Dermatology: Practical and Conceptual Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 1 Retrospective Analysis of Onychomycosis Risk Factors Using the 2003-2014 National Inpatient Sample Vrusha K. Shah1, Amar D. Desai2, Shari R. Lipner3 1 University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 2 Rutgers New Jersey Medical School, Newark, NJ, USA 3 Weill Cornell Medicine, Department of Dermatology, New York, NY, USA Key words: onychomycosis, comorbidity, dermatophytosis, nail, national Citation: Shah KV, Desai AD, Lipner SR. Retrospective Analysis of Onychomycosis Risk Factors Using the 2003-2014 National Inpatient Sample. Dermatol Pract Concept. 2024;14(2):e2024074. DOI: https://doi.org/10.5826/dpc.1402a74 Accepted: October 14, 2023; Published: April 2024 Copyright: ©2024 Shah et al. This is an open-access article distributed under the terms of the Creative Commons Attribution- NonCommercial License (BY-NC-4.0), https://creativecommons.org/licenses/by-nc/4.0/, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original authors and source are credited. Funding: None. Competing Interests: None. Authorship: All authors have contributed significantly to this publication. Corresponding Author: Shari R. Lipner, MD, PhD, Associate Professor of Clinical Dermatology, Weill Cornell Medicine, 1305 York Avenue, 9th Floor, New York, NY 10012. Tel. (646) 962-3376 E-mail: shl9032@med.cornell.edu Introduction: Onychomycosis, a fungal nail infection, is associated with significant morbidity and negative impact on quality of life. Therefore, understanding associated risk factors may inform onychomycosis screening guidelines. Objectives: This retrospective study investigated common demographic and comorbidity risk factors among hospitalized patients using the National Inpatient Sample. Methods: The 2003-2014 National Inpatient Sample (NIS) database was used to identify onychomy- cosis cases and age and sex matched controls in a 1:2 ratio. Chi-square tests and T-tests for indepen- dent samples were utilized to compare categorical and continuous patient factors. Demographic and comorbidity variables significant (P < 0.05) on univariate analysis were analyzed via a multivariate regression model with Bonferroni correction (P < 0.0029). Results: 119,662 onychomycosis cases and 239,324 controls were identified. Compared to controls, onychomycosis patients frequently were White (69.0% versus 68.0%; P < 0.001), Black (17.9% versus 5.8%; P < 0.0001), and insured by Medicare or Medicaid (80.1% versus 71.1%; P < 0.0001). Patients had greater hospital stays (9.69 versus 5.39 days; P < 0.0001) and costs ($39,925 versus $36,720; P < 0.001) compared to controls. On multivariate analysis, onychomycosis was commonly associated with tinea pedis (odds ratio [OR]: 111.993; P < 0.0001), human immunodeficiency virus (OR: 4.372; P < 0.001), venous insufficiency (OR: 6.916; P < 0.0001), and psoriasis (OR: 3.668; P < 0.001). Conclusions: Onychomycosis patients had longer hospital stays and greater costs compared to controls. Black patients were disproportionately represented among cases compared to controls. Onychomy- cosis was associated with tinea pedis, venous insufficiency, human immunodeficiency virus, psoriasis, obesity (body mass index [BMI] ≥ 30 kg/m2), peripheral vascular disease, and diabetes with chronic complications, suggesting that inpatients with onychomycosis should be screened for these conditions. ABSTRACT 2 Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 Introduction Onychomycosis, a fungal nail infection, is the most fre- quent nail condition seen in the clinical setting worldwide [1-4]. Onychomycosis is not just a cosmetic problem, and patients often have poor quality of life both physically and psychologically. Fortunately, timely and adequate treat- ment treats diseases and alleviates patient distress [5-7]. Onychomycosis prevalence is more common among me8 and increases with older age [8-10], and was the most com- mon nail diagnosis among