Abstract
The incidence of coccidioidomycosis (CM) infection has increased over the last 20 years. We investigated recent trends of CM-associated hospitalization in the United States. patients with CM-associated hospitalization were identified from the Nationwide Inpatient Sample, 2005–2012. The outcomes of interest were the trend of annual hospitalization, in-hospital mortality, and independent risk factors for mortality. A total of 30,870 hospitalizations with CM (29,584 of adults; 1,286 of children) were identified. Over the 8-year study period, the number of hospitalizations for CM fluctuated but increased overall with successively higher peaks in 2009 and 2011. The annual median length of stay (LOS) shortened from 6 to 7 days in 2005–2010 to 4 days in 2011 and 5 days in 2012. The inflation-adjusted hospital charges were highest in 2006 then trended down by 21% in 2012. The in-hospital mortality declined from the highest level in 2005 (5.2%) to a low in 2010 (1.1%), then increased modestly in 2011 (1.9%) and 2012 (1.5%). Hospitalizations were identified in 46 states, with nearly half in Arizona (49.1%), followed by California (36.8%), Texas (3.3%), and Nevada (1.6%). Logistic regression analysis in adults revealed that in-hospital mortality was associated with age groups 61–70 years and >70 years (OR = 3.3 and 3.5, respectively. Ref: 18–30 years) and Charlson Index ≥1 (OR = 2.0–8.3). In children, males had lower risk for mortality than females (OR = 0.2). This study shows that CM-associated hospitalizations occur widely throughout the United States with an increasing admission trend; however, patient outcomes have improved and the cost of hospitalization has decreased.
Keywords: Coccidioidomycosis, epidemiology, hospitalization, outcomes, trend
Introduction
Coccidioidomycosis (CM) is caused by the dimorphic fungi Coccidioides immitis and Coccidioides posadasii, which are native to some arid and desert areas of North America.1 Arizona and California are the most heavily concentrated endemic regions in the United States and have the majority of patients.1 However, in recent years, Coccidioides sp. and CM cases have been reported in the states like Washington, Utah, and Missouri, leading to unexpected nascent infections of local residents.2–5 Over the past 20 years, the incidence of CM has markedly increased in both endemic and nonendemic regions of the United States.6–8 These cases inevitably result in a great burden in terms of hospitalization. Few studies focusing on patients hospitalized with CM in Arizona and California have been published,9–10 and data with regard to other endemic and nonendemic areas have not been reported.
CM infection has drawn increasing interest among physicians not only in endemic areas, where growing population and migration increases risk of disease but also throughout the United States since local citizens travel frequently to endemic areas.11 The aims of this study were to determine the trend of economic burden of patients hospitalized with CM in endemic and nonendemic areas of the United States, evaluate the epidemiologic characteristics and clinical features of the hospitalized patients, and identify risk factors for mortality during CM hospitalizations.
Methods
Data source
We performed a retrospective study using data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample (NIS) from 2005 to 2012. The NIS is an all-payer inpatient care database representing a 20% stratified sample of nonfederal acute-care hospitals in the United States, including community, general, and academic centers but not long-term care facilities. Each discharge is weighted to allow for estimates projected to a national level. Each individual hospitalization is de-identified and maintained in the NIS as a unique entry with 1 primary discharge diagnosis and up to 24 secondary diagnoses (14 secondary diagnoses from 2005 to 2008, 24 secondary diagnoses from 2009 to 2012).12–14 Given that individual patient identifiers were unavailable, multiple hospitalizations of the same patient may be analyzed as part of the study. State-specific data are available in the NIS database in 2005–2011 but not in 2012.
Subject selection
International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9) codes were used to identify subjects from the database. We included subjects with a primary or second diagnosis code for coccidioidomycosis, including primary pulmonary CM, chronic pulmonary CM, nonspecific pulmonary CM, primary cutaneous CM, CM meningitis, progressive CM not including meningitis, and CM unspecified. ICD-9 codes used in this study are available in Table 1.
