Cow's milk protein allergy (CMPA) is a common food allergy in infants and young children and may be a risk factor for feeding difficulties. Studies exploring feeding difficulties and feeding behaviors in Thai children with CMPA are scarce.  To determine the prevalence of feeding difficulties and feeding behaviors in Thai children with CMPA compared to healthy controls.  A cross-sectional study was performed comparing children aged 1-6 years old diagnosed with CMPA and had eliminated cow's milk for at least 4 months with age-matched healthy children. Feeding difficulties were evaluated using the Montreal Children's Hospital Feeding Scale questionnaire, and feeding behaviors were measured using the Child Eating Behavior Questionnaire (CEBQ). p value = 0.01). The CMPA group had lower calcium, phosphorus, and zinc intake than the healthy controls. The prevalence of feeding difficulties between the two groups did not show a significant difference . The slowness in the eating subscale of feeding behaviors exhibited a lower score in the CMPA group than in the healthy group. Feeding difficulties was positively correlated with the desire to drink  but negatively correlated with the enjoyment of food subscale of CEBQ among the CMPA children .  One hundred and twenty-two participants were recruited (30 children with CMPA and 92 controls). The median age of the CMPA and control groups was 31.0  and 40.0  months, respectively ( Despite a similar prevalence of feeding difficulties between CMPA and healthy children, the CMPA group demonstrated some differences in feeding behaviors. The lower score of enjoyment of food and a higher score of desire to drink correlated with a higher degree of feeding difficulties in the CMPA children. The provision of appropriate nutrition for this group of children should be prioritized. The term feeding difficulties can be broadly defined as a variety of feeding problems such as prolonged mealtimes, crying/irritability at feeding time, food refusal, throwing and pushing away food, disruptive and stressful mealtimes, a lack of appropriate independent feeding, the introduction of distractions to increase intake, or failure to introduce advanced textures , 2. ThesThe common causes of feeding difficulties can be divided into two main factors: child and caregiver factors. Child factors leading to feeding problems include birth weight, organic causes, and traumatic feeding . PreviouCow's milk protein allergy (CMPA) is a common food allergy found in infants and young children. Previous studies reported that the estimated global prevalence of CMPA is 5.2% , with a Data from previous studies suggest that children with CMPA may be at risk of feeding difficulties. It is possible, therefore, that repeated painful experiences, such as reflux, vomiting, and constipation, can result in dysphoric feeding times and feeding difficulties. Furthermore, the delayed diagnosis of food allergies, especially in a critical period of oral motor skill development during the 7-18-month period, may lead to the delayed introduction of new tastes and textures. The bitter taste of hypoallergenic formula, a mainstream treatment of CMPA, can affect dietary avoidance and limit the variety of foods . Most prTo the best of our knowledge, there are no studies regarding feeding difficulties and feeding behaviors in Thai children with CMPA. In general, only a few previous studies investigated feeding behaviors using validated questionnaires and explored the risk factors for feeding difficulties in CMPA children. This study is aimed at determining the prevalence of feeding difficulties and exploring the feeding behaviors of Thai children with CMPA compared to those in the healthy group. Our study also assessed factors associated with feeding difficulties in Thai children with CMPA.This cross-sectional study was conducted between October 2021 and November 2022 at King Chulalongkorn Memorial Hospital, Bangkok, Thailand. The participants were recruited from allergy clinics, general outpatient clinics at King Chulalongkorn Memorial Hospital, and social networks.The inclusion criteria were 1- to 6-year-old Thai children born full term  with a 2500 to 4000 gram birth weight. Children with any chronic diseases such as neurologic, cardiac, pulmonary, liver, renal, hematologic, oncologic, genetic, metabolic, and autoimmune diseases were excluded from this study. The subjects were divided into two groups: a CMPA group and a healthy control group. The CMPA group included any child who had received a diagnosis of cow's milk protein allergy (CMPA) through either a regimen of cow's milk elimination followed by a rechallenge procedure or via the detection of a positive specific IgE or skin prick test, accompanied by the manifestation of clinically suspected symptoms upon cow's milk ingestion as assessed by pediatric allergists. In addition, all children in the CMPA group had to eliminate cow's milk and dairy products from their diet for at least 4 months to be eligible for the study. The control children were healthy children on the date of enrollment. Written informed consent was obtained from all participants' parents.This study was approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University .Demographic data, including age, sex, perinatal history , duration of receiving exclusive breastfeeding, age of starting complementary food, and caregiver's information , were collected by the researchers in a face-to-face interview. Data regarding the details of CMPA such as the child's age at diagnosis, age at the elimination of cow's milk and dairy products, number of food allergies, and allergic symptoms were also collected for the CMPA group.Dietary intake was evaluated by a well-trained dietician using a 24-hour dietary recall. The dietary data were computed to explore macronutrient and micronutrient intake using INMUCAL-Nutrients V. 4.0 software developed by the Institute of Nutrition, Mahidol University, Thailand.z-scores.Anthropometric data  were measured using a digital weighing scale . Body mass index (BMI) was calculated using weight divided by height or length squared. All measurements were performed twice, and averages were used for analysis. The anthropometric data were analyzed using World Health Organization (WHO) Anthro software (WHO Anthro v.3.2.2 for children aged 12 to 60 months and WHO Anthro Plus v.1.0.4 for children aged 61 to 83 months) to convert to age- and sex-specific T-scores and then divided into 4 groups: (1) no difficulties: T-score < 61; (2) mild difficulties: T-score 61-65; (3) moderate difficulties: T-score 66-70; and (4) severe difficulties: T-score > 70.Feeding difficulties and behaviors were determined using self-administered questionnaires completed by the parents. Feeding difficulties were evaluated by the Thai version of the Montreal Children's Hospital Feeding Scale (MCH-FS) questionnaire, which was translated into Thai language and validated by Benjasuwantep et al. . MCH-FS Feeding behaviors were measured using the validated Thai version of the Child Eating Behavior Questionnaire (CEBQ), with a Kaiser-Meyer-Olkin value of 0.865 and Cronbach's alpha ranging from 0.64 to 0.80 . The CEBz-score, height for age z-score, BMI for age z-score, phosphorus intake, and MCH-FS T-score. Categorical data including gender, caregiver's information , number of food allergies, allergic symptoms, and MCH-FS interpretation were shown as number and percentage, while continuous data including age, gestational age, birth weight, duration of receiving exclusive breastfeeding, age starting complementary food, anthropometry data, age at diagnosed CMPA, age at the elimination of cow's milk and dairy products, and dietary data were expressed as mean ± SD or median , as appropriate. The comparison of data between the CMPA and control groups was analyzed using the independent t-test, the Mann–Whitney U-test, or the chi-squared test. MCH-FS T-scores were adjusted for age. A univariate linear regression analysis was performed to determine factors associated with feeding difficulties. Factors with a p value from the univariate regression <0.10 were retained in the multiple regression by the backward elimination procedure. A p value of less than 0.05 was considered to be statistically significant.Statistical analysis was performed using IBM SPSS statistics version 22.0 . The normality of the data was checked using the Kolmogorov-Smirnov test before analysis. Data with a normal distribution included birth weight, weight for age One hundred and fifty-nine children were recruited, but thirty-seven children were excluded from the study because 4 children did not meet the inclusion criteria and 33 were denied participation due to their inconvenience in answering the questionnaire. A total of 122 children were enrolled for the analysis.p value = 0.01). There were no differences between the two groups in gestational age, birth weight, sex, duration of exclusive breastfeeding, age of starting complementary food, main caregivers and their educational level, and family income. No differences in weight for age, height, or length for age and BMI for age z-score between the CMPA and healthy groups were found .Baseline characteristics and anthropometric data are shown in p value < 0.05) .Participants in the CMPA group had a lower calcium, phosphorus, and zinc intake and a higher iron intake than the healthy group ( < 0.05) . Howeverp value < 0.05).Details of the dietary intake of both groups compared to the Thai Dietary Reference Intake (DRI) are shown in T-scores between the two groups. The prevalence of feeding difficulties was 36.7% in the CMPA group, while the healthy group was 43.5%, but no significant difference was found . Feeding behaviors assessed by CEBQ showed that the CMPA group had a lower score in the slowness in the eating subscale of feeding behaviors compared to the healthy group . No notable differences were observed in the other subscales . A possible explanation for our results may be the small sample size of the CMPA group. Additionally, most healthy children in this study were enrolled using social media, which may recruit children whose parents have greater concern about their eating behaviors. The presence of selective bias cannot be ruled out.Our study found no significant difference in the prevalence of feeding difficulties between the CMPA group (36.7%) and the healthy controls (43.5%). This finding is contrary to previous studies that suggested feeding difficulties among CMPA children were higher than those of healthy children. For example, a study by Maslin et al.  which enOur observations revealed that the CMPA group exhibited a decreased score in the slowness in the eating subscale compared to the healthy group. No significant distinctions were identified in the remaining subscales. This result is contrary to the study of Ercan and Tel Adıgüzel , who repOur results also revealed that the lower scores on the enjoyment of food subscale and the higher scores on the slowness in eating and food fussiness subscales were significantly correlated with higher feeding difficulties scores in all participants. These results are in line with those obtained by Rogers et al. , who fouChildren with CMPA tend to have significantly lower calcium, phosphorus, and zinc intake but higher iron intake compared to the healthy group. Similar trends have been reported by Boaventura et al.  in theirThis is the first study in Thailand to assess feeding difficulties and feeding behaviors in children with CMPA compared to healthy children. An additional strength of the study is the use of validated questionnaires to explore the prevalence of feeding difficulties and feeding behaviors. There are some limitations. Firstly, the healthy group was older than the CMPA group, which may have affected the results. However, age was controlled before comparing the feeding difficulties scores between the two groups. Furthermore, it is important to note that this study was performed at a single center, and the majority of the participants were from Bangkok and its vicinity, which may limit its generalizability. Nevertheless, the geographical variability may not necessarily impact feeding behaviors. Social media was also employed to enroll most of the children in the control group, which may have attracted children whose parents are concerned about their eating habits and may have affected the result. Lastly, there was a small sample size in the CMPA group which reduced the ability to find significant differences. Further research should be done on a larger scale, with data collection in a more representative cross-section of Thailand's urban and rural areas.Although this study found no significant difference in the prevalence of feeding difficulties between the CMPA group and the healthy control group, it is noteworthy that nearly half of all participants experienced feeding difficulties. The CMPA group also demonstrated a subtle difference in feeding behaviors, namely, slowness in eating. Notably, a decreased enjoyment of food and an increased desire to drink in CMPA children were found to be associated with more pronounced feeding difficulties. These findings suggest the potential impact of these factors on future feeding behaviors. It is important to emphasize that children diagnosed with CMPA exhibit reduced consumption levels of essential nutrients such as calcium, phosphorus, and zinc. As a result, it is advisable to actively promote adequate intake of these crucial nutrients among individuals with CMPA, accompanied by diligent monitoring of their nutritional status. This approach will ensure optimal growth and development in this population.