ambulatory care patients in the United States from 2007-2016 [11]. Previous studies have analyzed associations of comorbidity risk factors with ony- chomycosis and their impact on prognosis [12-18]. A com- prehensive analysis of risk factors among a large, matched, and nationally representative cohort of hospitalized ony- chomycosis patients may help to develop screening guide- lines in the United States. Objectives The primary objective was to identify risk factors associated with development of onychomycosis among hospitalized pa- tients compared to age and gender matched controls. The secondary objective was to characterize demographics of on- ychomycosis patients compared to controls. Methods The 2003-2014 National Inpatient Sample (NIS) database, a publicly available all-payer inpatient healthcare database developed for the Healthcare Cost and Utilization Project (HCUP) that contains unweighted data for about 7 million hospital stays each year [19], was utilized for this retrospec- tive analysis. NIS was queried using International Classifi- cation of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 110.1 for “Dermatophytosis of nail”, yielding 119,687 cases. Cases were matched to controls in a 1:2 ratio by age and sex. We analyzed demographics (age, sex, race), other patient information (quarter of discharge, length of stay, hospital costs/deaths, hospital region, insur- ance type), and associated comorbidities. The most common comorbidities associated with a di- agnosis of onychomycosis from available variables in the National Inpatient Sample were identified through a de- scending counts frequency analysis. Co-morbidities of inter- est that were unavailable through NIS including tinea pedis, hyperhidrosis, venous insufficiency, and psoriasis were iden- tified through ICD-9-CM codes which were recoded into new variables (Table 1). Statistical analyses were completed using IBM SPSS soft- ware v28.0.1.1. Patient distribution of demographic factors (age, sex, race), other patient information (quarter of dis- charge, hospital deaths, hospital region, insurance type), and Table 1. Comorbidity Variables Including Relevant ICD-9 Codes Variable ICD-9 Codes for Each Variable Tinea Pedis 110.4 Hyperhidrosis 780.8, 705.21, 705.22 Diabetes with chronic complications Co-morbidity variable provided by the National Inpatient Sample database Diabetes without chronic complications Co-morbidity variable provided by the National Inpatient Sample database Human Immunodeficiency virus/AIDS 042, V08 Peripheral Vascular Disease Co-morbidity variable provided by the National Inpatient Sample database Venous insufficiency 454.0, 454.1, 454.2, 454.8, 454.9, 459.10, 459.11, 459.12, 459.13, 459.19, 459.2, 459.30, 459.31, 459.32, 459.33, 459.39, 459.81, 459.89 Obesity (body mass index ≥ 30 kg/m2)‡ Co-morbidity variable provided by the National Inpatient Sample database Psoriasis 696.0, 696.1 Deficiency Anemias Co-morbidity variable provided by the National Inpatient Sample database Hypertension Co-morbidity variable provided by the National Inpatient Sample database Chronic Pulmonary Disease Co-morbidity variable provided by the National Inpatient Sample database Congestive Heart Failure Co-morbidity variable provided by the National Inpatient Sample database Depression Co-morbidity variable provided by the National Inpatient Sample database Hypothyroidism Co-morbidity variable provided by the National Inpatient Sample database Renal Failure Co-morbidity variable provided by the National Inpatient Sample database Fluid and Electrolyte Disorders Co-morbidity variable provided by the National Inpatient Sample database Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 3 associated comorbidities were compared between cases and controls using chi-square tests with a 0.05 level of signifi- cance. T-tests for independent samples were used to com- pare distributions of continuous variables including length of stay and hospital costs between cases and controls with a 