Is Appendicitis a Viral Disease

Introduction: What causes appendicitis is not known; however, studies have suggested a relationship between viral diseases and appendicitis. Building on evidence of cyclic patterns of appendicitis with apparent outbreaks consistent with an infectious etiology, we undertook an epidemiologic study of possible relationships between population rates of appendicitis and several infectious diseases. Methods: ICD-9-CM discharge diagnosis codes of the National Hospital Discharge Survey (NHDS) were queried from 1970-2005 to identify admissions for appendicitis, influenza, rotavirus and enteric infections. Cointegration analysis of time series data was used to determine if the disease incidence trends for these various disease entities varied over time together. Results: Rates of influenza and nonperforating appendicitis declined progressively from the late 1970s to1995 and rose thereafter, but influenza rates exhibited more distinct seasonal variation than appendicitis rates. Rotavirus infection showed no association with the incidence of nonperforating appendicitis. Perforating appendicitis showed a dissimilar trend to both nonperforating appendicitis and viral infection. Hospital admissions for enteric infections have substantially increased over the years but are not related to appendicitis cases. Conclusion: Neither influenza nor rotavirus are likely proximate causes of appendicitis given the lack of a seasonal relationship between these disease entities. However, because of significant cointegration between the annual incidence rates of influenza and nonperforated appendicitis, it is possible that these diseases share common etiologic determinates, pathogenetic mechanisms, or environmental factors that similarly affect their incidence. Alder et al. Appendicitis and Viral Illness Page 3 Introduction Appendectomy is the most common emergency general surgical procedure with more than 250,000 cases performed annually in the United States (1). Despite its ubiquitous nature, why appendicitis occurs remains unknown. Several theories exist attempting to explain this disease’s cause. At the heart of most appendicitis theories is luminal obstruction. The appendix becomes obstructed either by a fecolith or enlarged lymphoid tissues resulting in high luminal pressures that compromise mucosal integrity leading to infection. Infections are thought to cause appendicitis (2) by stimulating lymphoid hyperplasia which obstructs the appendix. Many viral disorders are associated with lymph node enlargement, which, in turn, can obstruct the appendiceal lumen. Viral infections could cause mucosal ulcerations that could result in subsequent bacterial infection of the appendix (3;4). Appendicitis has been associated with a viral prodrome compatible with a viral illness preceding the first symptoms of appendicitis. Early epidemiologic investigations found that appendicitis was more frequent during months when respiratory infections were present (5). Several epidemiologic patterns suggest a link between appendicitis and infections. Appendicitis outbreaks have been described. In one small Texas town, a significant cluster of cases was described over a very short period of time suggesting an infectious etiology (6). Larger scale investigations from Sweden revealed that the disease has a propensity to cluster in time and location (7). A 35-year epidemiologic investigation from our group uncovered apparent appendicitis outbreaks in the U.S. (8). To develop further evidence possibly linking specific infectious etiologies with appendicitis, we analyzed a national sample of hospital discharge data for associations between Alder et al. Appendicitis and Viral Illness Page 4 rates of appendicitis and certain candidate infectious diseases including influenza, rotavirus and other intestinal infections. Methods The annual National Hospital Discharge Survey (NHDS) databases for the years 19702005 were acquired from the Centers for Disease Control (CDC) ((http://www.cdc.gov/nchs/about/major/hdasd/nhds.htm) and the Inter-University Consortium for Political and Social Research web sites (http://www.icpsr.umich.edu/index-medium.html). The NHDS is the principal database used by the U.S. Government for monitoring hospital utilization. Each year approximately 300,000-hospital discharges are selected for the NHDS from the 35,000,000 total discharges nationally. The NHDS uses a complex, multistage design to ensure that the database is representative of the U.S. hospitalized population. Using U.S. Census information, the CDC provides statistical weighting factors for each patient entry in the NHDS database so that incidence and prevalence estimates of hospitalized disease can be made for the entire U.S. population. These weighting factors were used to determine the national prevalence of appendicitis. The estimated U.S. population for each year of the study was