Autoimmune thyroid disease (AITD) is characterized by thyroid dysfunction and deficits in the autoimmune system. Growing attention has been paid toward the field of gut microbiota over the last few decades. Several recent studies have found that gut microbiota composition in patients with AITD has altered, but no studies have conducted systematic reviews on the association between gut microbiota and ATID.We searched PubMed, Web of Science, Embase, and Cochrane databases without language restrictions and conducted a systematic review and meta-analysis of eight studies, including 196 patients with AITD.Bifidobacterium and Lactobacillus were decreased in the AITD group, and harmful microbiota like Bacteroides fragilis was significantly increased compared with the controls. Furthermore, the percentage of relevant abundance of other commensal bacteria such as Bacteroidetes, Bacteroides, and Lachnospiraceae was increased compared with the controls.The meta-analysis showed that the alpha diversity and abundance of certain gut microbiota were changed in patients with AITD compared to the controls. Chao1,the index of the microflora richness, was increased in the Hashimoto’s thyroiditis group compared to controls , while it was decreased in the Graves’ disease group . In addition, we found that some beneficial bacteria like This meta-analysis indicates an association between AITD and alteration of microbiota composition at the family, genus, and species levels.PROSPERO, identifier CRD42021251557. Hashimoto’s thyroiditis (HT) and Graves’ disease (GD) are the main types of autoimmune thyroid disease (AITD). AITDs are the most common organ-specific autoimmune disorders. Although the clinical manifestations of GD and HT are different, such as hyperthyroidism and hypothyroidism, respectively, GD and HT share similar immune-mediated mechanisms of disease, even alternating from one to the other , 2. Manyvia GPR109A  AND .Studies were considered eligible if they met the following criteria: 1) investigating the gut microbiota and patients diagnosed with AITD. 2) providing sufficient data on the relationship between AITD and intestinal microbiota and could be extracted to analyze the 95% confidence interval (CI). 3) written in English. 4) full-text availability. However, comments, animal model subjects, conference abstract, and reviews were excluded. We also excluded studies with incomplete outcome data on the percentages or relative abundance of gut microbiota and studies with fewer than 20 participants.Three reviewers independently extracted the following data from each study: authors, publication year, country of population, population age, clinical parameters of thyroid function, diagnosis of AITD, and microbiology assessment methods.Two reviewers completed the quality assessment using the Newcastle-Ottawa scale (NOS) to evaluate all the included studies, comprising the trial group selection, comparability, and exposure. The total score ranged from 5−9, where a higher score represents a higher quality of assessment. All the discrepancies or poor agreement were resolved through a consensus discussion with a third author.Standardized mean differences (SMD) were calculated between the HT and GD groups to assess the bacterial alpha diversity indices (Chao1). SMD >0 indicates that participants with HT have a higher level of richness in the intestinal microflora. A fixed- and random-effects were used to assess the percentages or relative abundances of certain gut microbiota with AITD compared with the healthy controls. We examined the statistical heterogeneity using the I2 statistic. I2 values of 25%, 50%, and 75% were related to low, moderate, and high heterogeneity, respectively. A Random-effects model was used to pool the results when high heterogeneity (I2>50%) existed. Additionally, the fixed-effects model was used if the heterogeneity was low. Furthermore, we performed a sensitivity analysis as well as Begg’s test to assess the potential influences of bias. All statistical analyses were performed using Stata software (version 12.0). and richness indices (ACE and Chao1). The Chao1 index was a reflex of microflora richness. The meta-analysis of four studies reported data about the Chao1 index between patients with AITD and healthy controls. We found that the Chao1 index was significantly different between the HT and GD groups compared with the controls. To explore the source of heterogeneity, we divided these four articles into two subgroups based on the entities of AITD. The random-effects model of subgroup meta-analysis showed that the Chao1 index was increased in the HT group compared to the controls , while it was decreased in the GD group . The effect size  was relatively small. There was no evidence of between-study heterogeneity I2 = 0%; Figure 2Firmicutes, one of the predominant phyla of the human gut microbiota, showed a lower abundance in patients with AITD than the controls (Firmicutes in the detected sample of HT was 48.3% (95%CI: 0.080 to 0.885) and 55.1% , slightly higher than that in the control group 35.2% , while the control group was 34.1% , while the percentage in healthy control was 14.5%  and 18% , whereas that in healthy controls was 17.8%  in patients with AITD and 0.1% (95%CI: 0.001−0.002) in healthy controls. The heterogeneity within the AITD group was low  compared to 0.4% in control group ,higher than the healthy controls , Dorea , Faecalibacterium , Synergistetes ,and Coprococcus  were negatively correlated with TPO-Ab or TR-Ab. In contrast, other commercial bacteria like Blautia, Lactobacillus, Alistipes, Ruminococcaceae, and Enterobacteriaceae were positively correlated with TPO-Ab.Several studies have revealed the significant correlations between clinical thyroid-related antibodies like TPO-Ab and TR-Ab, and different bacterial abundances by Spearman’s correlation distance. The Spearman correlation coefficient R-value between microbiota and immune indices, including TPO-Ab and TR-Ab, demonstrated that certain microbiota significantly correlated with thyroid function tests Table 3.To the best of our knowledge, this is the first meta-analysis to demonstrate the association between gut microbiota and AITD. This association has become a very popular topic and field in recent years. Many researchers want to illuminate the association and underlying mechanism linking AITD and microbiota, expecting to discover a novel target for early diagnosis or reversal of the host’s disordered immune system through fecal microbiota transplantation. Owing to the development of 16SrRNA sequencing technologies, significant alterations of the abundance and composition of gut microbiota have been found between AITD and healthy controls, suggesting that the gut-thyroid axis may play a pivotal role in the development and progress of AITD .Though HT and GD are considered the most common two forms of AITD, the pathogenesis and hallmark of HT and GD are quite different. The hallmark of HT is the high rate of TPO-Ab, and TG-Ab, while high TR-Ab level was detected in patients with GD . BesidesFirmicutes and Bacteroidetes are the main dominant microbiota at the phyla level. Traditionally, the ratio of Firmicutes and Bacteroidetes has been implicated in the predisposition of disease conditions. In our meta-analysis, the rate of Firmicutes and Bacteroidetes ratio of patients with AITD showed a lower level than their healthy counterparts. Besides, AITD patients showed a notable alteration in gut microbiota composition as compared to the controls. A random-effect model indicates that people with AITD showed a significantly increased relative abundance of pathogenic bacteria and a decreased proportion of beneficial bacteria such as Lactobacillus and Bifidobacterium. Lactobacillus and Bifidobacterium could be used as a probiotic to modulate the immune response and have no adverse effect on developing an experimental autoimmune thyroiditis mice model  or DAMPs (damage-associated molecular pattern molecules (DAMPs) patterns. Notably, the IL-1β, the subsequent effector molecules downstream of inflammasomes, can modulate the microbiota by regulating the production of antimicrobial peptides (AMPs)  . In addis (AMPs) . A studynd NF-kB , 46. MorRuminococcaceae, Blautia, and Alistipes, were significantly positively correlated with TPO-Ab. In contrast, other bacteria such as Bacteroides and Synergistetes were negatively correlated with TPO-Ab or TR-Ab. Furthermore, the gut microbiota is correlated with cell functions such as membrane transport, genetic information, or other cellular processes  of thyroid may provide guidance for the future study or diagnosis of AITD. We found that some intestinal microbiota, such as rocesses . Notablyrocesses , 48. TheSeveral limitations of this meta-analysis should be considered. First, most studies did not consider the effect of dietary habits. The consumption of various food or fiber can influence the composition of the commensal microbiota and its metabolites, SCFA . Second,Bifidobacterium and Lactobacillus, may be associated with the development of AITD to some extent. However, the way how microbiome affects the progress of AITD is still controversial, and the research data is limited. Therefore, a further multicenter approach is needed to clarify the underlying pathogenesis and progress of intestinal microbiota dysbiosis in AITD.This meta-analysis shows the interactions between the gut microbiota and the pathogenesis of AITD. Furthermore, certain beneficial intestinal bacteria decrease, such as The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.BG and ZS conceived the study. CW, FM, HW, and YY participated in the statistical analysis. BG and BS drafted the article. All authors read and approved the final version of the manuscript.This study was supported by the Department of Education in Liaoning Province, China (LJKZ0742).