0.05 level of significance. Demographic factors including age, sex, and race as well as co-morbidity variables were an- alyzed using univariate logistic regression with a 0.05 level of significance. Variables significant on univariate logistic re- gression were included in the multivariate regression model, performed with Bonferroni correction (P < 0.0029). The authors confirm that the ethical policies of the jour- nal have been followed. As this study was IRB exempt due to utilization of publicly available and deidentified data, no ethical approval was needed. Results We identified a total of 119,662 onychomycosis cases and 239,324 controls (Table 2). Age and sex were matched be- tween onychomycosis cases and controls with 56.7% males (P = 1.000) and 63.1% being 65 years or older (P = 1.000). Onychomycosis versus control patients were most fre- quently White (69.0% versus 68.0%; P < 0.001), followed by Black (17.9% versus 5.8%; P < 0.0001) and Native American (0.5% versus0.3%; P < 0.001), and were less likely to be Hispanic (9.1% versus 17.4%; P < 0.0001) and Asian or Pacific Islander (1.0% versus 6.7%; P < 0.0001). There was an even distribution of quarter of discharge be- tween cases and controls though onychomycosis cases were slightly more likely to be discharged in the winter months Table 2. Patient Descriptive Factor Distributions among Onychomycosis Patients Compared to Controls (1:2) Variable Onychomycosis Cases (N = 119662) Matched Controls (N = 239324) P value Sex (N, %) Male Female 67807 (56.7%) 51855 (43.3%%) 135614 (56.7%) 103710 (43.3%) 1.000 Age group (years) N, % 0-17 18-64 65+ 427 (0.4%) 43713 (36.5%) 75522 (63.1%) 854 (0.4%) 87426 (36.5%) 151044 (63.1%) 1.000 1.000 1.000 Race (N, %) White Black Hispanic Asian or Pacific Islander Native American Other 69285 (69.0%) 18001 (17.9%) 9121 (9.1%) 995 (1.0%) 465 (0.5%) 2567 (2.6%) 157723 (68.0%) 13482 (5.8%) 40385 (17.4%) 15599 (6.7%) 645 (0.3%) 4226 (1.8%) <0.001 <0.0001 <0.0001 <0.0001 <0.001 <0.001 Quarter of Discharge (N, %) 1 (January-March) 2 (April - June) 3 (July-September) 4 (October-December) 31706 (26.5%) 29752 (24.9%) 29123 (24.4%) 28891 (24.2%) 60321 (25.2%) 59652 (24.9%) 59021 (24.7%) 60330 (25.2%) <0.001 0.884 0.062 <0.001 Hospital data Length of stay (days ± standard error (SE)) Hospital costs (dollars ± SE) Hospitalization deaths (N, %) 9.69 ± 0.041 39925 ± 187.920 1624 (1.4%) 5.39 ± 0.016 36720 ± 119.819 9793 (4.1%) <0.0001 <0.001 <0.0001 Hospital region N, %) Northeast Midwest or North Central South West 31453 (26.3%) 39012 (32.6%) 33116 (27.7%) 16081 (13.4%) 4606 (1.9%) 1292 (0.5%) 8297 (3.5%) 225129 (94.1%) <0.0001 <0.0001 <0.0001 <0.0001 Insurance type (N, %) Government Medicare Medicaid Private Other type 95833 (80.1%) 83313 (69.6%) 12520 (10.5%) 17104 (14.3%) 6552 (5.5%) 170119 (71.1%) 147636 (61.7%) 22483 (9.4%) 54550 (22.8%) 14552 (6.1%) <0.0001 <0.0001 <0.01 <0.0001 <0.001 4 Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 Table 3. Patient Comorbidity Distribution among Onychomycosis Patients Compared to Controls (1:2) Comorbidities Onychomycosis Cases (N = 119662) Matched Controls (N = 239324) P value Tinea Pedis 8204 (6.9%) 167 (0.1%) <0.001 Hyperhidrosis 54 (<0.01%) 114 (<0.01%) 0.743 Diabetes with chronic complications 14942 (12.6%) 11425 (4.8%) <0.0001 Diabetes without chronic complications 26505 (22.3%) 44934 (18.8%) <0.001 Human Immunodeficiency virus/AIDS 1457 (1.2%) 715 (0.3%) <0.001 Peripheral Vascular Disease 17681 (14.9%) 13884 (5.8%) <0.0001 Venous insufficiency 9987 (8.3%) 2362 (1.0%) <0.0001 Obesity (body mass index ≥ 30 kg/m2) 17940 (15.1%) 12448 (5.2%) <0.0001 Psoriasis 1286 (1.1%) 678 (0.3%) <0.001 Deficiency Anemias 26423 (22.2%) 36525 (15.3%) <0.0001 Hypertension 72414 (60.8%) 118352 (49.5%) <0.0001 Chronic Pulmonary Disease 27023 (22.7%) 42336 (17.7%) <0.001 Congestive Heart Failure 16846 (14.2%) 23461 (9.8%) <0.0001 Depression 11928 (10.0%) 15476 (6.5%) <0.0001 Hypothyroidism 13846 (11.6%) 22312 (9.3%) <0.001 Renal Failure 15925 (13.4%) 14130 (5.9%) <0.0001 Fluid and Electrolyte Disorders 30396 (25.5%) 44586 (18.6%) <0.0001 from January to March (26.5% versus 25.2%; P < 0.001) and less likely to be discharged in the fall season from Oc- tober to December (24.2% versus 25.2%; P < 0.001). On- ychomycosis patients were also more likely to be publicly insured by Medicare (69.9% versus 61.7%; P < 0.0001) and Medicaid (10.5% versus 9.4%; P < 0.01) and less likely to have private insurance (14.3% versus 22.8%; P < 0.0001) than controls. Furthermore, onychomycosis patients versus controls had greater lengths of stay (9.69 versus 5.39 days; P < 0.0001), greater hospital costs (39,925 versus 36,720 dol- lars; P < 0.001), but fewer hospitalization deaths (1624 ver- sus 9793 deaths; P < 0.0001). A majority of onychomycosis cases were seen in hospitals in the Northeast (26.3% versus 1.9%; P < 0.0001), Midwest or North Central (32.6% ver- sus 0.5%; P < 0.0001), and Southern United States (27.7% versus 3.5%; P < 0.0001). A descending counts frequency analysis used to identify the most common comorbidities associated with onychomy- cosis from variables available in NIS showed that hyperten- sion (60.8%), fluid and electrolyte disorders (25.5%), chronic pulmonary disease (22.7%), diabetes without chronic com- plications (22.3%), deficiency anemias (22.2%), obesity (de- fined as a body mass index (BMI) of greater than 30 kg/m2) (15.1%), peripheral vascular disease (14.9%), congestive heart failure (14.2%), renal failure (13.4%), diabetes with chronic complications (12.6%), hypothyroidism (11.6%), depression (10.0%), and venous insufficiency (8.3%) were most repre- sented and were included in the analysis. Using Chi-square analysis, onychomycosis versus control patients more often had all associated comorbidities studied compared to controls (Table 3). The most commonly represented comorbidities in onychomycosis versus control patients included hypertension (60.8% versus 49.5%; P < 0.0001), fluid and electrolyte dis- orders (25.5% versus 18.6%; P < 0.0001), chronic pulmonary disease (22.7% versus 17.7%; P < 0.001), diabetes without chronic complications (22.3% versus 18.8%; P < 0.001), and deficiency anemias (22.2% versus 15.3%; P < 0.0001). Using univariate and multivariate logistic regression models, Black (odds ratio [OR]: 2.734; P < 0.0001) and Native American (OR: 1.430; P < 0.001) individuals had greater risk of having onychomycosis than White individu- als (Table 4). All comorbidities were significantly associated with greater risk of onychomycosis except hyperhidrosis (OR: 0.947; P = 0.743). The comorbidities most commonly associated with onychomycosis included tinea pedis (OR: 111.993; P < 0.0001), venous insufficiency (OR: 6.916; P < 0.0001), human immunodeficiency virus (OR: 4.372; P < 0.001), psoriasis (OR: 3.668; P < 0.001), obesity (OR: 2.407; P < 0.0001), peripheral vascular disease (OR: 2.294; P < 0.0001), and diabetes with chronic complications (OR: 2.047; P < 0.0001). Conclusions In this representative inpatient cohort, we found that ony- chomycosis was most commonly associated with tinea pedis, human immunodeficiency virus, venous insufficiency, psoria- sis, and diabetes mellitus. Given the longer hospital stays and Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 5 Table 4. Regression Analysis of Onychomycosis Patients Compared to Matched Controls (1:2) Variable Univariate P value Multivariate P value Sex Male Female Reference 1.000 (0.986-1.014) - 1.000 - - - - Age group (yrs) 0-20 21-64 65+ Reference 1.000 (0.890-1.124) 1.000 (0.890-1.124) - 1.000 1.000 - - - - - - Race White Black Hispanic Asian or Pacific Islander Native American Other Reference 3.039 (2.967-3.113) 0.514 (0.502-0.527) 0.145 (0.136-0.155) 1.641 (1.456-1.850) 1.383 (1.316-1.453) - <0.0001 <0.0001 <0.0001 <0.001 <0.001 Reference 2.734 (2.663-2.807) 0.472 (0.460-0.486) 0.143 (0.134-0.153) 1.430 (1.254-1.630) 1.377 (1.304-1.453) - <0.0001 <0.0001 <0.0001 <0.001 <0.001 Comorbidities Tinea Pedis