Study of Speech perception in noise (SPIN) test and Gap in noise (GIN) test in mild cognitive impairment in adult 

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MCI represents markedly heightened risk for worsening over the ensuing occurring of dementia. Mild cognitive impairment Mini-Mental State Examination Central auditory processing Central auditory processing disorder Speech Perception in Noise test and Gap in Noise test Background and Introduction Dementia is a medical condition that causes a slow loss of mental abilities, making it hard for people to live independently. The symptoms develop slowly, last a long time, and get worse over time. People with dementia often have changes in their thinking, daily activities, and behavior. This condition has a big impact on the individuals themselves, their families, the health-care system, and the economy (1). Dementia affected around 35.6 million individuals globally in 2010, with a projected increase to 115.4 million by 2050.Improved healthcare and greater life expectancy are driving this growth (2).Mild Cognitive Impairment (MCI) describes cognitive abnormalities that fall between normal aging and early dementia.These people show some signs of mental decline compared to before, but they can still manage their daily lives as they did before. Cognitive functions are usually divided into five areas: learning and memory, language, visual-spatial skills, executive functions, and psychomotor skills. These areas correspond roughly to specific parts of the brain (2). To diagnose MCI, only one area must be affected, but for dementia, more than one area must be affected. Doctors can find out which areas are involved In the early stages of MCI, patients often notice their own memory or thinking problems and may talk to their doctor about them. Diagnosing MCI or early dementia has significant long-term effects, since individuals with MCI are more likely to acquire dementia. For example, about 7.1% of people with MCI develop dementia each year, compared to just 0.2% of those without cognitive issues (2). If detailed psychological tests are not available, simpler screening tools like the Mini-Mental State Examination (MMSE) can be employed to detect dementia. However, these tests may not always catch MCI. It is very crucial to interpret test results in the context of the person's age, education, and sometimes their cultural background (3). Central auditory processing (CAP) is the brain’s ability to detect and interpret information via the central auditory pathways and to conduct the neurological processes that create the necessary electrical responses in the auditory system. Central auditory processing disorder (CAPD) is largely a problem of the central auditory nerve system (CANS). Frequently, individuals with CAPD exhibit normal hearing abilities and aural anatomy, but they have trouble processing sounds. CAPD is diagnosed by a set of auditory tests that measure the CANS's function (4). Partially screening CAP function can be done using tests like Gap in Noise (GIN) and Speech Perception in Noise (SPIN)(5). CAP seems to be clearly damaged in Alzheimer's patients (6). The current study to evaluate whether the CAP is affected in individual with mild cognitive dysfunction or not and the extent of affection. Materials and Methods participants This study was done at the Audiology Unit, Audio-vestibular unit ENT Department; Benha teaching hospital, during the period from june 2024 to february 2025. The study included a total of 60 participants aged between 50 and 65 years. Participants were recruited from the outpatient clinic and audiology unit. All subjects provided written informed permission before to participation. The research methodology was authorized by the Ethical Review Board of Al-Azhar Faculty of Medicine (Girls) in 2024, and all acquired data was kept strictly secret. This case-control study included 60 participants, divided into two subgroups (control and study groups). ( 1 ) The control group consisted of 30 healthy individuals aged 50 to 65 years, with no hearing loss by using Pure Tune Audiometry (PTA) and normal cognitive function with Arabic version of MMSE. ( 2 ) The study group consisted of 30 individuals aged 50 to 65 years with normal hearing using PTA but diagnosed with MCI by using Arabic version of MMSE. Exclusion criteria included participants refusing to participate in the study. participants with Sensory Neural Hearing Loss (SNHL), conductive or mixed hearing loss. Participants with dementia. Participants with previous diagnosis of neuropsychiatric disorder or taking any psychiatric medications. All participants underwent general and otological examinations. An otoscopic exam was done to check for earwax blockage or any issues in the outer or middle ear. The Arabic version of the MMSE questionnaire was employed, which assessed orientation in time and place, registration, calculation, attention, word recall, language, and the ability to copy a figure (7 &8). Using a two-channel diagnostic audiometer (Clinical Hearing Evaluator CE10, Germany) that was calibrated in accordance with ANSI requirements, acoustic assessments were carried out in a room that had been treated to alleviate noise. Sound-field testing, headphones, and a bone vibrator (RadioEar) were all components of the setup. Through the utilization of pulsed stimuli, pure tone audiometry was utilized to establish air conduction thresholds ranging from 250 to 8000 Hz and bone conduction thresholds ranging from 500 to 4000 Hz. The Speech Reception Thresholds (SRT) were evaluated with the help of bisyllabic Arabic phrases ( 9 ), and the Word Discrimination Scores (WDS) were conducted with the use of phonetically balanced Arabic words ( 10 ). In order to exclude aberrant middle ear function, imittancemetry was performed using an Interacoustic AT235 (manufactured in Denmark) with a penetrating tone of 226 Hz, calibrated in accordance with the ISO standard. The contralateral auditory reflex thresholds were assessed at 500, 1000, 2000, and 4000 Hz.The behavioral CAP assessment was conducted using two-channel computer compact discs that were connected to an audiometer and configured to transmit recorded speech material via earbuds. We utilized the Arabic variants of the GIN test ( 12 ) and SPIN ( 11 ). Utilizing an audiometer that is comparable to that employed in pure tone audiometry, recorded materials on compact disks were employed for the testing. Explicit instructions were provided to patients prior to testing, and they were re-instructed if they became perplexed or lost focus. The average duration for each patient was 50–55 minutes. SPIN test Objective: to evaluate monaural low redundancy. Description: The participant was situated in a sound-treated chamber and received the CD recorded material via earphones. CD-recorded voice at 50dBSL with ipsilateral speech noise presents a list of monosyllabic Arabic words. Twenty-five words comprise each list. The purpose of the GIN test is to evaluate the temporal resolution. Test stimuli were presented at 50 dB SL for the pure-tone average at 0.5, 1, and 2 kHz.Participants identify gaps in auditory stimuli during the GIN exam. The noise is a white noise that is Gaussian-distributed and has a sampling rate of 44.1 Hz.Noise segments may contain 0 to 3 gaps and have a duration of 6 seconds. The Beeps channel and earphones introduce interruptions of 2, 3, 4, 5, 6, 8, 10, 12, 15, and 20 ms. Data management and statistical analysis: SPSS version 26 (IBM Inc., USA) was implemented for statistical analysis. The unpaired Student's t-test was employed to compare quantitative variables, with a significance level of P < 0.05. The variables were presented as mean ± SD. The kappa (κ) statistic was employed