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Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based case–control study
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Original Article
Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study Tom J. Liu a, Hao-Chih Tai b, Kuo-Liong Chien c, Nai-Chen Cheng b,* a Division of Plastic Surgery, Department of Surgery, Fu Jen Catholic University Hospital, Fu Jen Catholic University, New Taipei City, Taiwan b Division of Plastic Surgery, Department of Surgery, National Taiwan University Hospital, College of Medicine, Taipei, Taiwan c Institute of Epidemiology and Preventive Medicine, College of Public Health, Health Data Research Center, National Taiwan University, Taipei, Taiwan
Received 6 September 2018; received in revised form 11 January 2019; accepted 15 January 2019
KEYWORDS Necrotizing fasciitis; Epidemiology; Mortality; Predisposing factors; Predictors of mortality
Background: Necrotizing fasciitis (NF) is a life-threatening soft tissue infection with low incidence that requires prompt surgery. In the initial stage, it is difficult to distinguish NF and cellulitis, and limited population-based reports are available. Methods: We queried inpatient data sets of National Health Institute Research Database in Taiwan from 2002 to 2011 for all patients with diagnoses of NF. Of them, only patients who underwent surgeries and had been admitted to intensive care units were included as the study group. Age and gender-matched patients with admission diagnoses of cellulitis were enrolled in a ratio of 1:4 as the control group. We calculated annual incidence, mortality rate, risk factors and predictors of mortality of NF. Results: The study group consisted of 7391 NF patients. Among them, 4715 patients (64%) were man and 2676 (36%) were women. The overall annual incidence of NF was 3.26 hospitalizations per 100,000 person-years, which rose with age with male predominance. The in-hospital mortality rate, which also rose with age, was 32.2%. Diabetes mellitus (adjusted odds ratio, 2.93; 95% confidence interval, 2.77-3.11; P value < 0.0001), alcoholism (2.64; 2.27-3.08; P < .0001), and chronic kidney disease (1.98; 1.84-2.14; P < .001) were identified as risk factors. Chronic kidney disease (1.86; 1.64-2.10; P < .001) and liver cirrhosis (1.68; 1.50-1.88; P < .001) were identified as predictors of in-hospital mortality.
* Corresponding author. National Taiwan University Hospital, No.7, Chung-Shan South Rd., Taipei, Taiwan. Fax: þ886 2 23708549 E-mail address: [email protected] (N.-C. Cheng). https://doi.org/10.1016/j.jfma.2019.01.014 0929-6646/Copyright ª 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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T.J. Liu et al. Conclusion: Age and the presence of chronic diseases are major risk factors as well as prognostic factors of NF in Taiwan. Diabetes mellitus increases the risk of NF, but does not adversely affect the outcome. Copyright ª 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
Introduction Necrotizing fasciitis (NF) is a rare life-threatening soft tissue infection that require prompt surgical and medical treatment.1,2 Generally, NF is classified into three types according to the causative pathogens.3 Type I infections are responsible for about 80% infections, which are polymicrobial and consist of a mix of aerobic and anaerobic bacteria.2,4 Type II infections are monomicrobial and classically caused by group A Streptococcus (Streptococcus pyogenes). Type III infections caused by Vibrio or Aeromonas species have been identified in patients in contact with contaminated water or food, usually presenting with fulminant sepsis and rapid progression.5 Despite the improvement in surgical techniques and intensive care, its mortality rate remained high, ranging from 12% to 43% in reported series.6e8 It is difficult to differentiate NF and cellulitis at the initial stage since the clinical presentation of both disease entities appears similar in the early phase.9e12 The diagnosis of NF relies heavily on clinical impression, so a high index of suspicion of NF is required in a patient presenting with cutaneous infection causing swelling, pain and erythema. However, previous studies of diagnostic evaluation of NF largely focused on results of blood tests or radiographic images.13 For example, Wong et al. proposed the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score to diagnose NF in 2004.12 They compared a set of laboratory risk indicators between NF and other soft tissue infections, and a statistically positive correlation between LRINEC score and a true diagnosis of NF has been reported.14 However, a recent meta-analysis study showed that LRINEC had poor sensitivity and should not be used to rule out NF.15 Apparently, factors other than laboratory data should be included when making a diagnosis of NF. Although previous studies have attempted to investigate the clinical characteristics of NF and cellulitis patients,16e18 little is known about the epidemiological profile and the mortality-associated factors of these patients. Because of the low incidence of NF (.72e9.2 per 100,000 person-years),7,8,19e21 relatively few populationbased studies of NF have been performed.19,22e25 In the United States, Holena et al. analyzed 9958 cases of NF and reported an overall mortality rate of 9.3%,22 and Mills et al. identified 688 cases of NF and found an overall mortality rate of 12%.8 In contrast to some multi-center studies, the aforementioned population-based studies have reported relatively lower mortality rates. For example, after examining data from 8 hospitals in New Zealand, the mortality rate was reported to be 23.5%.26 Goh et al. performed a
systemic review of 1463 NF cases from 9 series and estimated a mortality rate of 24.8%.27 The relatively higher incidence and lower mortality reported in these population-based studies suggested the possibilities of inclusion of non-NF cases. Therefore, the discrepancy in the literature calls for further well-designed studies to elucidate the epidemiology of NF, and to identify possible risk factors and predictors of mortality. Taiwan is a Southeast Asian country where people are predominantly ethnic Chinese. The National Health Insurance (NHI) program of Taiwan provides universal health coverage to the population since its inception in 1995. The size and representativeness of the research database of the NHI allows for epidemiological studies of rare diseases, such as NF. Therefore, the objective of this caseecontrol study was to identify the epidemiological risk factors of NF relative to a control group of cellulitis patients. Moreover, the predictors of mortality in NF patients was also investigated. To avoid the aforementioned pitfall of including non-NF cases in population-based studies, we limited NF cases to those who had undergone surgery and intensive care in this study.
Patients and methods Data source This study protocol was approved by the Research Ethics Committee of the National Taiwan University Hospital (201804082RINA). We used multiple data sets distributed by the National Health Research Institute, which has collaborated with the NHI Administration to construct the NHI research database. The data sets of inpatient expenditures contained inpatient claims of the 23 million NHI beneficiaries that represent >99% of the population. All data sets could be linked by using a unique individual identification number, which were scrambled before the release of data sets to protect patient privacy. For the precision of the claimed data, the Bureau of NHI performed expert reviews on a random sample of every 50e100 ambulatory and inpatient claims in each hospital and clinic quarterly. False reports of diagnosis may yield a severe penalty from the Bureau of NHI. Within inpatient claim, all patients from 2002 to 2011 with a primary diagnosis of International Classification of Diseases, Ninth Revision, Clinical modification (ICD-9-CM) code 728.86 (NF) with at least one operative debridement or amputation was identified. In an attempt to reduce over-diagnosis of NF, only patients who had been admitted in intensive care unit (ICU) were
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Predisposing factors of necrotizing fasciitis in Taiwan included into the NF group. On the other hand, patients with an admission diagnosis of cellulitis (ICD-9-CM: 682) without NF (ICD-9-CM: 728.86) were identified. After matched with NF group by age according to the age interval: below 40, 40e60, and beyond 60, and matched with gender in 1:4 ratio, these cellulitis patients were defined as the control group. We included only the first episode of NF or cellulitis as an incident case.
