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. 2025 May 28;68(4):260–272. doi: 10.5468/ogs.24272

Effect of L-carnitine supplementation on fertility outcomes among patients with polycystic ovary syndrome: a systematic review and dose-response meta-analysis of randomized clinical trials

Ahmed Abu-Zaid 1,✉, Ghadeer Adel Alghamdi 2, Alaa Saleh Alharbi 2, Saeed Baradwan 3, Saleh A K Saleh 4, Heba M Adly 5, Mooza M Alzayed 6, Mohammed Abuzaid 7, Raghad Sindi 8, Mohannad Alsabban 9, Osama Alomar 1,9
PMCID: PMC12301557  PMID: 40436023

Abstract

This systematic review and meta-analysis of randomized controlled trials (RCTs) assessed the effect of L-carnitine (LC) supplementation on the fertility outcomes of patients with polycystic ovary syndrome (PCOS). Online databases (Scopus, Web of Science, Cochrane Library, EMBASE, and PubMed) were searched to identify eligible RCTs published until March 2024. A dose-response meta-analysis was performed using a random-effects model. Meta-regression was also performed to investigate the source of heterogeneity based on the LC dose and duration of treatment. The pooled analysis included eight RCTs with 1,046 participants. The LC-treated group had significantly increased chemical and clinical pregnancy rates, ovulation rate, progesterone levels, number of preovulatory follicles >17 mm in diameter, and endometrial thickness compared to the untreated groups. The meta-analysis model indicated that LC supplementation did not change the serum levels of estrogen and testosterone; however, the dose-response meta-analysis indicated that prolonged LC intake significantly increased estrogen levels. LC supplementation has significant effects on fertility outcomes of women with PCOS. Additional large-scale longer RCTs are required to confirm the findings of this study.

Keywords: L-carnitine, Polycystic ovary syndrome, Fertility, Ovulation

Introduction

Polycystic ovary syndrome (PCOS) is the most common cause of infertility and chronic anovulation in women [1]. It is also linked to elevated levels of oxidative stress [2-4] and exposure to nonpersistent endocrine-disrupting chemicals [5]. The global prevalence of PCOS is estimated to be 5-10% [6]. Clinically, it is an endocrine disorder characterized by polycystic ovaries, hyperandrogenism, ovulatory and menstrual disorders, infertility, and related inflammatory and metabolic sequelae [7-11]. In addition, PCOS is associated with long-term health risks such as dyslipidemia, cardiovascular disease, insulin resistance, type two diabetes mellitus, obesity, alterations of the fibrinolytic system, and metabolic syndrome [12,13]. The primary endocrine characteristics of PCOS and its main etiology are hyperinsulinemia (or insulin resistance) and hyperandrogenemia [14]. Vitamin deficiencies, particularly vitamin D, have also been linked to PCOS [15].

Carnitine is a quaternary ammonium substance naturally synthesized in the body from the amino acids methionine and lysine [16]. L-carnitine (LC) is a biologically active form of carnitine, a non-essential amino acid derivative and a fatty acid metabolism cofactor [17,18]. Patients with PCOS have lower levels of serum LC [19], which may be related to insulin resistance and hyperandrogenism in affected patients. In recent years, LC has been used to ameliorate lipid and glucose metabolic dysfunctions in PCOS patients with PCOS to improve fertility [20]. LC also provides advantages to women resistant to clomiphene citrate (a drug used to treat infertility) during ovulation induction [21]. Furthermore, LC may reduce inflammation and oxidative stress and boost ovarian function [22]. Its administration can lead to a considerable decline in serum testosterone levels in patients with PCOS [23]. Additionally, LC may enhance insulin sensitivity, which affects the serum levels of ovarian hormones and androgens [24]. Therefore, LC may be beneficial as an adjunct therapy for PCOS [25].

A few meta-analyses have explored the impact of LC supplementation on the fertility outcomes of patients with PCOS [20,22]. However, the impact of LC has not been well-investigated, and the outcomes of these studies are controversial. Moreover, related clinical trials have reported inconsistent LC doses, varied treatment durations, small sample sizes, and possible confounding factors [20]. This systematic review and meta-analysis of randomized controlled trials (RCTs) was performed to comprehensively evaluate the effectiveness of LC on the fertility outcomes of patients with PCOS.