to evaluate agreement between categorical variables, while Pearson's test was employed to evaluate correlations for normally distributed variables and Spearman's test for non-normal variables. Sensitivity, specificity, PPV, and NPV were determined to evaluate the diagnostic performance of audiometric tests in the detection of cognitive impairment. In order to calculate likelihood ratios, the formulas were as follows: LR⁺ = sensitivity/(1 − specificity) and LR⁻ = (1 − sensitivity)/specificity. LR⁺ values > 10, 5–10, 2–5, and ≤ 2 indicated strong, moderate, weak, and minimal evidence for disease, respectively. Conversely, LR⁻ values < 0.1, 0.1–0.2, 0.2–0.5, and 0.5–1 indicated strong to minimal evidence for exclusion. Receiver operating characteristic (ROC) curves evaluated discriminative ability, with AUC values divided into five categories: poor (0.5–0.6), fair (0.6–0.7), good (0.7–0.8), very good (0.8–0.9), and exceptional (≥ 0.9). Result A total of 60 participants, divided into two subgroups control group and study group. ( 1 )The control group consisted of 30 healthy individuals aged 50 to 65 years, with no hearing loss by using Pure Tune Audiometry (PTA) and normal cognitive function with Arabic version of MMSE. ( 2 ) The study group consisted of 30 individuals aged 50 to 65 years with normal hearing using PTA but diagnosed with MCI by using Arabic version of MMSE. The two groups exhibited comparable age (p = 0.805) (table 1) . MCI is associated with subtle but significant deterioration in low-frequency hearing sensitivity and SRT (p < 0.05), while speech discrimination ability appears to be preserved (table 2) . Participants with MCI performed significantly worse than those with normal cognition in both tests. SPIN scores were markedly lower in the MCI group (p < 0.01), GIN performance was significantly reduced in the MCI group (p < 0.05) (table 3). The area under the ROC curve was 0.852, indicating good discriminating ability of the SPIN test (table 4). The ROC curve for the combined right and left SPIN test shows a higher ability of the SPIN test to correctly identify individuals with MCI, as it has high sensitivity (85%) with acceptable specificity (approximately 73%) (table 5). The GIN test has poor to fair discriminatory ability suggesting that the GIN test alone has limited diagnostic value for identifying MCI (table 6). Both GIN tests have moderate sensitivity (≈ 52%) with poor specificity (≈ 50) Rendering the test to limited standalone diagnostic utility in distinguishing MCI from normal cognitive status (table 7). SPIN test has Sensitivity = 98.3%, Specificity = 58.3%, PPV = 70.2%, NPV = 97.2%, LR⁺ = 2.36 and LR⁻ = 0.03 in agreement to MMSE (table 8). GIN test has Sensitivity = 10.0%, Specificity = 100.0%, PPV = 100.0%, NPV = 52.6%, LR⁺ = ∞ (infinite), LR⁻ = 0.90 in agreement to MMSE (table 9). SPIN shows a significant negative correlation with PTA thresholds at 500 Hz and 1 kHz as well with SRT in both ears. There is moderate positive and highly significant correlation with MMSE scores. Additionally, significant positive correlation with GIN performance (table 10). GIN scores exhibited a significant negative correlation with the 250 Hz hearing threshold highly significant negative correlation with SRT. In contrast, a significant positive correlation was found between GIN and SPIN scores (table 11). Age does not show a significant association with MMSE. MMSE scores exhibited significant negative correlations with the 2 kHz hearing threshold and SRT. SPIN shows the strongest positive correlation with MMSE. The correlation between MMSE and GIN was positive but did not reach statistical significance (table 12). Discussion MCI is a transitional phase that occurs between the onset of normal aging and the development of dementia.It is possible that the causes of dementia may also be applicable to MCI.It is widely believed that MCI is the result of a process that deteriorates over time, ultimately leading to Alzheimer's disease, despite the fact that this concept has not yet been thoroughly verified.The American Academy of Neurology has provided guidelines that substantiate this concept ( 13 ). CAPD is a term that denotes a functional disorder, rather than a specific disease ( 14 ). It is more prevalent in elderly individuals, who are at a greater risk of developing cognitive issues such as Alzheimer's disease and minor cognitive impairment ( 5 ). This case-control study comprised 60 participants, who were each assigned to one of two subgroups. The control group and the study group. Age was not a significant factor in the differentiation between normal cognition and MCI in this study sample, as there was no statistically significant difference between the two groups. Although both groups have normal hearing bilaterally, it has been observed that comparing hearing thresholds and speech discrimination scores between participants with normal cognition and those with MCI, significant differences were observed at certain frequencies. Statistically significant differences were observed at low to mid frequencies (250 Hz, 500 Hz, and 1 kHz), where the MCI group demonstrated significantly elevated PTA thresholds compared with NC participants, suggesting poorer peripheral hearing sensitivity in the MCI group at these frequencies. No significant differences were noted in speech discrimination scores or other frequency thresholds. These results indicate a potential correlation between cognitive decline (CD) and hearing impairment at specific frequencies, underscoring the significance of auditory assessments in populations at risk for MCI. The findings of this study are consistent with those of Lin et al. (2011), who discovered that hearing loss is associated with subpar performance on memory and problem-solving tests ( 15 ). Conversely, these findings contradict a study conducted by Diao et al. (2021) that posited that hearing loss is not a primary cause of cognitive impairments, despite the potential impact on specific abilities such as speech comprehension and abstract reasoning. High-frequency hearing loss may affect these abilities, but it does not affect overall cognitive function ( 16 ). The present study illustrated that participants with MCI exhibited substantially lower performance on both CAP measures than those with normal cognition. The MCI group exhibited significantly lower speech perception in noise (SPIN) scores than the NC participants, suggesting that they encountered significant challenges in comprehending speech in difficult auditory environments. In the same vein, the MCI group exhibited a substantial decrease in GIN performance, which was indicative of impaired temporal resolution capabilities. In contrast to typical cognitive aging, these results indicate that MCI is associated with substantial deficits in certain cognitive abilities, such as speech-in-noise perception and temporal processing. Similarly, Davidson and Souza (2023) have recently conducted research that suggests that sentences in speech-shaped noise are most significantly associated with executive/inhibitory processes and global measures of cognition. According to tests that include pitch pattern sequencing, temporal order tasks, low-redundancy speech tests, gaps in noise, and simple dichotic speech tests using single words or spoken digits, temporal processing, specifically temporal order tasks, is most strongly associated with working memory, fluid intelligence, and global measures of cognition ( 17 ). The diagnostic accuracy of the SPIN test in distinguishing between participants with MCI and those with normal cognition. Indicating that the SPIN test has a high degree of discrimination, the area under the ROC curve was 0.852. SPIN testing may be a valuable and accurate