P. vivax predominated in GM; in PM, the proportion of P. vivax and P. falciparum was similar; in CM, P. falciparum predominated. The main clinical findings were headache (49%), anemia (32%), fever (24%), and musculoskeletal pain (13%). The clinical manifestations were statistically higher in P. vivax infections. In submicroscopic GM (positive with qPCR and negative with thick blood smear), the frequency of anemia, sore throat, and a headache was statistically higher compared with pregnant women without malaria. GM, PM, and CM reduce birth weight and head circumference. In Colombia, this is the first research on the clinical characteristics of GM, PM, and CM; contrary to evidence from other countries, P. vivax and submicroscopic infections are associated with clinical outcomes.This study compared the clinical–parasitological profiles of gestational (GM), placental (PM), and congenital (CM) malaria in northwestern Colombia. A cross-sectional study with 829 pregnant women, 549 placentas, and 547 newborns was conducted. The frequency of GM was 35.8%, PM 20.9%, and CM 8.5%.  Plasmodium spp. in maternal peripheral blood, placental malaria (PM) or the presence of the parasite or its pigment hemozoin in this organ or in placental blood, and congenital malaria (CM), which corresponds to malaria of the newborn during the first week of life or later if there is no possibility of infection through a mosquito bite  AND “clinical manifestations”[Title/Abstract] and “malaria pregnant*”[Title/Abstract] AND “clinical profile”[Title/Abstract], with which only one Colombian study was found, this research concluded that most cases in pregnant women correspond to uncomplicated infections , the othP. falciparum; therefore, the main manifestations of P. vivax and its risk of causing PM and CM are unknown. (iii) Diagnosis is based on TBS, which generates underreporting and leads to ignorance of the clinical and epidemiological importance of submicroscopic infections. (iv) Surveillance of PAM in Colombia is limited to clinical cases, and paradoxically there are no clinical profiles for this disease. (v) In the search for PAM, only febrile symptomatic cases are screened, so this manuscript would help to expand the number of useful signs and symptoms to guide the search of patients or probable cases. (vi) Clinical–parasitological profile on PAM can help physicians to guide an early diagnosis, opportune and species-specific treatment, and avoid the consequences of PAM. The objective of this research was to compare the clinical–parasitological profile of GM, PM, and CM malaria, in northwestern Colombia. The specific objectives were as follows: (i) compare the frequency of clinical findings in each one of the three forms of PAM  comparing positive GM, PM, and CM versus negative pregnant women; (ii) compare the clinical findings between P. vivax, P. falciparum, mixed-malaria infections in GM, PM, and CM; (iii) compare the frequency of clinical findings in microscopic GM, PM, and CM versus the submicroscopic infections and negative pregnant women.Knowing the clinical–parasitological profile of PAM in the main endemic area of Colombia is important because of the following: (i) It generates evidence in an unexplored topic of malaria in the country. (ii) Clinical evidence is focused on countries with a predominance of P. vivax predominates (60–70% of cases), but P. falciparum also circulates [Cross-sectional in three different analysis units: for GM, we included 829 pregnant women; for PM, 549 placentas were included; and for CM, 547 newborns were included . Pregnant women were recruited in three local hospitals in the main malaria-endemic area of Colombia, located in the northwest of the country. This region reports approximately 60% of annual malaria cases in Colombia; it is highly endemic with an annual parasite index >25/1000 exposed, transmission is stable throughout the year, and rculates .It was not possible to have the same number of pregnant women, placentas, and newborns for multiple economic, social, or health system factors, such as the following examples: a pregnant woman was included, and we could not obtain the placenta or newborns sample because she presented a complication or risk for which her delivery was attended in another health institution ; some only consented to take one of the samples (for example blood from the pregnant woman or from the cord); others entered during pregnancy but did not sign (or withdrew) the consent for the placenta or newborn samples; the team that attended the delivery or the family of the pregnant women did not contact the research group to notify them of the date of delivery, among other economic and cultural reasons that prevented the delivery care at the local hospital .Pregnant women and newborns met the following inclusion criteria: receiving antenatal care or delivery at the local hospital of their municipality, pregnant women residing in the study region for at least one year, and having TBS and qPCR results for malaria. Pregnant women and newborns diagnosed with other diseases, infections, or complications of their health status, on antimalarial treatment at the time of the study, or without signing informed consent were excluded. The samples were collected between 2010 and 2019 using the same standardized procedures for collecting information and diagnosing malaria, which consist of applying the same form for extracting variables from the medical chart and using the same survey. For the processing of this information, the research group trained and standardized three nursing assistants who led the information collection.TBS and qPCR were performed on the same blood samples (at the same time). The diagnosis of GM was made with peripheral blood collected by venipuncture . In PM, placental blood was taken from a point near the insertion of the umbilical cord and another in the distal part of this organ; in CM, peripheral blood from the newborn by heel puncture or umbilical cord was used. In the case of a pregnant woman or newborn positive for TBS, antimalarial treatment was performed in accordance with the Colombian clinical practice guideline. In submicroscopic cases, we notified the physician of the result of the qPCR, and depending on his clinical evaluation, the doctor decided on the treatment.Plasmodium and primers polymorphic specific to P. falciparum, P. vivax, P. malariae, and P. ovale [P. falciparum, P. vivax, or mixed malaria is defined. The latter corresponds to the observation of parasitic forms of P. vivax and concomitant gametocytes of P. falciparum or regular asexual forms compatible with P. falciparum in a proportion of ≥40% of the 100 parasitic forms observed [For qPCR, Whatmann #3 filter paper was used for DNA extraction with the Saponin-Chelex method. PCR is the main molecular diagnosis of malaria with a detection limit of <0.02 parasites/μL. qPCR avoids post-amplification manipulation and quantifies the number of microorganisms; it includes a highly conserved region 18S rRNA of P. ovale . TBS is observed .The following variables were extracted from the medical chart of pregnant women: hemoglobin  , presencP. falciparum, P. vivax, or mixed malaria was performed with the Pearson chi-square test or Fisher’s exact test (n < 5). When the comparison of P. falciparum, P. vivax, or mixed malaria showed significant p values, multiple comparisons were made with the Bonferroni statistic. In order to compare the continuous variables with PM and CM, the Mann–Whitney U test was used; for causal species and microscopic or submicroscopic GM, the Kruskal–Wallis H with post hoc of Dunnett was used. A p-value < 0.05 was considered statistically significant.Categorical variables were described with absolute (#) and relative (%) frequencies, and the continuous variables were described with median and interquartile range . The comparison of the clinical findings between positive and negative for PAM and those affected by The Declaration of Helsinki and the specifications of Resolution 8430 of Colombia for research with pregnant women were applied. All pregnant women signed the informed consent  or assent (under 18 years of age) obtained in writing with the signature of the pregnant woman and a witness external to the research group. This study was classified as minimal risk, endorsed by the Ethics Committee of the University Research Headquarters (SIU), University of Antioquia, Act 21-101-961 of the year 2021. All data were anonymized to guarantee confidentiality.P. vivax, 34.3% were P. falciparum, and 2.7% were mixed malaria. The frequency of PM was 20.9% (115/549), with 94.8% submicroscopic, an equal proportion of P. vivax and P. falciparum (44.3%), and 11.3% mixed malaria. CM was 12.4% in umbilical cord blood and 2.2% in peripheral blood of the newborn, all submicroscopic cases, and with P. falciparum as the main causal species with 63.5% of the cases (The frequency of GM was 35.8% (297/829). Among the 297 positives, 45.1% were submicroscopic, 63% were he cases . The conhe cases , 24 , fever (23.8%), musculoskeletal pain (13.0%), shaking chills (10.9%), and vomiting (10.9%). Previous abortions occurred in 15.4% (87/566) and stillbirths in 2.1% (12/566). The following medians (interquartile range) were presented in the newborn: birth weight 3100 g (2852–3400), height 50 cm (49–51), head circumference 34 cm (33–34), and APGAR score 8 (7–9).P. vivax, except for sore throat and cough (p Chi2 = 0.293), stillbirths (p Chi2 = 0.342), or ITN use (p Chi2 = 0.086).We did not find an association between GM and diarrhea, but with all other clinical manifestations, there was a statistical association. According to the causal species, clinical findings were more frequent in women with nd cough . There wp Chi2 = 0.677) or stillbirths (p Chi2 = 0.498).In submicroscopic GM, a statistically higher frequency of anemia, cough, sore throat, and headaches was found compared to negative