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Osteoarthritis is a common multifactorial chronic disease that occurs in articular cartilage, subchondral bone, and periarticular tissue. The pathogenesis of OA is still unclear. To investigate the differences in serum metabolites between OA and the control group, liquid chromatography/mass spectrometry (LC/MS)-based metabolomics was used. To reveal the pathogenesis of OA, 12 SD male rats were randomly divided into control and OA groups using collagenase to induce OA for modeling, and serum was collected 7 days after modeling for testing. The OA group was distinguished from the control group by principal component analysis and orthogonal partial least squares-discriminant analysis, and six biomarkers were finally identified. These biomarkers were metabolized through tryptophan metabolism, glutamate metabolism, nitrogen metabolism, spermidine metabolism, and fatty acid metabolism pathways. The study identified metabolites that may be altered in OA, suggesting a role in OA through relevant metabolic pathways. Metabolomics, as an important tool for studying disease mechanisms, provides useful information for studying the metabolic mechanisms of OA. Osteoarthritis (OA) is an extremely common multifactorial chronic disease that leads to degeneration of joint cartilage, synovial inflammation and osteophyte formation . With thThe concept of metabolomics was first introduced in 1999 . MetabolSeveral untargeted metabolomics studies on OA have been reported ,14,15,16To verify that the rat OA model was successfully established, we stained rat articular cartilage with Safranin O and histologic examination (HE). As expected, in the OA group, the cartilage content was significantly reduced, the chondrocyte arrangement was disturbed, and the cartilage surface was irregular, which tentatively proved the success of rat modeling .As shown in http://www.Metaboanalyst.ca/, accessed on 30 March 2021) using a principal components analysis (PCA) model and found that the control and OA groups were distinguishable from each other. As seen in We used rapid resolution liquid chromatography/quadrupole-time of light/mass spectrometry (RRLC/Q-TOF/MS) to analyze the serum of the OA and control groups to find out the metabolic differences. The metabolites obtained after mass spectrometry-data-independent acquisition (MS-DIAL) software was imported into Metaboanalyst  is not clear. Early diagnosis is important because the number of people who develop KOA is increasing due to the aging population as well as to the increase in the number of obese people.By measuring the bodyweight of rats in the control and OA groups, the two groups were found to be well matched. The successful establishment of the OA model was verified by histologic examinations. According to the biochemical indexes, TC in the OA group was obviously higher than that in the control group, suggesting that the OA group was at risk of obesity. In addition, we found that serum levels of NO and PGE2 were significantly increased in the OA group, while levels of E2, which is associated with the promotion of bone formation, were significantly decreased.We used a metabolomics approach using LC/MS to collect metabolites and detect metabolic changes between the OA and the control groups. A significant separation between the OA and the control groups was achieved by performing multivariate statistical analysis under the positive and negative ion model, separately. Further analysis by OPLS-DA revealed six metabolites that were tentatively related to metabolic pathways such as nitrogen metabolism, carnitine metabolism, and tryptophan metabolism. We found that these potential biomarkers can demonstrate the occurrence of OA concerning multiple mechanisms, and next, we further investigated the changes in related metabolites.Tryptophan is a nutritionally essential amino acid that cannot be synthesized in vivo and must be provided through dietary sources. Tryptophan plays a rate-limiting role in protein synthesis, and its main role in the body is as a component of protein synthesis . TryptopThe evolution and progression in OA are associated not only with inflammation but also with alterations in amino acid metabolism, such as those of the arginine family of amino acids and related metabolites, such as γ-aminobutyric acid . γ-aminoIn the current study, elevated levels of carbamate were found in OA rat serum. It has been shown that the level of carbamic acid is much higher in patients with osteoarthritis than in normal subjects. Carbamic acid is involved in nitrogen metabolism , and infArginine has anti-inflammatory and antioxidant properties and is a prerequisite for the syncretization of many molecules . ArgininL-carnitine is a molecule capable of participating in fatty acid metabolism in mitochondria . Carniti1H-NMR to detect metabolites in synovial fluid in sheep [Mickiewicz et al. used in sheep . They obin sheep . Zhang ein sheep . In our n = 6) and the control group (n = 6). Rats were given anesthesia with 2.5% isoflurane. Briefly, collagenase was dissolved in 0.9% sterile saline, and osteoarthritis was induced by 50 μL (50 unit) injection into the right knee joint. The injections were given on the first and fourth days of the experiment. On day 7, rats were killed for the collection of serum. Serum was separated after collection and stored at −80 °C until processing.The collagenase-induced osteoarthritis (CIOA) model was established according to the protocol in the literature . HealthyCollection from the left knee joint of rats was carried out, and then fixed in 10% buffered formalin. The joints were decalcified and then paraffin-embedded. Then, the joints were stained with safranin O and hematoxylin-eosin (HE).Bodyweight measurements were performed on all rats. Blood tests and biochemical assays were measured for serum levels of WBC, ALT, AST, NO, PGE2, E2, and TC.g for 10 min at 4 °C, and the supernatant was taken for mass spectrometry measurement.We adopted the following protocol for the LC/MS untargeted metabolomics study of all serum samples: Before sample detection, the serum samples were melted at room temperature; 400 μL of methanol was added to 50 μL of the serum samples, shaken vigorously for 30 s, and then left for 10 min at room temperature; the samples were centrifuged at 3000× LC/MS-based metabolomics analysis has been described previously . Brieflym/z to 1000 m/z. Positive and negative modes were used to obtain data by optimizing the parameters: gas temperature, 350 °C; nebulizer, 40 psi; dry gas flow, 12 L/min; intrathecal gas temperature, 350 °C; intrathecal gas flow, 12 L/min.An Agilent 6520 Q-TOF mass spectrometer  with an electrospray ionzation (ESI) source was used to perform the MS analysis. The mass scan was performed in the range of 80 Peak identification and peak area normalization were performed on all data using MS-DIAL and Mass Profiler Professional  software. The data were chromatographed for peak identification and matching as well as peak area normalization. The data were stored in files and imported into the SIMCA-P11.0 software package  and multidimensional statistical analysis was performed using unsupervised PCA. In order to strengthen the differences between the OA group and the control group, a supervised pattern recognition method was further used for multidimensional statistical analysis, and OPLS-DA was established for the analysis.PCA and OPLS-DA analyses were used to compare the metabolite differences between the OA group and the control group. The metabolic pathways that were involved in the discrepant metabolites were analyzed using the KEGG, HMDB, and Massbank databases.http://www.kegg.com (accessed on 12 March 2021)KEGG: http://www.hmdb.ca/ (accessed on 20 March 2021)HMDB: http://www.massbank.jp (accessed on 30 March2021)Massbank: We investigated the metabolic differences between OA and controls by using a metabolomics approach with LC/MS. We identified potential biomarkers and showed metabolic disturbances in OA concerning amino acid metabolism, nitrogen metabolism, and carnitine metabolism. Based on the results of our study, we believe that the LC/MS metabolomics approach is an effective instrument for studying the mechanisms for OA and provides helpful information for learning about the diagnosis and treatment of OA.