method for identifying individuals with MCI, as these findings indicate. These findings are consistent with prior research that has demonstrated that CD and aging have distinct effects on speech perception in circumstances of noise. sssReports of hearing difficulties were more prevalent among men, and exposure to high workplace noise was linked to both perceived and actual hearing problems. The findings indicated that the reduced ability of elderly individuals to hear speech in noise is associated with increasing perceived hearing problems and deteriorating cognitive processing ( 18 ). This aligns with research conducted by Jalaei et al. (2019), which shown that word perception capacity in the presence of noise was significantly diminished in the MCI group compared to the control group. It is crucial to emphasize that the evaluation of speech in noise, including the SPIN test, imposes greater cognitive demands and incorporates additional interfering elements. This research was conducted on 20 senior people aged 65 to 75 years diagnosed with MCI and 20 matched old persons without cognitive impairments in similar age group. The Persian version of the MMSE questionnaire was utilized to examine the cognitive state of the control group. All the individuals had normal hearing thresholds. In our current study, it has been found that SPIN test demonstrates high sensitivity and moderate specificity, indicating its effectiveness in identifying individuals with MCI while maintaining reasonable specificity. These findings conflict with a research done by (Iliadou et al., 2017), that demonstrated that a measure of temporal resolution by GIN may give an early, although indirect, metric of left temporal cortical thinning linked with the transition between MCI and Alzheimer’s disease. Both temporal resolution tests (GIN) and Random Gap Detection Test (RGDT)) were effective in separating the MCI group from the age-matched control group ( 20 ). SPIN demonstrates excellent sensitivity and a very high NPV, supporting its usefulness as an effective screening tool for MCI and for ruling out MCI when results are normal. However, the moderate specificity and modest LR⁺ limit its ability to definitively confirm MCI when abnormal. Therefore, SPIN should be interpreted in conjunction with cognitive assessments and other CAP tests rather than employed as a standalone diagnostic measure. This finding diverges with the research conducted by Idrizbegovic et al. (2011), which indicated that speech perception scores in noisy environments remained within anticipated parameters for all groups after accounting for age and high-frequency hearing loss through the test's reference model. This discrepancy can be related to multiple factors such as older age group, presence of high frequencies hearing loss and different temporal processing test they employed ( 6 ). The study exhibited that GIN demonstrates excellent sensitivity but extremely poor specificity, limiting its usefulness as a screening tool for MCI. While an abnormal GIN result is highly suggestive of MCI, the test fails to identify most affected individuals. Consequently, GIN has limited clinical value when employed alone and should only be considered as a supplementary confirmatory measure in conjunction with more sensitive auditory or cognitive screening tools. The current study exhibited that SPIN scores exhibited significant negative correlations with PTA thresholds at 500 Hz and 1 kHz, as well as with SRT.SPIN exhibited a moderate positive and highly significant correlation with MMSE scores. Additionally, a significant positive correlation with GIN performance was noticed, suggesting that temporal processing abilities contribute to SPIN performance. these observations demonstrate that SPIN is affected by peripheral hearing factors at specific frequencies and central cognitive and temporal processing abilities, with cognition showing the strongest association. GIN scores indicated a substantial negative link with the 250 Hz hearing threshold and a highly significant negative correlation with SRT. The connection between GIN and MMSE was positive but did not achieve statistical significance. In contrast, a substantial positive association was identified between GIN and SPIN scores, suggesting an interaction between temporal processing ability and speech perception in noise. These findings indicate that GIN performance is influenced mainly by specific peripheral auditory factors and central auditory processing, with a weaker direct association with global cognitive status compared to SPIN. In the current study it was shown that the correlation between MMSE scores and various PTA hearing threshold and cognitive variables. Age does not show a significant association with cognitive performance. MMSE scores exhibited significant negative correlations with the 2 kHz hearing threshold and SRT, indicating that poorer mid-frequency hearing sensitivity and higher SRT are associated with lower cognitive performance. That finding is in accordance with a research study that exhibited the link between hearing loss and cognition. Their results are consistent with earlier research showing significant connections between higher hearing loss and lower cognitive function on both verbal and non-verbal cognitive tests( 15 ). In contrast, MMSE demonstrated a moderate positive and highly statistically significant correlation with SPIN performance, highlighting a substantial link between global cognitive performance and speech perception in noise. The correlation between MMSE and GIN was positive but did not reach statistical significance. These findings highlight cognitive performance, as measured by MMSE, is more strongly associated with speech-in-noise perception than with basic peripheral hearing sensitivity or temporal resolution alone. This is in agreement with recent study that noted it can be argued that theSPIN test may be a helpful screening tool for suspected CAPD and impaired cognitive function when the performance is considerably poorer than expected ( 18 ). Conclusions Both SPIN and GIN tests scores were significantly lower in patients with MCI than those of the normal cognitive group. There is possible association between hearing impairment at specific frequencies and CD. Better speech perception in noise tends to be linked with higher cognitive function. SPIN test may operates as an effective screening method for recognizing early CD as provides excellent sensitivity (98.3%) and moderate specificity (58.3%), making it a strong indicator for distinguishing MCI from normal cognition. MMSE has a sensitivity rate of around 70–80% for identifying individuals with dementia but is less effective in the detection of MCI and moderate specificity. Thus, using SPIN test as screening test for MCI is better and more accurate than MMSE. The GIN test has limited standalone diagnostic utility in distinguishing MCI from normal cognitive status. CAPD may promote communication difficulty with MCI patients. Abbreviations AD Alzheimer’s Disease APD Auditory Processing Disorder ASHA American Speech Language Hearing Association AUC Area Under the Curve CANS Central Auditory Nervous System CAP Central Auditory Processing CAPD Central Auditory Processing Disorder DDT Dichotic Digits Test DPT Duration Pattern Test DSI Dichotic Sentence Identification FPT Frequency Pattern Test GIN Gap In Noise k Kappa Statistic Lt Left LLR Likelihood Ratios LLR⁻ Negative Likelihood Ratio LLR⁺ Positive Likelihood Ratio MCI Mild Cognitive Impairment MMSE Mini–Mental Status Examination MoCA Montreal Cognitive Assessment NC Normal Cognition NCI No Cognitive Impairment NPV Negative Predictive Value PTA Pure Tone Audiometry r Pearson Correlation Coefficient RGDT Random Gap Detection Test ROC Receiver Operating Characteristic curve Rt Right SD Standard Deviation SinB Speech In Babble SNHL Sensory Neural Hearing loss SPIN Speech perception In Noise SRT Speech Reception Threshold SSI Synthetic Sentence Identification SSI-ICM Synthetic Sentence Identification with Ipsilateral Competing Message Declarations Data availability: The datasets acquired and/or analyzed during the current study are available from the corresponding author. Ethics declarations: Prior to enrollment, all participants' parents or legal guardians gave written informed consent. In 2024, the Al-Azhar Faculty of Medicine (Girls) Ethical Review Board authorized the study methodology, and all obtained data was treated with complete confidentiality.. Funding: NIL. Competing interest: NIL. References Duong S, Patel T, Chang F (2017) Dementia: What pharmacists need to know. Can Pharmacists Journal/Revue des Pharmaciens du Can 150(2):118–129 Knopman DS, Petersen RC (2014) :, Mayo Clin Proc. 2014; 89(10): 1452–1459 Hugo J, Ganguli M (2014) : Dementia and cognitive impairment: epidemiology, diagnosis, and treatment. 