pregnant women; the first three symptoms were statistically the same as those found in pregnant women with microscopic malaria (positive with both diagnostic tests) . We did p Chi2 = 0.490) or stillbirths (p Chi2 = 0.193). PM presented statistical differences with anemia, and there was no significant association with the other clinical findings . There was no statistical association of PM with previous abortions (findings . We did p = 0.012) was only found between height and mixed GM. In the mixed-GM group, the median was 45 cm (IR 45–46), and in negatives and pregnant women with P. falciparum and P. vivax, the median was 50 (IR 49–51).In the outcomes in the newborn, GM, PM, and CM did not present a statistical relationship with the APGAR score or with the height at birth; when disaggregating these comparisons according to the causal species, an association  were statistically more frequent in P. vivax ; this isSubmicroscopic GM presented an association with anemia, cough, sore throat, and headache, showing the need to implement molecular diagnostics, given the false negatives of TBS. Other publications report the same situation but focus their arguments on the sensitivity problems of TBS in non-febrile patients, the need to interrupt their transmission or the achievement of the goals of pre-elimination or elimination ,24,25,26In addition, our results are relevant to support subsequent research on the clinical utility of PAM molecular diagnosis since some authors indicate that PCR does not provide information on the viability of the microorganism; therefore, its clinical use is inadequate , so the search for symptomatic cases and the prescription of the treatment of malaria should continue to be carried out with TBS. In this sense, this study shows that submicroscopic cases presented some clinical findings statistically similar to those of microscopic PAM .P. vivax. Although higher pathogenicity has been reported for P. falciparum [P. vivax with serious effects such as anemia and other hematological complications, severe malaria, acute respiratory distress, and multiple organ failure [P. vivax in PAM [In PM, the frequency of anemia was higher in lciparum , the evi failure , as wellx in PAM ,9,10. Itx in PAM ,30.P. falciparum. This coincides with the available evidence on this topic [CM was associated with a reduction in weight and head circumference at birth. The effect on birth weight was higher in mixed malaria and is topic ,7,10,19 is topic ,32. AddiP falciparum or fetal and neonatal outcomes avoided when GM is treated during pregnancy [Regarding head circumference at birth, several studies have reported similar results, evidencing an association of PM with a decrease in head circumference; newborns with a small head in pregnant women infected with regnancy ,34,35,36The way in which health care is structured in Colombia restricts the number of times pregnant women are attended by health personnel; thus, important data from the medical chart are frequently omitted. The foregoing resulted in many women in this investigation not having a complete record of clinical manifestations. Molecular diagnosis with PCR is excluded as part of the treatment guidelines, with the placenta as a waste organ in hospitals, which leads to difficulties for studies of PM and structural barriers to accessing antenatal care in dispersed rural areas that are most affected by malaria, leading to problems of recruitment of all pregnant women exposed or at risk.P. vivax are associated with clinical findings. The differences in the causal species of GM, PM, and CM evidence the complexity of the parasitological component of PAM. The need to improve the completion of the medical chart and increase the number of studies on medical aspects of gestational, placental, and congenital malaria was also demonstrated.This research is one of the few available in Colombia on the clinical characteristics of PAM. Contrary to evidence from other countries, this study showed that submicroscopic infections and those caused by


The purpose of this study was to investigate the effects of 4 weeks of soleus stretching on ankle flexibility and dynamic balance, as well as selected monitoring and performance tests in soccer. Forty-five healthy female soccer players were randomly divided into a regular stretching group, a regular stretching group with soleus stretching, and a control group. Dynamic stretching protocols were performed for 4 weeks during three sessions per week as part of routine exercises. The regular group stretched three muscle groups , while the regular + soleus group also stretched the soleus muscle. Before and after the stretching intervention, the ankle range of motion test, Y-balance test, drop jump test, dynamic knee valgus test, and Illinois Agility Running Test were performed. Ankle ROM, Y-balance, and DJ significantly improved in both intervention groups compared to controls. Only the regular + soleus group showed improvement in the Illinois Agility Running Test. Additionally, athletes performing the additional soleus stretching had greater improvements in ankle ROM and DJ but not in DKV or Y-balance. The results showed that adding soleus stretching into regular protocols can provide benefits for female soccer players in terms of performance parameters. Soccer is a sport that offers numerous physical benefits to female athletes . HoweverIt has been demonstrated that dynamic stretching (DS) for lower limb muscles, including the gluteus, hamstrings, quadriceps, and calf muscles, is more effective than no stretching or static stretching (SS) in enhancing joint flexibility and athletic performance ,8,13. MuPrevious studies on training have mainly focused on the effects of stretching on lower limb muscles, without considering the soleus muscle. For example, Akbulut et al.  studied Although the soleus muscle plays a crucial role in tasks such as running , most stThe present study was a quasi-experimental research that focused on youth athletes in Iran’s Kerman province. The population consisted of 45 soccer players, and the sample size was determined based on previous studies by Barbosa et al.  and La GAfter completing the consent form and demographic information, participants were randomly divided into three groups: regular, regular + soleus, and control. The study was conducted in a way that kept the purpose and the different types of stretching exercises blinded to the subjects. Participants performed stretching exercises for 4 weeks, with three sessions per week as part of their soccer exercises. The coach and one of the researchers (E.H.) monitored the participants’ stretching exercises during this time. Additionally, participants were asked to perform the ankle range of motion (ROM) test, drop jump test, and functional tests in random order before and after the 4-week stretching exercises. Notably, before stretching exercises and test instructions, video demonstrations were provided to the participant groups to familiarize them with the exercises. The regular stretching group participants were instructed to perform bilateral full-range dynamic stretches on the quadriceps, hamstrings, and gastrocnemius for three sets each, with a duration of 30 s, while participants in the regular + soleus group performed an additional soleus stretch for the same duration. The control group was asked not to stretch throughout the intervention period. All measurements from the subjects’ dominant leg were used in the data analysis [In this study, there were three conditions: regular stretching alone (regular group), regular stretching with additional soleus stretching (regular + soleus group), and no stretching (control group). In the regular group, the hamstring, quadriceps, and gastrocnemius muscles were bilaterally stretched three times each for 30 s using a dynamic stretching technique. For the regular + soleus group, participants were instructed to additionally stretch the soleus for 3 sets × 30 s. According to the literature review, there was a one-minute break after stretching all muscle groups. Participants in the control group did not stretch and were asked to sit down for 8 min instead. The hamstrings stretch was performed by standing on the ground with feet shoulder-width apart and bending the trunk forward with the goal of contacting the right foot with the left hand and vice versa with a dynamic movement. Additionally, the subject stretched their quadriceps while standing on one leg. After that, one hand was used to grab the foot that was lifted (stretching leg), and the heel was pushed towards the buttocks by bending the knee. In order to stretch the gastrocnemius, the individual took one step forward while standing, while the knee of the leg in the back was fully extended. The dynamic stretch was induced by pushing the front knee forward . Lastly,A reliable and consistent method for evaluating ankle range of motion (ROM) in a closed kinetic chain is the weight-bearing lunge test , as recoThe OctoBalance device  was utilized to assess dynamic balance by measuring three lower limb excursion directions: anterior (YBT-A), posteromedial (YBT-PM), and posterolateral (YBT-PL) . During To begin the drop jump (DJ) test , particiTo measure dynamic knee valgus (DKV) angles , the froThe functional performance in this investigation was evaluated using the Illinois Agility Running Test , as desc2) was determined for all parameters, where a partial η2 of 0.02, 0.13, and 0.26 were defined as small, medium, and large, respectively. The significance level was set at p < 0.05, and the confidence interval was 95%.The statistical analyses were performed using SPSS 26.0 software . The normal distribution was evaluated using the Shapiro–Wilk test. A mixed-design analysis of variance (ANOVA) was applied to all variables, with a within-subject factor of time effect (pre-test and post-test), and a between-subject factor of group effect  along