Year :
2024
| Month :
June
| Volume :
18
| Issue :
6
| Page :
KC12 - KC18
Full Version
Carpal Tunnel Syndrome and Associated Factors among Healthcare Practitioners at Vaccine Centres in Saudi Arabia: A Cross-sectional Study
Published: June 1, 2024 | DOI: https://doi.org/10.7860/JCDR/2024/70222.19554
Asma Alonazi, Rahaf Almesned, Ryouf Alhamad, Batool Alyousef, Saif Almutairi, Faizan Kashoo
1. Associate Professor, Department of Physical Therapy and Health Rehabilitation, College of Applied Medical Sciences, Majmaah University, Al-Majmaah, Saudi Arabia.
2. Physical Therapy, Department of Physical Therapy and Health Rehabilitation, Majmaah University, Riyadh, Saudi Arabia.
3. Physical Therapy, Department of Physical Therapy and Health Rehabilitation, Majmaah University, Riyadh, Saudi Arabia.
4. Physical Therapy, Department of Physical Therapy and Health Rehabilitation, Majmaah University, Riyadh, Saudi Arabia.
5. Physical Therapy, Department of Physical Therapy, First Step Centre for Physiotherapy and Medical Rehabilitation, Riyadh, Saudi Arabia.
6. Master Physical Therapy, Department of Physical Therapy and Health Rehabilitation, Majmaah University, Riyadh, Saudi Arabia.
Correspondence Address :
Asma Alonazi,
Associate Professor, Department of Physical Therapy and Health Rehabilitation, College of Applied Medical Sciences, Majmaah University, Al-Majmaah 11952, Saudi Arabia.
E-mail: a.alonazi@mu.edu.sa
Abstract 
Introduction: Carpal Tunnel Syndrome (CTS) presents with symptoms like numbness, tingling, and weakness along the median nerve pathway. Risk factors include prolonged wrist positions, repetitive muscle contractions, and exposure to vibrations.
Aim: To determine the prevalence of CTS among healthcare practitioners at vaccine facilities in Saudi Arabia.
Materials and Methods: A cross-sectional study on a total of 150 healthcare practitioners (aged 25-30 years) working in vaccination centres in Riyadh, Saudi Arabia were recruited. The study was conducted from November 2021 to March 2022. The authors collected demographic data, Body Mass Index (BMI) and work shift information, and administered two validated questionnaires, the Boston Carpal Tunnel Syndrome Questionnaire (BCTSQ) and the Duruoz Hand Index (DHI). CTS symptoms were diagnosed using Phalen’s and Arm Raising Test (ART).
Results: Of the 150 practitioners (aged 25-45 years), predominantly in the 25-30 age group, n=65 (44.0%) tested positive on the Phalen’s test, and n=65 (43.5%) on the ART. Females had higher BCTSQ scores, while DHI scores were similar across genders. Spearman’s correlation analysis showed positive correlations between BCTSQ and DHI, and a moderate negative correlation between ART and DHI. Logistic regression analysed factors affecting the likelihood of CTS diagnosed by ART and Phalen’s Test. Higher BCTSQ and DHI scores increased the likelihood of CTS (ART: BCTSQ OR=0.843, DHI OR=1.064; Phalen’s Test: BCTSQ OR=0.830, DHI OR=1.069).
Conclusion: During the Coronavirus Disease-2019 (COVID-19) pandemic, the prevalence of CTS among healthcare practitioners at vaccine centres in Riyadh, Saudi Arabia reached up to 43-44%. The present study highlights that day shift workers face a higher risk of CTS compared to night shift workers, likely due to heavier daytime workloads. This underscores the need for ergonomic interventions and workload management, especially during high-demand periods like the vaccination campaign, to safeguard healthcare workers’ health and productivity.
Keywords
Boston carpal tunnel syndrome questionnaire, Duruöz hand index, Median nerve, Occupational injury
Introduction
The CTS is diagnosed clinically, primarily based on a symptom complex that encompasses numbness, tingling, and weakness of the thenar muscles, along with a burning sensation within the median nerve distribution (1),(2). These symptoms are often more prevalent at night though they may also manifest during repetitive hand tasks, particularly for individuals engaged in busy, demanding occupations. Numerous risk factors contribute to the prevalence of CTS. Various medical factors can exacerbate CTS. These include conditions like diabetes (3), obesity, rheumatoid arthritis (4), metabolic syndrome, pregnancy, thyroid diseases, trauma, renal failure, mass lesions, leukaemia, and multiple myeloma. These medical factors may further compound the systems and severity of CTS (5),(6). Additionally, environmental factors play a significant role, including prolonged positions involving excessive wrist flexion or extension, repetitive movements of wrist flexor muscles, and exposure to excessive vibration (7). Among these factors, repetitive movements are significant risk factors for the development of CTS (8).