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Behavioural Neurology 15 December 2022. https://doi.org/10.1155/2022/90016 62 Lin FR, Ferrucci L, Metter EJ, An Y, Zonderman AB, Resnick SM (2011) Hearing loss and cognition in the Baltimore Longitudinal Study of Aging. Neuropsychology 25(6):763–770. 10.1037/a0024238 Diao T, Ma X, Zhang J, Duan M, Yu L (2021) : The Correlation Between Hearing Loss, Especially High-Frequency Hearing Loss and Cognitive Decline Among the Elderly Front Neurosci. 2021;15:750874. 10.3389/fnins.2021.750874 Davidson A, Souza P (2023) : Relationships Between Auditory Processing and Cognitive Abilities in Adults: A Systematic Review Publication: Journal of Speech, Language, and Hearing Research Volume 67, Number 1 Pages 296–345 Nagaraj NK (2024) Hearing loss and cognitive decline in the aging population: emerging perspectives in audiology. Audiol Res 14(3):479–492 Ghannoum MT, Shalaby AA, Farghaly M, Hamdy M, Hamdy HS (2018) Central auditory processing findings in a group of cognitively impaired individuals. Hear Balance Communication 1–10. 10.1080/21695717.2018.1490117 Iliadou V (Vivian), Bamiou D-E, Sidiras C, Moschopoulos NP, Tsolaki M, Nimatoudis I, Chermak GD (eds) (2017) : The Use of the Gaps-In-Noise Test as an Index of the Enhanced Left Temporal Cortical Thinning Associated with the Transition between Mild Cognitive Impairment and Alzheimer’s Disease. Journal of the American Academy of Audiology, 28(5), 463–471. 10.3766/jaaa.16075 Tables Tables 1 to 12 are available in the supplementary files section Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8810437","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":637551848,"identity":"16203cbc-55a4-466c-b5f5-0a4ea8dbf86c","order_by":0,"name":"Amal Elsebaie Beshr","email":"","orcid":"","institution":"Al Azhar University","correspondingAuthor":false,"prefix":"","firstName":"Amal","middleName":"Elsebaie","lastName":"Beshr","suffix":""},{"id":637551849,"identity":"9c5dccd6-8833-4549-a082-92817d86c31a","order_by":1,"name":"Iman Ibrahim Eladawy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYBAC+QYQWcDACKTZf/+psAHyGBsP4NPCBiYNwFoYJHjOpIG0NJCghbftMJiPX4vY4WcPPhjYyfbPyDEwkGw7b7e2/TDQlhqbaJxapNPMDWcYJBvPuJFjkGBw7nbytjOJQC3H0nIbcGpJMJPmMWBObLidY3Agoex2stkBoBbGhsN4tKR/k/5jUJ84/3aOYcMBtnPJZucfEtKSYybNYHA4ccPtHGPGhrYDdmY3CNqSUybZY3DceOP9Z2XMDGeSE8xuAG1JwOMX+dnp2yR+VFTLzjtzeBszQ4Wdvdn59IcPPtTY4NSCBDgMQGQiWGUCYeUgwP4ARNoTp3gUjIJRMApGEgAAeI9k7TF6H9EAAAAASUVORK5CYII=","orcid":"","institution":"Al Azhar University","correspondingAuthor":true,"prefix":"","firstName":"Iman","middleName":"Ibrahim","lastName":"Eladawy","suffix":""},{"id":637551850,"identity":"d93a30d9-603d-41fc-a856-5d123a573a4d","order_by":2,"name":"Safaa Mahmoud Hammouda","email":"","orcid":"","institution":"Al Azhar University","correspondingAuthor":false,"prefix":"","firstName":"Safaa","middleName":"Mahmoud","lastName":"Hammouda","suffix":""},{"id":637551851,"identity":"414edfd4-90c8-4dfc-9c69-d3763ad52a46","order_by":3,"name":"Alaa Ahmed Adel Elsayed","email":"","orcid":"","institution":"Al Azhar University","correspondingAuthor":false,"prefix":"","firstName":"Alaa","middleName":"Ahmed Adel","lastName":"Elsayed","suffix":""}],"badges":[],"createdAt":"2026-02-06 19:38:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8810437/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8810437/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109067735,"identity":"471a9520-4afd-4397-8351-6ec18cb107b8","added_by":"auto","created_at":"2026-05-12 10:00:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":219218,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8810437/v1/ca44d0a5-3f49-420d-875a-1c8c6591663f.pdf"},{"id":108946050,"identity":"9955291c-4c5b-40ce-a87a-4b663c204d96","added_by":"auto","created_at":"2026-05-11 06:20:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36355,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8810437/v1/7e018012f5a06f025b61d1dc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Study of Speech perception in noise (SPIN) test and Gap in noise (GIN) test in mild cognitive impairment in adult ","fulltext":[{"header":"Background and Introduction","content":"\u003cp\u003eDementia is a medical condition that causes a slow loss of mental abilities, making it hard for people to live independently. The symptoms develop slowly, last a long time, and get worse over time. People with dementia often have changes in their thinking, daily activities, and behavior. This condition has a big impact on the individuals themselves, their families, the health-care system, and the economy (1). Dementia affected around 35.6 million individuals globally in 2010, with a projected increase to 115.4 million by 2050.Improved healthcare and greater life expectancy are driving this growth (2).Mild Cognitive Impairment (MCI) describes cognitive abnormalities that fall between normal aging and early dementia.These people show some signs of mental decline compared to before, but they can still manage their daily lives as they did before. Cognitive functions are usually divided into five areas: learning and memory, language, visual-spatial skills, executive functions, and psychomotor skills. These areas correspond roughly to specific parts of the brain (2). To diagnose MCI, only one area must be affected, but for dementia, more than one area must be affected. Doctors can find out which areas are involved In the early stages of MCI, patients often notice their own memory or thinking problems and may talk to their doctor about them. Diagnosing MCI or early dementia has significant long-term effects, since individuals with MCI are more likely to acquire dementia. For example, about 7.1% of people with MCI develop dementia each year, compared to just 0.2% of those without cognitive issues (2). If detailed psychological tests are not available, simpler screening tools like the Mini-Mental State Examination (MMSE) can be employed to detect dementia. However, these tests may not always catch MCI. It is very crucial to interpret test results in the context of the person's age, education, and sometimes their cultural background (3). Central auditory processing (CAP) is the brain’s ability to detect and interpret information via the central auditory pathways and to conduct the neurological processes that create the necessary electrical responses in the auditory system. Central auditory processing disorder (CAPD) is largely a problem of the central auditory nerve system (CANS). Frequently, individuals with CAPD exhibit normal hearing abilities and aural anatomy, but they have trouble processing sounds. CAPD is diagnosed by a set of auditory tests that measure the CANS's function (4). Partially screening CAP function can be done using tests like Gap in Noise (GIN) and Speech Perception in Noise (SPIN)(5). CAP seems to be clearly damaged in Alzheimer's patients (6). The current study to evaluate whether the CAP is affected in individual with mild cognitive dysfunction or not and the extent of affection.