Methods

This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines [26].

1. Literature search

The search strategy was completed without country, language, or date restrictions to identify related studies published until March 2024 on various databases (Scopus, Web of Science, Cochrane Library, EMBASE, and PubMed). The search approach focused on four essential components in RCTs with parallel or crossover designs including the population (PCOS patients), intervention (LC), comparator or control (no intervention or placebo), and outcomes (chemical and clinical pregnancy rates; ovulation and multiple gestation rates; serum estrogen, testosterone, and progesterone levels; endometrial thickness; and the number of pre-ovulatory follicles >17 mm in diameter).

The search strategy included the following: Carnitine OR L-carnitine OR Bicarnesine OR Acetylcarnitine OR Palmitoylcarnitine OR Levocarnitine AND Polycystic Ovary Syndrome OR Stein-Leventhal Syndrome OR Sclerocystic Ovarian Degeneration OR Sclerocystic Ovary Syndrome OR Sclerocystic Ovaries OR Sclerocystic Ovary OR hyperandrogenism OR Hypertrichosis OR Hirsutism OR “PCOS” OR “PCO”. The complete search strategy and syntaxes are presented in Supplementary Table 1.

2. Selection of studies

The identified citations were imported using the EndNote reference management software (Clarivate, Philadelphia, PA, USA). Screening was conducted by two investigators and began with the evaluation of titles and abstracts, followed by an examination of the full texts of the screened studies to identify eligible studies. Eligible trials were selected based on the inclusion criteria. Any inconsistencies were resolved by negotiation with a third investigator.

3. Inclusion and exclusion criteria

The inclusion criteria were as follows: 1) RCTs with crossover or parallel designs, 2) studies that evaluated the effect of LC supplementation on fertility in LC-treated PCOS patients compared to untreated counterparts, and 3) studies with a pre-post design and sufficient data on the evaluated outcomes in both the LC and placebo groups. The exclusion criteria were as follows: 1) uncontrolled or non-placebo-controlled RCTs, 2) studies that enrolled participants younger than 18 years of age, and 3) RCTs with insufficient data on fertility outcomes at baseline or follow-up assessments.

4. Data extraction

Two researchers independently extracted the required data from the full-text articles, and conflicts were resolved through discussions with a third researcher. The extracted information pertained to the characteristics of the trials (i.e., publication year, infertility duration, sample size, first author’s name, study setting, and dosage of LC supplement) and the demographics of the patients (e.g., sex, body mass index [BMI], and age). The initial and final values of the variables relevant to fertility and pregnancy outcomes were also extracted. Variables related to pregnancy outcomes, such as chemical and clinical pregnancy and ovulation rates, were extracted from the included studies. The clinical pregnancy rate refers to the number of pregnancies confirmed by both a positive pregnancy test (high levels of human chorionic gonadotropin [hCG] hormone) and ultrasound visualization of the gestational sac [27]. In contrast, the chemical pregnancy rate refers to early pregnancy loss that occurs shortly after implantation, typically within the first 5 weeks, detected by a positive pregnancy test (presence of hCG hormone), but not confirmed by ultrasound, and ending before it can be visualized on ultrasound [28]. The ovulation rate refers to the frequency or percentage of ovulation occurrences within a given population or group of individuals over a specific period and serves as an important measure in fertility and treatment studies to indicate how often ovulation occurs in women who are trying to conceive [29].

5. Risk of bias assessment

Two reviewers independently appraised the quality of the studies using the Cochrane risk of bias version 2 (RoB-2) tool [30] and disagreements were resolved through consensus. The RoB-2 consists of five domains: 1) bias arising from the randomization process, 2) bias due to deviations from intended interventions, 3) bias due to missing outcome data, 4) bias in the measurement of the outcome, and 5) bias in the selection of reported results. Each domain was assessed for the risk of bias, and judgments of “low”, “some concerns”, or “high” were made based on predefined criteria. This tool enhances transparency and consistency in evaluating study quality, providing a comprehensive framework for researchers to assess and communicate potential biases in the included studies.

