.59 &
  0.2496\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{12-1:00 pm} &
  135\ensuremath{\pm}6.20 &
  132.6\ensuremath{\pm}5.97 &
  0.3894\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00pm} &
  131.20\ensuremath{\pm}6.75 &
  117.60 &
  0.1908\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00 am} &
  139.2\ensuremath{\pm}2.15 &
  139.2\ensuremath{\pm}2.15 &
  1\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{12-1:00pm} &
  136.4\ensuremath{\pm}2.80 &
  136.40\ensuremath{\pm}2.80 &
  `1\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00 pm} &
  133.8\ensuremath{\pm}2.39 &
  133.8\ensuremath{\pm}2.80 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-2}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00am} &
  127\ensuremath{\pm}7.38 &
  123.6\ensuremath{\pm}6.79 &
  0.2976\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{12-1:00pm} &
  125.4\ensuremath{\pm}5.74 &
  122.6\ensuremath{\pm}5.89 &
  0.2959\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00pm} &
  124.2\ensuremath{\pm}7.15 &
  121.8\ensuremath{\pm}6.76 &
  0.4505\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00am} &
  131.8\ensuremath{\pm}2.39 &
  131.8\ensuremath{\pm}2.39 &
  1\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{12-1:00pm} &
  130\ensuremath{\pm}1.33 &
  130\ensuremath{\pm}1.33 &
  1\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00pm} &
  129.4\ensuremath{\pm}1.65 &
  129.4\ensuremath{\pm}1.65 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-3}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00am} &
  123.6\ensuremath{\pm}4.79 &
  121\ensuremath{\pm}5.68 &
  0.2828\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{12-1:00pm} &
  121.2\ensuremath{\pm}6.94 &
  119.8\ensuremath{\pm}7.97 &
  0.6802\\
\multicolumn{2}{p{\dimexpr(.2434\linewidth-2\tabcolsep)}}{5-6:00pm} &
  121.60\ensuremath{\pm}6.65 &
  119\ensuremath{\pm}6.62 &
  0.3924\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{127.6\ensuremath{\pm}1.26} &
  127.6\ensuremath{\pm}1.26 &
  1\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{128.6\ensuremath{\pm}2.99} &
  128.6\ensuremath{\pm}2.99 &
  1\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{128.8\ensuremath{\pm}2.35} &
  128.8\ensuremath{\pm}2.35 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-4}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\textbf{Test time} &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{\textbf{Pre}} &
  \textbf{Post} &
  \textbf{p-value}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{121\ensuremath{\pm}8.01} &
  117.2\ensuremath{\pm}8.28 &
  0.3109\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{116.6\ensuremath{\pm}6.67} &
  114.4\ensuremath{\pm}6.98 &
  0.4804\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{113.8\ensuremath{\pm}7.27} &
  112.4\ensuremath{\pm}6.92 &
  0.6643\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{128.8\ensuremath{\pm}1.40} &
  129\ensuremath{\pm}1.70 &
  0.7771\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{127.6\ensuremath{\pm}2.07} &
  127.8\ensuremath{\pm}2.20 &
  0.8364\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.28080000000000002\linewidth-2\tabcolsep)}}{128\ensuremath{\pm}3.40} &
  127.8\ensuremath{\pm}3.58 &
  0.8995\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Comparison of post values of Diastolic blood pressure among control and experimental groups (Data was expressed as mean and SD). (Exp-experimental group, Con-control group} }
\label{tw-cda25bbdef0b}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.2457\linewidth-2\tabcolsep}p{\dimexpr.04259999999999998\linewidth-2\tabcolsep}p{\dimexpr.241\linewidth-2\tabcolsep}p{\dimexpr.2582\linewidth-2\tabcolsep}p{\dimexpr.2125\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Day-1}\\
\rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Experiment group}\\
\tblmidrule 
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00 am} &
  90.80\ensuremath{\pm}3.79 &
  88.6\ensuremath{\pm}3.13 &
  0.1746\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{12-1:00 pm} &
  88.8\ensuremath{\pm}3.55 &
  86.8\ensuremath{\pm}3.55 &
  0.2242\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00pm} &
  84.8\ensuremath{\pm}2.15 &
  82.8\ensuremath{\pm}1.69 &
  0.0327*\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00 am} &
  89.2\ensuremath{\pm}3.01 &
  89.4\ensuremath{\pm}3.13 &
  0.8859\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{12-1:00pm} &
  87.8\ensuremath{\pm}2.39 &
  87.8\ensuremath{\pm}2.39 &
  1\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00 pm} &
  87.6\ensuremath{\pm}1.58 &