Healthcare practitioners often engage in highly repetitive movements, which include dynamic actions such as using syringe plungers, operating blood pressure bulbs, typing on keyboards, and performing various work-related tasks (9). These repeated movements can contribute to an increased incidence of CTS among this group of healthcare professionals.
Healthcare practitioners exhibit the highest incidence of overexertion injuries, prompting workplace health experts to seek methods to alleviate this risk. Furthermore, healthcare practitioners, particularly in busy settings such as vaccine centres in Riyadh, Saudi Arabia where they routinely administer numerous vaccination doses during one-day clinics, are susceptible to the development of finger, wrist, or forearm pain. As an illustrative example of such a busy setting, after the Saudi Pharmaceutical Industries and Medical Appliances Corporation (SPIMACO) in Saudi Arabia signed agreements approving the usage of the Pfizer-BioNTech vaccine and the AstraZeneca vaccine with associated side-effects (10), and the Moderna vaccine (11), the Saudi coronavirus vaccination campaign commenced in December 2020. Across the kingdom, almost 587 vaccine centres in Saudi Arabia were established, including 12 in Riyadh. From December 2020 to March 2022, these centres in Riyadh, Saudi Arabia administered approximately 10 million vaccine doses, involving about three million working hours and 144 million appointments. In addition, the operation can handle up to 500 thousand appointments per day, and more than 12 million text messages were sent for reservations, motivation, and reminders about the importance of receiving the vaccines (12). The unique occupational environment of vaccine centres in Riyadh, Saudi Arabia , characterised by repetitive hand movements, prolonged equipment use, and ergonomic challenges, presents a fertile ground for the development of CTS (13).
Numerous studies have investigated the prevalence and risk factors of CTS among healthcare practitioners, including nurses, physicians, and allied health professionals (9),(14),(15),(16),(17). However, limited attention has been given to healthcare practitioners specifically those working in vaccine centres in Riyadh, Saudi Arabia, where the demands and stressors of administering vaccinations may exacerbate ergonomic risk factors associated with CTS development. This may be due to their engagement in several mechanical and environmental stressors that workers in other fields do not commonly experience. Despite the growing importance of vaccination efforts, there remains a notable gap in the available literature regarding the prevalence, risk factors, and impact of CTS on the healthcare workforce in these settings. While CTS can affect individuals across various occupations (18),(19),(20), emerging evidence suggests that healthcare practitioners working in vaccine centres in Riyadh, Saudi Arabia may be at a heightened risk of developing this condition. Understanding the factors contributing to the increased prevalence of CTS in this population is crucial for implementing effective prevention and management strategies.
The present study aimed to address the gap by investigating the prevalence and risk factors of CTS among healthcare practitioners working in COVID-19 vaccine centres in Riyadh, Saudi Arabia. By examining the association between occupational factors, such as repetitive hand movements and ergonomic conditions, and the development of CTS symptoms, the present research seeks to provide valuable insights into the occupational health concerns of frontline healthcare workers during the COVID-19 pandemic.
Material and Methods
A cross-sectional study was conducted at the vaccine centres in Riyadh, Saudi Arabia, from November 2021 to March 2022. The Majmaah University Research Ethics Committee (MUREC) in Saudi Arabia reviewed and approved the present study under ethics project # (HA-01-R-088). Also, approval from the Saudi Ministry of Health (MOH) was obtained under project # (21-117E).
Inclusion criteria: The inclusion criteria for the present study comprised healthcare practitioners who worked at the vaccine centres in Riyadh, Saudi Arabia and experienced one or more of the following: numbness and tingling sensation in the median nerve territory of the hand, with or without pain, symptoms induced by repetitive hand movements or malposition, symptoms relieved by resting, rubbing, or shaking the hand, nighttime awakening and sleep disturbance, and weakness in thumb abduction.
Exclusion criteria: The present study excluded participants who presented with sensory or motor complaints in the upper extremities, upper extremity deformities, Parkinson’s disease, peripheral neuropathies, the presence of predisposing factors for peripheral neuropathies (such as hypothyroidism and diabetes), arthritic diseases, other neurologic conditions, a history of wrist or arm trauma, peripheral nerve repair, or pregnancy.