Collection of clinical data The information about demographics, the ever use of prescription drugs, such as steroid or nonsteroidal antiinflammatory drug (NSAID), and outcomes, including length of stay in hospital, frequency of surgery, amputation, and mortality, was retrieved from the inpatient data sets of both groups. Comorbidities were identified based on the following diagnostic codes which appeared once in the same patient’s inpatient data or more than three times in outpatient data: 1. Diabetes mellitus (ICD-9 CM: 250); 2. Obesity (ICD-9 CM: 2780); 3. Hypertension (ICD-9 CM: 401e405); 4. Ischemic heart disease (ICD-9 CM: 410e414); 5. Valvular heart disease (ICD-9 CM: 0932, 394e397, 424, 7463e7466, V422,V433); 6. Stroke (ICD-9 CM: 433e438); 7. Tobacco use (ICD-9 CM: 3051); 8. Alcoholism (ICD-9 CM: 303, 3050, V113); 9. Chronic kidney diseases (ICD-9 CM: 582, 5831e5837, 585e586, 588); 10. Cirrhosis of liver (ICD-9 CM: 5712, 5714, 5715, 5716, 5722e5728); 11. Human immunodeficiency virus infection (ICD-9 CM: 042, 043, 044, V08); 12. Tuberculosis infection (ICD-9-CM: 010e018 in combination with the prescription of at least two anti-tuberculosis medications for 28 days); 13. Gout (ICD-9-CM: 274); 14. Autoimmune disease (ICD-9-CM: 7100, systemic lupus erythematosus or 7102, Sjo ¨gren’s syndrome).
Statistical analysis
Incidence rate, per 100,000 person-years
The data were summarized using descriptive statistics. A Pearsonc2 test was conducted if the variable was categorical and an independent sample t test if continuous. For
3 categorical variables, descriptive analysis was presented as percentages and frequencies, and the continuous variables are expressed as the mean and standard deviation (SD) unless otherwise specified. The annual incidence rate (cases per 100,000 population) of NF was calculated using the number of defined NF cases as numerator and the number of yearly insured people in the NHI program during 2002e2011 as the denominator. The incidence rate was then stratified by age in 5-year interval and gender. We also calculated the mortality rate, which was defined as the number of mortality in NF cases as numerator and the number of NF patients during 2002e2011 as the denominator. The mortality rate was stratified by age in 10-year interval and gender. Univariate logistic regression was tested between (1) the NF and cellulitis groups, to identify the risk factors of NF; (2) the survivors and the non-survivors in the NF group, to identify the predictors of in-hospital mortality. A two-sided P < .05 indicated statistical significance. Multivariate logistic regression was used to assess risk factors by adding forward substitution factors identified as significant in the univariate logistic regression. All statistical analyses were conducted by SAS software version 9.3 (SAS Institute, Cary, NC).
Results General demographic data We identified 27202 patients with a diagnosis of NF (ICD-9CM: 728.86) who had received surgery from 2002 to 2011. Among them, 7391 patients had been admitted to ICU in the same hospitalization, so these patients were considered as patients with actual diagnosis of NF and identified as the study group. Of them, 4715 patients (64%) were man and 2676 patients (36%) were women. The median age was 63.8 years old. The overall annual incidence of NF was 3.26 hospitalizations per 100,000 person-years. The incidence rate rose with age, increasing from .06 to 22 hospitalizations per 100,000 person-years for age groups from 5 to 9 years to those 80 years (P < .0001). A higher incidence of NF was
25.00 20.00 15.00 10.00 5.00 0.00 Male
< 20 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80+ 0.15 0.30 0.67 1.16 2.04 3.46 4.86 6.22 9.56 9.98 12.73 16.28 18.56 22.39
Female 0.13 0.11 0.23 0.36 0.55 0.83 1.52 2.35 3.81 6.01 9.36 12.03 15.04 19.25
Age (year)
Figure 1
Annually incidence rate stratified by age in 5-year intervals and gender.
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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T.J. Liu et al.
found among males relative to females (4.12 vs. 2.37 hospitalizations per 100,000 population-years, respectively; P < .0001; Fig. 1). The overall in-hospital deaths were 2377 NF cases and the mortality rate was estimated to be 322 per 1000 hospitalizations. The mortality rates of NF in men (32.3%) and women (32%) were comparable (P Z .81). There was a strong positive association between patient’s age and mortality (odds ratio [OR], 1.02; 95 percent confidence interval [CI], 1.02 to 1.03; P < .0001; Fig. 2).
Risk factors of NF In univariate logistic regression, we also found significant differences of some comorbidities, such as diabetes mellitus, hypertension, ischemic heart disease, valvular heart disease, stroke, alcoholism, chronic kidney diseases, liver cirrhosis, tuberculosis, and gout between the NF group and the cellulitis group (P < .0001 respectively, Table 1). To further identify the underlying conditions which could be the risk factors of NF, we conducted multivariate logistic regression analysis using the variables with statistical significant differences in the univariate logistic regression. We identified diabetes mellitus (OR, 2.93; 95% CI, 2.77e3.11), alcoholism (OR, 2.64; 95% CI, 2.27e3.08), chronic kidney disease (OR, 1.98; 95% CI, 1.84e2.14), liver cirrhosis (OR, 1.47; 95% CI, 1.39e1.57), tuberculosis (OR, 1.44; 95% CI, 1.27e1.64), valvular heart disease (OR, 1.17; 95% CI, 1.06e1.30), and stroke (OR, 1.20; 95% CI 1.12e1.28) as risk factors of NF (Table 2).
Predictors of mortality due to NF We divided NF patients into survivors and non-survivors to examine which clinical features may be associated with mortality. After univariate logistic regression, the comorbidities which had significant differences, such as hypertension, ischemic heart disease, valvular heart disease, stroke, chronic kidney disease, liver cirrhosis, and tuberculosis (P < .0001 respectively) were used to conduct multivariate logistic regression analysis. Eventually, we identified age (OR, 1.02 per year of age; 95% CI 1.02e1.03),
Mortality rate, per 1000
600 500 400
300 200 100 0
<20
20 - 29
30 - 39
40 - 49
50 - 59
60 - 69
70 - 79
80 +
Male
67
189
219
282
273
327
356
493
Female
28
161
179
177
297
302
355
423
Age (year)
Figure 2 Mortality rate stratified by age in 10-year intervals and gender.
chronic kidney disease (OR, 1.86; 95% CI, 1.64e2.10), liver cirrhosis (OR, 1.68; 95% CI, 1.50e1.88), tuberculosis (OR, 1.45; 95% CI, 1.18e1.78), and stroke (OR, 1.19; 95% CI, 1.05e1.34) as independent predictors of mortality in NF patients (Table 3).
Discussion Several studies have reported the epidemiology of NF and shown variations in annual incidence rate, ranging from .72 to 9.2 per 100,000 person-years.19,21,25,28e30 Mortality rate of NF also varied from 12 to 43% in previous reports.6e8 The discrepancy may be attributed to the differences in the survey methods, the studied regions, ethnic groups, and time periods. However, since NF is an uncommon disease, studies focusing on its clinical features, and outcomes are usually based on relatively small case series and cohorts, thus limiting generalization of reported findings.25 Hence, using nationwide administrative data can reveal a more accurate epidemiological and clinical profile of NF. In Taiwan, NHI beneficiaries that represent >99% of the population of the 24 million inhabitants. Our study based on the research database of NHI could represent the general condition of NF in this island of southeast Asia. We adopted a more stringent criteria for NF diagnosis, so only those with both surgical and ICU admission history were included in the study group. Therefore, our calculated incidence may be underestimated. In a population-based NF study in the United States, the ICU admission rate was about 50%, and the overall incidence of NF was 6.9 hospitalizations per 100,000 person-years.31 If only the patients who had been admitted to ICU were defined as true NF patients in that study, the incidence was about 3.45, which was comparable to the incidence revealed in this study, 3.26 hospitalizations per 100,000 person-years. Similarly, another population-based NF study in the United States showed a mortality rate about 10%, which was relatively low comparing to our mortality rate of 32.2%.32 That was probably because we only included NF patients who had been admitted to ICU, thus resulting in a higher mortality rate and might overestimate it. In this study, age and male gender were found to exhibit positive correlation with the NF incidence. Moreover, using cellulitis patients as the control group, we identified the following risk factors of NF: diabetes mellitus, valvular heart disease, stroke, alcoholism, chronic kidney disease, liver cirrhosis, tuberculosis as risk factors associated with NF. Moreover, we identified age, stroke, chronic kidney disease, liver cirrhosis, tuberculosis as independent predictors of mortality among NF patients using multivariable analysis. About 20%e50% of NF patients were diabetic, and many previous studies had identified diabetes mellitus as a risk factor of NF.25,31e34 Other reported comorbidities or predisposing conditions associated with NF included obesity,25,31e34 hypertension,33,34 smoking,25,34 alcoholism,33 chronic renal disease,25 chronic liver disease,24,32 heart disease,33 and prescription of NSAID.35 With several common variables reported in the literature, age,31,32,36,37 female gender,36 immunocompromise status,37 streptococcal toxic shock syndrome,37 congestive heart failure,31 chronic renal and liver disease,31 and malignancy31 have
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Predisposing factors of necrotizing fasciitis in Taiwan Table 1
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Characteristics of NF patients and the matched cellulitis controls.