6. Certainty assessment

The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used to evaluate the certainty of the evidence. The evaluated outcomes were classified into four levels of quality (very low, moderate, low, and high) [31].

7. Statistical analysis

The STATA statistical software version 17 (StataCorp., College Station, TX, USA) was used for this meta-analysis. The DerSimonian-Laird test and random-effects model were used to estimate the odds ratio (OR) of some outcomes (ovulation, chemical and clinical pregnancy, multiple gestations, and abortion rates). In addition, the inverse-variance method was implemented to compute the weighted mean differences with 95% confidence intervals (CIs) for the remaining outcomes (serum levels of estrogen, progesterone, and testosterone; endometrial thickness; and the number of preovulatory follicles >17 mm in diameter). A random effects model was used for all calculations [32]. Statistical significance was set at P<0.05. Heterogeneity between trials was evaluated using the I2 statistic and Cochrane’s Q tests [33]. Heterogeneity was considered significant when the P-value of the Chi-square-based Q statistic was less than 0.10, or when the I2 score was higher than 50%. Leave-one-out sensitivity analysis was performed to determine the effect of each trial on the overall analysis. In this meta-analysis, we applied meta-regression to explore potential sources of heterogeneity and assessed the influence of study-level covariates on outcomes. This method allowed us to investigate the relationships between variables such as the dose and duration of LC supplementation. Additionally, a dose-response model was used to evaluate how different levels of exposure (supplement dosage and duration) affected the outcomes, providing a clearer understanding of the dose-dependent effects. Subgroup analyses were performed to detect possible sources of heterogeneity between studies based on participants’ BMI (obese: >30 kg/m2 vs. overweight: 25-29.9 kg/m2) and age (middle-aged adults: 31-50 years vs. young adults: 21-30 years).

Results

1. Study selection

A systematic search of several databases yielded 181 records. After excluding 79 duplicates, 99 citations were screened, and 81 reports were removed. The remaining 17 articles were evaluated for eligibility, and eight articles that met the inclusion criteria were included in this systematic review. The screening and selection processes for qualified trials are illustrated in Fig. 1.

Fig. 1.

Fig. 1.

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The PRISMA flowchart for literature review and study selection. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analysis.

2. Study characteristics

This systematic review and meta-analysis included eight RCTs with 1,216 participants. Table 1 shows the trial and patient characteristics. The studies included 50 to 274 patients with PCOS, with an average age of 25-31 years, and BMIs of 25-35 kg/m 2 . The mean duration of infertility was 25-91 months. The selected articles were published between 2018 and 2022. The RCTs were carried out in Iran [34-36] and Egypt [37-41]. The daily dose of LC supplements ranged from 1,000 to 3,000 milligrams.

Table 1.

Main characteristics of the included studies

Study Country N LC dosage (mg/day) Medication
 Infertility duration (months)
 Age (yr)
 BMI (kg/m2)
 Main outcomea
LC Control LC Control LC Control LC Control
Sangouni et al. [34] (2022) Iran 62 1,000 30.7±6.7 30.8±6.6 31.0±4.7 30.8±3.6 SHBGc
Abd-Elfattah et al. [37] (2019) Egypt 50 3,000 CC CC 26.12±3.28 25.64±2.63 31.22±2.56 31.79±2.72 Number of folliclesb, E2b, ovulation rateb, pregnancy rateb, and endometrial thicknessb
Chaleshtori et al. [35] (2022) Iran 148 3,000 CC CC 27.57±19.1 25.71±25.3 30.29±2.2 31.29±4.7 30.85±1.93 31.45±5.71 Number of folliclesb, ovulation rateb, pregnancy rateb, and endometrial thicknessb
Edris and Barakat [38] (2018) Egypt 124 3,000 Estradiol valerate Estradiol valerate 81.6±33.6 91.2±57.6 27.6±3.8 28.8±4.5 28.3±3.6 29.9±3.8 Ovulation rateb, pregnancy rateb, and endometrial thicknessb
El Sharkwy and Sharaf El-Din [39] (2019) Egypt 274 3,000 CC+metformin CC+metformin 39.6±10.8 44.4±9.6 25.7±1.7 26.1±2.2 35.5±3.2 34.4±3.4 Ovulation rateb, pregnancy rateb, and menstrual regularityb
Ibrahim [40] (2020) Egypt 211 2,000 CC CC 44.4±15.6 45.6±15.6 27.7±4.6 27.7±4.7 25.7±3.36 25.6±3.45 Number of folliclesb, size of folliclesb, E2b, ovulation rateb, pregnancy rateb, endometrial thicknessb, and progesteroneb
Kortam et al. [41] (2020) Egypt 94 3,000 CC CC 28.2±18.1 26.4±11.4 25.2±3.9 25.8±2.6 30.0±5.2 30.4±3.0 Ovulation rateb, pregnancy ratec, number of folliclesb, endometrial thicknessb, and progesteronec
Sheida et al. [42] (2023) Iran 83 3,000 71.04±35.28 71.4±47.4 30.00±5.01 31.57±4.70 28.06±3.38 28.22±3.33 E2b, ovulation ratec, pregnancy ratec, number of folliclesc, and endometrial thicknessc
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N, number; LC, L-carnitine; BMI, body mass index; SHBG, sex hormone-binding globulin; CC, clomiphene citrate; E2, estrogen.

