RMR was measured using QUARK RMR (reference device) and Fitmate GS (COSMED) in a random order for 30 min, each on fasted participants. In total, sixty-eight adults participated . Pearson correlation showed that RMR (r 0·86) and VO2 (r 0·86) were highly correlated between the two devices (P < 0·05). Intraclass correlation coefficients (ICC) showed good relative agreements regarding RMR (ICC = 0·84) and VO2 (ICC = 0·84) (P < 0·05). RMR measured by QUARK RMR was significantly higher (649 (sd 753) kJ/d) than Fitmate GS. Equations significantly overpredicted RMR. Accurate RMR (i.e. within ±10 % of the RMR measured by QUARK RMR) was found among 38 % of the participants for Fitmate GS and among 46–68 % depending on the equations. Bland–Altman analysis showed a low absolute agreement with QUARK RMR at an individual level for both Fitmate GS (limits of agreement (LOA): −828 to +2125 kJ/d) and equations (LOA ranged from −1979 to +1879 kJ/d). In conclusion, both Fitmate GS and predictive equations had low absolute agreements with QUARK RMR at an individual level. Therefore, these limitations should be considered when determining RMR using Fitmate GS or equations.Objective measurement of RMR may be important for optimal nutritional care but is hindered by the price and practicality of the metabolic monitoring device. This study compared two metabolic monitoring devices for measuring RMR and VO Predictive equations are widely used in clinical practice to estimate the RMR of individuals. These equations account for factors such as age, sex, height, weight and body composition; however, they do not account for other factors such as physical activity and health status that are known to affect the RMR,4. Therefore, these equations can significantly overestimate or underestimate the RMR,5. Accurate and objective measurement of the RMR is important for optimal nutritional care and improvement of health outcomes such as preventing unintentional weight loss or gaining weight, fewer complications and shorter length of hospital stay–8. Therefore, RMR should likely be measured objectively rather than predicted to determine the energy needs of individuals.RMR represents the amount of energy needed to sustain physiological function at rest. Fitmate GS has also been validated against the ‘gold standard’ in hospitalised patients, but not in healthy adults. Although Fitmate GS has been validated in healthy adults against Douglas bag, which has been considered by some researchers as the ‘gold standard’ against which a new device is evaluated, yet formal validation of the Douglas bag has not been carried out. Therefore, it is of interest to compare the RMR measurement among healthy adults between Fitmate GS with the previously validated QUARK RMR. In addition, both metabolic monitoring devices have not been investigated yet in the same individuals.Metabolic monitoring devices such as QUARK RMR (COSMED) are however relatively expensive, less portable and complicated to calibrate and use, making routine RMR measurement difficult and impractical. A new portable device, Fitmate GS (COSMED), is easier to calibrate, is portable, requires less space and less intensive training for operators and has lower operational costs. QUARK RMR has been validated against the ‘gold standard’ DELTATRAC (no longer in production) in healthy adults2 in healthy adults and (2) to compare the measured RMR with the RMR calculated from predictive equations.The aims of this study were (1) to compare QUARK RMR and Fitmate GS with canopy hood for measuring RMR and VOThis cross-sectional study included sixty-eight healthy adults recruited based on email invitations sent to the staff and students and by the word-of-mouth method. The inclusion criterion was an age of 18 years and over. Exclusion criteria encompassed pregnancy, lactation or suffering any of the following diseases: metabolic diseases (insulin-dependent), cancer, chronic obstructive pulmonary disease, rheumatoid arthritis, liver disease and cardiac failure with a pacemaker. For interested participants, the researchers provided a detailed information letter and consent form. Following this, the researchers checked the inclusion and exclusion criteria by telephone or in-person. The protocol was explained prior to the experiment.This study was conducted according to the guidelines laid down in the Declaration of Helsinki and was approved by the Melbourne Health Human Research Ethics Committee, Melbourne, Victoria, Australia (HREC/16/MH/346). All participants gave written informed consent.sd 1410) kJ/d using the QUARK RMR and 6866 (sd 1251) kJ/d using the DELTATRAC II system (Sensormedics). Based on the literature and our hypothesised mean difference, a sample size of thirty-one participants would be required to detect a mean difference of 628 kJ/d of RMR with an sd of 1255 kJ/d, a statistical power of 0·80 and an α level of 0·05.The mean RMR in healthy adults was previously reported to be 6987 (. Compliance to these instructions was verified on the day of the measurement by asking the participants if they followed the instructions and tests were rescheduled if non-compliant (n 2). Participants completed a short questionnaire assessing sex, age, medical history, number of medications used and physical activity. The International Physical Activity Questionnaire was used to assess the participants’ physical activity status over the past 7 d before the test. Physical activity level was categorised into high, moderate and low according to the scoring protocol which takes intensity, frequency and duration into account. Body weight was measured to the nearest 0·1 kg, and height was measured to the nearest 0·1 cm using a weighing scale and stadiometer, respectively. BMI was calculated by weight in kg divided by height in square meters. Direct-segmental multi-frequency bioelectrical impedance analysis  was used to measure body composition including skeletal muscle mass (expressed in kg), fat-free mass  and fat mass (expressed in %). RMR (in kJ/d) was measured using two metabolic monitoring devices: the QUARK RMR and Fitmate GS systems in a pre-set random order to avoid confounding due to order effects. Randomisation was performed using the allocation ratio of 1:1. The research team prepared an envelope which included sixty-eight cards (thirty-four printed ‘QUARK RMR’ and thirty-four printed ‘Fitmate GS’), to randomise the order of testing the devices. Participants were asked to pick a card from the envelope randomly.Before the measurement, participants were instructed to refrain from moderate to vigorous physical activity for 24 h, to be fasted overnight for at least 7 h and abstain from nicotine products for at least 2·5 h,17, while participants were in a supine position and instructed to limit movement, talking and to avoid sleeping. Participants were urged to indicate if any discomfort was experienced during the RMR measurement by raising their hand. After the first RMR measurement, participants were given a standardised break in which they were instructed to take a walk over a standardised trajectory at their usual pace for 10 min to interrupt the steady state achieved in the first RMR measurement and to align pre-test conditions (i.e. no prior resting period),19 for the measurements with the second device. The first 5 min of the data from both the measurements was discarded because the participants had to adapt their breathing while wearing the canopy hood,20. Data of RMR and VO2 between 5 and 30 min were averaged and used in the analysis. All participants were measured by the same researcher (S. S. Y. Y.).The metabolic monitoring devices were calibrated according to the manufacturers’ guidelines before each measurement. After completing the calibration procedure, the canopy hood was placed over the participants’ head. Each RMR measurement was conducted for 30 min2 readings during the measurement and printing the report. A protocolled methanol burning test,22 performed prior to this study by the manufacturer revealed a RQ (the ratio between the produced carbon dioxide and the oxygen consumed) of 0·68 which was within the acceptable range of 0·64–0·69,23. The QUARK RMR has been validated against the ‘gold standard’ DELTATRAC in healthy adults and was considered as the reference device in this study.The QUARK RMR (COSMED) is a metabolic monitoring device operated with an external power supply only and should be connected to a computer, monitor and printer for displaying the RMR and VO2) and carbon dioxide (VCO2) sensors, and therefore it directly measures the actual RQ. Steady state was achieved for QUARK RMR when the CV in VO2 and VCO2 were both <10 % during the 30-min measurement (discarding the first 5 min).On each measurement day, 5 min warm-up time of the system was required according to the manufacturer’s instructions before the calibration. Before the measurement, the researcher performed a flowmeter and gas calibration. For the flowmeter calibration, a calibration syringe was connected to a flowmeter and the syringe pistol was moved slowly in and out until the measured inspiratory and expiratory volumes were displayed on the screen indicating the end of the calibration. For gas calibration, the sampling line was disconnected from the flowmeter and connected to the front panel of the QUARK RMR. The output pressure of the oxygen cylinder was adjusted according to the ranges of output pressure, as shown on the screen. The QUARK RMR contains both oxygen  + 1·1 × (RQ × VO2)) × 1·44. The steady state was achieved for Fitmate GS when the CV in VO2 was <10 % during the 30-min measurement (discarding the first 5 min).The Fitmate GS (COSMED) is a portable desktop metabolic monitoring device. It is battery-operated, weighs 1·5 kg and has a built-in colour display and graphics printer. No warm-up time is required. Before each measurement, the researcher performed a flowmeter calibration. A calibration syringe was connected to the flowmeter, and the syringe pistol was moved slowly in and out until the results of the calibration were displayed on the screen. After that, an automatic O,25. Weight-based equations encompassed Harris & Benedict , Mifflin et al. , Muller et al. , Owen et al.,30 (sex and weight), Henry , Henry , Schofield , Schofield , WHO  and WHO . FFM-based equations encompassed Mifflin et al. (FFM), Muller et al.  and Owen et al.,30 .The RMR measured by the two metabolic monitoring devices were compared with predicted RMR calculated by commonly used predictive equationsContinuous variables with a normal distribution were presented as mean values and standard deviations, while those with a non-normal distribution were presented as medians and interquartile ranges (IQR). Categorical variables were presented as numbers and percentages.t tests were used to compare mean differences in the RMR and VO2 measured between the two metabolic monitoring devices. A low absolute agreement was defined as a difference in RMR > 628 kJ as this would result in a significant difference in