obtained from the U.S. Census Bureau as accessed through the CDC web site (http://wonder.cdc.gov/population.html). Disease incidence per geographic region was determined in regions as defined by in the NHDS. The NHDS converted from ICDA-8 encoding to ICD-9 in 1979. Before 1979, codes for the various forms of appendicitis diagnoses were the same in the ICDA-8 system as in the ICD9. The same was true for enteric infections. For cases in the database occurring from 1970 through 1978 procedures were identified as: drainage of appendiceal abscess (410), Alder et al. Appendicitis and Viral Illness Page 5 appendectomy (411), appendicostomy (412), closure of appendiceal fistula (413) and other appendectomy (419). Hospital admissions for influenza were identified by diagnostic codes ranging from 470 to 474. Abdominal pain was encoded with 785.5. Beginning in 1979, the ICD-9 coding system was implemented. Appendicitis was defined as a patient having any of the following 7 NHDS discharge diagnostic codes: 540.9 (Acute appendicitis), 541.0 (Appendicitis-Unqualified), 542.0 (Other appendicitis), 543.0 (Other diseases of the appendix), 543.0 (Unspecified disease of the appendix). Perforated appendicitis (540.0) or Appendiceal abscess (540.1) were aggregated into a single category called “perforated appendicitis”. Nonperforated appendicitis was defined as having any appendicitis diagnostic code except for 540.0 or 540.1. Procedures codes used were: Appendectomy (47.0), laparoscopic appendectomy (47.01), other appendectomy (47.09), incidental appendectomy (47.1), laparoscopic incidental appendectomy (47.11), other incidental appendectomy (47.19), drainage of an appendiceal abscess (47.2), “other” appendiceal operation (47.9), appendicostomy (47.91), closure of an appendiceal fistula (47.92), and other appendiceal operation (47.99). Incidental appendectomies were identified if there were any of the following 3 procedure codes: 47.1, 47.11 or 47.19. Nonincidental appendectomies were defined as having any appendectomy procedure codes excluding those for incidental procedures. A negative appendectomy was defined as having any procedure code: 47.0, 47.01 or 47.09 without any diagnostic coding for appendicitis. A diagnosis of any type of intestinal infectious disease was established if the diagnostic codes ranged from 008.00 to 008.89. Of these, a subset of intestinal viral diseases (ICD-9 008.6X) was assessed in greater detail. Only rotavirus (008.61) had sufficient numbers of admissions to be analyzed. A specific Rotavirus ICD-9-CM diagnostic code was introduced in 1993. There were too few cases to assess on a monthly basis. For that reason, rotavirus Alder et al. Appendicitis and Viral Illness Page 6 admissions were aggregated into 3-month quarters. All other data were analyzed by monthly or annual aggregations of the disease incidences. Disease incidence estimates can be affected by coding changes. When a major change in disease classification occurs, disease entities may be grouped differently, they may have new names or definitions that cause diseases to be classified in other sections of the coding schema than before, or the definitions for a disease may change resulting in its classification into new areas. When this occurs, plotting of the disease incidence over time will have discontinuities at the years in which the coding change was implemented. If the discontinuity is obvious and the trends on either side of the break are reasonably linear, then correction factors can be determined. Correction factors are calculated by dividing the disease incidence ratio for the years before the new code introduction by that for the years after the new codes were used. The resultant ratio is known as the comparability ratio. The ICD system is assessed for this phenomenon with each major update and comparability ratios published. Of the disease entities we studied, only intestinal infections had a significant discontinuity when ICDA-8 was converted to ICD-9 in 1979. We applied a correction factor of 5.49 to the pre-1978 data for intestinal infections, removing the observed 1978-1979/ ICD8 to ICD9 coding change-induced disease incidence discontinuity (9-11). Similarity in the long-term trending or wandering behavior of two disease rates was tested using the technique of cointegration analysis (12) which has been widely used in econometric time series analysis. See the Appendix for a discussion of cointegration testing. The analysis was based on an autoregressive modeling of the disease rate time series. In this setting two disease rates were considered to be cointegrated (varying together over time) if each rate was unit-root nonstationary and the processes showed significant indication that they were Alder et al. Appendicitis and Viral Illness Page 7 “tethered together” over time as measured by cointegration analysis. We tested the null hypothesis that the time