Sample size calculation:
Formula to calculate sample size: n=Z2×p×(1-p)/E2+Z2×p×(1-p)/N
n=sample size needed
Z=Z-score corresponding to the desired level of confidence (e.g., 1.96 for a 95% confidence level)
p=estimated population proportion (the proportion of healthcare practitioners experiencing a certain outcome)
E=margin of error (the desired precision or level of accuracy)
N=population size
Assuming a conservative estimated population proportion of 0.5 (to maximise the sample size) and a finite population size of, for instance, 10,000 healthcare practitioners in the Riyadh region, a sample size of approximately 150 was needed to estimate the prevalence of burnout among healthcare practitioners during the COVID-19 pandemic with a 95% confidence level and a margin of error of 5%.
Study Procedure
The participants were interviewed face-to-face. After signing the informed consent, questions on demographic data, including age, height (cm), weight (kg), Body Mass Index (BMI; kg/m2), dominant hand (right, left, or both), and work shift (day, night, or both) were collected. The BCTSQ was used to measure the intensity of symptoms and functional status in CTS (21). The BCTSQ contains two scales: the Symptom Severity Scale (SSS) and the Functional Status Scale (FSS). The SSS comprises 11 items rated on a Likert scale ranging from 1 (normal) to 5 (very serious). Meanwhile, the FSS encompasses eight items, similarly rated on a Likert scale from one (no difficulty) to five (inability to perform the activity). Higher scores on both scales indicate greater impairment in functional abilities (22),(23). Subsequently, the participants were requested to be seated in chairs in a relaxed and comfortable position, with their elbows flexed to allow maximal wrist flexion. Then, the DHI was utilised to assess activity limitations and hand-related impairment. The DHI, a self-report questionnaire consisting of 18 items, yields higher scores indicative of greater hand-related disability (24). Following the questionnaire administration, Phalen’s test was conducted, wherein participants were instructed to hold their hands at the wrist in extreme flexion for one minute. This manoeuvre is considered positive often when it reproduces painful symptoms, including nocturnal pain and paresthesia, typically localised to the thumb, index, and middle fingers but occasionally extending to the entire hand (25). Finally, ART was administered by instructing participants to elevate both hands above their heads for one minute. The test result was considered positive if paresthesia, numbness, or dull pain occurred (24). ART is the most sensitive and specific test for diagnosing CTS, with a reported positive predictive value of 98.3%, a negative predictive value of 81.9%, and an accuracy of 91.4% (26).
Statistical Analysis
The data were analysed using Statistical Package for Social Sciences (SPSS) version 19.0 Descriptive statistics were utilised to summarise the demographic data. The correlation between tests and questionnaires was determined using the Spearman’s correlation coefficient. Additionally, a binary logistic regression analysis was conducted to assess the predictive strength of demographic variables and workplace factors on the occurrence of CTS, as diagnosed by the ART and Phalen’s Test. All assumptions necessary for conducting binary logistic regression analysis were satisfied by the data. The significance level was set at 0.05.
Results
Participant characteristics: The study involved 150 healthcare practitioners at different vaccination centres in Riyadh, Saudi Arabia in the Riyadh region during the COVID-19 pandemic. Most participants 79 (52.7%), belonged to the age group between 25 and 30 years, while only a small number of participants 7 (4.7%), belonged to the age group between 46 and 50 years. Most participants in the study were female (n=94), 62.6%. The mean score of female participants on the BCTSQ was higher (mean=30.3.1, SD=12.5) than that of male participants (mean=25.1, SD=7.0). However, no statistically significant difference was found for DHI between genders, p=0.373 (Table/Fig 1).
The demographic distinctions among participants diagnosed with CTS classified as positive or negative, all of whom were employed at a vaccination centre during the COVID-19 pandemic is presented in [Table/Fig-2,3]. Individuals with positive CTS 65 (43.33%), as determined by the Phalen’s test, exhibited higher weight (mean=68.3, SD=15.6), BMI, and scored higher on the Boston Self-assessment Questionnaire and the DHI Questionnaire compared to those with negative CTS. Conversely, participants with positive CTS identified through the ART (n=46, 44%) did not display differences in weight (mean) or BMI but demonstrated higher scores on both questionnaires in comparison to individuals with negative CTS diagnosed via the ART.
Assessment of binary logistic regression: Logistic regression was performed to determine the effects of age, height, weight, BMI, gender, hand dominance, work shift, and BCTSQ and DHI scores on the likelihood that participants had CTS as diagnosed by ART (Table/Fig 4). The logistic regression model was statistically significant {χ2 (14)=44.326, p<0.001}. The model explained 34.3% (Nagelkerke R2) of the variance in CTS and correctly classified 75.3% of cases. A significant difference (p=0.021) was observed in the likelihood of developing CTS between shift workers, with day shift workers being 4.244 times more likely to develop CTS than those on other shifts. In addition, increasing scores on the BCTSQ and DHI were associated with an increased likelihood of exhibiting CTS, by 0.843 and 1.064 times, respectively. Similarly, for Phalen’s Test (Table/Fig 5), the logistic regression model was statistically significant {χ2 (14)=59.737, p<0.001}. The model explained 44.1% (Nagelkerke R2) of the variance in CTS and correctly classified 74.7% of cases. Increasing scores on the BCTSQ and DHI were associated with an increased likelihood of exhibiting CTS by 0.830 and 1.069 times, respectively (Table/Fig 5).