the recommended energetic consumption for an individual. Pearson correlation was used to analyse the overall correlation at the group level in RMR and VO2 between the two metabolic monitoring devices. A correlation coefficient (r) between 0·3 and 0·5 was considered low, 0·5 and 0·7 moderate and 0·7 and 0·9 high. Relative agreement in RMR and VO2 between the two metabolic monitoring devices was addressed by intraclass correlation coefficients (ICC) which were calculated using a two-way mixed model of consistency and interpreted as poor (below 0·50), moderate (0·50–0·75), good (0·75–0·90) or excellent (0·90 or higher).The number (%) of participants with and without steady state was calculated. Participants with steady state were defined as achieving a steady state for both QUARK RMR and Fitmate GS, while participants without steady state were defined as not achieving a steady state for QUARK RMR and/or Fitmate GS. Analysis stratified by participants with and without steady state, next to a pooled analysis, was conducted. Paired sample 2 between the two metabolic monitoring devices and to visually display the individual dispersion patterns of RMR and VO2 assessed by the two metabolic monitoring devices. Proportional bias was determined by a significant deviation of the slope of the regression line of the Bland–Altman plots for RMR and VO2 between the two metabolic monitoring devices,40. Since proportional bias was found, differences in log-transformed RMR and VO2 and the 95 % limits of agreement (LOA) (mean difference ± 1·96 sd) were presented in Bland–Altman plots. For the interpretation of log-transformed values, back transformations of the mean difference and the LOA were computed to obtain the values relating to the ratios of measurements by the two metabolic monitoring devices.Bland–Altman analysis was used to assess the absolute agreement in RMR and VOv. RMR measured by QUARK RMR were computed and assessed by paired t tests. The percentage of participants that had an accurate, underpredicted or overpredicted RMR was calculated. RMR was considered as accurate when it was within ±10 %; underpredicted if <−10 % and overpredicted if >10 % of RMR measured by QUARK RMR,4. The root-mean-squared prediction error (RMSE) was used to indicate the predictive performance of the model in our data set. A lower RMSE indicates a better performance of the Fitmate GS or equations in predicting the data,42,43.The absolute (kJ) and relative (percentages) differences between RMR measured by Fitmate GS and predicted RMR . The line of best agreement and the regression-based 95 % LOA  were presented in Bland–Altman plots.Bland–Altman analysis was also used to assess the absolute agreement in RMR between predictive equations and the reference device (i.e. QUARK RMR). Proportional bias was determined by a significant deviation of the slope of the regression line of the Bland–Altman plots for RMR between QUARK RMR and predictive equations. Since proportional bias was detected for all equations, data of RMR were log-transformed. After log-transformation of data, proportional bias still existed and therefore a regression approach for non-uniform differences was conductedP values of <0·05 were considered statistically significant. Visualisation of results was performed using GraphPad Prism 5.01.The Statistical Package for the Social Sciences (SPSS) version 21.0 was used for the statistical analyses (SPSS Inc.), and Excel (Microsoft Office Excel 2016) was used to compute RMSE. 2 and VCO2 were, respectively, 8 % (IQR 6–12) and 10 % (IQR 8–14) for QUARK RMR, and the median CV in VO2 was 7 % (IQR 5–11) for Fitmate GS. A steady state was reached in thirty-four and fifty participants for QUARK RMR and Fitmate GS, respectively, and twenty-nine for both QUARK RMR and Fitmate GS within the same participant. 2 between the QUARK RMR and Fitmate GS. The mean difference in RMR between the QUARK RMR and Fitmate GS was 649 (sd 753) kJ/d (P < 0·05). There were 47 % of the participants who showed <628 kJ/d difference in RMR measured by the two metabolic monitoring devices. A high positive correlation in RMR (r 0·86) and VO2 (r 0·86) was found between QUARK RMR and Fitmate GS (P < 0·05). ICC values showed good agreements between the QUARK RMR and Fitmate GS in the measurements of RMR (ICC = 0·84) and VO2 (ICC = 0·84) (P < 0·05). When the analysis was stratified by participants with (n 29) and without a steady state (n 39), there were no significant differences between the two groups in RMR, VO2 and their mean differences between QUARK RMR and Fitmate GS (P > 0·05). Pearson correlation and ICC of RMR and VO2 between QUARK RMR and Fitmate GS were high  in both groups.The median CV in VO2 (P = 0·005) indicating that the difference between the two metabolic monitoring devices was dependent on the RMR and VO2 measurement values . 2. After back transformation, a mean ratio of RMR measured by QUARK RMR and Fitmate GS was 1·12 with 95 % LOA from 0·85 to 1·47 times, that is RMR measured by QUARK RMR differed from the RMR measured by Fitmate GS by between −15 % and +47 %. There were five (7·4 %) participants who had a difference in RMR and VO2 measured by QUARK RMR and Fitmate GS outside the 95 % LOA.Bland–Altman analysis showed significant proportional bias for RMR and VOv. RMR measured by QUARK RMR. Paired t tests showed that predictive equations significantly overpredicted RMR measured by QUARK RMR, except for the Mifflin et al., Muller et al., Owen et al. and Henry 2005a equations. There were 52–71 % of the participants who showed <628 kJ/d difference in RMR measured by QUARK RMR and predictive equations. On the group level, predicted RMR by Mifflin et al. was the closest to the RMR measured by QUARK RMR (mean difference: −126 (sd 808) kJ/d, P = 0·206). equation had the lowest RMSE of all equations investigated in this study.Bland–Altman plots for all predictive equations compared with QUARK RMR showed proportional bias, in which equations overestimated the low RMR values and underestimated the high RMR values . The 95 2 between the QUARK RMR and Fitmate GS. Accurate RMR was found among 38 % of the participants for the Fitmate GS and among 46–68 % of the participants depending on the predictive equations. Mean RMR predicted by equations were closer to the mean RMR measured by QUARK RMR compared with those measured using Fitmate GS. Predictive equations had a low absolute agreement with QUARK RMR at the individual level due to wide LOA.In a group of healthy adults, RMR measured by Fitmate GS was lower and RMR calculated by predictive equations were higher than those measured by QUARK RMR. A good relative agreement and a low absolute agreement were found in the measurements of RMR and VO2  and RMR  between the two metabolic monitoring devices. However, Bland–Altman analysis in the same study showed no significant difference in RMR and VO2 measured by the two metabolic monitoring devices and LOA ranged from −1067 kJ/d to +1113 kJ/d compared with a significant difference of 649 kJ/d and an upper LOA of 2125 kJ/d in the present study. The wide LOA indicates a higher difference at the individual level in RMR between the two metabolic monitoring devices in the present study. The discrepancy may be explained by the different metabolic monitoring device used and/or study protocols. The RMR measurements in the aforementioned study were measured by the QUARK CPET which has different technical specifications compared with QUARK RMR and consisted of two 10-min sessions for each metabolic monitoring device and the participants remained in supine position until all measurements were completed. Data for the first 5 min were not discarded, although this is a recommendation from the best practice guideline for performing indirect calorimetry. The longer duration of RMR measurements in this study may result in higher variation due to extraneous factors and change in the physical state. However, current guidelines do not have a specific recommendation regarding the duration of the RMR measurement.This is the first study examining the agreement in RMR measurement between the QUARK RMR and Fitmate GS within the same individuals. A previous study comparing RMR measurements in the same individuals between the QUARK CPET and Fitmate using canopy hood among thirty healthy adults aged between 18 and 45 years found a high positive correlation and excellent relative agreement in VO and the ‘gold standard’ device DELTATRAC II among thirty-seven outpatients and hospitalised patients aged between 18 and 78 years, respectively. In both studies, expired air was not collected by canopy hood and the type of Fitmate used was not specified. There were no significant differences for RMR or VO2 between the two metabolic monitoring devices. LOA was between −636 kJ/d and +686 kJ/d against Douglas bag and −1402 kJ/d and +1686 kJ/d against DELTATRAC II. The reasons for different results may be specific to each study design, measurement protocol, gas collection device and study population. For example, RMR was measured simultaneously using the Fitmate and Douglas bag during two 10-min test sessions. This design may minimise the variation due to extraneous factors and change in the physical state. In the other study, RMR was measured by Fitmate with a mask for 15 min and DELTATRAC II with canopy hood for 20 min in patients. However, it has been reported that the mask method had a 7 % higher in RMR compared with the canopy hood method among healthy individuals.The Fitmate has also been validated against the Douglas bag system among sixty healthy adults aged between 19 and 65 years. There is no universal definition for steady state as it varies by measurement time, the CV and combination of gas-exchange variables (VO2 and VCO2). In the present study, 42·6 % of the participants reached a steady state for both QUARK RMR and Fitmate GS. Comparing the percentage of participants reaching a steady state with previous studies using either QUARK RMR or Fitmate GS is not possible because the criteria for the steady state were not defined and the percentage of participants who reached the steady state was not reported–11,44. Studies using a canopy hood but different metabolic monitoring devices reported that 93–95 % of healthy adults reached a steady state over five consecutive minutes within the 30 min,48. However, when stringent criteria of steady state were used (i.e. over ten consecutive minutes), only 47 % reached steady state and it may reflect increased participants’ anxiety over time. The percentage of participants who reached steady state in our study is comparable to previous studies which used different metabolic monitoring devices, given that our steady-state criteria are more stringent, in which variations in the VO2 and VCO2 should be <10 % over an average of 25 min instead of a minimum of 4 min as accepted by the best practice guideline.In the present study, all RMR measurements were included in the analysis because the conclusion of the findings remains unchanged