Hyperhidrosis Diabetes without chronic complications Diabetes with chronic complications Hypertension Obesity (body mass index ≥ 30 kg/m2) Human Immunodeficiency Virus/AIDS Peripheral Vascular Disease Venous Insufficiency Psoriasis Depression Renal Failure Hypothyroidism Deficiency Anemias Chronic Pulmonary Disease Congestive Heart Failure Fluid and Electrolyte Disorders 105.410 (90.422-122.882) 0.947 (0.685-1.310) 1.239 (1.218-1.261) 2.864 (2.792-2.937) 1.588 (1.566-1.611) 3.235 (3.158-3.313) 4.113 (3.760-4.500) 2.833 (2.767-2.900) 9.135 (8.730-9.560) 3.824 (3.483-4.198) 1.611 (1.571-1.652) 2.462 (2.404-2.521) 1.280 (1.252-1.309) 1.584 (1.557-1.613) 1.367 (1.343-1.390) 1.517 (1.485-1.549) 1.498 (1.473-1.523) <0.0001 0.743 <0.001 <0.0001 <0.0001 <0.0001 <0.001 <0.0001 <0.0001 <0.001 <0.001 <0.0001 <0.001 <0.0001 <0.001 <0.0001 <0.0001 111.993 (95.611-131.180) - 1.209 (1.184-1.235) 2.047 (1.983-2.113) 1.302 (1.279-1.324) 2.407 (2.340-2.477) 4.372 (3.950-4.839) 2.294 (2.232-2.357) 6.916 (6.578-7.271) 3.668 (3.295-4.083) 1.504 (1.460-1.548) 1.715 (1.666-1.767) 1.200 (1.169-1.232) 1.291 (1.264-1.319) 1.193 (1.169-1.217) 1.094 (1.066-1.122) 1.441 (1.412-1.470) <0.0001 - <0.001 <0.0001 <0.001 <0.0001 <0.001 <0.0001 <0.0001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 greater costs among the onychomycosis cohort as compared to controls, understanding associated demographics and co- morbidities may be used to develop onychomycosis screen- ing guidelines among hospitalized patients. With multivariate analysis, we found that onychomycosis patients were more often Black compared to patients of other races. A 2023 study from the All of Us initiative linking survey and electronic health record data also found that Black indi- viduals (OR: 1.29; 95% confidence interval [CI]: 1.23-1.36) were more likely to develop onychomycosis compared to White individuals [20]. In contrast, this same study found that Hispanic individuals (OR: 1.24; 95% CI: 1.17-1.31) were more likely to develop onychomycosis compared to White in- dividuals. A 2021 systematic review of onychomycosis clinical trials demonstrated that only 32/182 (17.5%) of onychomyco- sis trials reported race and/or ethnicity, with only 1613/8270 (19.5%) non-white participants represented among studies between 2005-2020 [21]. Since our data, as well as previous research found that Blacks were more likely to have onycho- mycosis compared to other races, our study highlights the need to include more diverse participants in onychomycosis clini- cal trials. We also found that the majority of onychomycosis pa- tients versus controls presented in hospitals in the Northeast, Midwest or North Central, and Southern United States. In contrast, in a study analyzing data from the Porter Novelli summer 2022 ConsumerStyles survey, there was no differ- ence (P = 0.621) in proportions of onychomycosis cases (N = 415) versus controls (N = 3727) by census regions, spe- cifically in the Northeast (18.1% versus 17.2%), Midwest (18.1% versus 21.0%), South (38.1% versus 38.2%), and West (25.8% versus 23.7%) [22]. The difference between 6 Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 our 2003-2014 results and the 2022 ConsumerStyles data might suggest that onychomycosis prevalence has changed over time and has now taken on a roughly equal distribution by region or that there are differences between the inpatient and outpatient burdens of onychomycosis. Furthermore, compared to controls, onychomycosis pa- tients were more likely to be discharged between January and March which is typically winter season. Similarly, a retrospective study of 59 pediatric (age <18 years) onycho- mycosis patients seen at a dermatology clinic in Dongguk University Gyeongju Hospital, Korea found that a major- ity (N = 22, 37.3%) of patients developed onychomycosis during the winter months (December through February) [23]. Greater discharge frequency during the colder months may be partly attributed to dampness experienced in the winter