Age (year) Median (Q1-Q3) 60 þ, n (%) Female, n (%) Comorbidities, n (%) Diabetes mellitus Obesity Hypertension Ischemic heart disease Valvular heart disease Stroke Tobacco use Alcoholism Chronic kidney diseases Cirrhosis of liver HIV infection Tuberculosis Gout Autoimmune disease NSAID, n (%) Never use Ever use Steroid, n (%) Never use Ever use
NF cases (N Z 7391)
Cellulitis cases (N Z 29564)
P value
63.8 (51.7e75.1) 4227 (57.2) 2676 (36.2)
63.5 (49.8e75.0) 16908 (57.2) 10704 (36.2)
.34 1.00 1.00
4242 (57.4) 62 (.8) 4562 (61.7) 2399 (32.5) 628 (8.5) 1928 (26.1) 60 (.8) 329 (4.5) 1533 (20.7) 2121 (28.7) 10 (.1) 408 (5.5) 1826 (24.7) 86 (1.2)
8698 (29.4) 250 (.9) 15317 (51.8) 7756 (26.2) 1899 (6.4) 5505 (18.6) 311 (1.1) 461 (1.6) 2699 (9.1) 5402 (18.3) 41 (.1) 921 (3.1) 6094 (20.6) 369 (1.3)
<.0001 .95 <.0001 <.0001 <.0001 <.0001 .06 <.0001 <.0001 <.0001 .94 <.0001 <.0001 .56
251 (3.4) 7140 (96.6)
1023 (3.5) 28541 (96.5)
.79
431 (5.8) 6960 (94.2)
2069 (7.0) 27495 (93.0)
.0004
NF, necrotizing fasciitis; OR, odds ratio; CI, confidence interval; HIV, human immunodeficiency virus; NSAID, nonsteroidal antiinflammatory drug; SD, standard deviation; Q1-Q3, quartile 1-quartile 3.
Table 2
Odds ratios and 95% confidence intervals of risk factors associated with NF. Adjusteda
Crude
Age Female vs. Male Comorbidities Diabetes mellitus Obesity Hypertension Ischemic heart disease Valvular heart disease Stroke Tobacco use Alcoholism Chronic kidney diseases Cirrhosis of liver HIV infection Tuberculosis Gout Autoimmune disease Medication NSAID Steroid
OR (95% CI)
P value
OR (95% CI)
P value
1.004 (1.002e1.005) 1.00 (.95e1.05)
<.0001 1.00
.995 (.994e.997)
<.0001
3.23 (3.07e3.41) .99 (.75e1.31) 1.50 (1.42e1.58) 1.35 (1.28e1.43) 1.35 (1.23e1.49) 1.54 (1.45e1.64) .77 (.58e1.02) 2.94 (2.55e3.40) 2.61 (2.43e2.79) 1.80 (1.70e1.91) .98 (.49e1.95) 1.82 (1.61e2.05) 1.26 (1.19e1.34) .93 (.74e1.18)
<.0001 .95 <.0001 <.0001 <.0001 <.0001 .06 <.0001 <.0001 <.0001 .94 <.0001 <.0001 .56
2.93 (2.77e3.11)
<.0001
.90 (.84e.96) .91 (.85e.97) 1.17 (1.06e1.30) 1.20 (1.12e1.28)
.07 .04 .001 <.0001
2.64 (2.27e3.08) 1.98 (1.84e2.14) 1.47 (1.39e1.57)
<.0001 <.0001 <.0001
1.44 (1.27e1.64) 1.01 (.94e1.08)
<.0001 .71
1.02 (.89e1.17) 1.21 (1.09e1.35)
.79 .0004
NF, necrotizing fasciitis; OR, odds ratio; CI, confidence interval; HIV, human immunodeficiency virus; NSAID, nonsteroidal antiinflammatory drug. a Adjusted for age, diabetes, hypertension, ischemic heart diseases, valvular heart disease, stroke, alcoholism, chronic kidney diseases, cirrhosis of liver, tuberculosis, gout, and medication.
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Characteristics of non-survivors and survivors in NF patients.
Age (year) Median (Q1-Q3) Female, n (%) Comorbidities, n (%) Diabetes mellitus Obesity Hypertension Ischemic heart disease Valvular heart disease Stroke Tobacco use Alcoholism Chronic kidney diseases Cirrhosis of liver HIV infection Tuberculosis Gout Autoimmune disease NSAID, n (%) Never use Ever use Steroid, n (%) Never use Ever use
Non-survivors (N Z 2377)
Survivors (N Z 5014)
P value
Adjusted ORa (95% CI)
68.5 (55.7e78.2) 856 (36.0)
61.7 (49.8e73.3) 1820 (36.3)
<.0001 .81
1.02 (1.02e1.03)
1364 (57.4) 19 (.8) 1609 (67.7) 864 (36.4) 245 (10.3) 759 (31.9) 13 (.6) 96 (4.0) 684 (28.8) 809 (34.0) 3 (.1) 176 (7.4) 621 (26.1) 33 (1.4)
2878 (57.4) 43 (.9) 2953 (58.9) 1535 (30.6) 383 (7.6) 1169 (23.3) 47 (.9) 233 (4.7) 849 (16.9) 1312 (26.2) 7 (.1) 232 (4.6) 1205 (24.0) 53 (1.1)
.99 .80 <.0001 <.0001 <.0001 <.0001 .08 .24 <.0001 <.0001 1.00 <.0001 .05 .21
2292 (96.4) 85 (3.6)
4848 (96.7) 166 (3.3)
.56
2272 (96.6) 105 (4.4)
4688 (93.5) 326 (6.5)
.0004
.94 (.83e1.06) .89 (.79e1.01) 1.11 (.93e1.32) 1.19 (1.05e1.34)
1.86 (1.64e2.10) 1.68 (1.50e1.88) 1.45 (1.18e1.78)
NF, necrotizing fasciitis; OR, odds ratio; CI, confidence interval; HIV, human immunodeficiency virus; NSAID, nonsteroidal antiinflammatory drug; Q1-Q3, quartile 1-quartile 3; SD, standard deviation. a Adjusted for age, hypertension, ischemic heart diseases, valvular heart disease, stroke, chronic kidney diseases, liver cirrhosis, tuberculosis, and steroid usage.