Table 1.
ICD-9 disease codes.
| Diagnosis | ICD-9 codes |
|---|---|
| Coccidioidomycosis | 114, 114.0∼114.5, 114.9 |
| Organ transplant | Liver: V42.7, 996.82, 50.5, 50.59 |
| Lung: V42.6, 996.84, 33.5, 33.50∼33.52 | |
| Kidney: V42.0, 996.81, 55.6, 55.69 | |
| Pregnancy | 630∼679 |
| Inflammatory bowel disease | 555.9, 556.0∼556.9 |
| Neutropenia | 288.0, 288.00∼288.04, 288.09 |
Study variables
The variables of age, gender, race/ethnicity, geographic region of hospital, state-specific data, in-hospital outcomes (death or survival), length of stay (LOS), total hospital charges, and some comorbidities (HIV/AIDS, alcohol abuse, anemia, congestive heart failure, COPD, diabetes, drug abuse, hypertension, liver disease, lymphoma, cancer with metastasis, obesity, renal failure, and solid tumor without metastasis) were extracted from the NIS data set to provide subject characteristics. Other variables that are relevant to immunocompromised hosts and might be associated with severe CM,15 such as inflammatory bowel disease (IBD), lupus, and neutropenia, were identified by ICD-9 diagnosis codes (Table 1) and included in the analysis. Although pregnancy is considered a risk factor for CM,16–17 the data set found no instances of CM with a secondary diagnosis of pregnancy; thus no analysis using this factor could be conducted. LOS and hospital charges were collected as continuous variables. Age was categorized in children into the following groups: ≤3 years, 4–6 years, 7–9 years, 10–12 years, 13–15 years, 16–17 years. In adults, age was categorized as follows: 18–30 years, 31–40 years, 41–50 years, 51–60 years, 61–70 years, and >70 years. All other variables were analyzed as categorical variables.
Outcomes
The main outcome of interest was the trend of hospitalization associated with CM (overall and regionally). Secondary outcomes of interest were mortality, LOS, and inflation-adjusted hospital charges. Additionally, we investigated the clinical features in the hospitalizations associated with CM and the risk factors for mortality. To explore geographic differences in hospitals with admissions for CM, the United States was divided into four regions: Northeast, Midwest, South, and West (see Table 2).18 We determined the yearly hospital burden using the per-hospitalization and cumulative median LOS and hospital charges for all hospitalizations in a calendar year. Hospital charge refers to the charge that the hospital levied to a patient. All dollar amounts were adjusted to inflation based on the year 2012. The LOS refers to the total number of continuous days a patient was hospitalized. The annual cumulative LOS and cumulative hospital charges were calculated by summing the total LOS and hospital charges for all hospitalizations in a calendar year.
Table 2.
Census regions of the United States.18
| Region | Included states |
|---|---|
| Northeast | Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont, New Jersey, New York, Pennsylvania |
| Midwest | Indiana, Illinois, Michigan, Ohio, Wisconsin, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota |
| South | Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, Texas |
| West | Arizona, Colorado, Idaho, New Mexico, Montana, Utah, Nevada, Wyoming, Alaska, California, Hawaii, Oregon, Washington |
Statistical analysis
Descriptive statistics were used to analyze baseline characteristics of all patients. Separate analyses were performed on children (age <18 years) and adults (age ≥18 years). To determine the risk factors for CM hospital mortality, subjects were divided into two groups based on death or survival at discharge.
Annual CM-associated hospitalizations were determined for the United States as a whole, and also for endemic and nonendemic areas, by region and state. A logistic regression model was developed using the outcome of survival or death as the dependent variables. Independent risk factors for mortality were identified after adjusting for potential confounders, including age (reference group: 18–30 years old in adults; ≤3 years old in pediatric patients), gender (reference: female), race/ethnicity (reference: Caucasian), Charlson index (reference: 0),19 presence of complications or comorbidities (HIV/AIDS, diabetes, connective tissue disease, etc.). In pediatric patients, since the incidence of complications, comorbidities and elevated Charlson index were low, they were not entered into to the logistic regression model.