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cstrong\u003eparticipants\u003c/strong\u003e \u003cp\u003eThis study was done at the Audiology Unit, Audio-vestibular unit ENT Department; Benha teaching hospital, during the period from june 2024 to february 2025. The study included a total of 60 participants aged between 50 and 65 years. Participants were recruited from the outpatient clinic and audiology unit. All subjects provided written informed permission before to participation. The research methodology was authorized by the Ethical Review Board of Al-Azhar Faculty of Medicine (Girls) in 2024, and all acquired data was kept strictly secret. This case-control study included 60 participants, divided into two subgroups (control and study groups). (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The control group consisted of 30 healthy individuals aged 50 to 65 years, with no hearing loss by using Pure Tune Audiometry (PTA) and normal cognitive function with Arabic version of MMSE. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The study group consisted of 30 individuals aged 50 to 65 years with normal hearing using PTA but diagnosed with MCI by using Arabic version of MMSE.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eExclusion criteria included participants refusing to participate in the study. participants with Sensory Neural Hearing Loss (SNHL), conductive or mixed hearing loss. Participants with dementia. Participants with previous diagnosis of neuropsychiatric disorder or taking any psychiatric medications.\u003c/p\u003e\u003cp\u003eAll participants underwent general and otological examinations.\u003c/p\u003e\u003cp\u003eAn otoscopic exam was done to check for earwax blockage or any issues in the outer or middle ear. The Arabic version of the MMSE questionnaire was employed, which assessed orientation in time and place, registration, calculation, attention, word\u003c/p\u003e\u003cp\u003erecall, language, and the ability to copy a figure (7 \u0026amp;8).\u003c/p\u003e\u003cp\u003eUsing a two-channel diagnostic audiometer (Clinical Hearing Evaluator CE10, Germany) that was calibrated in accordance with ANSI requirements, acoustic assessments were carried out in a room that had been treated to alleviate noise. Sound-field testing, headphones, and a bone vibrator (RadioEar) were all components of the setup. Through the utilization of pulsed stimuli, pure tone audiometry was utilized to establish air conduction thresholds ranging from 250 to 8000 Hz and bone conduction thresholds ranging from 500 to 4000 Hz. The Speech Reception Thresholds (SRT) were evaluated with the help of bisyllabic Arabic phrases (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), and the Word Discrimination Scores (WDS) were conducted with the use of phonetically balanced Arabic words (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn order to exclude aberrant middle ear function, imittancemetry was performed using an Interacoustic AT235 (manufactured in Denmark) with a penetrating tone of 226 Hz, calibrated in accordance with the ISO standard. The contralateral auditory reflex thresholds were assessed at 500, 1000, 2000, and 4000 Hz.The behavioral CAP assessment was conducted using two-channel computer compact discs that were connected to an audiometer and configured to transmit recorded speech material via earbuds. We utilized the Arabic variants of the GIN test (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and SPIN (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Utilizing an audiometer that is comparable to that employed in pure tone audiometry, recorded materials on compact disks were employed for the testing. Explicit instructions were provided to patients prior to testing, and they were re-instructed if they became perplexed or lost focus. The average duration for each patient was 50\u0026ndash;55 minutes.\u003c/p\u003e\u003cp\u003eSPIN test Objective: to evaluate monaural low redundancy.\u003c/p\u003e\u003cp\u003eDescription: The participant was situated in a sound-treated chamber and received the CD recorded material via earphones. CD-recorded voice at 50dBSL with ipsilateral speech noise presents a list of monosyllabic Arabic words. Twenty-five words comprise each list.\u003c/p\u003e\u003cp\u003eThe purpose of the GIN test is to evaluate the temporal resolution.\u003c/p\u003e\u003cp\u003e Test stimuli were presented at 50 dB SL for the pure-tone average at 0.5, 1, and 2 kHz.Participants identify gaps in auditory stimuli during the GIN exam. The noise is a white noise that is Gaussian-distributed and has a sampling rate of 44.1 Hz.Noise segments may contain 0 to 3 gaps and have a duration of 6 seconds. The Beeps channel and earphones introduce interruptions of 2, 3, 4, 5, 6, 8, 10, 12, 15, and 20 ms.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData management and statistical analysis:\u003c/h2\u003e \u003cp\u003eSPSS version 26 (IBM Inc., USA) was implemented for statistical analysis. The unpaired Student's t-test was employed to compare quantitative variables, with a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. The kappa (κ) statistic was employed to evaluate agreement between categorical variables, while Pearson's test was employed to evaluate correlations for normally distributed variables and Spearman's test for non-normal variables. Sensitivity, specificity, PPV, and NPV were determined to evaluate the diagnostic performance of audiometric tests in the detection of cognitive impairment. In order to calculate likelihood ratios, the formulas were as follows: LR⁺ = sensitivity/(1\u0026thinsp;\u0026minus;\u0026thinsp;specificity) and LR⁻ = (1\u0026thinsp;\u0026minus;\u0026thinsp;sensitivity)/specificity. LR⁺ values\u0026thinsp;\u0026gt;\u0026thinsp;10, 5\u0026ndash;10, 2\u0026ndash;5, and \u0026le;\u0026thinsp;2 indicated strong, moderate, weak, and minimal evidence for disease, respectively. Conversely, LR⁻ values\u0026thinsp;\u0026lt;\u0026thinsp;0.1, 0.1\u0026ndash;0.2, 0.2\u0026ndash;0.5, and 0.5\u0026ndash;1 indicated strong to minimal evidence for exclusion. Receiver operating characteristic (ROC) curves evaluated discriminative ability, with AUC values divided into five categories: poor (0.5\u0026ndash;0.6), fair (0.6\u0026ndash;0.7), good (0.7\u0026ndash;0.8), very good (0.8\u0026ndash;0.9), and exceptional (\u0026ge;\u0026thinsp;0.9).\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cp\u003eA total of 60 participants, divided into two subgroups control group and study group. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)The control group consisted of 30 healthy individuals aged 50 to 65 years, with no hearing loss by using Pure Tune Audiometry (PTA) and normal cognitive function with Arabic version of MMSE. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The study group consisted of 30 individuals aged 50 to 65 years with normal hearing using PTA but diagnosed with MCI by using Arabic version of MMSE.\u003c/p\u003e \u003cp\u003eThe two groups exhibited comparable age (p\u0026thinsp;=\u0026thinsp;0.805) \u003cb\u003e(table 1)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eMCI is associated with subtle but significant deterioration in low-frequency hearing sensitivity and SRT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while speech discrimination ability appears to be preserved \u003cb\u003e(table 2)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eParticipants with MCI performed significantly worse than those with normal cognition in both tests. SPIN scores were markedly lower in the MCI group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), GIN performance was significantly reduced in the MCI group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u003cb\u003e(table 3).