series had a unit root and, therefore, was nonstationary using the Augmented Dickey-Fuller test (13;14). Rejecting the null hypothesis (P ≤ 0.05) supports stationarity; whereas, failing to reject the null hypothesis (P > 0.05) supports unit root nonstationarity. Based on the evidence of a unit root, the next step was to test for a cointegrating relationship between nonperforated appendicitis and influenza, both nationally and regionally, We considered panel cointegration tests designed to increase the power of detecting cointegration when cross-section data (i.e. regional data in our case) are available. Panel cointegration tests proposed by Pedroni (15;16) and by Maddala and Wu (17) were also applied. All time series computations in this paper were done using the econometrics software package EVIEWS 6 © (1997 – 2007, Quantitative Micro Software, LLC, Irvine, California). 1 When we say that the co-integrated series are "tethered together" we are implying that, although the individual series themselves have random walk characteristics, a linear combination of them, a*appendicitis + b*influenza, behaves like a stationary time series. That is, the two non-stationary time series never wander too far apart. Alder et al. Appendicitis and Viral Illness Page 8 Results Both nonperforating appendicitis and influenza were declining in overall incidence until 1995. After that, both diseases’ overall incidence has been increasing (Figure 1). This “U”shaped curve was not observed for perforating appendicitis which has exhibited a slowly rising incidence over the years. Influenza exhibited a sharp increase in incidence in the winter months with the disease rarely observed during the remaining months of the year (Figure 2). Appendicitis occurs throughout the year with a slight tendency to occur more frequently in the summer months. Intestinal infections also are observed throughout the year but have a propensity to occur in the winter months. Influenza admissions occur mostly between December and February and rarely occur at other times of the year. Although the strong winter presence of influenza was not observed with appendicitis, the overall annual incidence for these diseases appears to wander in time together (Figure 3). The results of unit root tests for the national and regional data are shown in Tables 1 and 2 where it can be seen that the national data on nonperforated appendicitis and influenza as well as the regional data on both disease rates show evidence of a unit root since the null hypothesis of a unit rate is not rejected in any of the cases. Because of the small sample size of our overall analysis (i.e. 35 data points, one representing each years disease incidence), we also examined the consistency of the appendicitis-influenza disease incidence relationship in the 4 major U.S. regions. In Figure 4 we show normalized overlays of the incidence rates for nonperforated appendicitis and influenza for the four regions. From Table 1 it can be seen that the Augmented Dickey Fuller test shows evidence of a unit root for both disease incidence rates in each region. Table 2 shows that both the trace and maximum-eigenvalue tests indicate cointegration between nonperforated appendicitis and influenza both nationally and regionally. Panel cointegration tests Alder et al. Appendicitis and Viral Illness Page 9 proposed by Pedroni (15;16) and by Maddala and Wu (17) were also applied, and the results (not reported here) were consistent with those previously obtained in the region by region analysis using the Johansen tests. That is, the panel results, like these Johansen test results, were supportive of cointegration in all the major regions of the United States. Figure 5 shows the relationship between appendicitis and intestinal rotavirus infection. ICD-specific codes for rotavirus were only available after 1993. Because of the relatively low rotavirus incidence, data were aggregated into quarters rather than months. Rotavirus infection peaked in the winter months, but there was no obvious correlation between rotavirus infection and appendicitis, and the Dickey-Fuller tests showed no evidence of cointegration (data not shown). Unlike the secular trends in nonperforated appendectomy rates, intestinal infections have been steadily increasing in incidence (Figure 6). These infections have peak incidence in about March of any given year (Figure 2). The overall and peak admission rates in each year began increasing in 1989. As with influenza, the annual peak incidence for hospital admissions attributable to rotavirus infections occurs in March. Whereas influenza admissions are unusual in the non-winter months, intestinal infection admission rates are observed throughout the year. Of interest is the tendency for the within-year variation to dramatically increase in approximately 1989. Investigation showed that this was not due to a coding change, and we believe