when we stratified the data by the participants with and without a steady state. This is in line with a previous study in healthy adults which suggested that participants who do not achieve steady state should not be excluded from data analysis, recent studies among healthy young adults showed that a resting period before the RMR measurement could be omitted. In previous studies, during the 30-min RMR measurement, a steady state was achieved after 5 min and there was no difference in RMR between each of the 5-min segment after the first 5 min,19. Therefore, in this study, a rest period prior to both the RMR measurements was not imposed in order to minimise the total duration, to create a comfortable testing environment and to mimic the practicality in clinical practice.To the best of our knowledge, there is currently no standardised protocol for measuring RMR using indirect calorimetry. For example, although the best practice guideline recommends at least 20-min rest before the RMR measurement. Although QUARK RMR and Fitmate GS have been validated against the ‘gold standard’ DELTATRAC in healthy adults and hospitalised patients, respectively, our findings among healthy adults showed a good agreement in RMR measurement between the QUARK RMR and Fitmate GS at the group level but a low agreement of RMR compared with QUARK RMR at the individual level. Our study also showed that RMR predicted by equations had smaller mean differences with RMR measured by QUARK RMR compared with the mean differences between RMR measured by Fitmate GS and QUARK RMR. However, it is important to note that a small mean difference between group means is not necessarily a measure of accuracy, as a high positive difference between predicted and measured RMR might counterbalance a high negative difference between predicted and measured RMR.Metabolic monitoring devices such as QUARK RMR are known to be costly, less portable, requiring trained operators and complicated to calibrate. Because of these disadvantages, routine RMR measurement is difficult and impractical in clinical practice. Therefore, an inexpensive, easy-to-use, portable and accurate metabolic monitoring device for measuring RMR in the clinical setting is desirablea priori set value of 628 kJ/d). Despite the findings from other studies that have reported high levels of accuracy of Fitmate GS in healthy adults,44, our study shows that RMR measured using Fitmate GS should be interpreted with cautions since Fitmate GS underestimated RMR compared with QUARK RMR at a group level. One possible explanation for the lack of agreement between QUARK RMR and Fitmate GS could be because Fitmate GS assumes a fixed RQ of 0·85 and measures oxygen only. In the present study, a lower VO2 as measured by Fitmate GS compared with QUARK RMR could be the reason for underestimation of the RMR measured by Fitmate GS. Although using a metabolic monitoring device with high precision is ideal, it is also important to balance its feasibility and cost when implementing in clinical practice. Clinical judgement should be taken when determining the energy needs of an individual, and frequent monitoring of the energetic recommendation should be adopted. If both QUARK RMR and Fitmate GS are available in a setting, clinicians should use the same metabolic monitoring device for follow-up measurements for the same individual. Next to a standardised protocol in measuring RMR, the metabolic monitoring device used should preferably be the same within one cohort or when comparing between cohorts.Our findings suggested that objective measurement of RMR should be employed if possible as predictive equations cannot account for individual variances  in one, relatively large group of healthy adults. However, this study has some limitations. Participants were relatively healthy adults, and therefore whether these findings can be extended to adults with diseases is unknown. There was a good relative agreement in RMR and VOThe findings of the present study demonstrate a good relative agreement and a low absolute agreement between the QUARK RMR and Fitmate GS for measurement of RMR in healthy adults. Predictive equations appear to be superior to Fitmate GS on the group level. However, there was a low absolute agreement with QUARK RMR, and therefore, the objective measurement of RMR should be encouraged. As both Fitmate GS and predictive equations had low absolute agreements with QUARK RMR at an individual level, these limitations should be considered and clinical judgement should be taken when determining the energy needs of an individual.


LOXHD1 gene have been shown to cause DFNB77, a type of ARNSHL. To date, there are limited reports about the association between LOXHD1 gene and ARNSHL. In this study, we reported six patients from four Chinese families suffering from severe-to-profound nonsyndromic hearing loss. We performed targeted next generation sequencing in the six affected members and identified five novel pathogenic mutations in LOXHD1 including c.277G>A (p.D93N), c.611-2A>T, c.1255+3A>G, c.2329C>T (p.Q777∗), and c.5888delG (p.G1963Afs∗136). These mutations were confirmed to be cosegregated with the hearing impairment in the families by Sanger sequencing and were inherited in an autosomal recessive pattern. All of the five mutations were absent in 200 control subjects. There were no symptoms of Fuchs corneal dystrophy in the probands and their blood-related relatives. We concluded that these five novel mutations could be involved in the underlying mechanism resulting in the hearing loss, and this discovery expands the genotypic spectrum of LOXHD1 mutations.Hearing loss is one of the most common sensory disorders in newborns and is mostly caused by genetic factors. Autosomal recessive nonsyndromic hearing loss (ARNSHL) is usually characterized as a severe-to-profound congenital sensorineural hearing loss and later can cause various degrees of defect in the language and intelligent development of newborns. The mutations in  Totally about 278 million people suffer from hearing impairments, and the incidence of hearing loss is 1 to 3 per 1,000 for newborns [Hearing loss is one of the most common sensory diseases, affecting the life quality of 466 million individuals in the world (http://hereditaryhearingloss.org).According to the symptoms, hereditary hearing loss can be divided into two categories, syndromic 30%) and nonsyndromic (70%) 0% and no. So far,LOXHD1) gene mapped on chromosome 18q12-21 encodes a protein that localizes along the plasma membrane of stereocilia in the hair cells [LOXHD1 gene have been shown to cause DFNB77, a type of ARNSHL. The protein encoded by LOXHD1 contains 2,211 amino acids and 15 polycystin-1/lipoxygenase/alpha-toxin (PLAT) domains which are believed to be involved in targeting its protein to the plasma membrane. It played an important role in maintaining normal hair cell function in the cochlea [Lipoxygenase homology domains 1  . Other sLOXHD1 which were predicted to be the pathogenic variants from four Chinese families suffering from ARNSHL.In this study, we identified five novel mutations in Four Chinese families with autosomal recessive sensorineural hearing loss were recruited in the Otologic Center, Shandong Provincial ENT Hospital Affiliated to Shandong University . All theAll participants received ophthalmological and auditory tests, including pure tone audiometry (PTA), distortion product otoacoustic emission, auditory brainstem response, acoustic immittance, and tinnitus examination. The guideline of American Speech-Language-Hearing Association was used to determine the degrees of hearing loss . For thePrior to the study, the informed consent forms were provided to and signed by all the family members. Our study was approved by the ethics committee of the Institutional Review Board of Shandong Provincial ENT Hospital Affiliated to Shandong University (XYK20140101).http://www.1000genomes.org) and HapMap database (combined data from Phases II and III). We referred to the American Medical Genetics and Genomics Guide to interpret data [In order to discover the pathogenic variants in the four Chinese families, a DNA extraction kit was used to extract genomic DNA from the peripheral blood . Targeted next generation sequencing was used to screen mutations from 127 genes  in LOXHD1 gene were identified pathogenic variants based on predictive analysis using PolyPhen2, SIFT, and Mutation Taster. Sanger sequencing was used in all the subjects to verify variants in LOXHD1. The c.2329C>T (p.Q777X) and c.5888delG (p.G1963Afs∗136) mutations were both found in family F098∗ and family F564∗. The c.611-2A>T mutation was verified in family SD1226∗, while c.277G>A (p.D93N) and c.1255+3A>G were verified in family SD1391∗. Sequencing results are shown in Figures Five novel mutations (family F098∗), and c.5888delG (p.G1963Afs∗136) were classified as pathogenic; in addition, the mutation of c.277G>A (p.D93N) was classified as likely pathogenic. Moreover, all the mutations were newly identified and never reported previously  is a frameshift mutation in PLAT 14 domain, resulting in a truncated protein of LOXHD1. In addition, the mutations of c.611-2A>T and c.1255+3A>G can cause defects in alternative gene splicing of PLAT 2 and PLAT 4 domain, respectively. LOXHD1 that cause DFNB77-type deafness, as well as novel mutations identified in this study. These results showed that LOXHD1 mutations are found throughout all PLAT domains.The mutation of c.2329C>T (p.Q777X) is a nonsense mutation, which leads to a stop codon in PLAT 6 domain. The variant c.277G>A (p.D93N) is also a missense mutation found in PLAT 1 domain. But the mutation of c.5888delG  mutagenesis screen [The LOXHD1 was a sensorineural hearing loss at mid-to-high frequencies with no vestibular symptoms [LOXHD1 were limited and these mutations are relatively rare in Chinese population.In general, hearing loss caused by symptoms –8. They LOXHD1 mutations, whose hearing loss started at age 40 and gradually aggravated till 67 years old [LOXHD1 suffered from progressive hearing loss. Member III-2 was assessed by PTA at age of 7 y 4 m, 9 y 8 m, and 10 y 5 m, while the proband III-3 was assessed via conditional orientation response audiometry at age of 1 y 11 m, 2 y 5 m, 3 y 10 m, and 4 y 10 m. They were both diagnosed with slowly aggravated hearing loss. Further follow-up is needed to monitor the progression of hearing loss for these two patients [Normally, ARNSHL is characterized as a congenital hearing loss. However, previous studies have shown that the onset age of LOXHD1-related hearing loss had a large span, ranging from newborn, prelingual, childhood to even adulthood. Eppsteiner et al. reported a patient with compound heterozygous ears old . The proears old . Two mempatients .LOXHD1 than the controls. They concluded that LOXHD1 mutations may be related to dominant late onset of FCD [FCD is characterized as bilateral corneal guttae, corneal edema, discomfort, and blurred vision caused by a reduced density of endothelial cells . The onst of FCD . Tang ett of FCD .LOXHD1 gene showed no corneal abnormalities. Other studies also reported no symptoms of FCD were observed in the probands and their blood-related relatives [LOXHD1-related hearing loss and FCD is still unclear, we suggest that ophthalmologic examinations should be performed in patients with ARNSHL when LOXHD1 is suspected to be the pathogenic gene.Recently, Stehouwer et al. investigated 72 FCD patients and discovered that 45.8% of them had hearing disability, which was much higher than the control group . Howeverelatives , 33. AltLOXHD1 gene in six members from four Chinese families with congenital nonprogressive sensorineural hearing loss. Both the targeted next generation and Sanger sequencing were used to identify and verify the pathogenic mutations. Genetic analysis revealed that the five novel mutations in LOXHD1 were involved in the underlying pathogenic mechanism of hearing loss in those families studied, and these results have expanded the spectrum of LOXHD1 mutations. Future studies are needed to determine the relationship between phenotype and genotype of LOXHD1 gene mutations.In summary, we identified five novel mutations in