Dietary data was collected using a validated 168-item quantitative food frequency questionnaire (FFQ). Food insulin index (FII) was calculated by dividing the total insulin load by total energy intake . Total insulin load  was also calculated using a standard formula. p < 0.05). The highest tertiles of FII were associated with higher odds of NAFLD  and obesity  compared to the lowest tertiles. Potential confounders for the association were controlled. Mean participant age was 43.9 ± 5.9 years. Patients with NAFLD were significantly associated with higher body mass index, levels of liver enzymes, triglyceride, low density lipoprotein-cholesterol (LDL), total cholesterol, and fasting blood sugar (FBS) compared to the healthy subjects (This study found that adherence to a diet with high FII was associated with greater odds of NAFLD and overweight or obesity. Additional studies are required to better understand this association.  Nonalcoholic fatty liver disease (NAFLD) is a result of fat accumulation over 5% in the liver in the absence of any known risk factors like viral infection, drug abuse, immune or metabolic disorders , 2. The As there are no clear pharmacological treatments for this condition, the primary recommendation in most cases is lifestyle modification and related interventions . Among tThe Food Insulin Index (FII) is a new food ranking algorithm based on the body's insulin response to the use of Isoenergetic Reference Food in healthy individuals . This alTo the best of our knowledge, the association between FII and odds of NAFLD as well as FII and liver function have not been investigated. Thus, the present study aimed to investigate the relationship between FII in patients with NAFLD in order to understand the diet-based insulin response. ParticipantsThe current study was conducted after obtaining approval from the Research Council and Ethics Committee at Iran University of Medical Sciences, Tehran, Iran. This hospital-based case-control study was performed in Hazrat Rasoul Hospital, Tehran, Iran, in the years 2018–2019. In this study, 169 consecutive patients with NAFLD (randomly selected) diagnosed by a gastroenterologist were included in the case group, and 200 individuals without a history of NAFLD were recruited from the same hospital for the control group. Two dietitians (Mh. S. and S. F.) monitored the sampling of patients. NAFLD was diagnosed based on the chronic elevation of liver enzymes, absence of alcohol consumption, ultrasonography of the liver showing evidence of NAFLD based on echogenicity and visualization of vasculature, and parenchyma and diaphragm (Grades II and III). Patients with liver disease secondary to other known etiologies and a history of diabetes, CVDs, myocardial infarctions/strokes, cancers, viral hepatitis, Wilson’s disease, or autoimmune disorders of the liver were excluded. Pregnant and lactating women and subjects with arbitrary special diets were also excluded from the study. NAFLD patients were newly diagnosed and not treated with any medication or surgery before the study. Healthy subjects were considered as a control group and were included based on laboratory tests and liver ultrasonography (not suffering from stages of hepatic steatosis). The control group was selected from patients referred to other wards of the hospital, such as ophthalmology, orthopedics, maxillofacial surgery, and ear, nose, and throat wards, who were not diagnosed with NAFLD and had no history of alcohol consumption overall or had a history of alcohol consumption less than 10 mg/d in women and less than 20 mg/d in men. Case and control group subjects were age and sex-matched. Demographic data was collected through a general information questionnaire. At the beginning of the study, the levels of liver enzymes were recorded using the patient's existing medical record or newly obtained at a doctor’s appointment if unknown. In this study, the nutritionists performed the interviews, and thus the responder rate to the survey was complete. Furthermore, written informed consent was obtained from all participants. The General Practice Physical Activity Questionnaire (GPPAQ), a simple questionnaire reflecting an individual’s current physical activity, was used to assess the physical activity of participants . The stuAnthropometric assessment2). Anthropometric measurements were carried out by a trained dietician. Weight was measured with minimum clothes and no shoes using a standard SECA 700 digital scale  and recorded to the nearest 100 g. Height was measured in a standing relaxed shoulder position with no shoes to the nearest 0.5 cm using mounted tape . Body mass index (BMI) was calculated as weight (kg) divided by height in square meters , high density-lipoprotein (HDL)-C, low-density lipoprotein (LDL)-C, and glucose concentrations were measured by enzymatic methods using commercial kits . Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were determined by commercially available enzymatic reagents  on auto-analysis (BT-3000).Dietary assessmentTrained dietitians administered usual interviews to chart food intake. Validated semi-quantitative food frequency questionnaires (FFQ) with 168 food items were used to assess dietary intakes . For eacCalculation of food insulin index and glycemic indexFood insulin index (FII) refers to the incremental insulin area under the curve over 2 h in response to the consumption of a 1000-kJ portion of the test food divided by the area under the curve after ingestion of a 1000-kJ portion of the reference food. Glycemic index (GI) refers to the postprandial glucose response to a food compared with an equal amount of carbohydrate (50 g) from a reference food, usually glucose or white bread . GlucoseStatistical analysesp < 0.05 was considered significant. All statistical analyses were done using SPSS software .The normality of variables was evaluated by Kolmogorov-Smirnov and histogram tests. For the variables that did not have a normal distribution, the logarithmic equivalent (Ln transformation) of that variable was used in the analysis. The independent sample T test was used to compare the mean of food insulin index as well as the general characteristics and biochemical parameters among the case and control groups. To assess the relationship between FII and NAFLD in an adjusted model, multiple logistic regressions were used. Multiple logistic regressions adjusted for confounders were used to evaluate the association between FII and anthropometric and biochemical variables. The data is presented as mean ± standard deviation and odds ratio with 95% confidence interval. A value of p <0.001), higher levels of FBS, TG, LDL, TC, and ALT compared with the control group (p <0.05), and lower HDL and physical activity levels compared with the control group (p <0.05). The mean age and BMI of the study participants were 43.9 ± 5.9 years and 30.5 ± 2.6, respectively. The anthropometric and biochemical indices among case (NAFLD patients) and control groups are described in p <0.001). Subjects with NAFLD also had a higher intake of energy, fats, carbohydrates, saturated fatty acids, fructose, refined grains, high-fat dairy products, red and processed meats and a lower intake of total fiber, fruit, whole grains, and vegetables compared with the control subjects. There were no differences in the consumption of other dietary products between the groups. No significant differences were found between the NAFLD and control subjects based on the glycemic load see ; howeverp-value for trend = 0.017). Despite a significantly increasing trend of ORs across tertiles of FII for high LDL, HDL, and FBS levels, a similar trend was not seen in the triglyceride and liver enzyme levels. In addition, the highest versus the lowest tertiles of FII showed higher odds of overweight or obesity (OR and 95% CI = 3.61 (1.87–6.97), p-value for trend <0.001) in the final adjusted model for potential confounders including age, sex, and BMI.The odds ratios (ORs) and 95% confidence intervals (Cis) for NAFLD and obesity in the tertiles of FII are described in The present case-control study investigated the relationship between FII and the odds of NAFLD. It was found that FII and the glycemic index have a strong positive association with NAFLD and obesity odds among adult patients in Iran. Moreover, FII was significantly associated with lower HDL and higher liver enzyme, triglycerides, LDL, and FBS levels.According to our research, no study has yet investigated the association between FII and NAFLD. Importantly, recent research has recognized FII as a predictor of the risk of chronic diseases . SeveralSeveral possible mechanisms have been considered to explain the association between FII and the risk of NAFLD. Studies have suggested that dietary insulin load and FII could be considered as independent dietary risk factors for the development of insulin resistance that contributes to its pathogenesis NAFLD , 29. InsIn the present study, patients with NAFLD consumed lower amounts of vegetables and whole grains compared to refined grains, fructose, and saturated fatty acids that could typically lead to the risk of developing NAFLD and other biochemical disorders of impaired lipid profile and glucose metabolism; however, they had a lower intake of fiber, which is usually associated with a higher body mass index, fat accumulation, and higher levels of serum lipids . odds of overweight or obesity in the highest compared with the lowest tertiles of FII. In a German cohort study in young adults, a higher FII during puberty was associated with a higher percent of body fat (In the present study, a significant positive relationship was observed between FII and the body fat . Moreovebody fat . In contbody fat . This dibody fat . Some stbody fat , 39. It body fat . On the body fat , 29.There are a few limitations that need consideration while interpreting the results of the current study. Firstly, like all case–control studies, no causal relationship could be determined between FII and NAFLD. Secondly, using the 168-item FFQ questionnaire might contribute to a recall bias from tired participants, which might have been partially addressed by a trained interviewer. Thirdly, some properties of foods, like growing conditions, cultivation methods, storage, processing, and cooking conditions, and assay methods, might affect the antioxidant contents of the foods, and that needs to be considered as well . NeverthIn conclusion, a high FII diet may be associated with higher odds of developing NAFLD and obesity or overweight due to its positive association with plasma triglycerides, LDL, and FBS levels. Moreover, there is a negative association between FII and HDL and liver enzyme levels in NAFLD, suggesting that FII has long-term metabolic relevance, especially in individuals with a higher grade of insulin resistance. More studies are required to evaluate the association between FII and NAFLD in a larger population and to address any potential gender-based differences.