Spearman’s correlation analysis indicated that there was a strong, significant positive correlation between scores on the BCTSQ and the DHI (r=0.764, n=150, p<0.01), and a moderate, significant negative correlation between the DHI and ART (r=-0.308, n=150, p<0.01). Other significant correlations are shown in (Table/Fig 6).
Discussion
The present study aimed to determine the prevalence of CTS among Saudi vaccination practitioners during the COVID-19 pandemic, with the participation of 150 healthcare professionals. Phalen’s test, the BCTSQ, and the Disabilities of the Arm, Shoulder, and Hand (DHI) were utilised to evaluate CTS prevalence among the participants.
The findings revealed a high prevalence of CTS among participants, with 43.5% (n=65) exhibiting classical symptoms of CTS according to Phalen’s Test and 44.0% (n=66) according to the Arm Raise Test (ART). A summary of the table is provided indicating a prevalence ranging from 4.5 to 26.7% (Table/Fig 7) (27),(28),(30),(31),(32),(33),(34),(35),(36),(37),(38),(39).
Females scored higher on the BCTSQ than males, indicating a higher likelihood of developing CTS. These findings align with Schulze DG and Nilsen KB (2021), who evaluated the clinical utility of the CTS-6 and BCTSQ for assessing disease intensity in a Norwegian population (40). Similarly, a study in Saudi Arabia demonstrated that females experience higher rates of CTS compared to males (19), with female Saudi dentists being over twice as likely as their male counterparts to develop CTS symptoms. However, McDiarmid M et al., (2000) found no correlation between gender and CTS (41). Furthermore, evaluations of symptom severity using the BCTSQ and diagnostic screening with hand diagrams also yielded higher scores for females (42), while it appears that CTS incidence in males rises with age (43). The highest incidence of CTS occurs among the working population aged 25 to 45 years, with similar risk levels between males and females (18). Compared to the non working population, individuals engaged in employment exhibit a significantly elevated risk of developing CTS (44). Healthcare practitioners are particularly susceptible to CTS in their occupational settings compared to those in other professions (45). Gender differences play a significant role in CTS prevalence, with approximately 4-5% of the global population affected, showing a prevalence of 6% in males and 9.2% in females (46). Multiple studies consistently report that females are more prone to CTS than males (41),(43),(47),(48),(49),(50), possibly due to the inherently smaller cross-sectional space of the carpal tunnel in females compared to males, as observed in Magnetic Resonance Imaging (MRI) scans (48). The increased risk of CTS in pregnant and nursing females, as well as those in the first year of menopause, individuals using oral contraceptives, or undergoing hormone replacement therapy, suggests that hormonal factors may contribute to these gender disparities (51). Conversely, CTS prevalence in males tends to rise with age (43).
The prevalence of CTS was higher in ART when compared to Phalen’s test. This finding aligns with Ahn DS (2001), who found ART to be more sensitive and specific for identifying CTS than Phalen’s and Tinel’s tests (52). Additionally, Amirfeyz R et al., reported ART’s superiority over questionnaires and other clinical tests (53). Arab AA et al., (2018) concluded that ART as the most accurate test for CTS after studying 123 patients (26). In the present study, day shift workers were more prone to CTS due to heavier workloads, especially during the increased work hours of the COVID-19 vaccination period in Saudi Arabia. Shift and long-hour workers tested positive on ART for CTS, while night shift workers showed lower susceptibility. Similarly, in a study by Alhusain FA et al., experienced dentists experienced more CTS symptoms than younger ones (19).
Although there is a correlation between years of service and CTS incidence, no relationship was found between workload and the occurrence of CTS (54). Recent cases of CTS have shown an increase in Work-related Musculoskeletal Disorders (WMSDs), attributed to heightened strain and repetitive movements among individuals. Many healthcare professionals have reported WMSDs in atleast one body region (14). Working in the same position for prolonged periods and handling an excessive number of patients or samples per day were the most frequently reported work risk factors contributing to the development of WMSDs.