Background: Previous studies have demonstrated spatial cognitive deficits in patients with bilateral vestibulopathy (BVP). However, BVP patients frequently present with a concomitant sensorineural hearing loss, which is a well-established risk factor of cognitive impairment and incident dementia. Nonetheless, previous research on spatial cognitive deficits in BVP patients have not taken hearing status into account.Objective: This study aims to compare spatial cognition of BVP patients with healthy controls, with analyses adjusting for hearing status.Methods: Spatial cognition was assessed in 64 BVP patients and 46 healthy controls (HC) by use of the Virtual Morris Water Task (VMWT). All statistical analyses were adjusted for hearing (dys)function, sex, age, education, and computer use.Results: Overall, patients with BVP performed worse on all outcome measures of the VMWT. However, these differences between BVP patients and healthy controls were not statistically significant. Nonetheless, a statistically significant link between sensorineural hearing loss and spatial cognition was observed. The worse the hearing, the longer subjects took to reach the hidden platform in the VMWT. Furthermore, the worse the hearing, the less time was spent by the subjects in the correct platform quadrant during the probe trial of the VMWT.Conclusion: In this study, no difference was found regarding spatial cognition between BVP patients and healthy controls. However, a statistically significant link was observed between sensorineural hearing loss and spatial cognition. A growing body of literature recognizes that the function of the vestibular system goes far beyond balance and gaze stability. Both animal and human research suggests that the vestibular system plays a critical role in cognition –4. AccorThe link between spatial cognition and the vestibular system is of clinical importance for several reasons. First, cognitive training might yield therapeutic opportunities for BVP. Conventional treatment for patients with BVP is limited to counseling and intensive daily vestibular physical therapy to improve gaze and postural stabilization . HoweverSecond, interest has been directed toward the link between cognitive impairment and the vestibular system because of the rising prevalence of dementia. As in BVP patients, impaired spatial cognition is among the most frequently observed cognitive deficits in patients with dementia. One of the hallmark symptoms of Alzheimer's disease is wandering behavior and loss of topographic memory . The vesFurthermore, several studies have found significantly poorer vestibular function in patients with dementia compared with their healthy peers –20.These observations have led to the hypothesis that vestibular loss might cause cognitive decline and thus may contribute to the development of dementia. Given the rising prevalence of dementia and the lack of curative treatment, the identification of potentially modifiable risk factors is crucial .In the previous literature, however, little attention has been paid to the hearing status of vestibular patients when drawing conclusions about the link between cognitive decline and the vestibular system. A systematic review pointed out that none of the studies investigating cognition in BVP patients have adjusted their analysis for the hearing status of the enrolled subjects . HoweverThe goal of this study is to compare spatial cognitive performance, assessed using the VMWT, of BVP patients with healthy controls. In contrast to previous studies, the analyses in this study were specifically designed to take the hearing loss of BVP patients into account.ClinicalTrials.gov (NCT03690817). The majority of the enrolled participants received general cognitive assessment at another scheduled appointment on a different day. Results have been published earlier  and informed consent was obtained in all study participants before the start of the study. The study was registered on  earlier .BVP patients were recruited from the Otorhinolaryngology, Head and Neck Surgery Department at Antwerp University Hospital, Belgium. Inclusion criteria for the BVP group were (1) BVP disease duration of more than 6 months and (2) definite diagnosis of BVP as defined by the diagnostic criteria of the Bárány Society :Horizontal angular vestibulo-ocular reflex (VOR) gain <0.6 measured by the video head impulse test (vHIT), and/orReduced caloric response  on each side <6°/s), and/orReduced horizontal angular VOR gain <0.1 upon sinusoidal stimulation on a rotatory chair.Control participants were recruited by means of the population registries at the local city councils in southern Antwerp (Belgium), by advertisements in the hospital, and by approaching friends, family, and colleagues. Only control subjects with no history of vertigo, scores <5 on the Dizziness Handicap Inventory, and normal hearing thresholds at 0.25–8 kHz, based on age and sex , were enrolled in the study.The following additional inclusion criteria were applied for both BVP patients and healthy controls: (1) age ≥18 years, (2) fluency in Dutch, (3) no history of neurological diseases , (4) absence of clinical signs indicating dementia or mild cognitive impairment, and (5) normal or appropriate corrected vision.Regarding the necessity of computer use in the VMWT, all participants were asked about their frequency of computer use (daily vs. 2–5 days/week vs. seldom/never). Education of all participants was categorized as primary school, lower secondary school, upper secondary school, and college/university.By enrollment in the study, all BVP patients received new neuro-otological testing on site. The evaluation of the lower and mid frequencies function of the lateral semi-circular canals was performed by electronystagmography with bithermal caloric tests and rotatory chair test . At our clinic, rotatory chair tests are performed using sinusoidal rotation (0.05 Hz) with a peak velocity of 60°/s . More deTo assess spatial learning and spatial memory retrieval, the VMWT was used. This task was designed by Derek Hamilton and was inspired by the original animal research tool, which is considered the gold standard for testing spatial cognition in rodents , 31. A 1Before testing, all participants were given the same written instructions. Afterwards, time to ask questions to the examiner was foreseen. In both groups, four phase trials were performed:The first part consisted of one block of four trials with a hidden platform. Participants were familiarized with the concept of the game and the use of the key arrows. By observing the participant, the examiner checked for good understanding of the task. When necessary, supplemental explanations were given.The test was started with 20 hidden platform trials. A virtual environment with different visual cues was used than in the exploration trial see . The hid- The latency, i.e., time to reach the platform.- The covered path length, i.e., total distance traveled, divided by the pool diameter.- The heading error, when the participant has traveled a distance >25% of the pool diameter from the start position; the angular deviation is computed between the straight trajectory to the center of the platform and the starting position see .Performance during these hidden platform trials represent a measure for spatial learning performance.Subsequently, the platform was removed from the pool, unbeknownst to the participants. In this one trial, we measured the percentage of time a participant spent in the platform quadrant. A higher percentage was considered to be related to a better spatial memory retrieval of the participant.The last part of the test represents a control task for motor condition. Participants had to perform eight visible trials in which the platform was visible and participants had to swim to the platform as soon as possible. Again, latency and path length were recorded for each trial.To correct cognitive outcome measures for the hearing status of the enrolled participants, a pure tone audiometry was performed. The unaided hearing thresholds were measured in a sound-isolated booth. For air conduction, hearing thresholds were determined at 125, 250, 500, 1,000, 2,000, 3,000, 4,000, 6,000, and 8,000 Hz using a two-channel Interacoustics AC-40 audiometer and insert earphones. Bone conduction thresholds were tested at 250, 500, 1,000, 2,000, 3,000, and 4,000 Hz. The high Fletcher index, which is the mean of air conduction hearing thresholds at 1, 2, and 4 kHz, was calculated for both ears. The hearing status of a participant was defined by the high Fletcher index of the better-hearing ear.Data were stored in OpenClinica LLC , a secured online database for electronic data registration and data management developed for clinical research. For statistical analyses, IBMS SPSS Statistics  and “R” was used .t-test and χ2 test, or Mann–Whitney test and Fisher's exact test. Analogous to previous work, the 20 hidden platform trials were divided into three blocks: block 1 with trials 1–4, block 2 with trials 5–12, and block 3 with trials 13–20. First, for each performance variable of the hidden trial , a linear mixed model was fitted. A random effect of individual was added to account for the non-independence between observations from the same individual. Fixed effects included group , time , and their interaction. The latter interaction term evaluates whether there is a difference in learning between BVP patients and healthy controls during the VMWT. In other words, a statistically significant interaction term points out that during all 20 hidden trials, one group progressively found the platform faster compared with the other group, indicating a better learning curve in this group throughout the test.Depending on distribution, demographic data were analyzed with