a

Symbol is a sign of decreasing variables in the intervention group.

b

This symbol is a sign of increasing variables in the intervention group.

c

This sign indicates that there is no difference between the two groups.

3. Meta-analysis

1) Effect of LC supplementation on ovulation rate

The impact of LC consumption on the ovulation rate was explored in five trials with 776 participants (Fig. 2). A pooled analysis indicated that LC significantly improved the ovulation rate in the LC-treated group compared to their untreated counterparts (OR, 5.00; 95% CI, 3.32-7.52; P<0.001); there was low heterogeneity between RCTs (I2, 23.22; P=0.27).

Fig. 2.

Fig. 2.

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The effect of adding L-carnitine on pregnancy outcomes of PCOS patients. (A) Ovulation rate, (B) chemical pregnancy, (C) clinical pregnancy, (D) endometrial thickness, and (E) number of pre-ovulatory follicles >17 mm. CI, confidence interval; N, number; SD, standard deviation; diff, difference; PCOS, polycystic ovary syndrome.

2) Effect of LC supplementation on chemical pregnancy rate

This meta-analysis evaluated seven studies to identify the effect of LC supplementation on chemical pregnancy in 984 patients with PCOS (Fig. 2). An analysis of pooled data revealed that the chemical pregnancy rate was significantly greater in the LC group than in the non-LC group (OR, 4.50; 95% CI, 2.19-9.21; P<0.001) with a considerable degree of between-trial heterogeneity (I2, 73.91; P<0.001). In the subgroup analysis, obese (BMI >30 kg/m2) and young adult (aged 21-30 years) participants in the LC group had significantly higher chemical pregnancy rates compared to non-obese (BMI <30 kg/m2 ) and middle-aged adults (31-50 years) participants (Table 2).

Table 2.

Subgroup analysis

Variable No. of studies Effect size OR Effect size WMD 95% CI I2 (%) P for heterogeneity
Chemical pregnancy
 BMI (kg/m2)
  25-29.9 3 2.14 0.90-5.10 83.68 0.000
  >30 4 3.91 2.66-5.74 00.00 0.440
 Age (yr)
  Young adult (21-30) 4 3.07 1.91-4.95 50.42 0.090
  Middle-aged adult (31-50) 2 2.03 0.40-10.42 92.50 0.000
Clinical pregnancy
 BMI (kg/m2)
  25-29.9 3 2.88 0.87-9.51 84.37 0.000
  >30 1 3.00 1.64-5.47
 Age (yr)
  Young adult (21-30) 2 5.61 0.88-35.69 84.22 0.010
  Middle-aged adult (31-50) 2 1.73 0.56-5.33 81.49 0.020
Endometrial thickness
 BMI (kg/m2)
  25-29.9 3 1.75 0.95-2.56 91.82 0.000
  >30 3 2.84 0.77-4.91 97.53 0.000
 Age (yr)
  Young adult (21-30) 4 2.60 1.48-3.72 97.04 0.000
  Middle-aged adult (31-50) 2 1.61 1.17-2.05 00.00 0.450
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OR, odds ratio; WMD, weighted mean difference; CI, confidence interval; BMI, body mass index.