been identified as the predictors for morality in NF patients. While some of the aforementioned parameters were also found to be risk factors of NF or factors associated with NF mortality in this study, some predisposing conditions were not identified. For example, female gender and heart disease were not found to be associated with mortality in this study. As a population-based study, we believe our data may provide more convincing results and assist the clinical diagnosis of NF. Among the identified risk factors of NF and its mortality, a previous diagnosis of tuberculosis was rarely associated with NF in the literature. Khanna et al. reviewed 118 NF cases and found tuberculosis as the second most common comorbidity, accounting for 11 cases.38 However, only a few case reports had addressed the association between tuberculosis and NF.38e43 Stebbing et al. reported an immunocompromised patient who presented with NF as the initial presentation of miliary tuberculosis.43 Hefny et al. reported two NF cases with initial presentation of tuberculosis and suggested that the diagnosis of tuberculosis should be suspected in patients with recurrence of NF or unexpected slow response to surgery.41 The association of tuberculosis with NF may be mediated through the impaired immune status or poor respiratory function. The current study highlighted that tuberculosis should be recognized as a risk factor of NF and a potential predictor of mortality. Despite providing abundant epidemiological data, this study exhibited several limitations, primarily because of
the use of the administrative databases. First, misclassification of the disease coding is likely. For example, some comorbidities, such as tobacco uses, alcoholism, and obesity, may be important but the severity is unclear and the accuracy may be doubtful. Patients with severe cellulitis might be given a tentative diagnosis of NF at the first sight. By including only NF patients who had undergone related surgery and ICU admission, we minimized the possible misdiagnosis of non-necrotizing soft tissue infection as NF. Second, laboratory data, including the microbiology findings, were not included in this study. In recent years, our previous studies have revealed a change of causative bacteriology of NF in Taiwan.44e48 Unfortunately, the NHI research database does not include laboratory data, rendering these important factors unable to be analyzed in this study. The inherent limitation of claims database should be taken into account when interpreting results of our analyses and comparing them with those of other studies.
Conclusions To our knowledge, this is the first nationwide populationbased study of NF with a matched cellulitis control group. In Taiwan, we found the overall annual incidence of NF was 3.26 hospitalizations per 100,000 person-years, which rose with increasing age. The mortality rate was 32.2%. We
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Predisposing factors of necrotizing fasciitis in Taiwan identified age, male gender, diabetes mellitus, valvular heart disease, stroke, alcoholism, chronic kidney disease, liver cirrhosis, and tuberculosis as risk factors of NF. Moreover, age, stroke, chronic kidney disease, liver cirrhosis, and tuberculosis were identified as independent predictors of NF-associated mortality. Rarely mentioned in previous studies, we found tuberculosis as both a risk factor and predictor of mortality of NF. Therefore, further studies of NF in tuberculosis patients are needed to elucidate their association. The identified risk factors and predictors of mortality of NF will assist physicians to make clinical decisions when facing possible NF patients.
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Financial disclosure statement None of the authors has a financial interest in any of the products, devices, or drugs mentioned in this manuscript.
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Conflict of interest The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this article.
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Acknowledgements
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The authors acknowledge statistical assistance provided by the Center of Statistical Consultation and Research in the Department of Medical Research, National Taiwan University Hospital.
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Appendix A. Supplementary data
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Supplementary data to this article can be found online at https://doi.org/10.1016/j.jfma.2019.01.014.
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References
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from the National Surgical Quality Improvement Program database. Am J Surg 2010;200:790e6. discussion 796-797. Borschitz T, Schlicht S, Siegel E, Hanke E, von Stebut E. Improvement of a Clinical Score for Necrotizing Fasciitis: ’Pain Out of Proportion’ and High CRP Levels Aid the Diagnosis. PLoS One 2015;10:e0132775. Kato T, Fujimoto N, Honda S, Fujii N, Shirai M, Nakanishi T, et al. Usefulness of serum procalcitonin for early discrimination between necrotizing fasciitis and cellulitis. Acta Derm Venereol 2017;97:141e2. Wall DB, de Virgilio C, Black S, Klein SR. Objective criteria may assist in distinguishing necrotizing fasciitis from non necrotizing soft tissue infection. Am J Surg 2000;179:17e21. Wong CH, Khin LW, Heng KS, Tan KC, Low CO. The LRINEC (Laboratory Risk Indicator for Necrotizing Fasciitis) score: a tool for distinguishing necrotizing fasciitis from other soft tissue infections. Crit Care Med 2004;32:1535e41. Stevens DL, Bryant AE. Necrotizing soft-tissue infections. N Engl J Med 2017;377:2253e65. Bechar J, Sepehripour S, Hardwicke J, Filobbos G. Laboratory risk indicator for necrotising fasciitis (LRINEC) score for the assessment of early necrotising fasciitis: a systematic review of the literature. Ann R Coll Surg Engl 2017;99:341e6. Fernando SM, Tran A, Cheng W, Rochwerg B, Kyeremanteng K, Seely AJE, et al. Necrotizing soft tissue infection: diagnostic accuracy of physical examination, imaging, and LRINEC score: a systematic review and meta-analysis. Ann Surg 2019;269: 58e65. Aragon-Sanchez J, Quintana-Marrero Y, Lazaro-Martinez JL, Hernandez-Herrero MJ, Garcia-Morales E, BeneitMontesinos JV, et al. Necrotizing soft-tissue infections in the feet of patients with diabetes: outcome of surgical treatment and factors associated with limb loss and mortality. Int J Low Extrem Wounds 2009;8:141e6. Gurlek A, Firat C, Ozturk AE, Alaybeyoglu N, Fariz A, Aslan S. Management of necrotizing fasciitis in diabetic patients. J Diabet Complicat 2007;21:265e71. Kao LS, Knight MT, Lally KP, Mercer DW. The impact of diabetes in patients with necrotizing soft tissue infections. Surg Infect (Larchmt) 2005;6:427e38. Mulla ZD, Gibbs SG, Aronoff DM. Correlates of length of stay, cost of care, and mortality among patients hospitalized for necrotizing fasciitis. Epidemiol Infect 2007;135:868e76. Oud L, Watkins P. Contemporary trends of the epidemiology, clinical characteristics, and resource utilization of necrotizing fasciitis in Texas: a population-based cohort study. Crit Care Res Pract 2015;2015:618067. Das DK, Baker MG, Venugopal K. Increasing incidence of necrotizing fasciitis in New Zealand: a nationwide study over the period 1990 to 2006. J Infect 2011;63:429e33. Holena DN, Mills AM, Carr BG, Wirtalla C, Sarani B, Kim PK, et al. Transfer status: a risk factor for mortality in patients with necrotizing fasciitis. Surgery 2011;150:363e70. Arif N, Yousfi S, Vinnard C. Deaths from necrotizing fasciitis in the United States, 2003-2013. Epidemiol Infect 2016;144: 1338e44. Hung TH, Tsai CC, Tsai CC, Tseng CW, Hsieh YH. Liver cirrhosis as a real risk factor for necrotising fasciitis: a three-year population-based follow-up study. Singap Med J 2014;55: 378e82. Tunovic E, Gawaziuk J, Bzura T, Embil J, Esmail A, Logsetty S. Necrotizing fasciitis: a six-year experience. J Burn Care Res: Off Public Am Burn Assoc 2012;33:93e100. Das DK, Baker MG, Venugopal K. Risk factors, microbiological findings and outcomes of necrotizing fasciitis in New Zealand: a retrospective chart review. BMC Infect Dis 2012;12:348. Goh T, Goh LG, Ang CH, Wong CH. Early diagnosis of necrotizing fasciitis. Br J Surg 2014;101:e119e25.