with group–time interaction. If the group effect or interaction effect was found to be significant, a Tukey’s post hoc test was employed to detect potential differences. Effect size . Mean and standard deviation of dependent variables before and after interventions are presented in p < 0.05), group effect (p < 0.05), and group–time interaction (p < 0.05) for variables such as ankle-ROM, YBT, and DJ, and in the Illinois Agility Running Test. Although the time effect and group–time interaction for DKV were significant (p < 0.05), there was no significant difference in group effect (p > 0.05).All variables displayed a normal distribution (p < 0.05) observed between the regular group and the control group, the regular + soleus group, and the control group, as well as the regular group and the regular + soleus group in ankle range of motion (ROM) and drop jump (DJ) tests. Furthermore, in the Y-balance test (YBT), significant differences were noted between the regular group and the control group, as well as the regular + soleus group and the control group. In the Illinois Agility Running Test, a significant difference was observed between the regular + soleus group and the control group (p < 0.05).According to the results of the Tukey test , there wThe aim of this study was to investigate the long-term effects on ankle joint range of motion (ROM), Y-balance, drop jump (DJ), and DKV, and Illinois agility running. Our results demonstrated that both intervention groups (regular and regular + soleus) showed significant improvements in ankle ROM, Y-balance, and DJ compared to the control group. However, only the regular + soleus group showed an improvement in the Illinois Agility Running Test. Athletes who performed additional soleus stretching had greater improvements in ankle ROM and DJ but not in DKV or Y-balance. Improved ankle ROM in the two stretching protocols may be related to either changes in muscle structure by decreasing muscle stiffness  or changThe Y-balance test showed similar improvement in both intervention groups. Unilateral dynamic balance is especially critical for soccer players since most of their repetitive and explosive movements involve unilateral actions such as acceleration and deceleration tasks, rapid cutting maneuvers, kicking, jumping, and landing ,50. TherFemale soccer athletes perform a variety of movement patterns during matches that put cumulative loads on their lower extremity joints and musculature, making it important to identify individuals with poor movement patterns in order to develop injury-prevention strategies ,55,56,57t-test. Additionally, considering the soleus muscle, Huang et al. [Considering the Illinois Agility Running Test, our results showed a positive progress in regular + soleus stretching protocols when compared to the controls. These results are in line with studies of dynamic stretching warm-up protocols ,63. Ishag et al.  reportedThis study had some limitations that should be considered. Firstly, our sample size was small and to generalize these results to female soccer players it is recommended to conduct similar research with a larger sample size. Secondly, the duration of the study  was quite short. Therefore, it is suggested that the effects of soleus stretching should be investigated over a longer period. Additionally, follow-up tests over a prolonged duration might be considered in future studies. Thirdly, the physiological effects of stretching were not been investigated in this research. It is suggested to investigate these limitations in future research.The results of the study confirm that long-term (4 weeks) soleus stretching leads to significant improvements in ankle range of motion, Y-balance, DJ, and the Illinois Agility Running Test. Therefore, if soleus stretching is added to lower limb dynamic stretching in the long term, it could have a positive influence on the skills and performance of female players. Therefore, trainers are recommended to incorporate dynamic stretching into their training sessions and warm-ups to improve player abilities.


To systematically evaluate the diagnostic value of an artificial intelligence (AI) algorithm model for various types of diabetic retinopathy (DR) in prospective studies over the previous five years, and to explore the factors affecting its diagnostic effectiveness.A search was conducted in Cochrane Library, Embase, Web of Science, PubMed, and IEEE databases to collect prospective studies on AI models for the diagnosis of DR from January 2017 to December 2022. We used QUADAS-2 to evaluate the risk of bias in the included studies. Meta-analysis was performed using MetaDiSc and STATA 14.0 software to calculate the combined sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of various types of DR. Diagnostic odds ratios, summary receiver operating characteristic (SROC) plots, coupled forest plots, and subgroup analysis were performed according to the DR categories, patient source, region of study, and quality of literature, image, and algorithm.Finally, 21 studies were included. Meta-analysis showed that the pooled sensitivity, specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, area under the curve, Cochrane Q index, and pooled diagnostic odds ratio of AI model for the diagnosis of DR were 0.880 (0.875-0.884), 0.912 (0.99-0.913), 13.021 (10.738-15.789), 0.083 (0.061-0.112), 0.9798, 0.9388, and 206.80 (124.82-342.63), respectively. The DR categories, patient source, region of study, sample size, quality of literature, image, and algorithm may affect the diagnostic efficiency of AI for DR.AI model has a clear diagnostic value for DR, but it is influenced by many factors that deserve further study.https://www.crd.york.ac.uk/prospero/, identifier CRD42023389687.  AccoFundus color photography plays a key role in the screening of DR, which has traditionally relied on the clinical experience of ophthalmologists or retinal specialists who comprehensively evaluate the patient’s condition through routine ophthalmology examination, fundus scope, optical coherence tomography (OCT), and other methods. However, as DR is an insidious disease, most patients are not consciously aware of the existence of the disease, especially those living in areas with underdeveloped medical facilities, making it challenging for ophthalmologists to make an accurate and timely diagnosis of the patient’s condition from fundus color photography. In addition, ophthalmologists often adopt different intervention methods for DR patients with different disease states. Therefore, in order to delay the occurrence and development of DR, reduce the blinding rate, and improve the quality of life of patients, it is necessary to accurately distinguish the various types of DR at an early stage of the disease.As deep learning technology has advanced in recent years, the application of artificial intelligence (AI) in the medical field is receiving increasing attention. It involves the analysis and evaluation of image-related data through the establishment of relevant databases and application models, and information processing . In the 22.1Two reviewers (KL and SM) searched relevant prospective studies in the Cochrane Library, PubMed, Embase, Web of Science, and The Institute of Electrical and Electronics Engineers (IEEE) databases over the last 5 years. Each of the other reviewers re-evaluated whether the search strategy was appropriate and whether the included literature was consistent with the research purpose. The terms of our search were as follows:  AND (“diagnosis” OR “screen” OR “classification” OR “discriminate”) AND (“performance” OR “sensitivity” OR “specificity” OR “accuracy” OR “area under the curve” OR “auc”). The meta-analysis was conducted following the PRISMA   the study was a diagnostic study; (2) the subjects were type 2 or type 1 diabetic patients with DR; (3) the diagnostic measure was AI technology, and DR was diagnosed from fundus color images; (4) the study was complete with available data on sensitivity (SE), specificity (SP), number of patients and controls, and other outcome indicators; (5) prospective research in the last 5 years. Exclusion criteria: (1) Diagnostic measures do not belong to AI technology and no AI-related algorithm was used; (2) studies with duplicate data and incomplete original data; (3) studies with incomplete or inaccessible outcome indicators. ZW and ZL selected the studies independently according to the inclusion and exclusion criteria above. If there was a difference of opinion among the reviewers, a joint consultation was held with a third reviewer (XZ) before making a decision. Here are populations, interventions, comparators, outcomes, and study designs (PICOS) in our study. Population of our research comes from type 2 or type 1 diabetic patients with DR; interventions: patients with DR are diagnosed by AI technology.; comparators: patients with DR are diagnosed by clinical doctors;.study design: the study was a diagnostic study.2.3After obtaining the full articles, two reviewers (ZW and ZL) independently summarized the features of the included studies and extracted outcome indicators related to the diagnostic efficacy of AI from each study. We addressed divergence between the two reviewers’ data extraction by discussion and consultation with a third investigator (KL). Reviewers directly extracted SE, SP, and number of DR patients and total participants from the included studies. These indicators were used to calculate the outcome variables for the diagnostic meta-analysis, namely true-positives (TP), false-positives (FP), false-negatives (FN), and true-negatives (TN), which were then entered into contingency tables, followed by subsequent meta-analysis. If a study contained different types of DR or different algorithms, and there were multiple contingency tables, we assumed that they were independent of each other.2.4To assess the quality of the included Studies, two