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe area under the ROC curve was 0.852, indicating good discriminating ability of the SPIN test \u003cb\u003e(table 4).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe ROC curve for the combined right and left SPIN test shows a higher ability of the SPIN test to correctly identify individuals with MCI, as it has high sensitivity (85%) with acceptable specificity (approximately 73%) \u003cb\u003e(table 5).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe GIN test has poor to fair discriminatory ability suggesting that the GIN test alone has limited diagnostic value for identifying MCI \u003cb\u003e(table 6).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBoth GIN tests have moderate sensitivity (\u0026asymp;\u0026thinsp;52%) with poor specificity (\u0026asymp;\u0026thinsp;50) Rendering the test to limited standalone diagnostic utility in distinguishing MCI from normal cognitive status \u003cb\u003e(table 7).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSPIN test has Sensitivity\u0026thinsp;=\u0026thinsp;98.3%, Specificity\u0026thinsp;=\u0026thinsp;58.3%, PPV\u0026thinsp;=\u0026thinsp;70.2%, NPV\u0026thinsp;=\u0026thinsp;97.2%, LR⁺ = 2.36 and LR⁻ = 0.03 in agreement to MMSE \u003cb\u003e(table 8).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGIN test has Sensitivity\u0026thinsp;=\u0026thinsp;10.0%, Specificity\u0026thinsp;=\u0026thinsp;100.0%, PPV\u0026thinsp;=\u0026thinsp;100.0%, NPV\u0026thinsp;=\u0026thinsp;52.6%, LR⁺ = \u0026infin; (infinite), LR⁻ = 0.90 in agreement to MMSE \u003cb\u003e(table 9).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSPIN shows a significant negative correlation with PTA thresholds at 500 Hz and 1 kHz as well with SRT in both ears. There is moderate positive and highly significant correlation with MMSE scores. Additionally, significant positive correlation with GIN performance \u003cb\u003e(table 10).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGIN scores exhibited a significant negative correlation with the 250 Hz hearing threshold highly significant negative correlation with SRT. In contrast, a significant positive correlation was found between GIN and SPIN scores \u003cb\u003e(table 11).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAge does not show a significant association with MMSE. MMSE scores exhibited significant negative correlations with the 2 kHz hearing threshold and SRT. SPIN shows the strongest positive correlation with MMSE. The correlation between MMSE and GIN was positive but did not reach statistical significance \u003cb\u003e(table 12).\u003c/b\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMCI is a transitional phase that occurs between the onset of normal aging and the development of dementia.It is possible that the causes of dementia may also be applicable to MCI.It is widely believed that MCI is the result of a process that deteriorates over time, ultimately leading to Alzheimer's disease, despite the fact that this concept has not yet been thoroughly verified.The American Academy of Neurology has provided guidelines that substantiate this concept (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). CAPD is a term that denotes a functional disorder, rather than a specific disease (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). It is more prevalent in elderly individuals, who are at a greater risk of developing cognitive issues such as Alzheimer's disease and minor cognitive impairment (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). This case-control study comprised 60 participants, who were each assigned to one of two subgroups. The control group and the study group. Age was not a significant factor in the differentiation between normal cognition and MCI in this study sample, as there was no statistically significant difference between the two groups.\u003c/p\u003e \u003cp\u003e Although both groups have normal hearing bilaterally, it has been observed that comparing hearing thresholds and speech discrimination scores between participants with normal cognition and those with MCI, significant differences were observed at certain frequencies. Statistically significant differences were observed at low to mid frequencies (250 Hz, 500 Hz, and 1 kHz), where the MCI group demonstrated significantly elevated PTA thresholds compared with NC participants, suggesting poorer peripheral hearing sensitivity in the MCI group at these frequencies. No significant differences were noted in speech discrimination scores or other frequency thresholds.\u003c/p\u003e \u003cp\u003eThese results indicate a potential correlation between cognitive decline (CD) and hearing impairment at specific frequencies, underscoring the significance of auditory assessments in populations at risk for MCI. The findings of this study are consistent with those of Lin et al. (2011), who discovered that hearing loss is associated with subpar performance on memory and problem-solving tests (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Conversely, these findings contradict a study conducted by Diao et al. (2021) that posited that hearing loss is not a primary cause of cognitive impairments, despite the potential impact on specific abilities such as speech comprehension and abstract reasoning. High-frequency hearing loss may affect these abilities, but it does not affect overall cognitive function (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study illustrated that participants with MCI exhibited substantially lower performance on both CAP measures than those with normal cognition. The MCI group exhibited significantly lower speech perception in noise (SPIN) scores than the NC participants, suggesting that they encountered significant challenges in comprehending speech in difficult auditory environments.\u003c/p\u003e \u003cp\u003eIn the same vein, the MCI group exhibited a substantial decrease in GIN performance, which was indicative of impaired temporal resolution capabilities. In contrast to typical cognitive aging, these results indicate that MCI is associated with substantial deficits in certain cognitive abilities, such as speech-in-noise perception and temporal processing.\u003c/p\u003e \u003cp\u003eSimilarly, Davidson and Souza (2023) have recently conducted research that suggests that sentences in speech-shaped noise are most significantly associated with executive/inhibitory processes and global measures of cognition.\u003c/p\u003e \u003cp\u003eAccording to tests that include pitch pattern sequencing, temporal order tasks, low-redundancy speech tests, gaps in noise, and simple dichotic speech tests using single words or spoken digits, temporal processing, specifically temporal order tasks, is most strongly associated with working memory, fluid intelligence, and global measures of cognition (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe diagnostic accuracy of the SPIN test in distinguishing between participants with MCI and those with normal cognition. Indicating that the SPIN test has a high degree of discrimination, the area under the ROC curve was 0.852. SPIN testing may be a valuable and accurate method for identifying individuals with MCI, as these findings indicate. These findings are consistent with prior research that has demonstrated that CD and aging have distinct effects on speech perception in circumstances of noise. sssReports of hearing difficulties were more prevalent among men, and exposure to high workplace noise was linked to both perceived and actual hearing problems. The findings indicated that the reduced ability of elderly individuals to hear speech in noise is associated with increasing perceived hearing problems and deteriorating cognitive processing (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis aligns with research conducted by Jalaei et al. (2019), which shown that word perception capacity in the presence of noise was significantly diminished in the MCI group compared to the control group. It is crucial to emphasize that the evaluation of speech in noise, including the SPIN test, imposes greater cognitive demands and incorporates additional interfering elements.