Secondly, the associations of anthropometrics, muscle size, gross motor function classification system (GMFCS) level, and SMC with MJT were investigated using univariate and stepwise multiple linear regressions. The associations of MJT with growth-related parameters like age, weight, and height appeared strongest in the TD cohort, whereas for the SCP cohort, these associations were accompanied by associations with SMC and GMFCS. The stepwise regression models resulted in ranges of explained variance in MJT from 29.3 to 66.3% in the TD cohort and from 16.8 to 60.1% in the SCP cohort. Finally, the MJT deficit observed in the SCP cohort was further investigated using the TD regression equations to estimate norm MJT based on height and potential MJT based on MV. From the total MJT deficit, 22.6–57.3% could be explained by deficits in MV. This investigation confirmed the disproportional decrease in muscle size and muscle strength around the knee and ankle joint in children with SCP, but also highlighted the large variability in the contribution of muscle size to muscle weakness.Muscle weakness is a common clinical symptom in children with spastic cerebral palsy (SCP). It is caused by impaired neural ability and altered intrinsic capacity of the muscles. To define the contribution of decreased muscle size to muscle weakness, two cohorts were recruited in this cross-sectional investigation: 53 children with SCP  and 31 children with a typical development (TD) . Muscle volume (MV) and muscle belly length for m. rectus femoris, semitendinosus, gastrocnemius medialis, and tibialis anterior were defined from three-dimensional freehand ultrasound acquisitions. A fixed dynamometer was used to assess maximal voluntary isometric contractions for knee extension, knee flexion, plantar flexion, and dorsiflexion from which maximal joint torque (MJT) was calculated. Selective motor control (SMC) was assessed on a 5-point scale for the children with SCP. First, the anthropometrics, strength, and muscle size parameters were compared between the cohorts. Significant differences for all muscle size and strength parameters were found ( Cerebral palsy (CP) describes a group of permanent disorders of the development of movement and posture, causing activity limitation, that are attributed to non-progressive disturbances that occurred in the developing fetal or infant brain. It is the most common cause of childhood-onset physical disability . SpasticAnother consistent clinical finding in children with SCP is muscle weakness –7, definHowever, muscle weakness cannot be categorized as just a neural or just a musculoskeletal impairment. Both the neural ability to selectively activate the muscle and the intrinsic capacity of the muscle influence strength production , 7. FurtImproved access to muscle imaging techniques in clinical research has led to a great increase in the number of studies quantifying intrinsic muscle properties in children with SCP . Lower lThe physiological CSA (pCSA) of a muscle is the ratio of MV to fascicle length. This value represents the number of fascicles in parallel. It is therefore directly related to the force-generating capacity of a muscle. Since pCSA and muscle size show a strong association with muscle strength in TD populations , 41, it Most focal treatments for children with SCP, like strength training, casting, and botulinum neurotoxin-A injections, are administered at the muscular level , 44. KnoThe first aim of this investigation was to describe the deficits in muscle strength, muscle size, and their ratio for knee flexors and extensors, plantar, and dorsiflexors in children with SCP. Secondly, the muscle size–strength relationship was defined, combined with the influence of age, anthropometric measures, functional level, and SMC following a multiple linear regression approach. Finally, the contribution of muscle weakness due to decreased muscle size to the total deficit in muscle strength was defined for the four investigated joint movements.via hospital co-workers and students within the same age range of 5–12 years and could not have any known neurological or orthopedic lower limb problems. All data were collected as part of an ongoing project that was approved by the local Ethical Committee of the University Hospitals Leuven (S59945) and Ghent (EC/2017/0526). Written informed consent was obtained from all parents or caregivers.This investigation included a convenience sample of 84 participants, 53 with SCP  and a control group of 31 TD children, who were recruited at the Clinical Motion Analysis Laboratory at the University Hospitals Leuven, Belgium. Inclusion criteria for the SCP cohort were a confirmed diagnosis of SCP, age between 5 and 12 years, and gross motor function classification system (GMFCS) level I–III . BotulinThe clinical and anthropometric features of the participants are summarized in Three-dimensional freehand ultrasonography (3DfUS) acquisitions were performed by combining a conventional two-dimensional B-mode ultrasonography device  with a motion tracking system  . AccordiBoth data collection and processing were performed using STRADWIN software  for four lower limb muscles: m. rectus femoris (RF), m. semitendinosus (ST), m. tibialis anterior (TA), and m. gastrocnemius medialis (MG). The reliability of 3DfUS has been confirmed for the plantar flexor muscles –52, as wMaximum voluntary isometric contractions (MVIC) were collected for KE, KF, PF, and DF with a fixed dynamometer  in a previously described, custom-designed chair . The proData were analyzed using SPSS . A ratio of strength to muscle size was calculated for every joint movement by dividing the MJT by the corresponding MV. Percentage differences in muscle strength and muscle size between TD and SCP were calculated as shown below, where M represents the median of the specified parameter:A negative percentage indicated a deficit in the SCP group in comparison to the TD group. Normality of the data distribution was evaluated using the Shapiro–Wilk test, histograms, and QQ plots. Since most parameters were not normally distributed, all descriptive statistics are presented as median (interquartile range). Bonferroni corrections were applied for multiple testing and specified beneath each table.t-test  or the Mann–Whitney U-test.To investigate the first aim, differences between the TD and SCP cohort were assessed using a Student's r < 0.300), low (r = 0.300–0.499), moderate (r = 0.500–0.699), high (r = 0.700–0.899), or very high (r ≥ 0.900) (Z-scores. Based on the linear association with (n)MJT and the interassociations of potential independent variables within the categories anthropometrics , muscle morphology (MV and ML), and clinical scales (SMC and GMFCS), one parameter was selected per category to be used in the multivariate analyses. Multiple linear regression models were built using a backward approach . A first model included the same parameters for both cohorts from the categories anthropometrics and muscle morphology. In a second model for the SCP cohort, the additional explained variance by a clinical scale was explored. Standardized residuals and Cook's distance value were used to diagnose and remove outliers. Final models were assessed for normal distribution of residuals, multicollinearity, and heteroscedasticity.For the second aim, linear associations between anthropometric measures  MV and ML, SMC, GMFCS, and (n)MJT were explored by univariate linear regression. Standardized residuals (≥3 standard deviations) were used to remove outliers, and normal distribution of residuals and heteroscedasticity were checked. Correlation coefficients were classified as negligible (≥ 0.900) , and difpotential) based on their MV. The regression equation for MJT based on an anthropometric variable was used to estimate the expected norm value of muscle strength for children with SCP (MJTnorm). Muscle strength profiles based on the relative contribution of decrease in MV (MJTdeficitMV) and the other factors (MJTdeficitother) to muscle weakness were calculated as a percentage of the total strength deficit . For nMV, the median deficits ranged between 19.7% for the ST and 43.5% for the TA. Similarly, both ML and nML were significantly decreased in the SCP cohort for all four muscles except for nML of the RF, which was close to significance (p ≤ 0.011). Differences in median nML ranged from 4.6% for the RF to 11.3% for the MG. Similar to the alterations in muscle morphology, both MJT and nMJT were significantly decreased for all four joint movements (p < 0.001). Normalized MJT showed median decreases ranging from 47.1% for PF to 71.7% for DF. The ratio of joint torque over muscle size was also significantly decreased for KE, KF, and DF, with median deficits of 40.3–54.0% (p < 0.001), but PF showed a lower, non-significant deficit of 18.1% (p = 0.071).Descriptive results of participant characteristics are shown in r = 0.537–0.849, p ≤ 0.003). For PF, only age and height showed significant moderate associations . Associations of PF with weight and MV were close to significance but low . Similarly, in the SCP cohort, associations of anthropometrics and muscle morphology with MJT were significant for KE and KF, with coefficients ranging from low to high . For DF, height, MV, and ML were significant, whereas age and weight were close to significance . Only MV and ML were significant for PF with low associations . GMFCS level showed a low significant association with KE MJT and a low, close to significant association with KF , but negligible non-significant associations with PF and DF MJT . SMC was moderately significantly correlated with KE and PF MJT , close to significant for KF , and there was no association with DF MJT. Fisher's Z-scores did not demonstrate significant differences between the reported relationships for children with and without SCP, except for KE with weight (Z = 2.442) and age with DF MJT (Z = 1.764).The univariate associations of anthropometric parameters, muscle morphology, GMFCS, and SMC with MJT, as well as with nMJT, are depicted in r = 0.486–0.528, p ≤ 0.006). However, in the SCP cohort, nMV associated significantly with nMJT of KE, PF, and DF , and nML with KE nMJT . GMFCS showed low to moderate significant associations with KE and KF nMJT , and SMC showed low to moderate significant associations with KE, KF, and PF .To eliminate the influence of growth on the associations with MJT, the univariate analyses were also performed with normalized parameters . In the TD cohort, only the association of weight and height with KE nMJT remained significant (p ≤ 0.002), and explained variance ranged from 29.3% for PF to 66.3% for KE. The results in the SCP cohort for MJT (p ≤ 0.002), and in the first model, with the same independent variables as in the TD cohort, only MV was included per joint movement. Explained variance ranged from 16.8% for PF to 54.8% for KE. In the second model, also SMC was entered into the model. The model for DF MJT did not change, whereas SMC was included for KE, KF, and PF MJT. The regression coefficients increased accordingly, explaining an additional 5.3–11.1% of the variance compared to the first model (p ≤ 0.002)  . The incAlthough the correlation coefficients of MV with MJT were similar between TD and SCP, the regression coefficients or slopes of this relationship tended to be lower in the SCP cohort for all joint movements, except for KF. However, there was a large difference in the regression constant for KF . The chideficitMV) and the part resulting from other factors, like decreased neural control or alterations in muscle composition (MJTdeficitother). MJTdeficittotal as a percentage of MJTnorm ranged from 44.7% for PF to 73.3% for DF. The contribution of MJTdeficitMV was largest for KE with 57.3%, followed by PF (47.7%), DF (39.3%), and KF (22.6%). The muscle strength profiles for every participant are depicted in measured, MJTdeficitMV, and MJTdeficitother. deficittotal. However, the contribution of a deficit in MV appeared to increase with growth and therefore with increasing MJTnorm. The first aim of this investigation was to define the deficits in muscle strength, muscle size, and their ratio for KF, KE, PF, and DF in children with SCP. The children with SCP demonstrated significant deficits in MV compared to their TD peers, for all assessed muscles . Since tmeasured bars in The disproportionality in the deficits in muscle strength and size in children with SCP was a first confirmation of an altered muscle size–strength relationship. This was further confirmed in the ratio of torque over