that the source of the increased variation should be further investigated Alder et al. Appendicitis and Viral Illness Page 10 Discussion What causes appendicitis remains a mystery. Our previous analysis of appendicitis time trends demonstrated that the increasing appendicitis rates observed after 1995 paralleled the rise, and could possibly be related to, increased utilization of CT scanning and laparoscopic surgery (8). However, the year-to-year variation in the nonperforating appendicitis incidence and apparent disease outbreaks suggested that appendicitis is caused by an infectious agent (8). The current study was performed to further investigate this possibility. We did find that there were epidemiologic similarities between the rates of nonperforating appendicitis and influenza. The annual incidence rates for both diseases progressively fell in parallel over the two and one half decades from 1970 until 1995 and thereafter both began to rise in parallel. Moreover, time series analysis demonstrated statistically significant cointegration of the wanderings of the annual incidence rates of the two diseases. Appendicitis shared no common pattern with intestinal infections or with documented rotavirus infections. These findings suggest that nonperforating appendicitis may be caused by an infectious agent or other process related to influenza virus infection; however, since influenza has a winter peak that is not observed with nonperforating appendicitis, it an unlikely to be a proximate cause. These findings also suggest that our previously observed parallel rise in the nonperforating appendicitis after 1995 and in use of laparoscopic appendectomy and/or CT scanning was coincidental and not causative. Further evidence for the likelihood that appendicitis is caused by an infectious disease is the observation that the disease occurs in clusters. Several well defined disease outbreaks have been identified (6;18-20) in addition to our previously described pattern of disease outbreaks (8). Seasonal changes in appendicitis have also been described (21), however, we found that although Alder et al. Appendicitis and Viral Illness Page 11 there was a tendency for appendicitis to be more common in the summer months, the seasonal variation was modest, consistent with previous reports (22). The incidence of perforated appendicitis did not correlate with nonperforating appendicitis or with the other infectious diseases we evaluated, suggesting that perforated appendicitis has causative factors that are more complex than the simple delay in treating acute appendicitis. This has important clinical ramifications since appendectomy is generally performed as an emergency operation for fear of causing a perforation if treatment is delayed. Our epidemiologic findings suggest that patients who have perforated appendicitis have a different disease entity than those with nonperforating disease Intestinal infections have been increasing with time. In 1989 there was a marked upsurge in their annual peak incidence. These findings appear to contradict a theory explaining changes in the incidence of appendicitis called the hygiene hypothesis. The rising appendicitis rate observed in the early 20 century paralleled an improvement in living conditions with fewer intestinal infections (23;24). This observation led to the “hygiene hypothesis” wherein it was posited that better hygiene caused less exposure to infectious agents reducing the immune system’s ability to prevent appendicitis (25). Up to 1995 our findings were consistent with this hypothesis since increasing numbers of persons with intestinal infection could result in enhanced immunity to other gastrointestinal infections such as appendicitis. That both intestinal infections and nonperforating appendicitis appear to have increased in incidence for the past decade mitigates against the hygiene hypothesis. Our observation that intestinal infections are on the rise is interesting. One could hypothesize that increased use of potent antibiotics has changed the intestinal flora or that increased use of potent inhibitors of gastric acid secretion has reduced the pH barrier to intestinal Alder et al. Appendicitis and Viral Illness Page 12 infection. The intestinal infections resulting in hospitalization might be due to resistant strains of bacteria or from increased susceptibility to unidentified organisms that have become more pathogenic. Viral illness has been implicated by some researchers as the cause for appendicitis. Viral infection of the appendix could cause mucosal ulceration followed by secondary bacterial infection of the appendix. Alternatively, viral disease could result in lymphoid hyperplasia of the appendix with resultant obstruction and mucosal injury followed by bacterial infection. Several viral agents have been hypothesized to cause appendicitis. Coxsackie has been associated with cecal inflammation and