either In the absence of a significant interaction, linear mixed models were fitted for all performance variables of the hidden trials, with the main factors group  and time , without interaction term and hearing status as indicated by the high Fletcher index. Using these models, we evaluated whether there was a statistically significant different performance between the two participant's groups, BVP and healthy controls, across all trial blocks. Moreover, using this model, we assessed whether there was a statistically significant main effect of the hearing status on VMWT performance. In all of these models, the following covariates were added: age, sex, computer use, and education.To compare the spatial memory retrieval during the probe trial, a multiple linear regression model was fitted with the main factors group  and hearing status (high Fletcher index of the better-hearing ear). Again, age, sex, computer use, and education were entered as covariates.Finally, mean path lengths and latencies during the 10 visible trials were computed and used as dependent variables in a similar multiple linear regression model.p < 0.05). Hearing loss was more frequent in BVP patients . To diagnose BVP, the Bárány Society criteria needed to be fulfilled . As the Fletcher index increased by 1 dB, the latency was 0.11 second longer. There was no significant effect of hearing loss on path length or heading error.Second, as shown in p-value in multiple linear regression model of groups = 0.9).During the probe trial, BVP patients searched 38% (±23.3) of their time in the correct quadrant, whereas healthy controls spent 52.1% (±22.7) in the correct quadrant. However, this difference was not statistically significant between the two groups . This indicates that the worse the hearing, the poorer the memory retrieval. The results of the probe trial are demonstrated in Nonetheless, the analysis revealed a significant main effect of hearing loss on relative amount of time spent in the correct quadrant function. Although no significant group difference was observed, it seemed that, on the other hand, hearing loss was found to be statistically significantly associated with worse spatial cognition. The worse the hearing of BVP patients, the worse the spatial learning indicated by longer latencies in the hidden trial of the VMWT. Likewise, in the probe trial, hearing loss resulted in less time spent in the platform quadrant, which suggests worse spatial memory retrieval.Previous studies have not dealt with the hearing status of the enrolled BVP patients when drawing conclusions about the relationship between vestibular loss and cognitive decline . Given tNonetheless, for all future studies investigating cognition in BVP patients, our results implicate that it is obligatory to take the hearing status of BVP patients into account.In accordance with the present results, previous studies have demonstrated a link between spatial cognition and hearing loss. A recent meta-analysis showed a significant impairment of visuospatial abilities in patients with hearing loss across cross-sectional studies, using a wide variety of spatial cognitive tasks .Two recent animal studies investigated spatial cognition using the Morris Water Maze , 37. MicThe hippocampus is the area of the brain that has long been implicated in spatial memory. Animal and human studies have shown altered functioning and even atrophy of the hippocampus in subjects with vestibular loss [for review see ]. IntereIn previous literature, the VMWT seemed to be one of the most used tools to assess spatial cognition in vestibular patients . In patiFurthermore, the purely stationary set-up of the VMWT might underestimate the real-life spatial cognitive deficits of BVP patients as a result of loss of vestibular input. Previous research has established that, while navigating, an “inner neural map” is created, based on peripheral vestibular input. This neural representation of the external environment is computed in the hippocampus and entorhinal cortex and consists of several cooperative cell types: angular head velocity cells; head direction cells; place and grid cells . Rodent Moreover, attentional deficits are demonstrated in BVP patients , 6, 43. To sum up, the VMWT is a widely used method to assess spatial cognition in humans . SeveralBoth vestibular and hearing dysfunction are prevalent in the elderly , 44, 45.The subjects in our HC group were not perfectly matched to BVP patients regarding age, education, and computer experience. As HC were on average younger, more educated, and more computer experienced, VMWT performance could be relatively overestimated in the HC group. Regarding the observed negative effect of hearing loss on spatial cognition (longer latencies and less time spent in the correct quadrant), it is important to bear in mind that the majority of patients with hearing loss were in the BVP group. Therefore, it is not excluded that vestibular loss plays an additional role in spatial cognition, which could not be observed in this study protocol using healthy controls with normal hearing. Second, there was a correlation with hearing loss and age. Although all models were corrected for age, it is not excluded that age might play an important role in the observed link between spatial cognition and hearing loss.The present study assesses spatial cognitive performance in one of the largest BVP cohorts so far. The study was especially designed to determine the relative importance of hearing loss in spatial cognition of BVP patients, as this has been frequently overlooked. We found worse spatial cognitive performance on all outcome measures of BVP patients. However, these differences were not statistically significant between the BVP patients and healthy controls, when corrected for age, gender, education, level of computer use, and hearing loss. Interestingly, only hearing loss was found to be statistically significantly associated with worse spatial cognition. These findings highlight the need to correct for hearing loss in future studies investigating cognition in BVP patients. As the control group did not include subjects with severe hearing loss, an additional effect of vestibular loss on spatial cognitive performance cannot be excluded.These data have partially been presented on the 30th Bárány conference, Uppsala, June 2018.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 local ethics committee of the Antwerp University Hospital/University of Antwerp (protocol number 16/42/426). The patients/participants provided their written informed consent to participate in this study.BD: data collection, statistical analyses, study concept, and writing manuscript. GM, RB, and PV: study concept and supervision. JM: data collection. EF: study concept and statistical analyses. VV: study concept, writing manuscript, and supervision. 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.


Chronically elevated angiotensin II is a widely-established contributor to hypertension and heart failure via its action on the kidneys and vasculature. It also augments the activity of peripheral sympathetic nerves through activation of presynaptic angiotensin II receptors, thus contributing to sympathetic over-activity. Although some cells can synthesise angiotensin II locally, it is not known if this machinery is present in neurons closely coupled to the heart. Using a combination of RNA sequencing and quantitative real-time polymerase chain reaction, we demonstrate evidence for a renin-angiotensin synthesis pathway within human and rat sympathetic stellate ganglia, where significant alterations were observed in the spontaneously hypertensive rat stellate ganglia compared with Wistar stellates. We also used Förster Resonance Energy Transfer to demonstrate that administration of angiotensin II and angiotensin 1–7 peptides significantly elevate cyclic guanosine monophosphate in the rat stellate ganglia. Whether the release of angiotensin peptides from the sympathetic stellate ganglia alters neurotransmission and/or exacerbates cardiac dysfunction in states associated with sympathetic over activity remains to be established. •The stellate ganglia may act as a novel source for local angiotensin signaling.•Angiotensin peptides and receptors were identified in human and rat stellates.•Elevations in neuronal cGMP occur in response to angiotensin peptides.•RNA transcript expression was altered in young spontaneously hypertensive rats.•Angiotensin signaling at this site may be linked to dysautonomia in hypertension. Several1R [2+]i , however1R [2+]i .2+ via inhibition of the L-type Ca2+ channel and reuptake into sarcoplasmic reticulum stores [Mas1) was present within stellate ganglia of human and rat alongside the expression of previously reported classical AngII receptors . Considering the effects of AngII and Ang1–7 on cGMP generation, there exists a conceivable role for these peptides in presynaptic sympathetic nerve modulation [In our study, human sympathetic stellate ganglia expressed key genes and proteins required for AngII synthesis. We confirmed the presence of AngII in human stellate ganglia supporting immunocytological evidence from Bohlender et al., who recently demonstrated angiotensinergic innervation of the human right atrium, although the source of the neuronal fibers was not clear . We alsom stores . Of intedulation ,80. Givedulation ,11,81 thdulation ,61,82,834.1In this study, we carried out a hypothesis neutral, non-biased approach to sequencing the transcriptome of sympathetic stellate neurons of four-week-old preSHR and age-matched normotensive Wistar rats. There are several limitations to this approach. First, the stellate ganglion comprises a heterogeneous population of neuronal and supporting cells including fibroblasts and astrocytes, where we noted the presence of vimentin and glial fibrillary acidic protein (GFAP) respectively, however; a high number of identified transcripts were of neuronal phenotype. Secondly, to assess the pathways involved in AngII and Ang1-7 synthesis, the presence of the classical ACE-ACE2 pathway was explored. Recent literature has also highlighted the importance of alternative enzymatic pathways that may be involved in AngII synthesis and breakdown, including neprilysin, endopeptidases and other metalloproteases  whose tr5Our data here demonstrate that sympathetic stellate ganglia may act as a novel source for local AngII and Ang1-7 production to target pre- and post-synaptic cardiac excitability. Here, we describe the presence of genes and proteins involved in the synthesis of AngII and its metabolite Ang1-7, in addition to their receptor partners on sympathetic stellate ganglia from human and rat. We also demonstrate that alterations in RAS transcripts are evident in young prehypertensive SHR prior to the onset of hypertension, which may result in altered control of cardiac excitability. As such, these results may have implications for the pathogenesis and progression of dysautonomia and associated CVDs.None.