size, which was significantly lower in the SCP group in comparison to the TD group for three of the four muscle groups. Both KE and KF, as well as DF, showed deficits in strength per muscle size of 40.3–54.0%. Only PF was an exception, where the relative decrease in MV was almost equal to the relative decrease in MJT, resulting in a similar muscle strength-to-size ratio in the two cohorts. In the investigation by Elder et al. , the speZ = 2.442) and for DF MJT with age (Z = 1.764). Similarly, the associations of muscle morphology parameters with MJT were comparable between the cohorts. This is in contrast with previous results by Reid et al. where correlation coefficients of MV with KE and KF isometric MJT were significantly lower in the SCP cohort. However, in the same investigation, they found no differences in the correlation coefficient of MV with the isokinetic joint torque or joint work  with a much wider age range (7–20 years) than the current study sample. The first multiple regression model of MJT in the SCP cohort included MV for all four joint movements, resulting in explained variances ranging from 16.8 to 54.8% , as well as by the differences in neural control and common treatment at the muscular level. Additionally, muscle weakness, as well as the contributing factors to muscle weakness, largely varied between participants (The final aim of this investigation was to define the contribution of decreased muscle size to the deficits in muscle strength. The group results for the four joint movements indicated that the patterns in the proportion of muscle weakness explained by decreased MV and by other factors are muscle specific . The paricipants . This maicipants , 58, 59.There may be several additional underlying mechanisms, the “other factors,” causing the disproportional decrease in muscle strength. A simple, clinical measure of SMC was used to represent the neural component in this investigation and found to have moderately significant associations with MJT of KE, KF, and PF . The lacNext to the alterations in neural control, additional muscular changes may also be considered as underlying mechanism of the decreased muscle strength. Muscle architecture parameters, such as the pennation angle and fascicle length, are related to the pCSA and, therefore, to maximal strength. Yet, previous investigations found inconsistent outcomes for fascicle length in participants with SCP , 29. AddThe muscle strength profile resulting from the combined assessment of muscle strength and muscle morphology gives an indication of the contribution of muscle size deficits to muscle weakness. This could be used to optimize training prescriptions either aiming at enhancing neural drive or inducing muscle hypertrophy. However, for both underlying mechanisms of muscle weakness, the influence of training is not always consistent , 66, 67.Impaired muscle growth and muscle size deficits are also underlying causes for muscle contractures in children with SCP , 73. MusThere were some limitations to this investigation that should be considered when interpreting the results. First, there was an unequal distribution of GMFCS levels, with a multitude of children classified as GMFCS level I. This was influenced by the selected inclusion criteria related to previous treatment history and the ability to cognitively understand the test procedures, since orthopedic surgeries and cognitive problems are more common in children with higher GMFCS levels –82. ThisThis investigation confirmed the disproportional decreases in muscle size and muscle strength around the knee and ankle joint of children with SCP in comparison to TD children. Furthermore, associations of strength with growth-related parameters like age, weight, and height were strongest in the TD cohort, whereas these were also present but accompanied by associations with SMC and GMFCS in the SCP cohort. The correlation coefficients of the muscle size–strength relationship were similar, whereas the regression coefficient was decreased in the SCP cohort, indicating that only part of the muscle weakness can be attributed to smaller MVs. However, there was a lot of heterogeneity between the proportion of muscle weakness that was attributed to deficits in muscle size both between joint movements and between subjects. Future studies should investigate what other mechanisms underlie muscle weakness, as well as how muscle weakness and its components are influenced by treatment, growth, and aging.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethical Committee of the University Hospitals Leuven and Ghent. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.This study was designed by BH, KD, CV, PC, MD, and LB-O. BH, NP, IV, and NDB contributed to the data collection. AV and GM were involved in patient recruitment. BH was responsible for the data processing, with help from IV in the MATLAB coding and conducted all presented analyses. BH and KD contributed to the interpretation of the results and were involved in the critical revision and editing of the manuscript that was written by BH. All authors approved the final version of the manuscript and agreed to be accountable for the content of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


M = 35.55, SD = 9.16), including 155 females (78.3%) and 43 males (21.7%), were enrolled. The Posttraumatic Growth Inventory, Connor-Davidson Resilience Scale-10, Simplified Coping Style Questionnaire, and General Self-Efficacy Scale were used for data collection. The results found that PTG could be positively predicted by resilience. Positive coping style and self-efficacy mediated the relationship between resilience and PTG. The different levels of PTG were determined by the resident location, monthly income and education of the primary caregivers. The results suggest that it is critical to improve the mental health of the primary caregivers (parents and grandparents) of children with developmental disabilities. Our results also provide a scientific basis for future research.This study was conducted to investigate the relationship between posttraumatic growth (PTG), resilience, positive coping style, and self-efficacy among the primary caregivers of children with developmental disorders in Chongqing, China. A total of 198 primary caregivers (parents and grandparents) aged from 22 to 66 years old ( In China, approximately 4.04 million (6.65%) children are diagnosed with developmental disabilities . “DeveloAlthough the term “trauma” is used in the stress and coping literature to describe events such as death and disaster, it is also used to describe a subjective response to an event that overwhelms an individual’s emotional, cognitive, or physical ability to cope . MeanwhiResilience is a protective factor for PTG elevation . As prevThe development of PTG is also closely related to positive coping styles , includiPosttraumatic growth not only relieves caregivers’ anxiety and depression but also increases their self-efficacy and confidence in the face of the children’s disorders and their recovery. Studies  have shoMost related research has been limited to mothers of children with autism spectrum disorders, but few studies have acknowledged that the resilience, positive coping style and self-efficacy of the primary caregivers of children with developmental disabilities affect the production of PTG in caregivers. Even less is known about the underlying mechanism by which these factors influence PTG. One study  has showDue to the particularity of the research participants, the sample size was calculated as follows: The scale  had the largest number of items among the four scales. The sample size was 5–10 times the number of items (21) in this scale (21*5 = 105∼21*10 = 210), i.e., 105∼210 samples. In this study, a convenience sample of 200 participants was recruited from the Children’s Rehabilitation Center of the Pediatric Department of the Second Affiliated Hospital of the Army Medical University and DanFu Children’s Rehabilitation Institute. In practice, the sample size that signed informed consent and could be included in our study according to the inclusion criteria was relatively small. The researchers ended up with a total sample size of 200 at the two hospitals. The participants were the primary caregivers of children with diagnosed developmental disabilities, including parents and grandparents. The inclusion criteria were as follows: (1) being the primary caregiver of a child with developmental disabilities; (2) having children diagnosed with developmental disabilities by a pediatrician; (3) having basic reading comprehension ability and no communication barriers; (4) serving as a daily caregiving for at least 8 h; and (5) signing informed consent forms. The exclusion criteria were as follows: (1) serving as a caregiver for no more than 6 months within one periodic year and (2) having a mental disorder.M = 35.55; SD = 9.16). Before participating in the survey, the caregivers were asked to provide consent and complete privacy policy forms to declare their voluntary participation, and they were free to decline to participate at any step of the survey. The participants were informed that their responses would be confidential. The purpose, content and procedures of the survey were explained in detail. The primary caregivers completed the questionnaire by themselves with the guidance of professionally trained investigators. Questionnaires were distributed and collected on the same day, after no more than 8 h.A cross-sectional survey method was adopted to conduct a field questionnaire survey on the included subjects during September and November 2020. A total of 200 questionnaires were issued and collected, of which 198 were valid (two questionnaires were not completed), for a valid rate of 99%. There were 43 (21.7%) males and 155 (78.3%) females aged 22 to 66 years (The Chinese version of the Posttraumatic Growth Inventory (PTGI) has been shown to be a valid measure with excellent reliability and validity . The PTGThe Connor-Davidson Resilience Scale  is used to assess the overall self-efficacy of adults. The Chinese version adopted in this study has good reliability and validity . The scaThe covariates of this study include sociodemographic variables of the participants, namely, gender, age (a continuous variable), education level, monthly income (yuan per month), residence, marital status, and child’s diagnosis.EpiData3.3 was used for data entry, and the statistical software SPSS-25 was used to perform statistical analyses. Prior to the test of the mediation model, preliminary analyses were conducted. First, the basic data of primary caregivers and children were analyzed by general statistics and ANOVA to test whether the sociodemographic characteristic data were significantly different. Second, Pearson correlations were run to examine the relationships among resilience, positive coping style, self-efficacy and PTG.via the PROCESS macro in SPSS. The mediation tests were examined The alpha level is 0.05 and helps determine whether τ′ and τ are statistically significant. The significance of the indirect effect was decided based on its 95% confidence interval (CI) estimated using the percentile bootstrap method. If the CI does not include zero, the corresponding effect is statistically significant.F = 7.055, P < 0.001), significant income differences in PTG  = 2.738, P = 0.045), and significant residence differences in PTG  = 3.726, P = 0.026). However, the results also showed non-significant child’s diagnosis differences in PTG  = 0.021, P = 0.999). Moreover, the t-tests showed non-significant marital status differences in PTG (t(196) = −1.778, P = 0.770) . Researchers  recommen= 0.770) .M = 23.78, SD = 5.18), 0.770  for the positive coping style scale, 0.856 for