\u003c/p\u003e \u003cp\u003eThis research was conducted on 20 senior people aged 65 to 75 years diagnosed with MCI and 20 matched old persons without cognitive impairments in similar age group. The Persian version of the MMSE questionnaire was utilized to examine the cognitive state of the control group. All the individuals had normal hearing thresholds.\u003c/p\u003e \u003cp\u003eIn our current study, it has been found that SPIN test demonstrates high sensitivity and moderate specificity, indicating its effectiveness in identifying individuals with MCI while maintaining reasonable specificity.\u003c/p\u003e \u003cp\u003eThese findings conflict with a research done by (Iliadou et al., 2017), that demonstrated that a measure of temporal resolution by GIN may give an early, although indirect, metric of left temporal cortical thinning linked with the transition between MCI and Alzheimer\u0026rsquo;s disease. Both temporal resolution tests (GIN) and Random Gap Detection Test (RGDT)) were effective in separating the MCI group from the age-matched control group (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSPIN demonstrates excellent sensitivity and a very high NPV, supporting its usefulness as an effective screening tool for MCI and for ruling out MCI when results are normal. However, the moderate specificity and modest LR⁺ limit its ability to definitively confirm MCI when abnormal. Therefore, SPIN should be interpreted in conjunction with cognitive assessments and other CAP tests rather than employed as a standalone diagnostic measure.\u003c/p\u003e \u003cp\u003eThis finding diverges with the research conducted by Idrizbegovic et al. (2011), which indicated that speech perception scores in noisy environments remained within anticipated parameters for all groups after accounting for age and high-frequency hearing loss through the test's reference model. This discrepancy can be related to multiple factors such as older age group, presence of high frequencies hearing loss and different temporal processing test they employed (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study exhibited that GIN demonstrates excellent sensitivity but extremely poor specificity, limiting its usefulness as a screening tool for MCI. While an abnormal GIN result is highly suggestive of MCI, the test fails to identify most affected individuals. Consequently, GIN has limited clinical value when employed alone and should only be considered as a supplementary confirmatory measure in conjunction with more sensitive auditory or cognitive screening tools.\u003c/p\u003e \u003cp\u003eThe current study exhibited that SPIN scores exhibited significant negative correlations with PTA thresholds at 500 Hz and 1 kHz, as well as with SRT.SPIN exhibited a moderate positive and highly significant correlation with MMSE scores.\u003c/p\u003e \u003cp\u003eAdditionally, a significant positive correlation with GIN performance was noticed, suggesting that temporal processing abilities contribute to SPIN performance.\u003c/p\u003e \u003cp\u003ethese observations demonstrate that SPIN is affected by peripheral hearing factors at specific frequencies and central cognitive and temporal processing abilities, with cognition showing the strongest association.\u003c/p\u003e \u003cp\u003eGIN scores indicated a substantial negative link with the 250 Hz hearing threshold and a highly significant negative correlation with SRT.\u003c/p\u003e \u003cp\u003eThe connection between GIN and MMSE was positive but did not achieve statistical significance. In contrast, a substantial positive association was identified between GIN and SPIN scores, suggesting an interaction between temporal processing ability and speech perception in noise.\u003c/p\u003e \u003cp\u003eThese findings indicate that GIN performance is influenced mainly by specific peripheral auditory factors and central auditory processing, with a weaker direct association with global cognitive status compared to SPIN.\u003c/p\u003e \u003cp\u003eIn the current study it was shown that the correlation between MMSE scores and various PTA hearing threshold and cognitive variables. Age does not show a significant association with cognitive performance. MMSE scores exhibited significant negative correlations with the 2 kHz hearing threshold and SRT, indicating that poorer mid-frequency hearing sensitivity and higher SRT are associated with lower cognitive performance.\u003c/p\u003e \u003cp\u003eThat finding is in accordance with a research study that exhibited the link between hearing loss and cognition. Their results are consistent with earlier research showing significant connections between higher hearing loss and lower cognitive function on both verbal and non-verbal cognitive tests(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, MMSE demonstrated a moderate positive and highly statistically significant correlation with SPIN performance, highlighting a substantial link between global cognitive performance and speech perception in noise. The correlation between MMSE and GIN was positive but did not reach statistical significance.\u003c/p\u003e \u003cp\u003eThese findings highlight cognitive performance, as measured by MMSE, is more strongly associated with speech-in-noise perception than with basic peripheral hearing sensitivity or temporal resolution alone.\u003c/p\u003e \u003cp\u003eThis is in agreement with recent study that noted it can be argued that theSPIN test may be a helpful screening tool for suspected CAPD and impaired cognitive function when the performance is considerably poorer than expected (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eBoth SPIN and GIN tests scores were significantly lower in patients with MCI than those of the normal cognitive group.\u003c/p\u003e \u003cp\u003eThere is possible association between hearing impairment at specific frequencies and CD.\u003c/p\u003e \u003cp\u003eBetter speech perception in noise tends to be linked with higher cognitive function.\u003c/p\u003e \u003cp\u003eSPIN test may operates as an effective screening method for recognizing early CD as provides excellent sensitivity (98.3%) and moderate specificity (58.3%), making it a strong indicator for distinguishing MCI from normal cognition.\u003c/p\u003e \u003cp\u003eMMSE has a sensitivity rate of around 70\u0026ndash;80% for identifying individuals with dementia but is less effective in the detection of MCI and moderate specificity.\u003c/p\u003e \u003cp\u003eThus, using SPIN test as screening test for MCI is better and more accurate than MMSE.\u003c/p\u003e \u003cp\u003eThe GIN test has limited standalone diagnostic utility in distinguishing MCI from normal cognitive status.\u003c/p\u003e \u003cp\u003eCAPD may promote communication difficulty with MCI patients.