There was no statistically significant difference in the occurrence of CTS with hand dominance. This disagrees with a previous study on Saudi dentists, which reported that left-handedness was strongly associated with CTS symptoms, with an estimated Odds Ratio (OR) of 6.28 (95% CI 1.24-31.90) (19). Right-handed female nurse anaesthetists were more likely to have left-hand and bilateral CTS than operating room nurses, with an odds ratio of 3.85 (CI, 1.05-12.16) (15). The disparity may be attributable to the difference in physical work between the two occupations and the repetitive nature of the job performed in vaccination facilities. Furthermore, it’s worth noting that the sample distribution in this study was uneven, with the majority of the population being right-handed.
Limitation(s)
The present study is subject to certain limitations. Firstly, the absence of Nerve Conduction Velocity (NCV) testing, which is widely recognised for its superior sensitivity and specificity in diagnosing CTS (55),(56). Secondly, a previous study has reported a correlation between work-related pain and specific healthcare professions, such as Nurses, Dentists, and Physiotherapists (14). However, the present study did not document the specific occupations of the healthcare professionals participating in the research.
This gap in information limits our ability to explore potential associations between occupation and the prevalence of CTS. Future investigations should consider including this critical occupational data to gain deeper insights into this relationship. It’s worth noting that employing objective tools, like Electromyography (EMG) and NCV, is essential for confirming CTS diagnosis without introducing bias.
To address these limitations, future studies should incorporate these objective diagnostic tools to enhance the reliability of their findings. To introduce the incidence of work-related musculoskeletal pains in healthcare professionals, particularly those at high-risk, it is imperative to develop an awareness and education program aimed at prevention and effective management. Such a program is essential not only for the well-being of the healthcare workforce but also to enhance patient care efficiency.
Conclusion
Throughout the COVID-19 pandemic, a notable prevalence of CTS was observed, reaching as high as 43-44% among healthcare practitioners at vaccine centres in Riyadh, Saudi Arabia. The present study in Saudi Arabia revealed that day shift workers are at a higher risk of developing CTS compared to those on night shifts, potentially due to heavier workloads during daytime hours. This emphasises the importance of implementing measures to alleviate strain and promote ergonomic practices, especially during periods of increased workload such as the COVID-19 vaccination campaign. Healthcare organisations should prioritise strategies to mitigate the risk of CTS among their staff, including regular assessments, ergonomic interventions, and workload management, to ensure a healthy and productive workforce.
Acknowledgement
The authors extend their profound and heartfelt gratitude to MOH for their unwavering support. Additionally, they would like to express their appreciation to the Elm and Adeed companies. They are also deeply grateful to the directors of Riyadh’s vaccine centres for their invaluable assistance in facilitating and easing the sample collection process for the study. Furthermore, they would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under Project Number R-2024-1055.
Authors’ contribution: RaA, RyA, and BA conceived of the idea. AA, RaA, RyA, and BA planned the experiments and developed the theory. RaA, RyA, BA, and SA collected the data. AA and Faizan Kashoo verified the analytical methods and performed the computations. AA supervised the findings of the present work. RaA, RyA, and BA wrote the manuscript with support from AA. AA finalise the writing. All authors discussed the results and contributed to the final manuscript.
Reference
|
| | 1. | Padua L, Coraci D, Erra C, Pazzaglia C, Paolasso I, Loreti C, et al. Carpal tunnel syndrome: Clinical features, diagnosis, and management. Lancet Neurol. 2016;15(12):1273-84.
[ CrossRef] [ PubMed] | | 2. | Wipperman J, Goerl K. Carpal tunnel syndrome: Diagnosis and management. Am Fam Physician. 2016;94(12):993-9.
| | 3. | Zimmerman M, Gottsäter A, Dahlin LB. Carpal tunnel syndrome and diabetes- A comprehensive review. J Clin Med. 2022;11(6):1674.
[ CrossRef] [ PubMed] | | 4. | Smerilli G, Di Matteo A, Cipolletta E, Carloni S, Incorvaia A, Di Carlo M, et al. Ultrasound assessment of carpal tunnel in rheumatoid arthritis and idiopathic carpal tunnel syndrome. Clin Rheumatol. 2021;40(3):1085-92.
[ CrossRef] [ PubMed] | | 5. | MacDermid JC, Wessel J. Clinical diagnosis of carpal tunnel syndrome: A systematic review. J Hand Ther. 2004;17(2):309-19.
[ CrossRef] [ PubMed] | | 6. | Yurdakul FG, Bodur H, Çakmak ÖÖ, Ates¸ C, Sivas F, Eser F, et al. On the severity of carpal tunnel syndrome: Diabetes or metabolic syndrome. J Clin Neurol Seoul Korea. 2015;11(3):234.