All analyses were performed using Statistical Program for Social Sciences (SPSS) version 19.0 (IBM, Inc., Armonk, NY). The weighted discharge variable assigned to each discharge was used to project to national estimates. All statistical testing was two-sided. Because small but clinically irrelevant differences can become statistically significant in large databases such as NIS, a P value <.01 was considered statistically significant in all final analyses. The Office of Human Research Protection of the study institution has deemed that research utilizing the NIS and similar deidentified data sets is exempt from requiring institutional approval.
Results
Demographic characteristics
A total of 30,870 cases (29,584 adults and 1,286 children) met inclusion criteria for CM-associated hospitalization. In adults, the mean age was 51.2 ± 17.5 years. The proportion of men was 1.7-fold greater than women (62.5% vs. 37.5%). A majority of patients were Caucasian (54.9%), followed by Hispanics (24.7%), and African Americans (11.9%). In pediatric patients, the age distribution was skewed to older age (skewness: −0.54; kurtosis: −0.95) with a median of 12 years. Male children were 1.5-fold more common than female children (59.5% vs. 40.5%). Caucasians (43.2%), Hispanics (41.1%), and African Americans (6.8%) were the commonest races among children (Table 3).
Table 3.
Demographic features and comorbidities of adult and pediatric patients with coccidioidomycosis.
| Adults | Children | |
|---|---|---|
| Factor | N = 29,584 | N = 1286 |
| Age, mean ± SD | 51.2 ± 17.5 | 10.6 ± 5.3 |
| Gender, N (%) | ||
| Female | 11,066 (37.5) | 505 (40.5) |
| Male | 18,411 (62.5) | 743 (59.5) |
| Race, N (%) | ||
| Caucasian | 15,431 (54.9) | 485 (43.2) |
| Black | 3344 (11.9) | 76 (6.8) |
| Hispanic | 6936 (24.7) | 461 (41.1) |
| Asian/Pacific Islander | 1248 (4.4) | 36 (3.2) |
| Native American | 667 (2.4) | 39 (3.5) |
| Others | 491 (1.7) | 26 (2.3) |
| Charlson Index, N (%) | ||
| 0 | 13504 (45.6) | 956 (74.3) |
| 1 | 8421 (28.5) | 199 (15.5) |
| 2 | 4059 (13.7) | 121 (9.4) |
| 3 | 1805 (6.1) | 10 (0.8) |
| 4 | 912 (3.1) | 0 |
| ≥5 | 883 (3.0) | 0 |
| Comorbidities, N (%) | ||
| HTN | 11618 (39.3) | 55 (4.3) |
| Deficiency anemia | 7092 (24.0) | 142 (11.0) |
| DM without complications | 6236 (21.1) | 5 (0.4) |
| Chronic pulmonary disease | 6090 (20.6) | 149 (11.6) |
| Renal failure | 2612 (8.8) | 15 (1.2) |
| Obesity | 2106 (7.1) | 21 (1.6) |
| Congestive heart failure | 1684 (5.7) | 5 (0.4) |
| Liver disease | 1653 (5.6) | 20 (1.6) |
| Drug abuse | 1481 (5.0) | 5 (0.4) |
| DM with complications | 1385 (4.7) | 0 |
| Connective tissue disease | 1226 (4.1) | 35 (2.7) |
| Alcohol abuse | 881 (3.0) | 10 (0.8) |
| Solid tumor w/out metastasis | 367 (1.2) | 0 |
| Lupus | 317 (1.1) | 5 (0.4) |
| Lymphoma | 293 (1.0) | 5 (0.4) |
| Anemia due to blood loss | 272 (0.9) | 0 |
| Cancer with metastasis | 198 (0.7) | 0 |
| Neutropenia | 161 (0.5) | 20 (1.6) |
| HIV/AIDS | 102 (0.3) | 0 |
| IBD | 47 (0.2) | 5 (0.4) |
Hospitalization burden
Over the 8-year study period, the number of hospitalizations for CM fluctuated from year to year but increased overall with successively higher peaks in 2009 and 2011. Compared to 2006, hospitalizations increased 23.9% by 2011 (Fig. 1A). Although the annual admission fluctuated from 2005 to 2012, both the nadirs and peaks trended upwards.