the self-efficacy scale , and 0.833 for the PTG scale . These results indicate that the reliability of all scales used in the study was adequate. The correlation coefficients showed moderate relationships between the variables. PTG had a positive correlation with resilience , positive coping style  and self-efficacy . In addition, self-efficacy had a positive correlation with resilience  and a positive coping style . There was also a positive correlation between resilience and positive coping style . The means, standard deviations, α values, and correlations between factors are presented in We performed an internal consistency reliability analysis using Cronbach’s alpha (α). According to the results, the α reliability of the resilience scale was 0.775  ranged from 1.33 to 1.37, as the VIF values were less than 3, indicating no danger of multicollinearity , and after the mediation variables of positive coping style and self-efficacy were put into the model, the direct effect was statistically non-significant . In addition, resilience had a significant predictive effect on positive coping style , and the predictive effect of positive coping style on PTG was also significant . Resilience had a significant predictive effect on self-efficacy , and the predictive effect of self-efficacy on PTG was also significant   . We furt< 0.001) . AltogetOur goal in this study was to extend our understanding of the relationship of resilience, positive coping style, self-efficacy and PTG among the primary caregivers of children with developmental disabilities. Specifically, we hypothesized that resilience directly or indirectly predicted the generation of PTG among primary caregivers through positive coping styles and self-efficacy. Our results confirmed the hypothesis: (1) higher resilience was associated with higher levels of PTG, consistent with previous findings , and theConsistent with previous findings , our stuThe families of children with developmental disabilities face great economic, life, and other pressures. Thus, the primary caregivers of children with developmental disabilities might have significant psychological problems, gradually resulting in a public health problem. Most previous studies are limited to the exploration of PTG and the adverse factors  and protThe mental health of caregivers will affect the future treatment and rehabilitation of their children, so it is critical to provide psychological intervention on primary caregivers . In addiThe results of this study should be considered in light of the following three limitations. First, as the study relies on cross-sectional self-reported data with a relatively small sample size, it does not allow the identification of causality or generalization. Second, this research is based on a field survey conducted in two children’s rehabilitation institutions in the city of Chongqing; therefore, caregivers who did not apply for medical care or treatment in the institutions were excluded due to possible negligence or unawareness of the children’s situation and economic deprivation of the family, which could lead to sampling bias. Third, self-reported measures were used to assess resilience, positive coping style, self-efficacy and PTG; therefore, the results could have been impacted by common method variance. Future studies should include more samples of grandparents among primary caregivers and independently explore their PTG and the differences between grandparents and parents in detail, adding the third-person estimations apart from the self-reports so data have a meaning to the clinical practitioner. Moreover, this population can be followed longitudinally to examine causality. In addition, personality traits  were not included in this study and should be explored in more dimensions in future studies.Our study showed that the primary caregivers of children with developmental disabilities experienced PTG, while the education background, monthly income and residence of caregivers also had a significant impact on their PTG. Additionally, resilience directly and indirectly had a positive predictive effect on the PTG of the primary caregivers of children with developmental disabilities through a positive coping style and self-efficacy. This study further confirmed the important role of resilience in PTG generation. It enables primary caregivers to positively deal with stress and difficulties and increase their self-efficacy. Our research provides a scientific basis for the psychological and behavioral intervention of primary caregivers by clinical psychology and social workers, which can help primary caregivers to better cope with stress and traumatic events, and promote the emergence of PTG, which may be very important for their mental health .The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by the Medical Ethics Committee of Army Medical University, PLA (2020 NO.035-03). The patients/participants provided their written informed consent to participate in this study.WL contributed to the experiment design, did the experiment, analyzed the data, and contributed to article writing and editing. CX did the experiment and data analysis. XH did the experiment. JL and QZ contributed to article language revision. LP edited the article. ML contributed to the experimental design, supervision of the experiment, and project funding acquisition. WZL dealt with unexpected situations and experiment supervision in the study. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Inferior alveolar nerve (IAN) block injections are commonly used in clinical practice, but they are not free from complications. The aim of the present systematic review is to assess the nerve-related adverse effects of IAN block anesthesia. A structured and systematic search was performed on the major electronic databases  for studies published in English until 30 September 2021. A total of 131 articles were identified through database searching using combinations of keywords. Fifteen papers were included and assessed for eligibility. Overall, nerve damage following an IAN block anesthesia injection is a rare occurrence, probably due to the direct nerve trauma of the needle, a neurotoxic effect of the used anesthetic solution and/or a combination of them. From a medico-legal point of view, a balanced discussion prior to nerve block anesthesia should be pursued in order to avoid patients’ reluctance to undergo necessary dental treatment due to the remote eventuality of nerve injury. The temporary decrease in the perception of pain during dental treatments is able to reduce the onset of anxiety among dental patients, and it is fundamental in clinical practice . Local aWhen performing a local anesthetic technique in a dental setting, systemic to loco-regional complications may arise. According to Haas , adverseOverall, injection methods and anesthetic solutions are the most important factors when performing local anesthesia, as they play a decisive role in the success of anesthesia itself . The HalCurrently, it is not possible to provide an accurate estimate of the incidence of adverse phenomena due to IAN anesthetic techniques. Thus, the aim of the present systematic review is to assess the nerve-related adverse effects of IAN block anesthetic injection techniques.This systematic review was performed in accordance with the recommendations of the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement” . In accoA structured and systematic search was performed on the major electronic databases for studies published in the English language until 30 September 2021: PubMed, Cochrane Library, Web of Science, Scopus and CINAHL databases. Handsearching of the reference lists of included studies, relevant reviews, national clinical practice guidelines or other relevant documents was performed. Moreover, the Database of Abstracts of Reviews of Effects (DARE) was searched to examine any further existing systematic reviews and meta-analyses assessing the adverse effects related to IAN block injections.The following keywords were used in order to perform database searches: “mandibular”, “nerve injuries”, “nerve block”, “adverse effects”, “prolonged anesthesia”, “paresthesia” and “dysesthesia”, in combination with the Boolean operators “AND” and “OR”. A pilot search was undertaken in order to ensure that the search strategy was effective. The study focused on the Population/Patient, Intervention, Control/Comparison, Outcome(s) (P.I.C.O.S.) criteria . In partEligible studies were (a) studies published in the English language; (b) studies published in a peer-reviewed journal; (c) studies published until 30 September 2021; (d) clinical studies; I studies reporting non-surgical nerve injuries. Studies were excluded if they were: (a) reviews, editorials, commentaries, letters, book chapters, reports on prospective ideas and futuristic scenarios (protocols included) and dissertations. All the eligible citations were imported into a bibliographic software or citation management system and duplicates were removed. Selected papers were then imported into Rayyan QCRI , Doha, Qatar) for screening. Two reviewers (L.A. and M.M.) carried out the evaluations independently. The very first selection was made on the basis of papers’ title or abstract, and eligible ones were selected for full-text review. Titles and abstracts were screened by two independent review authors for assessment against the inclusion criteria for the review. Full-text studies that did not meet the inclusion criteria were excluded, and the reasons for exclusion were provided in the systematic review. At each stage of the study selection process, if a consensus was not reached, a third review author (A.S.) was consulted. The results of the search were reported in the final report and presented in a PRISMA flow diagram.For the assessment of each publication, Excel spreadsheets were compiled. Data were extracted using a standardized form which included (a) authors’ names and the year of publication, (b) the country in which the study was performed, (c) the study design, (d) the aim of the studI, (e) the sample size, (f) the mean age ± standard deviation or age range, (g) the used anesthetic solution, (h) the retrieved article main outcomes and (i) the retrieved article secondary outcomes. Both authors compared their assessments and confirmed the data on the basis of the compiled spreadsheets. In case of doubt, concerning the study data, the two reviewers resolved disagreements by discussion. In the case of doubt, a third reviewer solved discrepancies. The methodological quality of the studies included was assessed with the Cochrane Collaboration tool for assessing the risk of bias, as suggested in the Cochrane Handbook for Systematic Reviews of Interventions (version 6.2). The currently recommended risk-of-bias tools, such as the RoB 2 tool for randomized trials and the ROBINS-I tool for non-randomized studies, were used ,21. The n = 98, Cochrane Library n = 0, Web of Science n = 2, Scopus n = 11, CINAHL n = 20). Out of 131 papers, 14 were excluded as they were duplicates, and 7 were discarded because they were written in a language different from English . A total of 110 articles were further reviewed, assessing the coherency of titles and abstracts with the aim of the present review. During this stage, 67 records were excluded, due to several reasons: wrong population , wrong study design , wrong outcome . After abstract reviews, 43 articles were selected for further inspection. Out of 43 papers, 8 were not retrieved and, for this reason, excluded from the review. Thirty-five articles were assessed for eligibility. A total of 20 papers were excluded because they did not meet the inclusion criteria . A total of 15 articles were included in the present systematic review , Australia (n = 