investigators (SM and XZ) used Quality Assessment of the Diagnostic Accuracy Studies 2 (QUADAS-2)  and RevM2.52 test and Cochrane-Q test were used to evaluate heterogeneity caused by possible non-threshold effects in this meta-analysis. If I2>50%, it was considered as significant heterogeneity. Subsequently, bivariate random effects model was used to calculate the pooled sensitivity, specificity, area under the curve (AUC), diagnostic odds ratio (DOR), positive and negative likelihood ratios , among which area under the SROC curve indicates the diagnostic value of AI for DR. In order to explore how categories of DR, source of patients, sample size, country, quality of included studies and images, and different algorithms can influence the merged results, we performed subgroup analysis according to the above factors.We used MetaDiSc software (version 1.4) for the outcome variables . Summary receiver operating characteristic (SROC) plots and coupled forest plots were used to visualize the merger results. The IWe used the midas package in STATA14.0 to conduct a sensitivity analysis of the included studies to explore the source of heterogeneity. Furthermore, the incidence rate of DR (30%) was taken as the prior probability, and the posterior probability was calculated according to the summarized LR+ and LR-. The results were visualized in STATA14.0 and displayed with fagan plots. We have assess publication bias by plotting Deek’s funnel plot. The funnel plot is asymmetric when significant publication bias is present. All statistical results were considered significant if the two-tailed p value<0.05.33.1A flowchart of the literature search and study selection process is presented in 3.23.3The data were imported into MetaDiSc software (version 1.4) for analysis. It was found that the spearman correlation coefficient between the sensitivity logarithm and (1-specificity) logarithm was 0.001 (p=0.996>0.05), which was not significant. Therefore, there was no threshold effect Table 3.3.4MetaDiSc software was used to analyze the included data. The pooled SE was 0.880 (0.875-0.884), pooled SP was 0.912 (0.99-0.913), pooled LR+ was 13.021 (10.738-15.789), pooled LR- was 0.083 (0.061-0.112), combined AUC=0.9798, Q index =0.9388, and pooled DOR was 206.80 (124.82-342.63). Corresponding (SROC) plots and coupled forest plots are shown in 3.5To explore the source of heterogeneity, we performed meta regression according to the conditions of subgroup analysis using MetaDiSc software. We found that the p value of the algorithm term was 0.033<0.05, indicating that when different AI models are uses to diagnose DR, the algorithms used by the different models may be the source of heterogeneity. The results are shown in 3.6STATA 14.0 was used to first conduct a publication bias test for all data included in the study, followed by a publication bias test for different categories of DR. The results are shown in 4In recent years, several studies have investigated the use of AI for the assessment of incidence and diagnostic accuracy of DR. Meanwhile, the application of AI in the medical field is being continuously developed and subdivided . HoweverThere was no threshold effect in this analysis, but the heterogeneity among studies was high. Therefore, the random effects model was used to combine all indicators. DOR and AUC were the main indicators to judge the relationship between the diagnostic results and DR. The pooled DOR=206.80 and AUC=0.9798 for all included studies indicated that AI had a high diagnostic performance for DR. In order to make the study results more clinically relevant, we drew fagan plots and concluded that if AI showed a positive result based on fundus color photography, the probability of the patient having DR was 93%. If the AI diagnosis was negative, the patient had a 3% chance of DR.To explore the source of heterogeneity, we conducted meta regression, and found that the differences in AI algorithms may be the source of heterogeneity. To further explore the factors influencing the AI diagnosis of DR, we performed a subgroup analysis. We found that studies with patients from clinics, hospitals, or medical research centers had higher diagnostic efficacy than those with patients from other sources, and this may be because patients from hospitals or medical research centers are more representative, and retinopathy can be diagnosed more accurately by clinicians with a lower error rate; besides studies from non-Asian countries had higher diagnostic efficacy than studies from Asian countries, and we believed that this is because non-Asian countries have carried out artificial intelligence algorithm diagnosis DR for a long time, trained the algorithm more times, had a large data set, included more cases, and had relatively high data quality. Moreover, we have found that the greater the number of eyes included in the study, the higher the diagnostic efficacy. We hypothesized that the more cases included, the more times the algorithm would be trained, so the more accurate the diagnosis would be. When the image pixel was taken as the standard to judge the image quality, it was found that the higher the image quality, the higher the DOR value of the diagnostic result, which is similar to the findings of Yip et al. . When thSeveral studies have found that for screening, risk stratification, management, and prognosis of DR, the effect of AI cannot be ignored. Firstly, an AI-based automated system can improve the efficiency and coverage of DR diagnosis and treatment, since the traditional DR diagnosis and treatment process only relies on a pattern of manual identification, which is easily affected by the experience, skills, and other factors related to the ophthalmologist or relevant technical personnel; therefore, the efficiency of DR screening is relatively low . SecondlAs a novel diagnostic tool, there are still many problems with AI: (1) Although AI is getting better at diagnosing eye diseases, in our study, the false negative rate (FNR) was 12% and false positive rate FPR was 8.8%, which cannot be ignored. Further exploration of imaging features, increasing the sample size of the training set and test set, or further improving the performance of the algorithm are all feasible methods to solve these problems . (2) At The ophthalmologist will play an important role in judging the clinical value of emerging AI technologies, in addition to a guiding role in integrating complementary imaging information with clinical data to provide more complete diagnostic information . Even ifThis study has the following limitations: (1) the collected DR data lacked proliferative diabetic subtype or further classification of DR, which may affect the evaluation of the diagnostic value; (2) some studies lacked four-grid table data or contained a small number of samples; therefore, the diagnostic value of the representative algorithm may not be truly reflected; (3) In the meta regression, we did not further analyze patient information, such as age, sex, and duration of the disease, which may be a source of heterogeneity and need further study; (4) only English studies were included, which may cause a bias due to the lack of literature in other languages; (5) The gold standard is the decision made by an ophthalmologist or retinologist based on the fundus color image, which means that AI may not perform well on images that an ophthalmologist cannot recognize; (6) Most of the AI algorithm models used in studies are self-developed or debugged models. Since the researchers did not clarify the pre-training degree and learning amount of each model, we could not include these factors in the analysis; (7) there are problems with direct comparison of diagnostic accuracy. As can be seen from the high diagnostic accuracy of VTDR, the diagnostic accuracy differs between mild retinopathy and severe retinopathy. Therefore, the overall accuracy will change depending on the composition ratio of the disease stage of the image for accuracy verification. For example, if many of the accuracy verification images are of mild retinopathy, it is difficult to recognize the lesions, so false negatives increase and accuracy is predicted to decrease.In conclusion, this meta-analysis suggests that AI-based fundus color imaging has a high predictive ability for DR. The diagnosis rate is much higher than the manual, method, which can contribute to the clinical development of the follow-up strategy or diagnosis and treatment plan and has a high practical application value. However, AI still has a certain rate of missed diagnosis and misdiagnosis, and is easily affected by the patient source, number and representativeness of sample, algorithm of the AI model, quality of images, use of cameras, and type of algorithm. Correspondingly, the performance of AI for diagnosis of DR can be further improved by obtaining more detailed patient data, collecting a large number of samples from multi-centers, deep mining of image features, optimizing AI algorithm architecture, and using high-resolution cameras for images. If the diagnosis and treatment strategies formulated by ophthalmologists are combined with AI, the work efficiency can be greatly improved and the utilization rate of medical resources can be increased, in addition to providing a more scientific and efficient way for early screening, diagnosis, and treatment of DR.The original contributions presented in the study are included in the article/KL and SM were responsible for searching the studies in the databases. ZW and ZL designed the entire research idea, selected the appropriate studies after careful searching, and extracted the data from each study. SM and XZ completed the quality assessment. Final meta-analysis was completed by ZW. XZ and YD conceived the study and wrote the first draft. The four authors jointly revised the manuscript. All authors contributed to the article and approved the submitted version.