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8 28. Davies HD, McGeer A, Schwartz B, Green K, Cann D, Simor AE, et al. Invasive group A streptococcal infections in ontario, Canada. Ontario group A streptococcal study group. N Engl J Med 1996;335:547e54. 29. Sarani B, Strong M, Pascual J, Schwab CW. Necrotizing fasciitis: current concepts and review of the literature. J Am Coll Surg 2009;208:279e88. 30. Widjaja AB, Tran A, Cleland H, Leung M, Millar I. The hospital costs of treating necrotizing fasciitis. ANZ J Surg 2005;75: 1059e64. 31. Oud L, Watkins P. Necrotizing fasciitis associated with pregnancy: a population-based cohort study. Infect Dis Ther 2014; 3:307e20. 32. Psoinos CM, Flahive JM, Shaw JJ, Li Y, Ng SC, Tseng JF, et al. Contemporary trends in necrotizing soft-tissue infections in the United States. Surgery 2013;153:819e27. 33. Czymek R, Hildebrand P, Kleemann M, Roblick U, Hoffmann M, Jungbluth T, et al. New insights into the epidemiology and etiology of Fournier’s gangrene: a review of 33 patients. Infection 2009;37:306e12. 34. Faucher LD, Morris SE, Edelman LS, Saffle JR. Burn center management of necrotizing soft-tissue surgical infections in unburned patients. Am J Surg 2001;182:563e9. 35. Souyri C, Olivier P, Grolleau S, Lapeyre-Mestre M, French Network of Pharmacovigilance C. Severe necrotizing soft-tissue infections and nonsteroidal anti-inflammatory drugs. Clin Exp Dermatol 2008;33:249e55. 36. Endorf FW, Klein MB, Mack CD, Jurkovich GJ, Rivara FP. Necrotizing soft-tissue infections: differences in patients treated at burn centers and non-burn centers. J Burn Care Res: Off Public Am Burn Assoc 2008;29:933e8. 37. Golger A, Ching S, Goldsmith CH, Pennie RA, Bain JR. Mortality in patients with necrotizing fasciitis. Plast Reconstr Surg 2007; 119:1803e7. 38. Khanna AK, Tiwary SK, Kumar P, Khanna R, Khanna A. A case series describing 118 patients with lower limb necrotizing fasciitis. Int J Low Extrem Wounds 2009;8:112e6.
T.J. Liu et al. 39. Salgado Ordonez F, Funez Liebana R, Perez Nadal F, Garcia Gonzalez E. Necrotizing fasciitis as the first manifestation of tuberculosis in a immunocompromised patient. Reumatol Clı´nica 2006;2:212e6. 40. Dobos KM, Quinn FD, Ashford DA, Horsburgh CR, King CH. Emergence of a unique group of necrotizing mycobacterial diseases. Emerg Infect Dis 1999;5:367e78. 41. Hefny AF, Abu-Zidan FM. Necrotizing fasciitis as an early manifestation of tuberculosis: report of two cases. Ulus Travma Acil Cerrahi Derg 2010;16:174e6. 42. Kwon HH, Baek SH, Park SH. Miliary tuberculosis and necrotizing tuberculous fasciitis–an unusual coexistence in a rheumatoid arthritis patient. Int J Rheum Dis 2010;13: 171e4. 43. Stebbings AE, Ti TY, Tan WC. Necrotizing fasciitis–an unusual presentation of miliary mycobacterium tuberculosis. Singap Med J 1997;38:384e5. 44. Cheng NC, Chang SC, Kuo YS, Wang JL, Tang YB. Necrotizing fasciitis caused by methicillin-resistant Staphylococcus aureus resulting in death. A report of three cases. J Bone Joint Surg Am 2006;88:1107e10. 45. Cheng NC, Horng SY, Chang SC, Tang YB. Nosocomial infection of Aeromonas hydrophila presenting as necrotizing fasciitis. J Formos Med Assoc 2004;103:53e7. 46. Cheng NC, Tsai JL, Kuo YS, Hsueh PR. Bacteremic necrotizing fasciitis caused by Vibrio cholerae serogroup O56 in a patient with liver cirrhosis. J Formos Med Assoc 2004;103: 935e8. 47. Cheng NC, Wang JT, Chang SC, Tai HC, Tang YB. Necrotizing fasciitis caused by Staphylococcus aureus: the emergence of methicillin-resistant strains. Ann Plast Surg 2011;67: 632e6. 48. Cheng NC, Yu YC, Tai HC, Hsueh PR, Chang SC, Lai SY, et al. Recent trend of necrotizing fasciitis in Taiwan: focus on monomicrobial Klebsiella pneumoniae necrotizing fasciitis. Clin Infect Dis 2012;55:930e9.
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Original Article
Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study Tom J. Liu a, Hao-Chih Tai b, Kuo-Liong Chien c, Nai-Chen Cheng b,* a Division of Plastic Surgery, Department of Surgery, Fu Jen Catholic University Hospital, Fu Jen Catholic University, New Taipei City, Taiwan b Division of Plastic Surgery, Department of Surgery, National Taiwan University Hospital, College of Medicine, Taipei, Taiwan c Institute of Epidemiology and Preventive Medicine, College of Public Health, Health Data Research Center, National Taiwan University, Taipei, Taiwan
Received 6 September 2018; received in revised form 11 January 2019; accepted 15 January 2019
KEYWORDS Necrotizing fasciitis; Epidemiology; Mortality; Predisposing factors; Predictors of mortality
Background: Necrotizing fasciitis (NF) is a life-threatening soft tissue infection with low incidence that requires prompt surgery. In the initial stage, it is difficult to distinguish NF and cellulitis, and limited population-based reports are available. Methods: We queried inpatient data sets of National Health Institute Research Database in Taiwan from 2002 to 2011 for all patients with diagnoses of NF. Of them, only patients who underwent surgeries and had been admitted to intensive care units were included as the study group. Age and gender-matched patients with admission diagnoses of cellulitis were enrolled in a ratio of 1:4 as the control group. We calculated annual incidence, mortality rate, risk factors and predictors of mortality of NF. Results: The study group consisted of 7391 NF patients. Among them, 4715 patients (64%) were man and 2676 (36%) were women. The overall annual incidence of NF was 3.26 hospitalizations per 100,000 person-years, which rose with age with male predominance. The in-hospital mortality rate, which also rose with age, was 32.2%. Diabetes mellitus (adjusted odds ratio, 2.93; 95% confidence interval, 2.77-3.11; P value < 0.0001), alcoholism (2.64; 2.27-3.08; P < .0001), and chronic kidney disease (1.98; 1.84-2.14; P < .001) were identified as risk factors. Chronic kidney disease (1.86; 1.64-2.10; P < .001) and liver cirrhosis (1.68; 1.50-1.88; P < .001) were identified as predictors of in-hospital mortality.