2), Canada (n = 2), Denmark (n = 2), France (n = 1), Germany (n = 1), India (n = 1), Italy (n = 1) and Japan (n = 1). Full-text articles that met the eligibility criteria are included in The studies included in the present review were conducted in nine different countries: the USA  showed a lingual sensory disturbance, with a complete recovery after 6 months in 94.5% of the cases. Moreover, 1.04% of the patients included in that study complained of other disturbances such as trismus (0.4%), lasting pain in the area of treatment (0.3%) or swelling of the cheek (0.08%). In 0.08% of the cases, lingual sensory disturbances and pain arose at the same time . An estiOverall, the subjects included in both the studies received one or a combination of the following anesthetic solutions: articaine with or without epinephrin, lidocaine with or without epinephrin, lidocaine with octapressin, butanilicaine, mepivacaine with or without epinephrin, prilocaine and bupivacaine ,25. PrilOverall, the included studies evaluated cases of nerve damage caused by IAN block injection techniques during a 24-year-long period (1987–2011) in either children or adults. Different anesthetic solutions with different concentrations were considered with articaine, prilocaine, lidocaine, mepivacaine, bupivacaine or a combination of them being the most used ones. Four studies reported the incidence of nerve involvement related to the anesthetic injection, being 1:609,000 in the study by Gaffen and Haas , 1:13,80When considering the anesthetic type and its concentration, articaine and prilocaine were the two drugs mostly associated with a higher frequency of paresthesia. In particular, Garisto et al. reported that 4% anesthetic solutions (prilocaine and articaine) were more highly associated with the development of paresthesia than those of a lower concentration . MoreoveOverall, cases involving five males and four females were described. Bendgude et al. reported a case of prolonged anesthesia in a 4-year-old male patient: due to the prolonged anesthesia, a ulcerative lesion of the lower lip as well as a scratch was assessed, with satisfactory healing after 2 weeks . ChevaliThe quality of the studies included in the review was evaluated using the protocols described by Sterne et al.  and by tAs previously stated, the IAN block anesthesia technique is a safe and common procedure used all over the world, but it is not free from complications. One of them is represented by the possible damage that may affect nerves, mostly the LN, the IAN and the CTN. Nerve damage may determine the types of alteration and degrees of sensitivity of the respective areas of innervation. Overall, trigeminal nerve lesions and their clinical consequences represent an important challenge in modern dentistry, especially in oral surgery. The relevance of the symptomatology that afflicts the patient in the case of damage to a sensitive nerve and the inevitable consequences for the professional determine the main issue of this type of lesion, especially from a medico-legal point of view.Unfortunately, an accurate estimate of the exact incidence of the phenomenon is not possible due to the underestimation of such eventualities and the lack of reliable data on the number of anesthesia procedures performed. Moreover, the fact that some articles were older than 10 years may have limited the results of the present systematic review. However, the limitation was not imposed on the time span of publication because the authors deemed the included papers relevant for the purpose of the present study. Generally, reviews that only rely on published data may lead to poor and inconsistent outcome definitions and assessments, due to the limited information available from this type of report on incompletion or lack of specificity. Golder et al. investigated published versus unpublished studies, finding that a median of 43% of published studies reported adverse event data, in comparison to a median of 83% of unpublished studies . FurtherOther important aspects to consider are the type and concentration of anesthetic solution used, as these may influence the risk of nerve damage. In particular, articaine and prilocaine are considered the two drugs most commonly associated with a higher frequency of nerve disturbance, especially when 4% solutions are used. Garisto et al. indicated that 4% anesthetic solutions are more commonly associated with the development of paresthesia than those of a lower concentration . SimilarOverall, the clear mechanism of nerve injury is still debated . Two difMost of the subjects who experienced nerve-related adverse effects following an IAN block reported an electric shock-like or burning sensation ,35,36,37The results of the present systematic review suggest that nerve damage following an IAN block anesthesia injection is a rare occurrence. Even if a clear mechanism of nerve injury has not been established yet, all clinicians should be aware that nerve damage may occur as a result of the direct nerve trauma of the needle, a neurotoxic effect of the used anesthetic solution and/or a combination of them. From a legal point of view, the risk of nerve damage is not usually discussed during consent prior to nerve block anesthesia, especially not for surgical treatments. The patients’ information on possible nerve damage can be moderate as its occurrence is very unlikely to happen. In addition, if the patient does not receive balanced information on the risks/benefits of the procedures, the patient may decide to avoid the dental treatment due to the remote eventuality of nerve injury. However, if it occurs, it must be documented early, and clinicians should avoid denying responsibility or promise that it will resolve soon. Referral to a specialist is recommended.


Background: Exposure to lead (Pb) during the early life stages has been associated with the development of metabolic syndrome (MetS). Longitudinal studies of Pb exposure in critical developmental windows in children are limited.Methods: Our study included 601 mother–child dyads from the PROGRESS  birth cohort. Blood lead levels (BLLs) were assessed during the second and third gestational trimesters, in cord blood at delivery, and at ages 1, 2, and 4 years. Bone lead levels in the patella and tibia were assessed at 1 month postpartum and evaluated in separate models. To account for cumulative exposure , we dichotomized the BLLs at each stage visit and determined the following: “higher” if a BLL was at least once above the median (HPb) and “lower” if all BLLs were below the median (LPb). We analyzed fasting glucose, HbA1c, triglycerides (TGs), total cholesterol (TC), high-density lipoprotein cholesterol (cHDL), low-density lipoprotein cholesterol (cLDL), body mass index, waist circumference (WC), body fat percentage, and systolic (SBP) and diastolic blood pressure (DBP) at two study visits between 6 and 12 years of age and created cutoff points based on the clinical guidelines for each indicator. Mixed effects models were used to analyze each outcome longitudinally for each BLL score, adjusting for child's sex, size for gestational age, child's age, maternal parity, mother's age, and socioeconomic status.Results: We observed associations for HPb exposure and TC in all stages  and postnatally  and for prenatal HPb and TGs . HPb at all stages was associated with WC , BMI , SBP , and DBP . Pb levels in the patella were associated with cHDL  and those in the tibia with TGs .Conclusion: Early life exposure to Pb may alter early indicators of MetS. A follow-up of these children will allow for more definition on the impact of longer-term exposures. Exposure to lead (Pb) has been declared second on the list of 10 highest priority toxic substances to public health due to established multisystem toxicity and widespread exposure by the World Health Organization (WHO) and the Agency for Toxic Substances and Disease Registration (ATSDR) .in utero and early childhood, are key to study the effects of Pb exposure on organ growth and development, which may contribute to adverse health outcomes later in life   .MetS is defined as a set of physiological, biochemical, clinical, and metabolic factors that increase the risk of cardiovascular diseases such as myocardial infarction, atherosclerosis, systemic arterial hypertension, cerebrovascular disease, and diabetes mellitus type 2 , 14. TheThe presence of MetS during childhood and preadolescence significantly increases the risk of diabetes mellitus type 2 and cardiovascular disease in adulthood , 19. TheDespite growing evidence supporting a link between Pb exposure and MetS risk factors, there are only a few existing longitudinal studies among pediatric populations that examined perinatal Pb exposure and its relationship with increased risk of MetS in childhood and preadolescence , 18. Then = 600 mother–child dyads since.The participants of this study are part of the PROGRESS  prenatal cohort from Mexico City. Pregnant women receiving medical and prenatal care in the Mexican Social Security Institute (IMSS) were invited to participate. The recruitment period took place between July 2007 and February 2011. To be eligible for the study, women had to be at <20 weeks gestation, ≥18 years of age, without current or prior pathologies of heart or kidney disease, accessibility to a phone, plan to reside in Mexico City for the next 3 years after their admission to the study, not use steroid drugs (including glucocorticoids) or antiepileptic medications, and not consume alcohol daily. The institutional boards and ethics committees of Harvard School of Public Health, Icahn School of Medicine in Mount Sinai, and the National Institute of Public Health in Mexico approved the project, as well as the collaborating institutions: National Institute of Perinatology (INPer), IMSS, and the American British Cowdray (ABC) Medical Center. Participants granted their informed consent for participation in the study. There were 948 women followed during pregnancy and who gave birth to a live child; children had follow-up visits at 1, 6, 12, 18, 24, 48, and 72, and 96 months of age. The cohort had most of its dropouts between birth and at the stage 24 visit and has maintained stable retention at around n = 174 and n = 247, respectively. For stage 48, we have the data for 501 children. Children who had an extremely low birth weight equivalent to <1,500 g and gestational age <32 weeks were excluded (n = 21). On average, 601 children had data for at least one incidence of MetS for stage 72 and 540 had data for stage 96, with varying covariate data during the study follow-up that are indicated in the corresponding results table.The inclusion criteria for this study were: having data of at least one blood lead level (BLL) during pregnancy and one postpartum  and outcome data (i.e. MetS indicators) at 72 and 96 months. Some of the children's blood samples from stages 12 and 24 were randomly lost during transportation from Mexico to the laboratory in the USA, leaving a total of Prenatal exposure was evaluated with blood measurements from women in the second and third trimesters of pregnancy and in umbilical cord blood. Postnatal Pb exposure was assessed from children's blood samples collected at 12, 24, and 48 months of age. All blood samples were drawn in trace metal-free tubes and refrigerated at 4°C until shipment to the laboratory where they were frozen at −20°C until analysis. Pb concentration was measured by external calibration using the Agilent 8800 ICP Triple Quad  in MS/MS mode in the Trace Metals Laboratory at the Icahn School of Medicine at Mount Sinai. The limit of detection was <0.2 μg/dl and the instrument precision (given as %RSD) was ~5%. Good precision and accuracy were shown using blinded quality control samples obtained