N = 26), OSA-mild (N = 39), OSA-moderate (N = 37), and OSA-severe (N = 55). The electrocardiogram was extracted from the PSG recordings, and a 15-min beat-by-beat series of RR intervals were generated every hour during the first 6 h of sleep. Linear and nonlinear HRV approaches were employed to calculate 32 indices of HRV. Specifically, time- and frequency-domain, symbolic analysis, entropy measures, heart rate fragmentation, acceleration and deceleration capacities, asymmetry measures, and fractal analysis. Results with indices of sympathovagal balance provided support to reinforce previous knowledge that patients with OSA have sympathetic overactivity. Nonlinear indices showed that HRV dynamics of patients with OSA display a loss of physiologic complexity that could contribute to their higher risk of development of cardiovascular disease. Moreover, many HRV indices were found to be linked with clinical scores of PSG. Therefore, a complete set of HRV indices, especially the ones obtained by the nonlinear approaches, can bring valuable information about the presence and severity of OSA, suggesting that HRV can be helpful for in a quick diagnosis of OSA, and supporting early interventions that could potentially reduce the development of comorbidities.Obstructive sleep apnea (OSA) is one of the most common sleep disorders and affects nearly a billion people worldwide. Furthermore, it is estimated that many patients with OSA are underdiagnosed, which contributes to the development of comorbidities, such as cardiac autonomic imbalance, leading to high cardiac risk. Heart rate variability (HRV) is a non-invasive, widely used approach to evaluating neural control of the heart. This study evaluates the relationship between HRV indices and the presence and severity of OSA. We hypothesize that HRV, especially the nonlinear methods, can serve as an easy-to-collect marker for OSA early risk stratification. Polysomnography (PSG) exams of 157 patients were classified into four groups: OSA-free ( Obstructive sleep apnea (OSA) is a common respiratory sleep disorder characterized by partial or total airway obstruction episodes, impairing the efficient gas exchange during sleep . It has The hypoxic/hypercapnic episodes suffered by patients with OSA elicit responses, such as sympathetic activation, aiming to re-establish the expected blood oxygen levels. Chronically, recurrent episodes of chemoreceptors activation due to hypoxic events can trigger sustained cardiac dysautonomia, with sympathetic predominance, that can contribute to the development of cardiovascular diseases and increase the risk of cardiac events in patients with OSA .Furthermore, polysomnography (PSG), the gold standard test for the identification and classification of OSA, is a complex and expensive procedure, leading patients to wait months to years before receiving an adequate diagnosis . It is eThe analysis of heart rate variability (HRV) is a valuable probe to investigate the neural control of the heart and is associated with cardiac risk in several diseases, including OSA . HRV repChanges in HRV are observed in various diseases, including OSA, since it is well demonstrated that OSA markedly affects the autonomic function, especially in its more severe forms . NeverthThe present study aims to analyze and correlate a variety of HRV indices, calculated with both linear and nonlinear approaches, in patients with different degrees of severity of OSA  evaluated by PSG. We hypothesize that the more recent nonlinear methods for assessing HRV, included in this study, provide important markers for stratifying OSA severity.PSG exams were performed at the University Hospital of Ribeirão Preto Medical School of the University of São Paulo (HC-FMRP/USP) between 2015 and 2021. The data collection and the analysis protocols were carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) and authorized by the Research Ethics Committee of HC-FMRP/USP (Protocol # 42058720.6.000.5440/4.550.2327).Patients older than 18 years old, with a minimum sleep recording period of 5 h and 15 min in the PSG, and with RR series containing no more than 2.5% of artifacts identified (see next section) were included in the study. Out of 301 exams collected, 144 were not used due to problems with the recording files, such as insufficient collected time, corrupted files, poor signal quality, and/or arrhythmias (96 recordings); exams from patients under 18 years old (2 recordings); and exams with missing data in the report (46 recordings). The final sample was composed by 157 recordings.W was applied to the RR series, creating a median line. Next, a lower and upper tolerance were defined as the median line shifted down and up, respectively, by a factor of T (tolerance). This tolerance corresponds to a percentage of the average median line. The optimal values of W and T were manually chosen for each series, varying in the range W =  and T = . Finally, all RR values below the lower or above upper tolerance were replaced using linear interpolation. When the number of corrections exceeded 2.5% of the total number of beats, the patient was excluded from the study (10 RR series were excluded from the study for this reason).The PSG exam records variables such as electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), electrocardiogram (ECG), thoracic and abdominal movements by piezo-electric straps, pulse oximetry, nasal pressure transducer system and nasal and mouth thermocouple airflow sensor to monitor the airflow, microphone to detect snores, sensor to determine body position, and a video camera to monitor the patient during sleep. So, ECG recordings from the PSG exams (sampling rate: 512 Hz) were obtained and, after visual inspection, segments of 15 min from each hour were extracted for each patient from the first 6 h of recording. The segment selection was based on a visual assessment on the quality of the ECG, avoiding the presence of artifacts as much as possible. Time series of successive RR intervals were generated  for each 15-min segment and corrected for remaining artifacts and/or ectopic beats. Artifacts were identified as follows: first, a moving median window of size Corrected RR series were used to calculate HRV indices using the computer software PyBios . Linear n < 15 (α1), where n is the number of RR intervals considered , fuzzy entropy , distribution entropy , dispersion entropy , permutation entropy , attention entropy (AttEn), and phase entropy . The details of the calculation of these approaches are described elsewhere  of RR intervals series was performed by the detrending fluctuation analysis (DFA) in the scaling range 5 < nsidered . Entropylsewhere . The acclsewhere . Besideslsewhere . For Porlsewhere . BrieflyThe PSG report, provided by a qualified physician, was used as the source of indices of interest to determine the presence and severity of OSA, which were: apnea/hypopnea index (AHI), arousal index (AI), percentage of the total sleep time that the patient achieved oxygen saturation below 90% (T90), and oxygen saturation nadir during sleep (SatMin). The AHI represents the number of apneic/hypopnea events divided by the total hours of sleep. An apnea event is defined as a reduction >90% of the airflow, lasting at least 10 s (associated with a respiratory effort), and the hypopnea event is characterized by a reduction >30% of the airflow in a period >10 s, associated with an oxygen desaturation >3% during this period or with arousal . AHI is post-hoc test of Dunn was applied. For the gender differences between groups, the chi-square test was applied. Finally, the Spearman’s correlation coefficient was used to evaluate the correlation strength between HRV and PSG indices. In all cases, statistical significance was considered when p ≤ 0.05.The Shapiro-Wilk test was used to check the normality of each variable. Since most variables showed a non-normal distribution, the results are shown as median (first and third quartiles), and the Kruskal-Wallis test was applied to compare groups. When differences were observed, the Regarding the entropy measures, SampEn, FuzzyEn, and DispEn showed a reduction in patients with moderate or severe forms of OSA, while AttEn increased in severe patients compared to normal individuals. DistEn, PermEn, PhaseEn were not significantly different among groups. The DFA short-term scaling exponent was found higher in patients with moderate and severe OSA as compared to healthy individuals. The AC/DC method showed that only the acceleration capacity is reduced in a moderate form of OSA. HRF showed that the occurrence of W0 patterns is increased in the severe OSA as compared to mild OSA and normal subjects. The rate of occurrence of W1 patterns is decreased in mild and moderate OSA compared to the normal group. Moreover, similar to the LF/HF ratio, 0V from symbolic analysis, DFA-α1, AttEn, the W0 index of HRF showed a linear increase as the severity of OSA rises. None of the three asymmetry indices are different among all groups.The present study evaluated the relationship between HRV indices, calculated by several approaches, and four important PSG-derived clinical scores of OSA. Studies using ECG-based methods as a screening tool for patients with OSA have been described before . HoweverThe HRV indices calculated in the time domain were extensively demonstrated to be associated with cardiac risk in several situations . To our Our findings from spectral analysis and symbolic dynamics strongly suggest a cardiac autonomic imbalance, with sympathetic predominance, in patients with OSA. It is well accepted that high values of the LF/HF ratio and 0V, together with the reduction of 2UV symbols, are linked to an increase in sympathetic and a decrease in parasympathetic cardiac modulation, respectively . AdditioFrom nonlinear methods, fractal and entropy measurements were found altered in patients with OSA, which is in line with several previous observations in the literature . The DFAAlthough none of the asymmetry indices were found different among groups, the acceleration capacity is decreased in patients with moderate OSA. Therefore, OSA seems not to affect the number of accelerations and decelerations but may affect the magnitude of heart rate accelerations. In agreement with this idea, the study from Another promising nonlinear approach to evaluating HRV is heart rate fragmentation. We showed that the occurrence of W0 patterns is increased in severe OSA, while a reduction in W1 patterns occurred in mild and moderate forms of OSA, when compared to healthy subjects. In the first studies conducted by