* Corresponding author. National Taiwan University Hospital, No.7, Chung-Shan South Rd., Taipei, Taiwan. Fax: þ886 2 23708549 E-mail address: [email protected] (N.-C. Cheng). https://doi.org/10.1016/j.jfma.2019.01.014 0929-6646/Copyright ª 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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T.J. Liu et al. Conclusion: Age and the presence of chronic diseases are major risk factors as well as prognostic factors of NF in Taiwan. Diabetes mellitus increases the risk of NF, but does not adversely affect the outcome. Copyright ª 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
Introduction Necrotizing fasciitis (NF) is a rare life-threatening soft tissue infection that require prompt surgical and medical treatment.1,2 Generally, NF is classified into three types according to the causative pathogens.3 Type I infections are responsible for about 80% infections, which are polymicrobial and consist of a mix of aerobic and anaerobic bacteria.2,4 Type II infections are monomicrobial and classically caused by group A Streptococcus (Streptococcus pyogenes). Type III infections caused by Vibrio or Aeromonas species have been identified in patients in contact with contaminated water or food, usually presenting with fulminant sepsis and rapid progression.5 Despite the improvement in surgical techniques and intensive care, its mortality rate remained high, ranging from 12% to 43% in reported series.6e8 It is difficult to differentiate NF and cellulitis at the initial stage since the clinical presentation of both disease entities appears similar in the early phase.9e12 The diagnosis of NF relies heavily on clinical impression, so a high index of suspicion of NF is required in a patient presenting with cutaneous infection causing swelling, pain and erythema. However, previous studies of diagnostic evaluation of NF largely focused on results of blood tests or radiographic images.13 For example, Wong et al. proposed the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score to diagnose NF in 2004.12 They compared a set of laboratory risk indicators between NF and other soft tissue infections, and a statistically positive correlation between LRINEC score and a true diagnosis of NF has been reported.14 However, a recent meta-analysis study showed that LRINEC had poor sensitivity and should not be used to rule out NF.15 Apparently, factors other than laboratory data should be included when making a diagnosis of NF. Although previous studies have attempted to investigate the clinical characteristics of NF and cellulitis patients,16e18 little is known about the epidemiological profile and the mortality-associated factors of these patients. Because of the low incidence of NF (.72e9.2 per 100,000 person-years),7,8,19e21 relatively few populationbased studies of NF have been performed.19,22e25 In the United States, Holena et al. analyzed 9958 cases of NF and reported an overall mortality rate of 9.3%,22 and Mills et al. identified 688 cases of NF and found an overall mortality rate of 12%.8 In contrast to some multi-center studies, the aforementioned population-based studies have reported relatively lower mortality rates. For example, after examining data from 8 hospitals in New Zealand, the mortality rate was reported to be 23.5%.26 Goh et al. performed a
systemic review of 1463 NF cases from 9 series and estimated a mortality rate of 24.8%.27 The relatively higher incidence and lower mortality reported in these population-based studies suggested the possibilities of inclusion of non-NF cases. Therefore, the discrepancy in the literature calls for further well-designed studies to elucidate the epidemiology of NF, and to identify possible risk factors and predictors of mortality. Taiwan is a Southeast Asian country where people are predominantly ethnic Chinese. The National Health Insurance (NHI) program of Taiwan provides universal health coverage to the population since its inception in 1995. The size and representativeness of the research database of the NHI allows for epidemiological studies of rare diseases, such as NF. Therefore, the objective of this caseecontrol study was to identify the epidemiological risk factors of NF relative to a control group of cellulitis patients. Moreover, the predictors of mortality in NF patients was also investigated. To avoid the aforementioned pitfall of including non-NF cases in population-based studies, we limited NF cases to those who had undergone surgery and intensive care in this study.
Patients and methods Data source This study protocol was approved by the Research Ethics Committee of the National Taiwan University Hospital (201804082RINA). We used multiple data sets distributed by the National Health Research Institute, which has collaborated with the NHI Administration to construct the NHI research database. The data sets of inpatient expenditures contained inpatient claims of the 23 million NHI beneficiaries that represent >99% of the population. All data sets could be linked by using a unique individual identification number, which were scrambled before the release of data sets to protect patient privacy. For the precision of the claimed data, the Bureau of NHI performed expert reviews on a random sample of every 50e100 ambulatory and inpatient claims in each hospital and clinic quarterly. False reports of diagnosis may yield a severe penalty from the Bureau of NHI. Within inpatient claim, all patients from 2002 to 2011 with a primary diagnosis of International Classification of Diseases, Ninth Revision, Clinical modification (ICD-9-CM) code 728.86 (NF) with at least one operative debridement or amputation was identified. In an attempt to reduce over-diagnosis of NF, only patients who had been admitted in intensive care unit (ICU) were
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Predisposing factors of necrotizing fasciitis in Taiwan included into the NF group. On the other hand, patients with an admission diagnosis of cellulitis (ICD-9-CM: 682) without NF (ICD-9-CM: 728.86) were identified. After matched with NF group by age according to the age interval: below 40, 40e60, and beyond 60, and matched with gender in 1:4 ratio, these cellulitis patients were defined as the control group. We included only the first episode of NF or cellulitis as an incident case.
Collection of clinical data The information about demographics, the ever use of prescription drugs, such as steroid or nonsteroidal antiinflammatory drug (NSAID), and outcomes, including length of stay in hospital, frequency of surgery, amputation, and mortality, was retrieved from the inpatient data sets of both groups. Comorbidities were identified based on the following diagnostic codes which appeared once in the same patient’s inpatient data or more than three times in outpatient data: 1. Diabetes mellitus (ICD-9 CM: 250); 2. Obesity (ICD-9 CM: 2780); 3. Hypertension (ICD-9 CM: 401e405); 4. Ischemic heart disease (ICD-9 CM: 410e414); 5. Valvular heart disease (ICD-9 CM: 0932, 394e397, 424, 7463e7466, V422,V433); 6. Stroke (ICD-9 CM: 433e438); 7. Tobacco use (ICD-9 CM: 3051); 8. Alcoholism (ICD-9 CM: 303, 3050, V113); 9. Chronic kidney diseases (ICD-9 CM: 582, 5831e5837, 585e586, 588); 10. Cirrhosis of liver (ICD-9 CM: 5712, 5714, 5715, 5716, 5722e5728); 11. Human immunodeficiency virus infection (ICD-9 CM: 042, 043, 044, V08); 12. Tuberculosis infection (ICD-9-CM: 010e018 in combination with the prescription of at least two anti-tuberculosis medications for 28 days); 13. Gout (ICD-9-CM: 274); 14. Autoimmune disease (ICD-9-CM: 7100, systemic lupus erythematosus or 7102, Sjo ¨gren’s syndrome).
Statistical analysis
Incidence rate, per 100,000 person-years
The data were summarized using descriptive statistics. A Pearsonc2 test was conducted if the variable was categorical and an independent sample t test if continuous. For
3 categorical variables, descriptive analysis was presented as percentages and frequencies, and the continuous variables are expressed as the mean and standard deviation (SD) unless otherwise specified. The annual incidence rate (cases per 100,000 population) of NF was calculated using the number of defined NF cases as numerator and the number of yearly insured people in the NHI program during 2002e2011 as the denominator. The incidence rate was then stratified by age in 5-year interval and gender. We also calculated the mortality rate, which was defined as the number of mortality in NF cases as numerator and the number of NF patients during 2002e2011 as the denominator. The mortality rate was stratified by age in 10-year interval and gender. Univariate logistic regression was tested between (1) the NF and cellulitis groups, to identify the risk factors of NF; (2) the survivors and the non-survivors in the NF group, to identify the predictors of in-hospital mortality. A two-sided P < .05 indicated statistical significance. Multivariate logistic regression was used to assess risk factors by adding forward substitution factors identified as significant in the univariate logistic regression. All statistical analyses were conducted by SAS software version 9.3 (SAS Institute, Cary, NC).
Results General demographic data We identified 27202 patients with a diagnosis of NF (ICD-9CM: 728.86) who had received surgery from 2002 to 2011. Among them, 7391 patients had been admitted to ICU in the same hospitalization, so these patients were considered as patients with actual diagnosis of NF and identified as the study group. Of them, 4715 patients (64%) were man and 2676 patients (36%) were women. The median age was 63.8 years old. The overall annual incidence of NF was 3.26 hospitalizations per 100,000 person-years. The incidence rate rose with age, increasing from .06 to 22 hospitalizations per 100,000 person-years for age groups from 5 to 9 years to those 80 years (P < .0001). A higher incidence of NF was
25.00 20.00 15.00 10.00 5.00 0.00 Male
< 20 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80+ 0.15 0.30 0.67 1.16 2.04 3.46 4.86 6.22 9.56 9.98 12.73 16.28 18.56 22.39
Female 0.13 0.11 0.23 0.36 0.55 0.83 1.52 2.35 3.81 6.01 9.36 12.03 15.04 19.25
Age (year)
Figure 1
Annually incidence rate stratified by age in 5-year intervals and gender.