  87.6\ensuremath{\pm}1.58 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-2}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00am} &
  82\ensuremath{\pm}1.33 &
  79.8\ensuremath{\pm}1.14 &
  0.0009***\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{12-1:00pm} &
  80.6\ensuremath{\pm}1.90 &
  78.8\ensuremath{\pm}1.03 &
  0.0168*\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00pm} &
  79.4\ensuremath{\pm}1.65 &
  77.4\ensuremath{\pm}1.65 &
  0.0142*\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00am} &
  85.8\ensuremath{\pm}1.99 &
  85.6\ensuremath{\pm}2.27 &
  0.8364\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{12-1:00pm} &
  84.2\ensuremath{\pm}2.20 &
  84.20\ensuremath{\pm}2.20 &
  1\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00pm} &
  83\ensuremath{\pm}1.70 &
  83\ensuremath{\pm}1.70 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-3}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00am} &
  81\ensuremath{\pm}1.05 &
  79\ensuremath{\pm}1.41 &
  0.0021**\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{12-1:00pm} &
  78.8\ensuremath{\pm}1.40 &
  78\ensuremath{\pm}2.98 &
  0.4523\\
\multicolumn{2}{p{\dimexpr(.2883\linewidth-2\tabcolsep)}}{5-6:00pm} &
  78.8\ensuremath{\pm}3.16 &
  77\ensuremath{\pm}2.87 &
  0.1985\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{81.4\ensuremath{\pm}1.65} &
  81.4\ensuremath{\pm}1.65 &
  1\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{80.8\ensuremath{\pm}1.40} &
  80.8\ensuremath{\pm}1.40 &
  1\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{81.4\ensuremath{\pm}2.67} &
  81.4\ensuremath{\pm}2.67 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-4}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\textbf{Test time} &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{\textbf{Pre}} &
  \textbf{Post} &
  \textbf{p-value}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{80.20\ensuremath{\pm}3.19} &
  77.4\ensuremath{\pm}3.27 &
  0.0686\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{79.6\ensuremath{\pm}1.26} &
  76\ensuremath{\pm}1.33 &
  0.0001***\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{79.4\ensuremath{\pm}2.99} &
  76.4\ensuremath{\pm}2.80 &
  0.0324*\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{81.60\ensuremath{\pm}1.26} &
  81.6\ensuremath{\pm}1.26 &
  1\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{80.60\ensuremath{\pm}0.97} &
  80.60\ensuremath{\pm}0.97 &
  1\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.2836\linewidth-2\tabcolsep)}}{81\ensuremath{\pm}2.36} &
  81\ensuremath{\pm}2.36 &
  1\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Comparison of post values of partialpressure of oxygen (\%) among control and experimental groups (Data wasexpressed as mean and SD). (Exp-experimental group, Con- control group} }
\label{tw-1bd71e469e59}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.23740000000000002\linewidth-2\tabcolsep}p{\dimexpr.0532\linewidth-2\tabcolsep}p{\dimexpr.27199999999999996\linewidth-2\tabcolsep}p{\dimexpr.2125\linewidth-2\tabcolsep}p{\dimexpr.22490000000000002\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Day-1}\\
\rowcolor{kwdboxcolor}\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack Experiment group}\\
\tblmidrule 
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00 am} &
  91.30\ensuremath{\pm}5.89 &
  93\ensuremath{\pm}5.70 &
  0.5200\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{12-1:00 pm} &
  94.30\ensuremath{\pm}3.80 &
  95.80\ensuremath{\pm}3.55 &
  0.3740\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00pm} &
  95.60\ensuremath{\pm}2.22 &
  96.90\ensuremath{\pm}1.91 &
  0.1777\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00 am} &
  94.20\ensuremath{\pm}0.63 &
  94.4\ensuremath{\pm}0.84 &
  0.5560\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{12-1:00pm} &
  96\ensuremath{\pm}0.00 &
  96.40\ensuremath{\pm}0.84 &
  0.1510\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00 pm} &
  95.40\ensuremath{\pm}0.52 &
  95.40\ensuremath{\pm}0.52 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-2}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00am} &
  96.1\ensuremath{\pm}1.60 &
  97.5\ensuremath{\pm}1.35 &
  0.0485*\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{12-1:00pm} &
  96.9\ensuremath{\pm}1.10 &
  97.3\ensuremath{\pm}0.82 &
  0.3696\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00pm} &
  97.8\ensuremath{\pm}0.79 &
  99\ensuremath{\pm}0.47 &
  0.0006***\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00am} &
  96.30\ensuremath{\pm}0.48 &
  96.30\ensuremath{\pm}0.48 &
  1\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{12-1:00pm} &