The correlation analysis showed that many HRV indices are slightly but significantly correlated with PSG scores. In general, AI showed higher correlation coefficients with HRV than those with AHI, T90, or SatMin. This suggests that the autonomic imbalance of OSA is more related to sleep fragmentation than to the number of apneic/hypopneic events. This is in agreement with several studies that evaluated the association of HRV with several sleep disorders . Here, tUnlike studies with classical linear HRV approaches, far fewer studies can be found evaluating the relationship between nonlinear HRV and OSA. Here, we demonstrated that DFA (short-term exponent) and some entropies are correlated, although slightly, with the top PSG scores used to detect and classify OSA, i.e., AHI, AI, T90, and SatMin. While SampEn, FuzzyEn, and DispEn showed an inverse relationship with AHI and MI, DFA-α1 and AttEn showed positive associations. The importance of entropy and fractal dynamics in the prognosis of diseases is widely demonstrated . Here, wThe results presented here using a large number of HRV indices advocates for the importance of using a comprehensive set of HRV indices in the characterization of OSA and its severity. Since no single HRV index was highly correlated to OSA severity markers, the different HRV indices may provide complementary information. Studies combining those indices through machine learning models are being conducted to identify the importance of each one when they are combined in a single predictive model.Finally, it is essential to highlight some limitations of our study. First, the groups are unbalanced regarding the number of patients because patients with severe OSA represent the most prevalent group. Second, the segments of HRV obtained from PSG recordings were not standardized regarding the sleep phase or the presence of apneic/hypopneic episodes. And third, we did not consider comorbidities and medications in use by the patients. Further studies are necessary to evaluate the influence of those factors on the predictive value of HRV metrics in OSA.In the present study we evaluated the relationship between a wide variety of HRV indices and the presence/severity of OSA. In addition to changes in several indices of HRV in patients with OSA, we showed a significant relationship in a number of these indices with important PSG scores commonly used to define the presence and severity of this disease. More specifically, we highlight LF/HF ratio, 2LV, DFA-α1, SampEn, FuzzyEn, DispEn, and Bin-1V as the most relevant, since they showed significant correlation to at least three out of four OSA severity indices. Our findings point to HRV indices, especially nonlinear ones, as proper adjuvant markers in OSA stratification, which can help to screen these patients, aiming for a quick diagnosis and prevention of the risk of developing the comorbidities related to this clinical syndrome.


Impulse control behaviors (ICBs) frequently coexist with Parkinson’s disease (PD). However, the predictors of ICBs in PD remain unclear, and there is limited data on the biological correlates of ICBs in PD. In this study, we examined clinical, imaging, and biological variables to identify factors associated with longitudinal changes in ICBs in early-stage PD.The data for this study were obtained from the Parkinson’s Progression Markers Initiative, an international prospective cohort study that evaluates markers of disease progression in PD. We examined clinical, imaging, and biological variables to determine their associations with ICBs over a period of up to 5 years. Cox regression models were employed to investigate the predictors of ICBs in early-stage, untreated PD.p < 0.001), while it decreased in HC . Longitudinally, the presence of ICBs in PD was associated with depression, anxiety, autonomic dysfunction, and excessive daytime sleepiness (EDS). However, there was no significant association observed with cognitive dysfunction or motor severity. Treatment with dopamine agonists was linked to ICBs at years 3 and 4. Conversely, there was no association found between ICBs and presynaptic dopaminergic dysfunction. Additionally, biofluid markers in baseline and the first year did not show a significant association with ICBs. A predictive index for ICBs was generated, incorporating three baseline characteristics: anxiety, rapid eye movement sleep behavior disorder (RBD), and p-tau levels in cerebrospinal fluid (CSF).The study enrolled 401 individuals with PD and 185 healthy controls (HC). At baseline, 83 PD subjects (20.7%) and 36 HC (19.5%) exhibited ICBs. Over the course of 5 years, the prevalence of ICBs increased in PD (from 20.7% to 27.3%, During the early stages of PD, there is a notable increase in ICBs over time. These ICBs are associated with depression, anxiety, autonomic dysfunction, EDS, and the use of dopaminergic medications, particularly dopamine agonists. Anxiety, RBD, and p-tau levels in CSF are identified as predictors for the incident development of ICBs in early PD. Further longitudinal analyses will provide a more comprehensive understanding of the associations between ICBs and imaging findings, as well as biomarkers. These analyses will help to better characterize the relationships and implications of these factors in the context of ICBs in early PD. These non-motor symptoms include impulse control behaviors (ICBs), which can be particularly detrimental . ICBs arSeveral studies have reported a wide variation in the prevalence of PD-ICBs, ranging from 3.5% to 59.0%. However, it is important to note that the majority of these studies were conducted on patients with intermediate to advanced stages of the disease who were already undergoing drug treatment . The mecWhile numerous cross-sectional studies have investigated ICBs in PD, there is a limited number of studies that have examined their longitudinal incidence and prevalence. Furthermore, only a few studies have followed ICBs longitudinally for more than 5 years. The ICARUS study aimed to address this gap by examining longitudinal changes in the occurrence of ICBs over a 2-year period. The findings from this study indicated that the presence of ICBs remained relatively stable between the initial visit and the 2-year follow-up visit . HoweverGiven the existing knowledge gaps, our objective was to conduct a systematic investigation to provide a more comprehensive understanding of the prevalence, clinical spectrum, longitudinal evolution over a 5-year period, and biological correlates of ICBs in PD. To accomplish this, we utilized the Parkinson’s Progression Markers Initiative (PPMI) cohort. Additionally, we sought to assess the baseline biological factors that could potentially predict the development of ICBs in PD. By addressing these research objectives, we aimed to contribute valuable insights into the understanding and characterization of ICBs in PD, ultimately enhancing our knowledge of this important aspect of the disease.2.2.1.All the data utilized in this study were obtained from the PPMI database, which has been previously published and is accessible on the PPMI websiteDuring the screening process, individuals with PD were required to meet the following criteria: (1) exhibit at least two of the following: resting tremor, bradykinesia, and rigidity, or have an asymmetric resting tremor or asymmetric bradykinesia; (2) have received an idiopathic PD diagnosis within the past 2 years and remain untreated; (3) be aged 30 years or older; (4) undergo a screening dopamine transporter SPECT scan that demonstrates a dopamine transporter deficit. Regarding the healthy controls (HC), the following criteria were applied: (1) match PD participants in terms of age, gender, and education; (2) exhibit no significant neurological dysfunction; (3) demonstrate no cognitive impairment, as assessed by a Montreal Cognitive Assessment (MoCA) score of greater than 26; (4) have no family history of PD.2.2.To evaluate PD-ICBs, we employed the validated short version of the Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease (QUIP-S), a widely recognized and extensively validated tool recommended for screening ICBs in individuals with PD. The QUIP-S has been proven effective over time and is considered a reliable assessment instrument for this purpose . The scaFurthermore, demographic and clinical data were collected for all subjects. Motor symptoms and disease severity were assessed using the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS)  and Hoehhttp://ppmi-info.org/  imaging to assess the dopamine transporter in all subjects. The analysis of the DaTscan images was performed according to the relevant manuals available at nfo.org/ . Biologinfo.org/ .2.3.All statistical analyses were conducted using SPSS 26. The t-test or chi-square test was used to compare baseline demographics and clinical characteristics between PD subjects and controls, as well as to compare demographics, clinical characteristics, DaTscan measures, and medication use at each time point between patients with PD with and without ICBs. Mann–Whitney U tests were employed to compare biologics between patients with PD with and without ICBs. T-test for normally distributed data, Mann–Whitney U tests for non-normally distributed data, and chi-square for categorical variables.Logistic mixed models were employed to examine changes in ICB-related characteristics over time in patients with PD and HC separately. These models were also used to assess differences in ICBs between the two groups over time. In the latter models, an interaction term between visit and groups was initially tested to evaluate potential differential effects over time. If the interaction test did not reach statistical significance at the 0.10 level, the interaction term was removed from the model, and the overall group differences were reported.In addition, Cox regression models were utilized to explore the univariate and multivariable relationships between baseline demographic, clinical, biological, imaging, and sedative use predictors and the prevalence of ICBs in PD, as well as their predictive value for changes over a 5-year period. To account for covariance, a specific scheme was adopted. For the DaTscan variables, if either the contralateral or ipsilateral side of the putamen or caudate measure exhibited statistical significance in univariate analysis, the contralateral side of the measure was prioritized for inclusion in the multivariate model. Likewise, for CSF biomarkers and the CSF ratios, only the biomarker was included in the multivariate model if both the specific