3) Effect of LC supplementation on clinical pregnancy rate

The effects of LC supplementation on clinical pregnancy were assessed in four RCTs that included 566 women with PCOS (Fig. 2). The analysis showed that the clinical pregnancy rate was substantially higher in the experimental group than in the placebo group (OR, 4.35; 95% CI, 1.48-12.75; P=0.01). However, significant heterogeneity was detected between the studies (I2, 79.92; P<0.001). The subgroup analysis did not reveal any significant changes in these findings (Table 2).

4) Effect of LC supplementation on endometrial thickness

The association between endometrial thickness and CL intake was analyzed in six studies involving 710 patients with PCOS (Fig. 2). The meta-analysis revealed that endometrial thickness significantly increased following LC intake in comparison with the untreated groups (WMD, 2.24; 95% CI, 1.42-3.07; P<0.001). Substantial heterogeneity was observed between the trials (I2, 95.26; P<0.001). The subgroup analysis did not show any significant differences in these results (Table 2).

5) Effect of LC supplementation on the number of pre-ovulatory follicles >17 mm in diameter

The meta-analysis of four RCTs including 503 participants displayed a substantial increment in the number of pre-ovulatory follicles >17 mm in the LC group compared with the control group (WMD, 1.11; 95% CI, 0.68-1.53; P<0.001) (Fig. 2). Heterogeneity between the studies was also noticeable (I2, 87.83; P<0.001).

6) Effect of LC supplementation on serum estrogen levels

The effect of LC administration on serum estrogen levels was examined in three trials involving 388 women with PCOS (LC group vs. control group) (Fig. 3). A pooled analysis indicated that LC consumption did not significantly change serum estrogen values (WMD, 61.24; 95% CI, -8.41 to 130.89; P=0.08), with substantial between-trial heterogeneity (I2, 99.63; P<0.001).

Fig. 3.

Fig. 3.

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The effect of adding L-carnitine on hormones of PCOS patients. (A) Estrogen, (B) total testosterone, and (C) serum progesterone. N, number; SD, standard deviation; diff, difference; CI, confidence interval; PCOS, polycystic ovary syndrome.

However, a dose-response meta-analysis indicated that prolonged LC intake significantly increased estrogen levels (P=0.023).

7) Effect of LC supplementation on serum testosterone levels

The meta-analysis of four RCTs with 662 patients with PCOS investigated the impact of LC supplementation on serum testosterone levels (Fig. 3). LC did not have a significant effect on serum testosterone levels in the LC group compared to the controls (WMD, -0.43 ng/mL, 95% CI, -1.01 to 0.16; P=0.15). In addition, considerable between-study heterogeneity was observed (I2, 97.70; P<0.001).

8) Effect of LC supplementation on serum progesterone levels

The effect of LC supplementation on serum progesterone levels was assessed in four trials that involved 453 participants (Fig. 3). A meta-analysis showed that serum levels of progesterone in the LC-treated significantly increased after LC intake compared to the untreated group (WMD, 3.58; 95% CI, 3.16-4.00; P<0.001), with a significant degree of heterogeneity between studies (I2, 0.00; P=0.42).

9) Other outcomes

It was shown that LC did not change the serum levels of sex hormone-binding globulin [34], abortion rate, or cause multiple pregnancies [40]. However, LC supplementation did significantly improve menstrual regularity in the LC group compared to the placebo group.

4. Risk of bias assessment

Five studies [37,38,40-42] reported concerns regarding the overall risk of bias, two trials had a low risk of bias [34,35], and one study [39] had a high risk of bias. The risk of bias evaluation for each domain is shown in Supplementary Fig. 1.

5. Sensitivity analysis

Leave-one-out analysis revealed that changes in chemical pregnancy, clinical pregnancy, ovulation rates, serum testosterone and estrogen levels, number of preovulatory follicles >17 mm, and endometrial thickness outcomes were similar to those observed in the main analysis. However, significant changes in progesterone levels were observed after removing one study [38] related to progesterone levels (Supplementary Fig. 2).