season along with wearing closed-toed shoes which may increase risk of onychomycosis. With multivariate analysis, tinea pedis was the most commonly represented comorbidity among onychomycosis patients in our cohort, which is consistent with a 1999-2004 retrospective study analyzing 311 toenail clippings, in which, of thirty-three toenail clippings from patients who also had tinea pedis, 23 showed presence of dermatophytes and ten lacked dermatophytes [24]. Therefore, with concomitant tinea, odds of having versus not having onychomycosis was 2.73 (P < 0.001). Similarly, in a prospective epidemiological study on the prevalence of tinea pedis and concurrent ony- chomycosis among males residing in two boarding schools in Turkey found that among 410 males, 51.5% (N = 211) of residents had tinea pedis with 14.2% (N = 30) of tinea pedis cases having concurrent toenail onychomycosis [25]. In a 2015 multicenter, double-blinded, 48-week randomized (3:1) controlled trial of 1,655 patients assessing efinacon- azole efficacy compared to vehicle for onychomycosis treat- ment, there was a 29.4% (P = 0.003) versus 16.1% (P = 0.045) cure rate with efinaconazole when treating versus not treat- ing coexisting tinea pedis, respectively [26]. Therefore, early identification of tinea pedis may reduce onychomycosis risk and treatment of coexisting tinea pedis improves outcomes for onychomycosis patients. We also found a significant correlation between venous and peripheral vascular disease with onychomycosis, con- sistent with prior studies. In a 2005 cross-sectional study, among 42 outpatient onychomycosis patients and 39 con- trols, venous insufficiency was more frequent among ony- chomycosis patients versus controls (15/42, 35.7% versus 6/39, 15.4%; P = 0.037) [27]. Furthermore, in a 2000 pro- spective epidemiological study of 254 patients presenting to a vascular clinic, there was a significant association between onychomycosis and peripheral arterial disease (ROR: 4.8, P =0.02) [28]. Obesity was relatively common in onychomycosis patients compared to controls with multivariate regression analysis. In a 2002 Hong Kong epidemiological study of 1014 patients with foot diseases, including onychomycosis, risk factors included vascular disease, diabetes, and obesity [29]. Similarly, in a 2009-2010 study of adult patients hospi- talized in inpatient clinics at the Haydarpaşa Numune Train- ing and Research Hospital in Turkey, onychomycosis was more prevalent among the obese patients (BMI ≥ 30 kg/m2) as compared to controls (91/250, 36.4% versus 19/120, 15.8%; P < 0.001) [30]. In addition, in a 2004-2005 nested case- control study of 1245 patients with type 2 diabetes mellitus from a Taiwanese clinic, in onychomycosis patients, odds of obesity (BMI  ≥  27  kg/m2) versus normal weight was 2.31 (95% CI: 1.45-3.13; p=0.001) [31]. Therefore, we propose for obese patients to be screened for onychomycosis. Human immunodeficiency virus (HIV) was also sig- nificantly associated with onychomycosis risk in our study, similar to previous literature. In a 2011 study of 100 HIV and acquired immunodeficiency syndrome (AIDS) patients attending Hospital Correia Picanço in Brazil, 32 were di- agnosed with onychomycosis [32]. In a 2011 retrospective chart review study of 280 Mexican patients with HIV, 20% (N = 54) had onychomycosis [33]. In another observational cross-sectional study of 205 Mexican patients attending an HIV/AIDS clinic, 26.3% (N = 54) had onychomycosis, and HIV+ patients with versus without onychomycosis had lower CD4+ cell counts at 379.5 cells/μL versus 448 cells/μL respectively (no p-value reported) [34]. Therefore, our study corroborates that HIV infection may be a risk factor for on- ychomycosis, which may help to inform screening guidelines. We also found that psoriasis was associated with a greater risk of onychomycosis. The relationship between onychomycosis and psoriasis remains controversial [35,36]. Some studies have found a positive association between