We found a significant association (R2D = 0.17) between the number of detected otoacoustic emissions and apathy symptoms. The presbycusis with cochlear dysfunction group had worse performance than controls in global cognition, language and executive functions, and severe apathy symptoms than the other groups. The neuropsychiatric symptoms and language deficits were the main determinants of functional impairment in both groups of subjects with presbycusis. Atrophy of insula, amygdala, and other temporal areas were related with functional impairment, apathy, and language deficits in the presbycusis with cochlear dysfunction group. We conclude that (i) the neuropsychiatric symptoms had a major effect on functional loss in subjects with presbycusis, (ii) cochlear dysfunction is relevant for the association between hearing loss and behavioral impairment, and (iii) atrophy of the insula and amygdala among other temporal areas are related with hearing loss and behavioral impairment.Hearing loss is an important risk factor for dementia. However, the mechanisms that relate these disorders are still unknown. As a proxy of this relationship, we studied the structural brain changes associated with functional impairment in activities of daily living in subjects with age related hearing loss, or presbycusis. One hundred eleven independent, non-demented subjects older than 65 years recruited in the ANDES cohort were evaluated using a combined approach including (i) audiological tests: hearing thresholds and cochlear function measured by pure tone averages and the distortion product otoacoustic emissions respectively; (ii) behavioral variables: cognitive, neuropsychiatric, and functional impairment in activities of daily living measured by validated questionnaires; and (iii) structural brain imaging—assessed by magnetic resonance imaging at 3 Tesla. The mean age of the recruited subjects  was 73.95 ± 5.47 years (mean ± SD) with an average educational level of 9.44 ± 4.2 years of schooling. According to the audiometric hearing thresholds and presence of otoacoustic emissions, we studied three groups: controls with normal hearing ( Age-related chronic disorders, including sensory, neurological, and mental syndromes are among the major contributors for disability . DementiAnother common cause of disability in elders is age-related hearing loss, or presbycusis. It is the third most prevalent condition in the elderly population, reaching 80% in those older than 85 years . HearingIn this present study, we hypothesized that the atrophy of the temporal lobe, among other brain areas related with hearing loss, will be associated not solely with neuropsychiatric symptoms and cognitive impairment, but also with functional loss in subjects with presbycusis. Our main objective was to study structural brain changes associated with functional impairment, neuropsychiatric and cognitive variables in independent non-demented subjects with presbycusis. In addition, in line with our previous work , we evalA total of 199 adults aged ≥65 years were screened in the Auditory and Dementia study (ANDES) between 2016 and 2018 from a primary health center located in the Recoleta district in Santiago, Chile. All subjects gave written informed consent in accordance with the Declaration of Helsinki. Only 111 subjects were included in this study according to the following criteria. Inclusion criteria were to (i) be older than 65 years at the beginning of the study, (ii) possess a Mini-Mental State Examination (MMSE) score of ≥24, and (iii) demonstrate preserved functionality measured by a Pfeffer’s Functional Activities Questionnaire score of <25 . Exclusi®) in a soundproof room placed in the Otolaryngology Department of the Clinical Hospital of the University of Chile. Subjects were instructed to respond when they perceived a tone at a specific frequency and intensity. The lowest-intensity sound they could hear was registered in decibels for each frequency, including 0.125, 0.25, 0.5, 1, 2, 3, 4, 6, and 8 kHz for each ear separately. Pure tone average (PTA) hearing thresholds were calculated using 0.5, 1, 2, and 4 kHz frequencies per ear, and the PTA in the better-hearing ear was used for subsequent analyses. Subjects were classified according to the PTA of the better hearing ear into normal hearing (≤20 dB) and presbycusis (>20 dB).Hearing thresholds were measured by an experienced audiologist with a clinical audiometer  fitted to the external ear canal. The acoustic stimuli were two pure tones of different frequencies (f1 and f2) that elicited a DPOAE at 2f1–f2. The difference between the intensity of f1 and f2 tones was 10 dB (65 and 55 dB SPL), while the frequency ratio of f2/f1 was fixed at 1.22. We presented eight pairs of primary tones (f1 and f2) in each ear, eliciting eight different 2f1–f2 frequencies: 707, 891, 1,122, 1,414, 1,781, 2,244, 2,828, and 3,563 Hz. The testing time for DPOAE measurements was 180 s for each ear. The detection of the DPOAEs was based on a signal to noise amplitude criterion: a DPOAE must be at least 6 dB above the average level of the noise floor sampled at several frequencies surrounding the emission frequency.Distortion product otoacoustic emissions (DPOAE) were used as a measure of the loss of outer hair cells in both ears. DPOAE measurements were performed in the same soundproof room as audiogram evaluations using a sensitive microphone . For the subsequent analyses we used the sum of DPOAE obtained in both ears . Using a bimodal distribution of the presence of DPOAE in our data (see This variable was measured by the informant using the Technology-Activities of Daily Living Questionnaire (T-ADLQ) . The T-AA trained clinical neuropsychologist administered and scored all neuropsychological tests that were done blinded to the audiological status of the subjects. The cognitive domains were assessed using the following measures: (i) global cognitive functioning, the Chilean version of the MMSE ; (ii) epNPS were measured using different questionnaires: for global measurement we used the Chilean version of the Neuropsychiatric Inventory Questionnaire (NPI-Q) . The NPIImaging data were acquired using a MAGNETOM Skyra 3 Tesla whole body MRI Scanner  using a T1 MPRAGE sequence. Contiguous images across the entire brain were acquired with the following parameters: time echo (TE) = 232 ms, time repetition (TR) = 2,300 ms, flip angle = 8_, 26 slices, matrix = 256 _ 256, voxel size = 0.94 _ 0.94 _ 0.9 mm3. We also registered T2 weighted turbo spin echo (TSE)  and fluid attenuated inversion recovery (FLAIR)  to inspect structural abnormalities. The acquisition duration was 30 min with a total of 440 images for each subject.The morphometric analysis was carried out using the software FreeSurfer version 6 running under Centos 6.0 . A singlAfter the whole-brain analysis, we selected regions of interest that have been consistently implicated in previous neuroimaging studies relating audition, cognition, and dementia . To defiConsidering that our study explores audition, cognition, NPS and functional impairment, we looked for the main cortical and subcortical brain areas responsible for the following functions in the literature: (i) temporal cortex  was atrophied in a longitudinal hearing impairment study ; (ii) ciR2D . Cognitive, neuropsychiatric, auditory, and brain volume variables were compared between the three groups  using ANCOVA with gender, age, and years of education as covariates using Tukey post hoc tests for specific comparisons. Partial correlations were run between measures of functional impairment and brain volume values. A p-value < 0.05 was considered significant. All results are reported without multiple comparison corrections between tests. However, in order to limit false positive results, we included a multiple comparison correction between tests. We also corrected by the total number of statistical tests used using a Holm-Bonferroni procedure  version 20 for Windows  and R project version 3.3.3 was used for statistical analysis. The associations of hearing function (PTA of the better hearing ear and DPOAE) with neuropsychiatric symptoms, cognitive performance, and functionality in ADL (T-ADLQ) were examined using partial correlations and Poisson regressions. We first adjusted a Poisson regression to then evaluate the same model against a quasi-Poisson regression. If no substantial change was observed in deviances, the Poisson model was kept. For Poisson regression models, we presented pseudo R2D . We thenrocedure . This con = 111, 69 female) was 73.95 ± 5.47 years (mean ± SD) with an average educational level of 9.44 ± 4.2 years of schooling. According to the audiometric hearing thresholds, 40 normal-hearing subjects and 71 with presbycusis participated. The average number of detected DPOAE as sum of both ears was 6.95 ± 5.56, which had a non-normal, bimodal distribution . Based on PTA and DPOAEs results, the sample was stratified into three groups: (i) controls (36 subjects), (ii) presbycusis with more preserved cochlear function , and (iii) presbycusis with cochlear dysfunction . Four subjects from the control group who did not fit this classification criteria were excluded from the study. A summary of demographic data, including age, sex, education, hearing level, and cardiovascular risk factors is presented in The mean age of the recruited subjects , and both were correlated with age . When age, gender, and education were included, PTA and DPOAE were correlated with the nomination score  and with executive functions . There was a significant association obtained through multiple Poisson regressions between apathy and the number of detectable DPOAE in both ears (β = –0.015 (±0.003), z = –4.16, p = 3.18e-05#, R2D = 0.17) including age, gender, and years of education , again DPOAE was a significant regressor . When performing the same analysis with PTA instead of DPOAE, PTA was not a significant regressor.PTA and DPOAE numbers were significantly correlated  = 6.03, p = 0.003]. No difference was found in the depressive symptoms score .The analysis of the neuropsychiatric symptoms showed that most subjects (72%) have at least one neuropsychiatric symptom. The most common neuropsychiatric symptoms were sleeping disorders (35%), irritability (32%), depressive symptoms (30%), and apathy (22%). Among these NPS, only the apathy severity scored by the AES-i showed significant differences between the three groups, with more severe apathy symptoms in the presbycusis and cochlear dysfunction groups , executive function  and nomination . In the entire sample, the mean percentage of functional impairment in ADL was 9.8 ± 8 (mean ± SD) which is considered a low value. No significant differences were observed for the percentage of functional impairment between the