Figure 1.
Trends of annual hospitalizations and in-hospital mortality for coccidioidomycosis. (A) The trends of annual hospitalizations (2005-2012) in the West region and the entire United States were parallel, with the nadirs (in 2005, 2007, 2008, 2010 and 2012) and peaks (in 2006, 2009 and 2011) trending upwards. (B) The South, Midwest and Northeast regions comprised 9.3% of hospitalizations in the country. Compared to the year of 2005, the annual hospitalizations in 2012 decreased by 22.3% in the South, while increased in the Midwest by 14.3% and Northeast regions 16.6%. (C) In-hospital mortality (entire United States) was the highest in 2005 (5.2%), decreased to a nadir level in 2010 (1.1%), followed by a modest increase in 2011 (1.9%) and 2012 (1.5%).
CM hospitalizations were recorded in all 46 states enrolled in the NIS database. The large majority of hospitalizations occurred in the West (90.7%, N = 28000) with an annual trend of hospitalization that paralleled that of the whole country (Fig. 1A). The South, Midwest, and Northeast regions comprised 5.2% (N = 1605), 2.8% (N = 864), and 1.3% (N = 401) of the remaining hospitalizations, respectively. In the South, the total number of hospitalizations decreased by 22.3% by 2012. In the Midwest and Northeast regions, hospitalizations increased in 2012 compared to the year of 2005 (14.3% and 16.6%, respectively; Fig. 1B). Based on the data from 2005 to 2011, nearly half of the hospitalizations were in Arizona (49.1%, N = 13,171), followed by California (36.8%, N = 9872), Texas (3.3%, N = 885), and Nevada (1.6%, N = 429). Hospitalizations in both Arizona and California increased by 42.5% and 54.5%, respectively, from 2005 to 2011. In Texas, the annual rate of hospitalizations fluctuated around the 7-year median of 124 hospitalizations. In Nevada, the annual hospitalization rate (median = 52 hospitalizations) varied considerably but exhibited a general upward trend: a 150% increase in 2011 compared to 2005.
The annual median LOS for CM admissions shortened from 6 or 7 days initially to 4 or 5 days in the last two years of the study period. Over the 8 years of study, the annual cumulative LOS was the lowest in 2012 (27,895 days), a decrease of 44% compared to the highest year in 2006 (49,856 days). The inflation-adjusted hospital charges were highest in 2006, after which they trended down by 21% in 2012. The annual cumulative inflation-adjusted hospital charges also trended lower.
In-hospital mortality and risk factors for death
Over the 8-year study period, the in-hospital mortality declined from a high in 2005 (5.2%) to a low in 2010 (1.1%), followed by a modest increase in 2011 (1.9%) and 2012 (1.5%) (Fig. 1C). The overall in-hospital mortality was 2.7% and 3.2% in adults and children, respectively.
The logistic regression model in adults revealed that both age groups of 61–70 years (OR = 3.29; 95% CI: 2.43–4.45. Ref: 18–30 years) and >70 years (OR = 3.49; 95% CI: 2.57–4.76. Ref: 18–30 years) had increased risk for in-hospital mortality. With regard to race, Hispanics and Asian/Pacific Islanders (OR = 2.02; 95% CI: 1.68–2.43 and OR = 1.57; 95% CI: 1.12–2.21, respectively. Ref: Caucasian) demonstrated higher risk of in-hospital mortality. There was no significant difference in the mortality between male and female patients (P = .08). The comorbidities used in the regression model appear in Table 3. The Charlson index was closely associated with mortality: a higher score increased the risk of in-hospital death. In addition, the comorbidities of deficiency anemia (OR = 1.3; 95% CI: 1.1–1.5) and neutropenia (OR = 3.9; 95% CI: 2.4–6.4) increased the risk of mortality (Table 4).