6. GRADE assessment

The overall certainty of the evidence for the assessed outcomes following LC supplementation is shown in Supplementary Table 2.

7. Meta regression and dose-response analysis

The results of the meta-regression and dose-response analyses are presented in Supplementary Table 3. Meta-regression analysis did not show any significant effect of the dose or duration of LC supplementation on the heterogeneity of this meta-analysis. A dose-response meta-analysis indicated a positive relationship between the duration of LC supplementation and estrogen levels.

Conclusion

This systematic review and meta-analysis of eight RCTs was conducted to elucidate the effect of LC on the fertility outcomes of women with PCOS. LC significantly increased chemical and clinical pregnancy, ovulation rates, serum progesterone levels, the number of pre-ovulatory follicles >17 mm in diameter, and endometrial thickness in the LC-treated group compared to their untreated counterparts. However, the serum levels of estrogen and testosterone did not vary significantly between LC-treated and non-treated groups. Subgroup analysis revealed that obese participants in the LC group had a significantly higher pregnancy rates than non-obese individuals. In addition, young adults in the LC-treated group had substantially higher rates of chemical pregnancies than middle-aged adults. The quality of evidence for all outcome variables examined in this review was low, which was attributed to a serious risk of bias and significant inconsistency among the trials included in this meta-analysis. The implications of this low certainty of evidence suggest that our confidence in the effect estimates is limited, and that the true effects may differ substantially from the reported findings. Consequently, these findings should be interpreted with caution, warranting further high-quality research to confirm the potential benefits of LC supplementation for PCOS-related infertility.

In a recent meta-analysis of seven RCTs among infertile women with PCOS, LC significantly improved clinical pregnancy and ovulation rates [20], which is in line with the findings of the present study. In contrast, another meta-analysis of four RCTs indicated a non-significant effect of LC on clinical pregnancy and ovulation rates [22]. A systematic review revealed that LC supplementation improved follicle and ovarian cell size, whereas no significant effects were observed on sex hormones [43].

Currently, L-carnitine is not universally integrated into the infertility treatment guidelines for patients with PCOS. However, it has been suggested that LC may be helpful as an adjunct therapy for PCOS [20] and it has beneficial effects on the treatment of infertility [44]. Oxidative stress has been reported to significantly affect female reproduction via lipid peroxidation in oocytes [45]. To preserve the quality of oocytes, it is essential to maintain proper lipid oxidation with or without minimal production of free radicals [46]. A previous review proposed that LC have significant functional capabilities to regulate the metabolic and oxidative stress of the reproductive system in women and to ameliorate or restore their reproductive functions [47]. The vast majority of human studies used LC supplements as a therapeutic agent to improve or treat female infertility [48,49]. LC supplementation has been shown to have beneficial effects in the management of PCOS, amenorrhea, and endometriosis [48]. In addition, LC consumption may enhance oocyte health and increase the levels of sex and gonadotropin hormones [50,51]. Furthermore, LC is considered to be a potent antioxidants with minimal side effects [52]. LC is used during the follicular phase as a scavenger of oxidative stress substances produced during prior ovulation cycles and to reverse the production of reactive oxygen species [37]. Moreover, LC supplementation ameliorates endometrial blood flow and maintains healthy endometrial receptivity during the peri-implantation phase by scavenging free radicals and reducing oxidative stress and lipotoxicity [40].

In terms of cost-effectiveness, L-carnitine supplementation can be a relatively affordable adjunct to PCOS treatment, especially when compared to more expensive pharmacological options, such as metformin or fertility treatments. However, accessibility may vary across different healthcare settings, with some regions having a limited availability of L-carnitine supplements or requiring prescriptions for access. In low-resource settings, the cost of supplements may be a barrier to their widespread use, despite the potential benefits for PCOS management. Integrating L-carnitine into treatment regimens for PCOS requires the consideration of both cost-effectiveness and the socioeconomic conditions of patients to ensure broader accessibility and optimal health outcomes.