three groups .When comparing cognitive tests between the three groups , the groF = 8.35; p = 0.0003#; R2 = 0.38] and PCD  groups, these models were significant and explained similar variance, 38 and 40% respectively . In the PCD group, apathy severity (measured by AES-i), nomination and the percentage of functional loss (measured by T-ADLQ) were distinctly associated with brain volume atrophy.AES-i showed significant inverse correlations with bilateral volume of amygdala, insula, and inferior temporal gyrus. Nomination (Boston) score was directly correlated with left orbitofrontal, right thalamus and bilateral hippocampus, anterior cingulate, and insula volume . HoweverIn order to explore the mechanisms that relate presbycusis and dementia, we analyzed the structural brain changes associated with mild functional and behavioral impairment in presbycusis subjects. We found that functional loss was related with atrophy in the anterior insula and amygdala, among other temporal areas in subjects with presbycusis and cochlear dysfunction. We found a neural link relating presbycusis and mild functional impairment.As a first step, we presented a detailed assessment of cognitive, neuropsychiatric, and audiological variables related with functional impairment in presbycusis subjects, excluding other non-neural causes of disability. We reached a significant model that explained nearly 40% of the variability of functional loss in both presbycusis groups. The variables that were significantly related with functional loss included the NPS, nomination impairment, and cochlear dysfunction , 3. SurpOn the other hand, the cochlear function, measured by the sum of the total DPOAEs detected in both ears, appeared to be significant predictor of functional loss in the PCF group, which was mainly comprised of mild presbycusis subjects. The lack of effect of DPOAE in the PCD group is probably caused by the low variability in the number of DPOAEs in this group (0.92 ± 1.49) compared to the PCF (9.09 ± 2.87) (mean ± SD) due to our classification criteria. Our findings suggest that the loss of DPOAE is a more sensitive measure for predicting functional impairment in subjects with mild presbycusis than PTA (average thresholds between 0.5 and 4 kHz). This is also supported by the behavioral analysis  showing R2D = 0.17), most of the variance was due to DPOAE instead of known related variables such as age and education or gender. The most important determinants of functional impairment in presbycusis were the NPS, specifically apathy and irritability. Apathy is widely defined as a marked “loss of motivation” , which hIn line with the behavioral results, we found significant correlations between functional impairment and atrophy of bilateral insula and several areas of the temporal cortex, including the bilateral hippocampus and amygdala in the PCD group but not in the PCF group. Also, there were significant associations with subcortical areas, including the left thalamus and the nucleus accumbens . Among tOn the other hand, the amygdala receives corticofugal projections from the auditory cortex, direct projections from subcortical regions of the ascending auditory, and from other sensorial pathways . It has Finally, it is important to note that the brain atrophy associated with functional impairment in presbycusis subjects with cochlear dysfunction could be related with neurodegeneration, especially considering the high prevalence of AD biomarkers in cognitively normal subjects older than 65 years . In factWe demonstrated that in independent non-demented subjects with presbycusis, cochlear dysfunction was related with neuropsychiatric symptoms, language dysfunction, and functional impairment in activities of daily living. These behavioral changes were associated with atrophy of the insula and amygdala, among other temporal areas. These regions regulate the sensorial, cognitive, and emotional processing necessary for decision making and behavior, suggesting a neural link between presbycusis and dementia. Cochlear dysfunction may be considered a biomarker of progressive functional impairment in presbycusis subjects.p-value correction, many results were significant; however, others did not pass such correction. For this reason, we advise caution on the interpretation of results, and we encourage other authors to research how PTA and DPOAE may be of help in understanding dementia and neural degeneration.Potential limitations of this study are as follows. First, we have focused only on the volumetric measurements. Future studies could investigate the possible functional connectivity between cortical and subcortical structures and their collective contributions to functional impairment and behavioral symptoms in presbycusis. Secondly, future studies might address whether low- (<0.5 kHz) and high-frequency (>4 kHz) audiogram thresholds are associated with cognitive and brain structural changes in presbycusis. Thirdly, the cross-sectional design of the present study does not permit causal inferences. Longitudinal studies are necessary to unravel the determinants and neural mechanisms of functional impairment in presbycusis. Finally, this study used a large number of statistical tests: 7 correlations, 3 linear regressions, 4 Poisson regressions, 15 ANCOVAs, and 70 partial correlations. This naturally increases the chances of detecting effects that may not be reproducible. When using cross-statistical tests The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.The studies involving human participants and all the procedures were reviewed and approved by the Ethical and Scientific Committee of the Clinical Hospital of the Universidad de Chile, permission number OAIC 752/15. The patients/participants provided their written informed consent to participate in this study.CB analyzed the data and wrote the manuscript. RV and SS participated to analyze the data. AL, BM, MM, and MA performed the data acquisition. PD and CD performed experimental design, data analysis, and edited the manuscript.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.


The aim of this study was to evaluate the status of early hearing detection and intervention after newborn hearing screening (NHS) in South Korea. A retrospective review of Korean national health insurance service data of all infants receiving the 4-month old national infant health checkup between 2010 and 2016 from a nationwide population-based database was conducted. Based on the results of the NHS-administered hearing questionnaires as part of the national infant health checkup, individuals were classified into “pass”  or “refer”  groups. Next, an analysis was conducted of age and the frequencies of tracking audiologic tests and surgeries of the middle ear (ME) and cochlear implants (CI). Diagnostic auditory brainstem response and audiometry, and surgeries of ME and CI were significantly performed more and earlier in the refer group compared with the pass group. For infants in the pass group who were presumed to have delayed or acquired hearing loss, the time of the first audiology tests and CI surgery was significantly delayed compared to those in the refer group; the average ages for first CI were 37 and 52 months in the refer group and pass group, respectively. Therefore, for early detection of delayed-onset hearing loss, regular hearing screening programs should be considered throughout the preschool ages. In many countries, newborn hearing screening (NHS) tests are conducted on all newborns, leading to a gradual decrease in the age when deafness or hearing loss can be detected4. However, not all children with hearing loss can be identified using the hearing screening test in the neonatal period, and progressive, acquired or delayed-onset hearing impairment may occur as they developed6.Early detection and intervention of hearing impairment in infants and children is associated with better outcomes in language and communication development7. The national infant health checkup program is a type of population surveillance program consisting of history taking, physical examination, screening for visual acuity, and questionnaires for medical, dental, nutritional, educational, and hearing for each screening period . Korean citizens and registered foreigners are enrolled in the National Health Insurance Service (NHIS); all medical data covered by the NHIS , are compiled into a single NHIS information database. The national official registration classifies an individual as hearing disabled when the hearing thresholds on both sides are over 60 dB HL for bilateral hearing loss or on one side is more than 80 dB HL and on the other side is over 40 dB HL for unilateral hearing loss. The national registration records for hearing disabled are also managed by the NHIS information data system8.In November 2007, the Korean government launched a national health checkup program for infants and children to conduct screening tests for overall growth development and evaluations of hearingThe NHS test has been covered by the NHIS since October 2018. Prior to this time, neonatal caregivers conducted NHS tests for their babies at their own expenses, and there were no national statistical records to trace screening and conforming test results and aural interventions. For this reason, the results of the NHS test before applying health insurance were indirectly known only through hearing questionnaires of national infant health checkups of 4-month old children.The aim of this study was to analyze the status of early detection and intervention after NHS test in Korea, using the results of hearing questionnaires during the national infant health checkup (4 months of age) from 2010 to 2016.8. The National Health Information Database of the NHIS contains comprehensive data on health spending reimbursements and national health checkups by age and provides detailed medical information on all hospitalizations and medical utilization in Korea.This study was conducted using nationwide data from the Korean NHIS information databaseThe population of this study included infants who underwent the 4-month age national infant health checkup between January 2010 and December 2016. First, retrospective data of the 4-month-old infant health checkup were merged with data on the health-spending reimbursements of the NHIS database from January 2010 to June 2018  tests, behavioral audiometry , national official registration as hearing disabled, and middle ear (ME) and cochlear implant (CI) surgeries as factors for hearing detection and intervention were analyzed. Mortality as an analytical factor was added because it is one of the most accurate factors in the NHIS database. Age at the first ABR test and CI surgery were also analyzed as potential factors for early detection and intervention.Based