on- ychomycosis and psoriasis. For example, in a 2017-2018 Brazilian cross-sectional outpatient study of 38 patients with psoriasis, 57.9% (N = 22) of patients had onychomyco- sis [35]. In a 2003-2005 prospective study of 113 psoriatic patients and 106 non-psoriatic controls, 47.6% and 28.4% (P = 0.0054) were diagnosed with toenail onychomycosis re- spectively [37]. However, other studies have shown a lesser prevalence of onychomycosis among psoriasis patients. For example, a prospective controlled trial of psoriasis patients seen at a dermatology outpatient clinic in Turkey found that, of the 168 psoriasis patients and 164 controls, 13.1% (N = 22) and 7.9% (N = 13) of patients had onychomycosis, respec- tively (P > 0.05) [38]. Furthermore, in our study, patients with diabetes had in- creased risk of onychomycosis development similar to pre- vious literature. For example, in a 2016 Italian retrospective Original Article | Dermatol Pract Concept. 2024;14(2):e2024074 7 References 1. Falotico JM, Lipner SR. Updated Perspectives on the Diagno- sis and Management of Onychomycosis. Clin Cosmet Investig Dermatol. 2022;15:1933-1957. DOI: 10.2147/CCID.S362635. PMID: 36133401. 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PMID: 24945173. study including 668 non-diabetic and 47 diabetic patients, 55.3% (N = 26) of diabetic patients and 25.2% (N = 169) of non-diabetic patients were diagnosed with onychomycosis (P < 0.0001) [39]. In a 2008-2009 Japanese cross-sectional observational study of 71 patients, an unadjusted multiple logistic regression model found that not washing feet every- day was associated with a significantly increased risk of on- ychomycosis among diabetic patients (OR: 3.45, 95% CI: 1.24-9.65; P = 0.018), though data was not significant in the age and sex adjusted model (OR: 2.37; 95% CI: 0.76-7.33; P = 0.136) [40]. We found a greater risk of onychomycosis among patients with diabetes with chronic complications compared to those without chronic complications, suggesting that better diabetic control may decrease onychomycosis risk. We also found significant relationships between onycho- mycosis and depression, deficiency anemias, and fluid and electrolyte disorders. These comorbidities and their mecha- nisms leading to onychomycosis development have not been studied extensively, and may be a topic for future research. Limitations of this study include its retrospective nature and inclusion of only inpatient data. Therefore, these trends, common risk factors, and the overall burden of onychomy- cosis may not be generalizable to the outpatient setting. In addition, onychomycosis cases were not necessarily myco- logically confirmed. Data on diagnosing physician specialty were unavailable. Furthermore, we used International Clas- sification of Diseases, 9th edition codes to create the comor- bidity variables for tinea pedis, human immunodeficiency virus, hyperhidrosis, and psoriasis. Consequently, cases with the comorbidity that were not classified within the ICD-9 codes we included may have been missed. There may also have been missing data among the variables we included us- ing the National Inpatient Sample. Further, inaccurate ICD-9 coding of conditions could have affected our data by includ- ing cases that were incorrectly classified as onychomycosis in our analysis. Our study was limited to NIS data 2003-2014, and studies analyzing more recent data are warranted. In sum, in this inpatient cohort, we identified numerous comorbidity risk factors associated with an increased risk of developing onychomycosis among hospitalized patients including tinea pedis, venous insufficiency, human immuno- deficiency virus, psoriasis, obesity, peripheral vascular dis- ease, and diabetes with chronic complications. Black patients were disproportionately represented among onychomycosis cases compared to controls. Onychomycosis patients were more likely to have longer hospital stays and greater costs. 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