This systematic review is an inaugural meta-analysis that exclusively examined the effect of LC supplementation on fertility outcomes in patients with PCOS. This is a comprehensive overview of the related RCTs. However, this study has several limitations. The trial duration and LC dosage were heterogeneous, which may have affected the outcomes. Another limitation was the lack of detailed information on the serological testing methods or test kits used in the included studies. Additionally, variations in ultrasound equipment and procedures may have influenced the results. Specifically, the included studies did not report whether standards such as frequency bandwidth (e.g., using transducers with a frequency bandwidth of 8 MHz) were followed during ultrasound procedures to assess polycystic ovarian morphology in patients with PCOS. This variability could affect the reliability and comparability of the findings across different studies. Furthermore, there was a significant degree of heterogeneity between the studies related to the majority of outcomes. This heterogeneity can be attributed to various factors, including differences in the doses and durations of LC supplementation. Additionally, the diversity of the populations studied, such as variations in demographic characteristics and underlying health conditions, contributed to the heterogeneity observed. Consequently, this high level of heterogeneity may limit the reliability and generalizability of the findings, potentially limiting the overall conclusions that can be drawn from the meta-analysis. The overall quality of evidence in this meta-analysis ranged from low to extremely low. Subgroup analyses were not conducted for some of the evaluated outcomes because of the limited number of trials. These findings require further validation and clarification owing to potential confounders or insufficient statistical power. Future RCTs should consider utilizing standardized LC supplement doses and durations to provide homogeneous findings across trials and demonstrate the effectiveness and safety of LC.

In summary, LC significantly increased chemical and clinical pregnancy, ovulation rates, serum levels of progesterone, the number of pre-ovulatory follicles >17 mm in diameter, and endometrial thickness in the LC-treated group compared to their untreated counterparts. However, serum levels of estrogen and testosterone did not differ substantially between the two groups. Due to the serious risk of bias in the included studies and a high level of inconsistency between results, large, well-designed, randomized clinical trials with longer durations are needed to draw conclusive results regarding the effect of LC on fertility outcomes in patients with PCOS.

Footnotes

Conflicts of interest

All authors report no conflict of interest.

Ethical approval

Not applicable as the current investigation is a systematic review and meta-analysis of published literature, and it does not involve humans or animals.

Patient consent

Not applicable.

Funding information

None.

Supplementary Material

Supplementary Fig. 1.

Assessment of the risk of bias in the included studies. ID, identifier; D, domain.

Supplementary Fig. 2.

Sensitivity analysis of the effect of L-carnitine among patients with PCOS. (A) Chemical pregnancy, (B) clinical pregnancy, (C) ovulation rate, (D) endometrial thickness, (E) estrogen, (F) total testosterone, (G) serum progesterone, and (H) number of pre-ovulatory follicles >17 mm. CI, confidence interval; PCOS, polycystic ovary syndrome.

Supplementary Table 1.

The search strategy of databases

Supplementary Table 2.

Certainty of evidence of the interested outcomes based on the GRADE approach

Supplementary Table 3.

Meta-regression and dose-response analysis of the interested variables

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Fig. 1.

Assessment of the risk of bias in the included studies. ID, identifier; D, domain.

ogs-24272-Supplementary-Fig-1.pdf (153.2KB, pdf)
Supplementary Fig. 2.

Sensitivity analysis of the effect of L-carnitine among patients with PCOS. (A) Chemical pregnancy, (B) clinical pregnancy, (C) ovulation rate, (D) endometrial thickness, (E) estrogen, (F) total testosterone, (G) serum progesterone, and (H) number of pre-ovulatory follicles >17 mm. CI, confidence interval; PCOS, polycystic ovary syndrome.

ogs-24272-Supplementary-Fig-2.pdf (98.7KB, pdf)
Supplementary Table 1.

The search strategy of databases

ogs-24272-Supplementary-Table-1.pdf (57.8KB, pdf)
Supplementary Table 2.

Certainty of evidence of the interested outcomes based on the GRADE approach

ogs-24272-Supplementary-Table-2.pdf (85.6KB, pdf)
Supplementary Table 3.

Meta-regression and dose-response analysis of the interested variables

ogs-24272-Supplementary-Table-3.pdf (35.2KB, pdf)

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