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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T.J. Liu et al.
found among males relative to females (4.12 vs. 2.37 hospitalizations per 100,000 population-years, respectively; P < .0001; Fig. 1). The overall in-hospital deaths were 2377 NF cases and the mortality rate was estimated to be 322 per 1000 hospitalizations. The mortality rates of NF in men (32.3%) and women (32%) were comparable (P Z .81). There was a strong positive association between patient’s age and mortality (odds ratio [OR], 1.02; 95 percent confidence interval [CI], 1.02 to 1.03; P < .0001; Fig. 2).
Risk factors of NF In univariate logistic regression, we also found significant differences of some comorbidities, such as diabetes mellitus, hypertension, ischemic heart disease, valvular heart disease, stroke, alcoholism, chronic kidney diseases, liver cirrhosis, tuberculosis, and gout between the NF group and the cellulitis group (P < .0001 respectively, Table 1). To further identify the underlying conditions which could be the risk factors of NF, we conducted multivariate logistic regression analysis using the variables with statistical significant differences in the univariate logistic regression. We identified diabetes mellitus (OR, 2.93; 95% CI, 2.77e3.11), alcoholism (OR, 2.64; 95% CI, 2.27e3.08), chronic kidney disease (OR, 1.98; 95% CI, 1.84e2.14), liver cirrhosis (OR, 1.47; 95% CI, 1.39e1.57), tuberculosis (OR, 1.44; 95% CI, 1.27e1.64), valvular heart disease (OR, 1.17; 95% CI, 1.06e1.30), and stroke (OR, 1.20; 95% CI 1.12e1.28) as risk factors of NF (Table 2).
Predictors of mortality due to NF We divided NF patients into survivors and non-survivors to examine which clinical features may be associated with mortality. After univariate logistic regression, the comorbidities which had significant differences, such as hypertension, ischemic heart disease, valvular heart disease, stroke, chronic kidney disease, liver cirrhosis, and tuberculosis (P < .0001 respectively) were used to conduct multivariate logistic regression analysis. Eventually, we identified age (OR, 1.02 per year of age; 95% CI 1.02e1.03),
Mortality rate, per 1000
600 500 400
300 200 100 0
<20
20 - 29
30 - 39
40 - 49
50 - 59
60 - 69
70 - 79
80 +
Male
67
189
219
282
273
327
356
493
Female
28
161
179
177
297
302
355
423
Age (year)
Figure 2 Mortality rate stratified by age in 10-year intervals and gender.
chronic kidney disease (OR, 1.86; 95% CI, 1.64e2.10), liver cirrhosis (OR, 1.68; 95% CI, 1.50e1.88), tuberculosis (OR, 1.45; 95% CI, 1.18e1.78), and stroke (OR, 1.19; 95% CI, 1.05e1.34) as independent predictors of mortality in NF patients (Table 3).
Discussion Several studies have reported the epidemiology of NF and shown variations in annual incidence rate, ranging from .72 to 9.2 per 100,000 person-years.19,21,25,28e30 Mortality rate of NF also varied from 12 to 43% in previous reports.6e8 The discrepancy may be attributed to the differences in the survey methods, the studied regions, ethnic groups, and time periods. However, since NF is an uncommon disease, studies focusing on its clinical features, and outcomes are usually based on relatively small case series and cohorts, thus limiting generalization of reported findings.25 Hence, using nationwide administrative data can reveal a more accurate epidemiological and clinical profile of NF. In Taiwan, NHI beneficiaries that represent >99% of the population of the 24 million inhabitants. Our study based on the research database of NHI could represent the general condition of NF in this island of southeast Asia. We adopted a more stringent criteria for NF diagnosis, so only those with both surgical and ICU admission history were included in the study group. Therefore, our calculated incidence may be underestimated. In a population-based NF study in the United States, the ICU admission rate was about 50%, and the overall incidence of NF was 6.9 hospitalizations per 100,000 person-years.31 If only the patients who had been admitted to ICU were defined as true NF patients in that study, the incidence was about 3.45, which was comparable to the incidence revealed in this study, 3.26 hospitalizations per 100,000 person-years. Similarly, another population-based NF study in the United States showed a mortality rate about 10%, which was relatively low comparing to our mortality rate of 32.2%.32 That was probably because we only included NF patients who had been admitted to ICU, thus resulting in a higher mortality rate and might overestimate it. In this study, age and male gender were found to exhibit positive correlation with the NF incidence. Moreover, using cellulitis patients as the control group, we identified the following risk factors of NF: diabetes mellitus, valvular heart disease, stroke, alcoholism, chronic kidney disease, liver cirrhosis, tuberculosis as risk factors associated with NF. Moreover, we identified age, stroke, chronic kidney disease, liver cirrhosis, tuberculosis as independent predictors of mortality among NF patients using multivariable analysis. About 20%e50% of NF patients were diabetic, and many previous studies had identified diabetes mellitus as a risk factor of NF.25,31e34 Other reported comorbidities or predisposing conditions associated with NF included obesity,25,31e34 hypertension,33,34 smoking,25,34 alcoholism,33 chronic renal disease,25 chronic liver disease,24,32 heart disease,33 and prescription of NSAID.35 With several common variables reported in the literature, age,31,32,36,37 female gender,36 immunocompromise status,37 streptococcal toxic shock syndrome,37 congestive heart failure,31 chronic renal and liver disease,31 and malignancy31 have
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Predisposing factors of necrotizing fasciitis in Taiwan Table 1
5
Characteristics of NF patients and the matched cellulitis controls.
Age (year) Median (Q1-Q3) 60 þ, n (%) Female, n (%) Comorbidities, n (%) Diabetes mellitus Obesity Hypertension Ischemic heart disease Valvular heart disease Stroke Tobacco use Alcoholism Chronic kidney diseases Cirrhosis of liver HIV infection Tuberculosis Gout Autoimmune disease NSAID, n (%) Never use Ever use Steroid, n (%) Never use Ever use
NF cases (N Z 7391)
Cellulitis cases (N Z 29564)
P value
63.8 (51.7e75.1) 4227 (57.2) 2676 (36.2)
63.5 (49.8e75.0) 16908 (57.2) 10704 (36.2)
.34 1.00 1.00
4242 (57.4) 62 (.8) 4562 (61.7) 2399 (32.5) 628 (8.5) 1928 (26.1) 60 (.8) 329 (4.5) 1533 (20.7) 2121 (28.7) 10 (.1) 408 (5.5) 1826 (24.7) 86 (1.2)
8698 (29.4) 250 (.9) 15317 (51.8) 7756 (26.2) 1899 (6.4) 5505 (18.6) 311 (1.1) 461 (1.6) 2699 (9.1) 5402 (18.3) 41 (.1) 921 (3.1) 6094 (20.6) 369 (1.3)
<.0001 .95 <.0001 <.0001 <.0001 <.0001 .06 <.0001 <.0001 <.0001 .94 <.0001 <.0001 .56
251 (3.4) 7140 (96.6)
1023 (3.5) 28541 (96.5)
.79
431 (5.8) 6960 (94.2)
2069 (7.0) 27495 (93.0)
.0004
NF, necrotizing fasciitis; OR, odds ratio; CI, confidence interval; HIV, human immunodeficiency virus; NSAID, nonsteroidal antiinflammatory drug; SD, standard deviation; Q1-Q3, quartile 1-quartile 3.