from the Maternal and Child Health Bureau and the Wisconsin State Laboratory of Hygiene Cooperative Blood Lead Proficiency Testing Program. BLLs were analyzed as continuous variables (given in micrograms per deciliter) and as categorical variables classified according to the median exposure per stage, described below.To account for cumulative exposure, at the prenatal, postnatal, and cumulative stages, we dichotomized the BLLs using the median for each study visit as the cutoff point. Two categories were obtained: “higher,” when a BLL was at least one time above the median (HPb), and “lower,” if all BLLs were below the median (LPb).We measured bone Pb levels at 1 month postpartum in maternal tibia  and patella (trabecular bone) using a K-shell X-ray fluorescence instrument for 30 min in each leg. The measures were computed, averaged, and weighted by the inverse of the proportion of the measurement error corresponding to each determination. Negative values, produced when the true values are below the detection limit of the instrument, were imputed with random draws from a uniform distribution between 0 and the lower limit of 2 μg lead/g bone mineral .Metabolic syndrome risk factors (IMetS), which were assessed at the 72- and 96-month visits, included the following: glucose, glycated hemoglobin (HbA1c), total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (cHDL), low-density lipoprotein cholesterol (cLDL), body fat percentage (BF%), waist circumference (WC), body mass index (BMI), systolic blood pressure (SPB), and diastolic blood pressure (DBP).2) and the z-score with BMI for age indicator using the WHO “Anthro” software  were used to obtain measures of TC, cHDL, cLDL, and TGs. The levels of HbA1c were determined using the Miura 200 automated analyzer . The weight, height, and waist circumference were measured during both follow-ups in triplicate and the average of each measurement obtained. The weight and height data were used to calculate the BMI . This measurement was taken in duplicate with a 3-min difference between each, and the average of the measurements was used.z-scores were classified according to the WHO Child Growth Standards , parity collected through standardized questionnaires during the second trimester of pregnancy, child's size for gestational age (Fenton score), sex, and age at the 72- and 96-month visits. SES was measured using the Mexican Association of Market Intelligence and Opinion Agencies questionnaire. With reference to our study population, which belongs to a middle–lower SES, we collapsed the variable into three categories: lower, medium, and higher. Parity considered two categories (including the current pregnancy): primiparous (less than or one pregnancy) and two or more pregnancies.t-test and the Mann–Whitney U test were used for continuous variables and the chi-square test used for categorical variables.Descriptive analyses were carried out for the evaluation of extreme or implausible values in the database. In the case of continuous variables, the mean and standard deviations were obtained, as well as the ranges or the median and interquartile range, as appropriate. Frequencies and percentages were obtained for categorical variables. Student's z-scores to ensure that obesity did not impact the results. Models were utilized considering three developmental windows: prenatal, postnatal, and cumulative. We stratified our models by sex to assess possible effect modifications of the associations. Outliers of the IMetS were excluded (n = 4), three with biologically implausible BF% data and one with a BMI z-score for age ≥5 SD. All analyses were performed using Stata version 14 software .To assess the association between exposure to Pb and IMetS, linear mixed effects models and logistic mixed effects models were utilized. BLLs were evaluated both as continuous and dichotomous. IMetS were assessed as continuous and categorized. The models were adjusted for sex, maternal and child ages, parity, SES, and the Fenton score. Secondary analyses were additionally adjusted for the BMI As a sensitivity analysis, mixed effects models were utilized with a subsample that had the complete follow-up data to verify that loss to follow-up and the presence of missing values did not affect the results.General characteristics of the 601 mother–child dyads included in this study are described in The characteristics of the 601 participants included in these analyses were compared to those of non-participants, and the differences were not statically significant (results not shown).p < 0.05).The main finding for IMetS classified according to the cutoff points was the presence of at least one IMetS in children: 61.6% for the stage 72 study visit and 63.7% for the stage 96 study visit. The prevalence of glucose ≥100 mg/dl was found to be higher in boys than that in girls. Most of the IMetS showed an increase in prevalence between stages 72 and 96 and were more prevalent among overweight and obese participants. Between stages 72 and 96, increases of 6 percentage points for overweight and 13.6 percentage points for obesity were found in boys. Similar increases were found in girls, 8.6 percentage points for overweight and 7.5 percentage points for obesity .n = 586 for all stages, n = 585 for the prenatal stage, and n = 509 for the postnatal stage. Glycosylated hemoglobin and TGs: n = 583 for all stages, n = 582 for the prenatal stage, and n = 508 for the postnatal stage. WC and BMI: n = 601 for all stages, n = 600 for the prenatal stage, and n = 519 for the postnatal stage. Systolic and diastolic blood pressure: n = 599 for all stages, n = 598 for the prenatal stage, and n = 517 for the postnatal stage. The prenatal stage included measurements of the blood lead levels during the second and third trimesters of pregnancy. The postnatal stage included measurements of the blood lead levels at birth and at 1, 2, and 4 years of age.Body fat percentage models only adjusted for maternal and infant ages because of the limited number of each category in categorical covariates. The glucose model in the postnatal stage was adjusted for socioeconomic status, sex, maternal age, infant age, and parity. Glucose, TC, cHDL, and cLDL: The Pb data available decreased to 75.6% for stage 12 and to 64.3% for stage 24. To assess the effect of loss to follow-up, we assessed the associations with a subsample of children who had complete data for all visits. The results were similar to those reported in the initial sample. Our results did not change in the models using continuous BLLs (results not shown) or in the sensitivity analysis including children with complete data . FinallyOur study found associations between Pb exposure in early life and the different early-stage risk indicators of MetS. Although in some cases the direction of such associations was opposite that of our hypotheses, these suggest a disruption of the expected normality and should be evaluated. Pre- and postnatal HPb exposures were inversely associated with children's TC, WC, BMI, elevated TGs, and blood pressure at ages 6–12 years. Pb in cortical bone was associated with higher odds of having cHDL <45 mg/dl, and Pb in trabecular bone showed lower odds of elevated TGs. Evidence from studies in children remains controversial, and our results are in line with some, but not all. To illustrate this, below, we present a summary of the associations reported in other studies; details can be found in Our study suggests that HPb, both postnatally and during all stages, was associated with higher odds of having lower TC levels. This result could be explained by the effect of prenatal exposure to Pb in the regulation of cholesterol metabolism , 28. AccIn our study children with higher levels of Pb in the patella were more likely to have cHDL levels <45 mg/dl. These results were similar to prior evidence, which showed that prenatal BLLs were inversely associated with cHDL at age 10–18 years  althoughPrenatal BLLs and tibia Pb levels were inversely associated with TGs. Most of the evidence has reported null associations , 20, yetNot surprisingly, we observed that an increased prevalence of overweight and obesity added to the increased WC measures and BF% at the stage 96 study visit, which could be due to changes in body composition associated with age .z-scores . In prior studies of the PROGRESS cohort, Renzetti et al.  (z-scores at 48 months)   and Kups months)  reported months) .in utero resulting in lower weight  and BF%  . SimilarContrary to what we expected, our results showed that HPb was associated with less likelihood to have elevated SBP and DBP (above the 90th percentile). Positive associations have been shown between Pb exposure and SBP using different biomarkers such as maternal toenail , maternaWe are aware of the possibility of a type 1 error due to multiple comparisons; however, after Bonferroni adjustments, the presented associations between HPb and TC were still statistically significant. One of our study limitations is having missing BLLs in the 12- and 24-month postnatal stages, but the results in the models indicated that these losses did not influence the associations found.Exposure to lead continues to be a public health problem in Mexico since the main source of exposure is the use of lead-glazed low-temperature ceramics to prepare, serve, and store food. Lead will leach into food with each use, even in very old and worn-out dishes. This type of ceramics is widespread in Mexico, and recent studies using representative national data have shown a clear association between their use and BLLs in 1- to 4-year-old children , 45.The strengths of this study include it being the first epidemiological study that evaluated the association between repeated measures of exposure to Pb  and the risk of IMetS longitudinally at two different time points, between ages 6 and 12 years. A particular strength is our extensive data on Pb exposure in both blood  and bone [indicator of chronic exposure  and endogenous exposure during pregnancy and long-term exposure in mothers]. The PROGRESS cohort is a prospective study that collected data on 11 risk factors of IMetS evaluated at two different ages, as well as covariates for model adjustment.In this study, a longitudinal comprehensive assessment of early risk indicators of MetS in children, we observed small changes according to the biomarkers and developmental windows of Pb exposure. These changes should be assessed across adolescence and early adulthood.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by National Institute of Public Health, Mexico Icahn School of Medicine at Mount Sinai, New York, USA. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.KM-S and MT-O: conceptualization, methodology, formal analysis, writing—original draft, writing—review and editing, and visualization. AA and EO-P: conceptualization, methodology, formal analysis, writing—original draft, and writing—review and editing. MP-Z: investigation and writing—review and editing. AM-G: investigation. RW and MM: writing—review and editing, supervision, project administration, and funding acquisition. AS: methodology, writing—original draft, and writing—review and editing. All authors contributed to the article and approved the submitted version.This work was supported by funding from the National Institute of Environmental Health Sciences P30 ES023515, R01 ES014930, R01 ES013744, and R24 ES028522 to RW. This work is a product of KM-S Master's thesis at the National Institute of Public Health, Mexico—as such we have no funding for the publication fees of this manuscript. MT-O is a researcher at the Mexican Social Security Institute and does not have funding resources for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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