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"103%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAlzheimer’s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAuditory Processing Disorder\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eASHA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAmerican Speech Language Hearing Association\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eArea Under the Curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCANS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCentral Auditory Nervous System\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCentral Auditory Processing\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCAPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCentral Auditory Processing Disorder\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDDT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDichotic Digits Test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDPT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDuration Pattern Test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDSI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDichotic Sentence Identification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFPT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFrequency Pattern Test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGIN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGap In Noise\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ek\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eKappa Statistic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLLR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLikelihood Ratios\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLLR⁻\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNegative Likelihood Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLLR⁺\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePositive Likelihood Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMild Cognitive Impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMini–Mental Status Examination\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMoCA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMontreal Cognitive Assessment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal Cognition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo Cognitive Impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNegative Predictive Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePTA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePure Tone Audiometry\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation Coefficient\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRGDT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRandom Gap Detection Test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eROC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eReceiver Operating Characteristic curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSinB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSpeech In Babble\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSNHL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSensory Neural Hearing loss\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSPIN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSpeech perception In Noise\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSRT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSpeech Reception Threshold\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSSI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSynthetic Sentence Identification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSSI-ICM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSynthetic Sentence Identification with Ipsilateral Competing Message\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The datasets acquired and/or analyzed during the current study are available from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations:\u003cbr\u003e\u0026nbsp;\u003c/strong\u003ePrior to enrollment, all participants' parents or legal guardians gave written informed consent. In 2024, the Al-Azhar Faculty of Medicine (Girls) Ethical Review Board authorized the study methodology, and all obtained data was treated with complete confidentiality..\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eFunding:\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eNIL.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003cstrong\u003eCompeting interest:\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eNIL.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDuong S, Patel T, Chang F (2017) Dementia: What pharmacists need to know. Can Pharmacists Journal/Revue des Pharmaciens du Can 150(2):118\u0026ndash;129\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnopman DS, Petersen RC (2014) :, Mayo Clin Proc. 2014; 89(10): 1452\u0026ndash;1459\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHugo J, Ganguli M (2014) : Dementia and cognitive impairment: epidemiology, diagnosis, and treatment. 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Journal of the American Academy of Audiology, 28(5), 463\u0026ndash;471. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3766/jaaa.16075\u003c/span\u003e\u003cspan address=\"10.3766/jaaa.16075\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 12 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-egyptian-journal-of-otolaryngology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [The Egyptian Journal of Otolaryngology](https://ejo.springeropen.com/)","snPcode":"43163","submissionUrl":"https://submission.springernature.com/new-submission/43163/3","title":"The Egyptian Journal of Otolaryngology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mild cognitive impairment, Mini-Mental State Examination, Central auditory processing, Central auditory processing disorder, Speech Perception in Noise test, and Gap in Noise test","lastPublishedDoi":"10.21203/rs.3.rs-8810437/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8810437/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cdiv language=\"En\" outputmedium=\"All\" class=\"ArticleTitle\"\u003eStudy of Speech perception in noise (SPIN) test and Gap in noise (GIN) test in mild cognitive impairment in adult\u003c/div\u003e \u003cdiv language=\"En\" class=\"ArticleSubTitle\"\u003eBackground: Mild Cognitive impairment (MCI) is the term for individuals who lie between the cognitive alterations of aging and early dementia. MCI represents markedly heightened risk for worsening over the ensuing occurring of dementia.\u003c/div\u003e","manuscriptTitle":"Study of Speech perception in noise (SPIN) test and Gap in noise (GIN) test in mild cognitive impairment in adult ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 06:20:10","doi":"10.21203/rs.3.rs-8810437/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-01T14:50:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-10T08:54:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"The Egyptian Journal of Otolaryngology","date":"2026-04-09T14:32:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-egyptian-journal-of-otolaryngology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [The Egyptian Journal of Otolaryngology](https://ejo.springeropen.com/)","snPcode":"43163","submissionUrl":"https://submission.springernature.com/new-submission/43163/3","title":"The Egyptian Journal of Otolaryngology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b6f23a6-8005-43ff-9b2c-f9f8429dab50","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"10","date":"2026-05-01T14:50:28+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T06:20:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 06:20:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8810437","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8810437","identity":"rs-8810437","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}