Table 2
Odds ratios and 95% confidence intervals of risk factors associated with NF. Adjusteda
Crude
Age Female vs. Male Comorbidities Diabetes mellitus Obesity Hypertension Ischemic heart disease Valvular heart disease Stroke Tobacco use Alcoholism Chronic kidney diseases Cirrhosis of liver HIV infection Tuberculosis Gout Autoimmune disease Medication NSAID Steroid
OR (95% CI)
P value
OR (95% CI)
P value
1.004 (1.002e1.005) 1.00 (.95e1.05)
<.0001 1.00
.995 (.994e.997)
<.0001
3.23 (3.07e3.41) .99 (.75e1.31) 1.50 (1.42e1.58) 1.35 (1.28e1.43) 1.35 (1.23e1.49) 1.54 (1.45e1.64) .77 (.58e1.02) 2.94 (2.55e3.40) 2.61 (2.43e2.79) 1.80 (1.70e1.91) .98 (.49e1.95) 1.82 (1.61e2.05) 1.26 (1.19e1.34) .93 (.74e1.18)
<.0001 .95 <.0001 <.0001 <.0001 <.0001 .06 <.0001 <.0001 <.0001 .94 <.0001 <.0001 .56
2.93 (2.77e3.11)
<.0001
.90 (.84e.96) .91 (.85e.97) 1.17 (1.06e1.30) 1.20 (1.12e1.28)
.07 .04 .001 <.0001
2.64 (2.27e3.08) 1.98 (1.84e2.14) 1.47 (1.39e1.57)
<.0001 <.0001 <.0001
1.44 (1.27e1.64) 1.01 (.94e1.08)
<.0001 .71
1.02 (.89e1.17) 1.21 (1.09e1.35)
.79 .0004
NF, necrotizing fasciitis; OR, odds ratio; CI, confidence interval; HIV, human immunodeficiency virus; NSAID, nonsteroidal antiinflammatory drug. a Adjusted for age, diabetes, hypertension, ischemic heart diseases, valvular heart disease, stroke, alcoholism, chronic kidney diseases, cirrhosis of liver, tuberculosis, gout, and medication.
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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T.J. Liu et al. Table 3
Characteristics of non-survivors and survivors in NF patients.
Age (year) Median (Q1-Q3) Female, n (%) Comorbidities, n (%) Diabetes mellitus Obesity Hypertension Ischemic heart disease Valvular heart disease Stroke Tobacco use Alcoholism Chronic kidney diseases Cirrhosis of liver HIV infection Tuberculosis Gout Autoimmune disease NSAID, n (%) Never use Ever use Steroid, n (%) Never use Ever use
Non-survivors (N Z 2377)
Survivors (N Z 5014)
P value
Adjusted ORa (95% CI)
68.5 (55.7e78.2) 856 (36.0)
61.7 (49.8e73.3) 1820 (36.3)
<.0001 .81
1.02 (1.02e1.03)
1364 (57.4) 19 (.8) 1609 (67.7) 864 (36.4) 245 (10.3) 759 (31.9) 13 (.6) 96 (4.0) 684 (28.8) 809 (34.0) 3 (.1) 176 (7.4) 621 (26.1) 33 (1.4)
2878 (57.4) 43 (.9) 2953 (58.9) 1535 (30.6) 383 (7.6) 1169 (23.3) 47 (.9) 233 (4.7) 849 (16.9) 1312 (26.2) 7 (.1) 232 (4.6) 1205 (24.0) 53 (1.1)
.99 .80 <.0001 <.0001 <.0001 <.0001 .08 .24 <.0001 <.0001 1.00 <.0001 .05 .21
2292 (96.4) 85 (3.6)
4848 (96.7) 166 (3.3)
.56
2272 (96.6) 105 (4.4)
4688 (93.5) 326 (6.5)
.0004
.94 (.83e1.06) .89 (.79e1.01) 1.11 (.93e1.32) 1.19 (1.05e1.34)
1.86 (1.64e2.10) 1.68 (1.50e1.88) 1.45 (1.18e1.78)
NF, necrotizing fasciitis; OR, odds ratio; CI, confidence interval; HIV, human immunodeficiency virus; NSAID, nonsteroidal antiinflammatory drug; Q1-Q3, quartile 1-quartile 3; SD, standard deviation. a Adjusted for age, hypertension, ischemic heart diseases, valvular heart disease, stroke, chronic kidney diseases, liver cirrhosis, tuberculosis, and steroid usage.
been identified as the predictors for morality in NF patients. While some of the aforementioned parameters were also found to be risk factors of NF or factors associated with NF mortality in this study, some predisposing conditions were not identified. For example, female gender and heart disease were not found to be associated with mortality in this study. As a population-based study, we believe our data may provide more convincing results and assist the clinical diagnosis of NF. Among the identified risk factors of NF and its mortality, a previous diagnosis of tuberculosis was rarely associated with NF in the literature. Khanna et al. reviewed 118 NF cases and found tuberculosis as the second most common comorbidity, accounting for 11 cases.38 However, only a few case reports had addressed the association between tuberculosis and NF.38e43 Stebbing et al. reported an immunocompromised patient who presented with NF as the initial presentation of miliary tuberculosis.43 Hefny et al. reported two NF cases with initial presentation of tuberculosis and suggested that the diagnosis of tuberculosis should be suspected in patients with recurrence of NF or unexpected slow response to surgery.41 The association of tuberculosis with NF may be mediated through the impaired immune status or poor respiratory function. The current study highlighted that tuberculosis should be recognized as a risk factor of NF and a potential predictor of mortality. Despite providing abundant epidemiological data, this study exhibited several limitations, primarily because of
the use of the administrative databases. First, misclassification of the disease coding is likely. For example, some comorbidities, such as tobacco uses, alcoholism, and obesity, may be important but the severity is unclear and the accuracy may be doubtful. Patients with severe cellulitis might be given a tentative diagnosis of NF at the first sight. By including only NF patients who had undergone related surgery and ICU admission, we minimized the possible misdiagnosis of non-necrotizing soft tissue infection as NF. Second, laboratory data, including the microbiology findings, were not included in this study. In recent years, our previous studies have revealed a change of causative bacteriology of NF in Taiwan.44e48 Unfortunately, the NHI research database does not include laboratory data, rendering these important factors unable to be analyzed in this study. The inherent limitation of claims database should be taken into account when interpreting results of our analyses and comparing them with those of other studies.
Conclusions To our knowledge, this is the first nationwide populationbased study of NF with a matched cellulitis control group. In Taiwan, we found the overall annual incidence of NF was 3.26 hospitalizations per 100,000 person-years, which rose with increasing age. The mortality rate was 32.2%. We
Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014
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Predisposing factors of necrotizing fasciitis in Taiwan identified age, male gender, diabetes mellitus, valvular heart disease, stroke, alcoholism, chronic kidney disease, liver cirrhosis, and tuberculosis as risk factors of NF. Moreover, age, stroke, chronic kidney disease, liver cirrhosis, and tuberculosis were identified as independent predictors of NF-associated mortality. Rarely mentioned in previous studies, we found tuberculosis as both a risk factor and predictor of mortality of NF. Therefore, further studies of NF in tuberculosis patients are needed to elucidate their association. The identified risk factors and predictors of mortality of NF will assist physicians to make clinical decisions when facing possible NF patients.
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Financial disclosure statement None of the authors has a financial interest in any of the products, devices, or drugs mentioned in this manuscript.
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Conflict of interest The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this article.
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Acknowledgements
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The authors acknowledge statistical assistance provided by the Center of Statistical Consultation and Research in the Department of Medical Research, National Taiwan University Hospital.
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Appendix A. Supplementary data
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Supplementary data to this article can be found online at https://doi.org/10.1016/j.jfma.2019.01.014.
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References
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Please cite this article as: Liu TJ et al., Predisposing factors of necrotizing fasciitis with comparison to cellulitis in Taiwan: A nationwide population-based caseecontrol study, Journal of the Formosan Medical Association, https://doi.org/10.1016/j.jfma.2019.01.014