Table 4.
Independent risk factors for mortality in adult patients with coccidioidomycosis.
| Factor | OR (95% CI) | P |
|---|---|---|
| Gender | Reference: Female | |
| Male | 1.2 (1.0–1.4) | .075 |
| Age, years | Reference: Age 18–30 | |
| 31–40 | 1.1 (0.8–1.5) | .604 |
| 41–50 | 1.3 (0.9–1.7) | .151 |
| 51–60 | 1.3 (0.9–1.8) | .126 |
| 61–70 | 3.3 (2.4–4.5) | <.001* |
| >70 | 3.5 (2.6–4.8) | <.001* |
| Race | Reference: Caucasian | |
| Black | 1.0 (0.8–1.7) | .761 |
| Hispanic | 2.0 (1.7–2.4) | <.001* |
| Asian/Pacific Islander | 1.6 (1.1–2.2) | .009* |
| Native American | 0.4 (0.2–1.0) | .047 |
| Others | 3.3 (2.2–4.9) | <.001* |
| Charlson Index | Reference: Charlson Index = 0 | |
| 1 | 2.0 (1.6–2.5) | <.001* |
| 2 | 2.8 (2.1–3.7) | <.001* |
| 3 | 5.0 (3.4–7.3) | <.001* |
| 4 | 4.3 (2.5–7.1) | <.001* |
| ≥5 | 8.3 (4.3–16.1) | <.001* |
| Comorbidities | Reference: No comorbidities | |
| HTN | 0.6 (0.5–0.7) | <.001* |
| Deficiency anemia | 1.3 (1.1–1.5) | .004* |
| DM without complications | 0.7 (0.5–0.8) | <.001* |
| Chronic pulmonary disease | 0.7 (0.6–0.9) | .001* |
| Renal failure | 0.7 (0.5–0.9) | .016 |
| Obesity | 0.5 (0.3–0.8) | .002* |
| Congestive heart failure | 1.2 (1.0–1.6) | .126 |
| Liver disease | 1.0 (0.8–1.4) | .945 |
| Drug abuse | 1.3 (0.9–1.8) | .178 |
| DM with complications | 0.4 (0.2–0.5) | <.001* |
| Connective tissue disease | 1.4 (1.0–1.9) | .044 |
| Alcohol abuse | 0.9 (0.6–1.5) | .698 |
| Solid tumor w/out metastasis | 1.5 (1.0–2.3) | .084 |
| Lupus | 0.8 (0.4–1.6) | .449 |
| Lymphoma | 0.8 (0.5–1.3) | .398 |
| Anemia due to blood loss | 0.7 (0.3–1.8) | .474 |
| Cancer with metastasis | 1.6 (0.8–3.1) | .191 |
| Neutropenia | 3.9 (2.4–6.4) | <.001* |
| HIV/AIDS | 0.8 (0.3–2.0) | .653 |
| IBD | 3.2 (1.2–8.6) | .019 |
* P<.01.
The logistic regression model for pediatric patients showed that males had a significantly lower risk for in-hospital mortality than females (OR = 0.2; 95% CI: 0.1–0.5). Additional factors analyzed were not associated with mortality.
Discussion
According to data from the Centers for Disease Control and Prevention, the incidence of CM increased from 5.3 to 42.6 per 100,000 population in endemic areas from 1998 to 2011.7 Using a nationwide database, we demonstrated a substantially increasing trend of hospitalizations for CM from 2005 to 2012. To date, a few publications have reported the hospitalized rates of CM in highly endemic areas like Arizona and California,9–10 but little to no data exists on the nationwide hospitalized burden of CM. In spite of the increased annual CM hospitalizations, our study revealed a decreasing trend in LOS and inflation-adjusted hospital charges for CM patients. In addition, we found that CM hospitalizations occurred in all 46 states which were enrolled in NIS database, with the large majority of patients in Arizona and California. In these two states, the increase in the number of CM-associated hospitalizations found in our study is concordant with the increasing incidence of CM in recent years, as shown in prior studies.9–10 The Southern United States is a region of low CM endemicity in general, with the one exception being the western part of Texas. However, hospitalizations increased in the Midwest and Northeast, where no endemicity of CM has been reported before. CM hospitalizations in Nevada trended higher, but the hospitalization number was quite small in this state.