biomarker and its associated ratio were found to be significant. CSF ratios were considered in the multivariate model only if there were instances where neither of the two biomarkers reached significance, but the CSF ratio showed significant associations. Lastly, plot Nomogram based on Cox result for better representation.3.3.1.p < 0.001). In contrast, HC participants demonstrated a significant decrease in the proportion classified as having ICBs (p = 0.005). Furthermore, there was a significant difference in the rates of change in ICBs over time between the PD and HC groups .p < 0.001), any other behavior (p < 0.001), or DDS (p < 0.001) also showed a significant increase over time. On the other hand, HC participants with ICDs (p < 0.001) or any other behavior (p = 0.014) demonstrated a significant longitudinal decrease in the proportion , HS (p < 0.001), CB (p < 0.001), BE (p < 0.001), or excessive hobbyism (p < 0.001) also significantly increased over time. Conversely, HC participants with HS (p = 0.003), CB (p = 0.012), BE (p < 0.001), or excessive hobbyism (p = 0.038) demonstrated a significant longitudinal decrease in the proportion  or multiple ICBs (p < 0.001) significantly increased over time. Conversely, HC participants with one ICB (p = 0.019) or multiple ICBs (p = 0.024) demonstrated a significant longitudinal decrease in the proportion  and those without ICBs (n = 318) are presented in The demographic characteristics and PD characteristics of participants with PD who had ICBs at baseline  at baseline and year 1 . However3.3.To determine the baseline demographic, clinical, biological, imaging, and pharmacological variables that predict the incident development of ICBs over time, we evaluated the 318 participants with PD in this cohort who did not have ICBs at baseline. Among them, 116 participants (36.5%) subsequently developed ICBs. Results based on in-sample concordance and cross-validated prediction accuracy revealed that the best model included three variables: STAI-state subscore, RBD, and p-tau . Additio4.de novo, untreated PD at baseline. Furthermore, to our knowledge, this is the only study that has examined the association between biologics and ICBs in patients with PD. At baseline, there were no differences in the prevalence of ICBs between untreated patients with PD and HC. However, over time, the occurrence of ICBs increased among patients with PD while decreasing among HC. These findings are consistent with previous longitudinal studies that have examined ICBs in PD . That is, we performed a subgroup analysis of the dataset, taking into account the EOPD± classification. Interestingly, we observed no significant gender differences from baseline to year 5 in the EOPD+ subgroup, whether patients had ICBs or not. In contrast, within the EOPD− subgroup, it was only in the fifth year that the proportion of men in the ICBs+ group surpassed that in the ICBs− group . This suWe speculate that the lack of significant association between ICBs and motor impairment measured in Part III of the MDS-UPDRS or other disease characteristics  may be due to the early stage of PD in our cohort and the possibility of interactions arising during disease progression or drug interventions. These factors were also not reported as significant predictors of ICBs in previous studies. However, we observed significant associations between ICBs and the neuro-psychiatric and non-motor symptoms assessed in Part I and the patient-reported experiences of daily living assessed in Part II of the MDS-UPDRS. This is not surprising, as previous studies have identified numerous non-motor symptoms as risk factors for ICBs in PD. These findings suggest that non-motor symptoms captured in Part I and Part II of the MDS-UPDRS may play a more prominent role in the development of ICBs in early-stage PD patients , 16, 38.Our findings, in line with previous research, support the association between ICBs and anxiety in PD . This reThe relationship between EDS and ICBs in early PD is intriguing and has not been systematically explored. A study found associations between poor sleep efficiency, restless legs symptoms, and increased daytime sleepiness with impulsivity in PD . The stuThe association between ICBs and autonomic dysfunction has not been systematically explored in early PD. Similar to EDS, our study did not identify autonomic dysfunction as an independent risk factor for the development of ICBs, although a significant difference was observed between autonomic dysfunction and ICBs at the 5-year follow-up. We speculate that autonomic damage may contribute further to the development of ICBs in patients. Interestingly, a study found that autonomic dysfunction is associated with reduced amygdala grey matter volume , which iMany previous studies have indicated that drugs, particularly dopaminergic agonists, play a significant role in the development of ICBs in PD. However, limited research has focused on ICBs in early PD patients without medication use. A previous study proposed that PD itself may not increase the risk of developing ICBs, suggesting that the higher prevalence of ICBs in the PD population is driven by PD medications or other treatments such as deep brain stimulation. They suggested that certain clinical and demographic variables, such as younger age and family or personal history of similar behaviors, might simply moderate the risk of ICB development . HoweverThe novelty of our current study lies in the analysis of the association between biomarkers and ICBs in early PD patients. Unfortunately, we did not find a significant link between presynaptic dopaminergic dysfunction, as measured by DaTscan, and the occurrence of ICBs. However, a previous study based on pilot data from the PPMI suggested that the availability of dopamine receptors in the right striatum consistently decreased in PD patients with ICBs . The disImpulsivity and reward-based decision-making are mediated by a complex neural network involving interconnected mesocortical and mesolimbic circuits. One hypothesis is that a combination of pre-existing biological and genetic risk factors contributes to the relative preservation of dopamine receptor functions. An alternative hypothesis is that the relative preservation of dopamine receptors may lead to impaired inhibition of impulsivity, potentially contributing to the development of ICBs in PD patients. However, in our study conducted in early PD patients, we did not find evidence supporting these hypotheses. Further exploration of these relationships in advanced-stage PD patients is warranted.Although no significant association was found between ICBs and CSF biomarkers, such as NfL or urate, at baseline and year 1, our multifactorial analysis suggested that levels of p-tau in CSF may serve as an independent risk factor for the development of ICBs. This finding is novel and has not been proposed before. However, it’s important to note that the CSF data in our study were limited to the first year, and further confirmation of this association in patients with longer disease duration is necessary. Given the role of p-tau as a biomarker of neurodegeneration, it will be of great interest to investigate in future analyses whether CSF p-tau values increase at higher rates in individuals with ICBs. This could provide insights into the potential relationship between ICBs and the progression of neurodegenerative processes. Further studies with longer-term follow-up and more comprehensive CSF biomarker assessments are warranted to explore this potential link.5.Despite the comprehensive exploration of factors associated with ICBs in early PD, there are several limitations to acknowledge in our study. Firstly, the assessment of ICBs relied on a short version of the QUIP, which primarily screened for the presence of ICBs but did not provide a detailed evaluation of the severity of symptoms. This limited our ability to capture the full spectrum of ICB-related symptoms and their impact on patients. Additionally, we acknowledge that there are pending longitudinal data analyses for CSF and imaging data beyond the initial years of follow-up. The analysis of CSF data from years 2 to 5 and imaging data from years 3 and 5 on this cohort is still underway. These data could provide valuable insights into the long-term associations between these factors and the development of ICBs in early PD. These limitations highlight the need for further studies that employ more comprehensive and detailed assessment methods for ICBs and include longer-term follow-up to better understand the complexity of ICBs in PD.6.de novo unmedicated PD patients, provides valuable insights into the clinical and biological factors associated with ICBs in PD. We observed that the prevalence of ICBs increases over time in PD patients, while it decreases over time in the healthy control group. Our findings support previous research indicating that ICBs are associated with comorbid conditions such as depression and anxiety, as well as autonomic dysfunction, EDS, and the use of dopaminergic medications, particularly dopamine agonists. Moreover, our study identified several predictors of the incident development of ICBs in early PD. These predictors include anxiety, RBD, and elevated levels of p-tau in CSF. These findings suggest that these factors may play a role in the pathogenesis of ICBs in PD and could potentially be used as indicators for the development of preventive strategies or targeted interventions. Overall, our study contributes to the understanding of ICBs in PD and highlights the importance of considering both clinical and biological factors in assessing the risk and progression of ICBs in early PD patients. Further research is needed to validate these findings and to explore potential mechanisms underlying the observed associations.In conclusion, our study, which included the largest longitudinal case–control cohort of The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The studies involving humans were approved by Ethics Committee of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.XZ: Conceptualization, Data curation, Formal analysis, Visualization, Writing – original draft. JG: Supervision, Validation, Writing – review & editing. NW: Supervision, Validation, Resources, Writing – review & editing. YW: Supervision, Validation, Resources, Writing – review & editing. LS: Supervision, Validation, Resources, Writing – review & editing. ZL: Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing. YZ: Conceptualization, Funding acquisition, Methodology, Resources, Visualization, Writing – review & editing.