[ CrossRef] [ PubMed] | | 7. | Geoghegan JM, Clark DI, Bainbridge LC, Smith C, Hubbard R. Risk factors in carpal tunnel syndrome. J Hand Surg. 2004;29(4):315-20.
[ CrossRef] [ PubMed] | | 8. | Uchiyama S, Itsubo T, Nakamura K, Kato H, Yasutomi T, Momose T. Current concepts of carpal tunnel syndrome: Pathophysiology, treatment, and evaluation. J Orthop Sci. 2010;15(1):01-13.
[ CrossRef] [ PubMed] | | 9. | Abbas MAF, Afifi AA, Zhang ZW, Kraus JF. Meta-analysis of published studies of work related carpal tunnel syndrome. Int J Occup Environ Health. 1998;4(3):160-67.
[ CrossRef] [ PubMed] | | 10. | Darraj MA, Al-Mekhlafi HM. Prospective evaluation of side-effects following the first dose of Oxford/AstraZeneca COVID-19 vaccine among healthcare workers in Saudi Arabia. Vaccines. 2022;10(2):223.
[ CrossRef] [ PubMed] | | 11. | Aldali J, Meo SA, Al-Khlaiwi T. Adverse effects of Pfizer (BioNTech), Oxford-AstraZeneca (ChAdOx1 CoV-19), and Moderna COVID-19 vaccines among the adult population in Saudi Arabia: A cross-sectional study. Vaccines. 2023;11(2):231.
[ CrossRef] [ PubMed] | | 12. | Assiri A, Al-Tawfiq JA, Alkhalifa M, Al Duhailan H, Al Qahtani S, Dawas RA, et al. Launching COVID-19 vaccination in Saudi Arabia: Lessons learned, and the way forward. Travel Med Infect Dis. 2021;43:102119.
[ CrossRef] [ PubMed] | | 13. | Wright MC. Hand intensive leisure activities and repetitive motion injuries of the distal upper extremities. Loma Linda University Electronic Theses, Dissertations & Projects. 2001.
| | 14. | Yasobant S, Rajkumar P. Work-related musculoskeletal disorders among health care professionals: A cross-sectional assessment of risk factors in a tertiary hospital, India. Indian J Occup Environ Med. 2014;18(2):75-81.
[ CrossRef] [ PubMed] | | 15. | Diaz JH. Carpal tunnel syndrome in female nurse anesthetists versus operating room nurses: Prevalence, laterality, and impact of handedness. Anesth Analg. 2001;93(4):975-80.
[ CrossRef] [ PubMed] | | 16. | Lalumandier JA, McPhee SD. Prevalence and risk factors of hand problems and carpal tunnel syndrome among dental hygienists. J Dent Hyg. 2001;75(2):130-34.
| | 17. | Kurtul S, Mazican N. Prevalence and risk factors for self-reported symptoms of carpal tunnel syndrome among hospital office workers: A cross-sectional study. Int J Occup Saf Ergon. 2023;29(2):461-65.
[ CrossRef] [ PubMed] | | 18. | Patil A, Rosecrance J, Douphrate D, Gilkey D. Prevalence of carpal tunnel syndrome among dairy workers. Am J Ind Med. 2012;55(2):127-35.
[ CrossRef] [ PubMed] | | 19. | Alhusain FA, Almohrij M, Althukeir F, Alshater A, Alghamdi B, Masuadi E, et al. Prevalence of carpal tunnel syndrome symptoms among dentists working in Riyadh. Ann Saudi Med. 2019;39(2):104-11.
[ CrossRef] [ PubMed] | | 20. | Lee IH, Kim YK, Kang DM, Kim SY, Kim IA, Kim EM. Distribution of age, gender, and occupation among individuals with carpal tunnel syndrome based on the National Health Insurance data and National Employment Insurance data. Ann Occup Environ Med. 2019;31:e31.
[ CrossRef] [ PubMed] | | 21. | Levine DW, Simmons BP, Koris MJ, Daltroy LH, Hohl GG, Fossel AH, et al. A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome. JBJS. 1993;75(11):1585-92.
[ CrossRef] [ PubMed] | | 22. | Erensoy H. Translation and validation of the Arabic version of the Boston carpal tunnel syndrome questionnaire. Neurosci J. 2019;24(4):296-301.
[ CrossRef] [ PubMed] | | 23. | Leite JC de C, Jerosch-Herold C, Song F. A systematic review of the psychometric properties of the Boston Carpal Tunnel Questionnaire. BMC Musculoskelet Disord. 2006;7:78.
[ CrossRef] [ PubMed] | | 24. | Gökşenoğlu G, Paker N, Çelik B, Buğdayci D, Demircioğlu D, Kesiktaş N. Reliability and validity of Duruoz Hand Index in carpal tunnel syndrome. Turk J Phys Med Rehabil. 2018;64(3):277.