The increased hospitalizations for CM and the existence of hospitalizations outside endemic areas might be the result of several factors. First, more and more small pockets of endemicity are being identified in traditionally non-endemic regions.20–21 Second, a growing number of immunocompromised patients who have higher risk of developing severe CM are more likely to be hospitalized when infected. Third, greater use of biologic therapies for various conditions increases the risk for opportunistic fungal infections, including CM.
The demographic characteristics of CM patients reported in previous publications showed that the age distribution and sex ratio of CM patients varied with time and with different endemic areas.7 During 1998–2011, the incidence of CM in California was highest in persons aged 40–59 years and more males were affected. In Arizona, however, the disease affected more patients over 60 years of age.7 Race has also been found to influence the outcomes of CM infection. African Americans and Hispanics have been shown to have higher hospitalization rates than Caucasians, while all non-Caucasians (including African Americans, Hispanics, Asian and Pacific Islanders, and Native Americans) have higher risk for mortality.22 Our study mirrored the evidence that advanced age contributed to increased mortality, and that non-Caucasian patients had a higher risk for mortality. We also found in adults that gender made no contribution to the risk of mortality, whereas in children, females harbored higher risk for mortality than males. Furthermore, in adults, we found that high Charlson Index was significantly associated with increased in-hospital mortality.
Our study has several limitations. First, like most database studies, administrative data is subject to miscoding and thus erroneous diagnoses. Nevertheless, we do not suspect a systematic bias toward the diagnosis. Second, the NIS lacks outpatient information and medication use. Antifungal treatment is effective and greatly improves patient prognosis.23–25 Failure to include the effect of treatment in our study might exaggerate the effect of the risk factors on patient outcomes. Third, the NIS database lacks data from certain states. The number of states enrolled in NIS increased from 42 to 46 during the study period of 2005 to 2012, with most of the missed states being in nonendemic areas of CM. The one exception is New Mexico, which though an endemic state for CM,1 was not included in the NIS database until 2009. Hence, we presume that our study may have underestimated the hospitalizations for CM in this state. Forth, the NIS database cannot identify readmission information. The hospitalizations recorded do not represent the real case numbers. Hence, the prevalence of diseases as well as the effect of readmission on in-hospital mortality in logistic regression model cannot be evaluated. Finally, since the NIS database for year 2012 did not provide state-specific data, the annual and monthly state-based hospitalization analysis was limited to the years 2005–2011.
In summary, to our knowledge, this is the first study to evaluate the nationwide hospital burden and outcomes of patients hospitalized for CM. We analyzed the clinical characteristics and outcomes of adult and pediatric patients separately, the latter of which have rarely been reported before. In spite of the increasing hospitalizations, their economic burden has decreased, in part as a result of decreases in both the yearly cumulative LOS and hospital charges. Declining in-hospital mortality may reflect earlier diagnosis and improved management of CM in recent years. Given the existence and increasing tendency of CM-associated hospitalization in some nonendemic areas, heightened awareness of CM among healthcare providers throughout the country is warranted. Lastly, the large database utilized in this study enabled the determination of CM infection prognostic factors, which may assist in the treatment of patients and highlight strategies to improve their outcomes.
Acknowledgments
The study received partial support from a University of Nevada School of Medicine grant from the National Institute of General Medical Sciences (P20GM103440).
Declaration of interest
The authors report no conflicts of interest. The authors alone are responsible for the content and the writing of the paper.
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