  96.9\ensuremath{\pm}0.32 &
  96.9\ensuremath{\pm}0.32 &
  1\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00pm} &
  97.2\ensuremath{\pm}0.42 &
  97.2\ensuremath{\pm}0.42 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Day-3}}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{\textbf{Test time}} &
  \textbf{Pre} &
  \textbf{Post} &
  \textbf{p-value}\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00am} &
  98\ensuremath{\pm}0.47 &
  99\ensuremath{\pm}0.47 &
  0.0002***\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{12-1:00pm} &
  98.4\ensuremath{\pm}0.70 &
  99.1\ensuremath{\pm}0.57 &
  0.0243*\\
\multicolumn{2}{p{\dimexpr(.29060000000000002\linewidth-2\tabcolsep)}}{5-6:00pm} &
  98.9\ensuremath{\pm}0.32 &
  99.5\ensuremath{\pm}0.53 &
  0.0064*\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{97.2\ensuremath{\pm}0.42} &
  97.2\ensuremath{\pm}0.42 &
  1\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{97.3\ensuremath{\pm}0.48} &
  97.3\ensuremath{\pm}0.48 &
  1\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Day-4}\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Experiment group}}\\
\textbf{Test time} &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{\textbf{Pre}} &
  \textbf{Post} &
  \textbf{p-value}\\
5-6:00am &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{99.30\ensuremath{\pm}0.67} &
  99.9\ensuremath{\pm}0.32 &
  0.0203\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{99.7\ensuremath{\pm}0.48} &
  100\ensuremath{\pm}0.00 &
  0.0652\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{99.9\ensuremath{\pm}0.32} &
  100\ensuremath{\pm}0.00 &
  0.3306\\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack \textbf{Control group}}\\
12-1:00pm &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{98.50\ensuremath{\pm}0.53} &
  98.50\ensuremath{\pm}0.53 &
  1\\
5-6:00pm &
  \multicolumn{2}{p{\dimexpr(.32519999999999996\linewidth-2\tabcolsep)}}{98.9\ensuremath{\pm}0.32} &
  98.9\ensuremath{\pm}0.32 &
  1\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Comparison of post values of SerumTroponin T among control and experimental groups (Data was expressed as mean and SD). (Exp-experimental group, Con- control group} }
\label{tw-189317fe0e0a}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.18089999999999996\linewidth-2\tabcolsep}p{\dimexpr.35300000000000004\linewidth-2\tabcolsep}p{\dimexpr.30419999999999998\linewidth-2\tabcolsep}p{\dimexpr.1619\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}Group & Serum Troponin T Pre & Serum Troponin T Post & P value\\
\tblmidrule 
Experimental &
  497.4\ensuremath{\pm}140.58 &
  305.2\ensuremath{\pm}146.26 &
  0.0079**\\
Control &
  472.60\ensuremath{\pm}72.91 &
  273.4\ensuremath{\pm}43.34 &
  0.0001***\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
However, there are other studies reported that there was no reduction in the level of pain followed by the acupressure\unskip~\citep{540985:12333530}. Acupressure was also applied successfully for the management of post-surgery nausea and vomiting and recommended implementation of acupressure as a routine treatment along with the medical treatment. 

Further, patients who underwent the acupressure were discharged earlier when compared to the control group\unskip~\citep{540985:12333531}. The present study results are in accordance with earlier studies as we have assessed the bio-physiological indicators of pain. As it is known that followed by the pain there is an increase in the heart rate and blood pressure. However, after the acupressure, there was a significant decrease in the heart rate and blood pressure within the normal limits.

Serum Troponin T is a well-known indicator for the myocardial infarction. It is a part of the troponin complex that regulates the muscle contraction both in skeletal and cardiac muscle \unskip~\citep{540985:12333532}. Increased levels of troponin T indicates severe myocardial injury \unskip~\citep{540985:12333533}. In the present study, it was observed that there was a significant decrease in the troponin T levels followed by the acupressure. This was in accordance with earlier studies which stated that acupressure may have cardioprotective activity probably acts by reducing the levels of troponin \unskip~\citep{540985:12333534}. 
    
\section{Conclusion}
There was a significant decrease in the heart rate and blood pressure and a significant increase in the partial pressure of oxygen. Further, there was a decrease in the serum troponin T levels. The study support implementation of the acupressure 
    

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