[ CrossRef] [ PubMed] | | 25. | Wiesman IM, Novak CB, Mackinnon SE, Winograd JM. Sensitivity and specificity of clinical testing for carpal tunnel syndrome. Can J Plast Surg. 2003;11(2):70-72.
[ CrossRef] [ PubMed] | | 26. | Arab AA, Elmaghrabi MM, Eltantawy MH. Carpal tunnel syndrome: Evaluation of its provocative clinical tests. Egypt J Neurosurg. 2018;33:01-04.
[ CrossRef] | | 27. | Aghilinejad M, Choobineh AR, Sadeghi Z, Nouri MK, Ahmadi AB. Prevalence of musculoskeletal disorders among Iranian steel workers. Iran Red Crescent Med J. 2012;14(4):198.
| | 28. | Harris-Adamson C, Eisen EA, Dale AM, Evanoff B, Hegmann KT, Thiese MS, et al. Personal and workplace psychosocial risk factors for carpal tunnel syndrome: A pooled study cohort. Occup Environ Med. 2013;70(8):529-37.
[ CrossRef] [ PubMed] | | 29. | Hegmann KT, Thiese MS, Kapellusch J, Merryweather AS, Bao S, Silverstein B, et al. Association between cardiovascular risk factors and carpal tunnel syndrome in pooled occupational cohorts. J Occup Environ Med. 2016;58(1):87-93.
[ CrossRef] [ PubMed] | | 30. | Trinkoff AM, Lipscomb JA, Geiger-Brown J, Storr CL, Brady BA. Perceived physical demands and reported musculoskeletal problems in registered nurses. Am J Prev Med. 2003;24(3):270-75.
[ CrossRef] [ PubMed] | | 31. | Smith DR, Wei N, Kang L, Wang RS. Musculoskeletal disorders among professional nurses in mainland China. J Prof Nurs. 2004;20(6):390-95.
[ CrossRef] [ PubMed] | | 32. | Bonfiglioli R, Mattioli S, Armstrong TJ, Graziosi F, Marinelli F, Farioli A, et al. Validation of the ACGIH TLV for hand activity level in the OCTOPUS cohort: A two-year longitudinal study of carpal tunnel syndrome. Scand J Work Environ Health. 2013;39(2):155-63.
[ CrossRef] [ PubMed] | | 33. | Roquelaure Y, Ha C, Pelier-Cady M, Nicolas G, Descatha A, Leclerc A, et al. Work increases the incidence of carpal tunnel syndrome in the general population. Muscle Nerve. 2008;37(4):477-82.
[ CrossRef] [ PubMed] | | 34. | Burt S, Crombie K, Jin Y, Wurzelbacher S, Ramsey J, Deddens J. Workplace and individual risk factors for carpal tunnel syndrome. Occup Environ Med. 2011;68(12):928-33.
[ CrossRef] [ PubMed] | | 35. | Violante FS, Farioli A, Graziosi F, Marinelli F, Curti S, Armstrong TJ, et al. Carpal tunnel syndrome and manual work: The OCTOPUS cohort, results of a ten-year longitudinal study. Scand J Work Environ Health. 2016;42(4):280-90.
[ CrossRef] [ PubMed] | | 36. | Gerr F, Marcus M, Monteilh C. Epidemiology of musculoskeletal disorders among computer users: Lesson learned from the role of posture and keyboard use. J Electromyogr Kinesiol. 2004;14(1):25-31.
[ CrossRef] [ PubMed] | | 37. | Franzblau A, Salerno DF, Armstrong TJ, Werner RA. Test-retest reliability of an upper-extremity discomfort questionnaire in an industrial population. Scand J Work Environ Health. 1997;23(4):299-307.
[ CrossRef] [ PubMed] | | 38. | Nordander C, Ohlsson K, Åkesson I, Arvidsson I, Balogh I, Hansson GÅ, et al. Exposure-response relationships in work-related musculoskeletal disorders in elbows and hands-A synthesis of group-level data on exposure and response obtained using uniform methods of data collection. Appl Ergon. 2013;44(2):241-53.
[ CrossRef] [ PubMed] | | 39. | Roquelaure Y, Mariel J, Fanello S, Boissiere JC, Chiron H, Dano C, et al. Active epidemiological surveillance of musculoskeletal disorders in a shoe factory. Occup Environ Med. 2002;59(7):452-58.
[ CrossRef] [ PubMed] | | 40. | Schulze DG, Nilsen KB. Clinical utility of the 6-item CTS, Boston-CTS, and hand-diagram for carpal tunnel syndrome. Front Neurol. 2021;12:683807.