on the national surgical code classification, ME surgeries were divided into two types: (1) otitis media with effusion, such as ventilation tube (V-tube) insertion and myringotomy, and (2) ME surgeries that have conductive hearing loss, such as obstruction of the external auditory canal, exploratory tympanotomy, tympanoplasty, myringoplasty, patch graft for tympanic membrane perforation under microscopy, mastoidectomy, stapes surgery, ossicular reconstruction, and ME tumors.www.sas.com/en_us/home.html). Group comparisons for qualitative data (proportions for one variable to another variable) were performed with Pearson’s chi-square test, whereas for quantitative data such as the means of two groups, we used Student’s t-test or the Wilcoxon test. P values < 0.05 were considered statistically significant.Statistical analysis was performed using SAS software version 9.3 , and the need for informed consent was waived by the Institutional Review Board because of the retrospective database nature of the study. All methods were performed in accordance with the relevant guidelines and regulations.P < 0.0001, Table P < 0.0001, Table A review of the data from 2010 to 2016 led to the inclusion of 1,741,556 infants in this study, with 1,730,615 in the pass group and 10,941 in the refer group. The mean referral rate was 0.63%  compared with the pass group (9945 infants (0.57%) P < 0.000, Table 1The percentage of infants who underwent ME operations due to otitis media effusion more than once in the refer group ranged from 0.25 to 6.99%, which was much higher than that in the pass group (0.01–0.57%) Table .P < 0.0001)  than in the pass group   in the pass group and 240 (2.19%) in the refer group. The refer group received significantly more CI surgeries than the pass group (P < 0.05). Between 2013 and 2016, the median age of the 1st CI surgery in the refer group was younger than that in the pass group; however, this difference was not statistically significant. Analysis of data from the national health checkup program in subsequent years revealed that the median age of the 1st CI surgery was getting younger in both groups, and the median age of the two groups in 2015 and 2016 were similar  than in the pass group   was significantly higher than that of the pass group   from 2010 to 2016. In this study, the diagnostic ABR-conducting rate of infants who did not pass the NHS test was 31.47%. In this study, the extraction period between 2015 and 2016 was shorter than the other periods (approximately 2–3 years in length); therefore, there were fewer infants and tests when compared with other years.9. JCIH recommended that the EHDI program aim to obtain follow-up diagnostic ABR tests in more than 95% of infants who do not pass the NHS test9. Therefore, the ABR-conducting rate in Korea was very low compared to JCIH’s recommendation. According to the hearing screening and follow-up survey in the United States administered between 2006 and 2012, referral rates decreased from 2.3 to 1.6%, and the diagnosis rates of referred infants increased from 4.8 to 10.3%10. In the early 2000s, the diagnosis rate of infants who did not pass the NHS test in the United States was also very low.Although the NHS is important, it is more important to establish a tracking system for timely EHDI and to undertake regular surveillance to detect infants with delayed-onset or progressive hearing impairmentIn this study, potential factors impacting the low diagnostic ABR rate were identified, and they included parents who may (1) not have enough guidance and awareness of the EHDI program or (2) not perform it due to cost because at that time, there was no national support. It is difficult to perform successful EHDI in accordance with the guidelines recommended by the parents themselves without the help of the government or related agencies. Therefore, it is necessary for the national web registration system that interfaces with the birth registration system to guide and track NHS data so that providers and parents can (1) manage infants for timely hearing screening, (2) follow-up for diagnosis and (3) identify those who missed NHS or ABR testing to improve coverage.12. In infants with sensorineural hearing loss, early detection of otitis media with effusion is critical since otitis media-mediated hearing loss has a greater effect on auditory cues necessary for language development than normal middle ear or cochlear function14. In a retrospective study, otitis media with effusion was identified in 64.5% of infants who did not pass the NHS; otitis media with effusion required V-tube insertion in 22.4% of cases, and 11% of all referred infants had sensorineural hearing loss after resolution of the effusion15. Therefore, for infants referred from NHS with otitis media with effusion, clinicians should conduct proper follow-up to ensure that their hearing is normal when the otitis media subsides17.In the refer group, (1) the ME surgery rate due to otitis media with effusion was 3.64%, (2) the rate for all ME surgeries except V-tube insertion and myringotomy was 3.99%, (3) the rate of registration as hearing disabled in the national registration (≥ 60 dB HL in both ears) was 1.52% and (4) the percentage of infants who underwent CI surgery (at least ≥ 70 dB HL in both ears) was 2.19%. In later years, the ME surgery rate due to otitis media with effusion was approximately 5% in the refer group; however, this rate decreased in 2015 and 2016. The ME surgery rate due to otitis media with effusion in the pass group gradually decreased from 1.33 to 0.06%; it is thought that a gradual increase in the use of protein-conjugated pneumococcus vaccination was at least partially responsible for this decrease18. In the NHS results in Hungary, 17 out of 37 (45.9%) infants with hearing impairment had sensorineural hearing loss, 2 (5.4%) had conductive hearing loss, and 18 (48.6%) reported middle ear effusion, which improved spontaneously19. Hearing loss in infants and children who had ME surgery is likely to resolve after ME surgery. Therefore, early detection of children with conductive hearing loss is also important.The rates of all ME surgeries except V-tube insertion and myringotomy were 3.99% and 0.65% in the refer group and pass group, respectively. In the 8-year NHS results in Miyazaki prefecture, Japan, among 169 infants with hearing loss, 10 (12.5%) had bilateral conductive hearing loss and 31 (34.8%) had unilateral hearing loss; four of those with bilateral conductive hearing loss had ossicular reconstruction surgery, two of whom were no longer using hearing aids20.In this study, 11,188 infants (0.65%) in the pass group also had conductive hearing loss and underwent ME surgery. In these cases, their hearing was good enough to pass the NHS test in the neonatal period, and it could be considered that they experienced delayed-onset hearing loss or post-testing progression. Some countries recommend regular hearing screenings and checks of middle-ear status at 9, 18, 30 or 36 months of age and 60 months of age to detect delayed or progressive hearing loss early, combined with other developmental surveillanceP < 0.0001). Fortunately, in the later years analyzed in this study, the age of first diagnostic ABR and CI surgery between the two groups became similar, a change that could be the result of efforts of the Otorhinolaryngology Society and the government—specifically, education and promotion through NHS guidelines, persistent workshops and online training. Even if infants passed the NHS test, they should receive regular hearing screenings through preschool ages for early detection of delayed-onset hearing loss.The percentage of infants treated with CI surgery (at least ≥ 70 dB HL in both ears more than 2 years old) was 2.19% (240 infants) in the refer group and 0.01% (157 infants) in the pass group. However, among infants in the pass group who were presumed to have delayed or acquired hearing loss, the mean age of the first diagnostic ABR tests and CI surgery was significantly delayed compared to the refer group; the average age of the first CI was 37 and 52 months in the refer group and pass group, respectively , which was significantly higher than that of the pass group . To the author’s knowledge, no reports in the literature have demonstrated that children with hearing loss under the age of 8 have a higher mortality rate than children with normal hearing. According to a report from the National Health Interview Survey in the USA, deafness in adults was associated with a higher mortality rate compared with nondeaf adults; however, this was the case for adults with postlingual deafness, not childhood deafnessImportantly, our study has some limitations. First, the tracking period was not the same for each year of the national checkup of the infant populations included in the analysis. For example, an analysis of the medical use of infants with testing performed in 2010 included 8 years of data, while infants tested in 2016 yielded only 2 years of medical use data for analysis. As a result, the number of infants and children who underwent the ABR test, ME and CI surgery gradually decreased as the national checkup age was delayed. Therefore, in future research, a long-term analytical study is needed so that the same period can be tracked and analyzed for each checkup year.The second limitation is that this study cannot explain why the mortality of the refer group is higher than that of the pass group, since only the results of the national infant checkup and the mortality rate itself were analyzed. These results do not indicate that hearing loss is a direct cause of high mortality, and further studies to analyze associated factors  are warranted.Nevertheless, the significance of this study is that it can be of practical help when the government establishes a policy for deaf or hard-of-hearing children by providing data on how many confirmation tests were performed and when and how much aural rehabilitation or surgeries were received according to the NHS results. Previously, it was predicted that the refer group will be diagnosed with hearing loss earlier and receive more timely aural intervention compared with the pass group; however, few large-scale studies have been conducted to characterize the types and timing of the related surgeries  in infants.In conclusion, audiologic tests and ME and CI surgeries were significantly more common in the refer group than in the pass group. In infants in the pass group who had delayed-onset hearing loss, the time of the first audiologic tests and CI surgery were significantly delayed compared to those in the refer group. Therefore, for early detection of delayed-onset hearing loss, regular hearing screening programs after the NHS tests should be considered through the preschool ages.