periappendiceal lymphoid hyperplasia (26;27). Animal studies have shown that Coxsackie infection can result in an appendicitis-like syndrome (28;29). Lymph nodes and serum obtained from appendicitis patients have shown evidence for simultaneous adenovirus infection (30-32). Measles virus and cytomegalovirus (CMV) have also been associated with appendicitis (33-35) . Bacterial infection with pathogens such as Yersinia enterocolitica has been implicated in appendicitis pathogenesis (36). One viral illness that we could investigate was rotavirus since the NHDS database had sufficient numbers of these cases allowing for a comparison between rotavirus and appendicitis admissions. We found no correlation for these disease entities suggesting that rotavirus is not a cause of appendicitis. Most theories regarding the underlying causes of appendicitis rely on the notion that the appendix becomes obstructed. This line of thinking dates back to Reginald Fitz’s first description of appendicitis wherein he had observed fecoliths on autopsies and assumed that they contributed to the pathogenesis of this disease (37). Animal studies have shown that artificially elevating appendiceal luminal pressure can result in appendicitis (38). Although an attractive hypothesis, experimental evidence suggests that the role of fecoliths as a cause for appendicitis is limited Alder et al. Appendicitis and Viral Illness Page 13 (39). Intraoperative intraluminal pressure measurements revealed that pressures were normal in acute appendicitis and only became elevated in late stage disease suggesting that obstruction occurs as inflammation progresses (40). Although fecoliths can be seen in appendicitis specimens, they only occur rarely (41). Factors more complex than simple obstruction must contribute to appendicitis pathogenesis. In conclusion, although influenza and nonperforating appendicitis have dissimilar seasonal peak incidences, parallel year-to-year peak incidence trends suggest a viral etiology for appendicitis. No association was found between the intestinal infections, rotavirus, and appendicitis. Further work more precisely identifying infectious agents in cases of appendicitis is necessary to identify potential causative agents. Alder et al. Appendicitis and Viral Illness Page 14 Table 1. Augmented Dickey-Fuller test statistic, , with the lag order of the DickeyFuller test equation and p-values (one-sided) taken from MacKinnon (42). P-values > 0.05 suggest that the time series are nonstationary due to a unit root. τ ADF * The lag order of the Dickey-Fuller test was determined by successive deletion of lags until the last augmenting term is statistically significant at the 5% level. The choice of the order of the augmenting terms is important for insuring that the test statistics have the correct size and are as powerful as possible for detecting the alternative hypothesis of stationarity. Alder et al. Appendicitis and Viral Illness Page 15 Table 2. Johansen Multiple Equation Tests for Cointegration. P-values (one-sided) found in the parenthesis test the null hypothesis of no cointegrating relationship between influenza and nonperforating appendicitis incidence versus the alternative hypothesis of cointegration between the series. Therefore, p-values <0.05 indicate cointegration, i.e. that the disease incidences are “tethered together” over time. These reported p-values were obtained from MacKinnon, Huag, and Michelis (43). * The order of the lagged differences in the Johansen Error Correction Model (ECM) multivariate test equation was determined by first choosing the optimal lag length for a levels vector autoregression (VAR) on the data and then reducing that optimal lag length by one to accommodate the differencing imposed by the Johansen ECM equation. The optimal lag length of the levels VAR was chosen by minimizing the Schwartz Bayesian goodness-of-fit criteria. The lag length is again important for assuring that the test statistics have the correct size and are as powerful as possible for potentially detecting the relevance of alternative hypotheses. Given the sample size of our data, we choose the Schwartz criterion because it tends to choose more parsimonious models. Alder et al. Appendicitis and Viral Illness Page 16 Figure 1. Monthly hospital admission rates for perforated and nonperforated appendicitis and influenza from 1970 to 2005. Data are presented as the number of hospital admissions per month per 10,000 U.S. population. The left axis represents the scale for influenza rates and the right scale for appendicitis. Influenza occurs almost exclusively in the winter months; whereas, appendicitis is present throughout the year. Appendicitis and The Flu 1970-2005 Year 19 70 19 71 19 72 19 73 19 74 19 75 19 76 19 77 19 78 19 79 19 80 19 81 19 82 19 83 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 Fl u C as es /M on th /1 0, 00 0 P op ul at io n