[ CrossRef] [ PubMed] | | 41. | McDiarmid M, Oliver M, Ruser J, Gucer P. Male and female rate differences in carpal tunnel syndrome injuries: Personal attributes or job tasks? Environ Res. 2000;83(1):23-32.
[ CrossRef] [ PubMed] | | 42. | An TW, Evanoff BA, Boyer MI, Osei DA. The prevalence of cubital tunnel syndrome: A cross-sectional study in a US metropolitan cohort. JBJS. 2017;99(5):408-16.
[ CrossRef] [ PubMed] | | 43. | Çirakli A, Ulusoy EK, Ekinci Y. The role of electrophysiological examination in the diagnosis of carpal tunnel syndrome: Analysis of 2516 patients. Niger J Clin Pract. 2018;21(6):731-34.
[ CrossRef] [ PubMed] | | 44. | Pazzaglia C, Caliandro P, Padua L. Work increases the incidence of carpal tunnel syndrome in the general population. Muscle Nerve. 2008;38(4):1345-46.
| | 45. | Franklin GM, Haug J, Heyer N, Checkoway H, Peck N. Occupational carpal tunnel syndrome in Washington State, 1984-1988. Am J Public Health. 1991;81(6):741-46.
[ CrossRef] [ PubMed] | | 46. | Genova A, Dix O, Saefan A, Thakur M, Hassan A. Carpal tunnel syndrome: A review of literature. Cureus. 2020;12(3):e7333.
[ CrossRef] | | 47. | Moghtaderi A, Izadi S, Sharafadinzadeh N. An evaluation of gender, body mass index, wrist circumference and wrist ratio as independent risk factors for carpal tunnel syndrome. Acta Neurol Scand. 2005;112(6):375-79.
[ CrossRef] [ PubMed] | | 48. | Sassi SA, Giddins G. Gender differences in carpal tunnel relative cross-sectional area: A possible causative factor in idiopathic carpal tunnel syndrome. J Hand Surg Eur. 2016;41(6):638-42.
[ CrossRef] [ PubMed] | | 49. | Mitake T, Iwatsuki K, Hirata H. Differences in characteristics of carpal tunnel syndrome between male and female patients. J Orthop Sci. 2020;25(5):843-46.
[ CrossRef] [ PubMed] | | 50. | Yang C, Chen HH, Lee MC, Kao HK, Lin YT, Chen CT, et al. Risk factors of carpal tunnel syndrome in Taiwan: A population-based cohort study. Ann Plast Surg. 2022;88(1):74-78.
[ CrossRef] [ PubMed] | | 52. | Nordstrom DL, Vierkant RA, DeStefano F, Layde PM. Risk factors for carpal tunnel syndrome in a general population. Occup Environ Med. 1997;54(10):734-40.
[ CrossRef] [ PubMed] | | 52. | Ahn DS. Hand elevation: A new test for carpal tunnel syndrome. Ann Plast Surg. 2001;46(2):120-24.
[ CrossRef] [ PubMed] | | 53. | Amirfeyz R, Clark D, Parsons B, Melotti R, Bhatia R, Leslie I, et al. Clinical tests for carpal tunnel syndrome in contemporary practice. Arch Orthop Trauma Surg. 2011;131(4):471-74.
[ CrossRef] [ PubMed] | | 54. | Sari RK, Prasetio DB, Wardani RS. Workload, repetitive wrist movements, years of service with carpal tunnel syndrome. J Ris Kesehat. 2020;9(2):159-64.
[ CrossRef] | | 55. | Padua L, Lo Monaco M, Padua R, Gregori B, Tonali P. Neurophysiological classification of carpal tunnel syndrome: Assessment of 600 symptomatic hands. Ital J Neurol Sci. 1997;18(3):145-50.
[ CrossRef] [ PubMed] | | 56. | Kuroiwa T, Nimura A, Takahashi Y, Sasaki T, Koyama T, Okawa A, et al. Device development for detecting thumb opposition impairment using carbon nanotube-based strain sensors. Sensors. 2020;20(14):3998. [ CrossRef] [ PubMed] |
DOI: 10.7860/JCDR/2024/70222.19554
Date of Submission: Feb 18, 2024
Date of Peer Review: Mar 12, 2024
Date of Acceptance: Apr 19, 2024
Date of Publishing: Jun 01, 2024
AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? Yes
• For any images presented appropriate consent has been obtained from the subjects. NA
PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: Feb 19, 2024
• Manual Googling: Mar 18, 2024
• iThenticate Software: Apr 17, 2024 (10%)
ETYMOLOGY: Author Origin
EMENDATIONS: 6
|