Can progression of odontogenic infections to cervical necrotizing soft tissue infections be predicted?


The progression of odontogenic infections to necrotizing soft tissue infections (NSTIs) is unknown. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score is used to predict risk of NSTI. This study aimed to (1) estimate the frequency at which odontogenic infections progress to NSTIs, (2) measure the value of LRINEC in predicting progression to NSTI, and (3) estimate the charges associated with managing NSTIs. This retrospective cohort study enrolled all subjects admitted for the management of odontogenic infections from 2001 to 2013. The primary predictor was the LRINEC score. The primary outcome was NSTI. The secondary outcome was billing charges. Descriptive and bivariate statistical analyses were performed, with significance set at a P -value of <0.05. Of 479 odontogenic infections, (1.0%) progressed to NSTI. The mean LRINEC for NSTI was 5.8 and for odontogenic infection was 3.4 ( P = 0.043). LRINEC parameters for the prediction of NSTIs had 60% sensitivity, 68.4% specificity, 20% positive predictive value, and 92.9% negative predictive value. The mean charge for NSTI was $319,337 and for odontogenic infections was $19,291 ( P = 0.051). One percent of odontogenic infections progressed to NSTIs. The LRINEC score was not able to identify all NSTIs. NSTIs are 16 times more costly.

Necrotizing soft tissue infections (NSTIs) and descending necrotizing mediastinitis are rare but rapidly progressive, usually polymicrobial, infections with high limb and life mortality. Mortality rates of between 30% and 50% have been reported for descending necrotizing mediastinitis. With advancements made in the medical field, other sources have reported a slight decrease in the mortality rate to 20–40%. Early diagnosis and aggressive treatment is critical to limit the associated morbidity and mortality.

The progression of odontogenic infections to NSTIs is well described, but the frequency of this progression and predictive factors are unclear. To better discriminate patients with NSTIs from those with other soft tissue infections, Wong et al. proposed the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score . The LRINEC score is a numeric score that ranges from 0 to 13 and is computed using six laboratory indices: C-reactive protein (CRP), white blood cell (WBC) count, haemoglobin (Hb), sodium, creatinine, and blood glucose. Individual point values are summed to give the total LRINEC score ( Table 1 ). With this system, a score ≤5 indicates <50% risk of NSTI, a score of 6–7 indicates 50–75% risk of NSTI, and a score ≥8 indicates a >75% risk of NSTI.

Table 1
Laboratory Risk Indicator of Necrotizing Fasciitis (LRINEC).
Laboratory parameter, units LRINEC score
CRP, mg/l
<150 0
≥150 4
Total WBC count ×10 9 /l
<15 0
15–25 1
>25 2
Hb, g/dl
>13.5 0
11–13.5 1
<11 2
Sodium, mmol/l
≥135 0
<135 2
Creatinine, mg/dl
≤1.6 0
>1.6 2
Glucose, mg/dl
≤180 0
>180 1

CRP, C-reactive protein; WBC, white blood cell; Hb, haemoglobin.

In the original study, which used patient records from two tertiary hospitals over a 5-year period, all patients diagnosed with necrotizing fasciitis were compared with a random cohort of patients diagnosed with cellulitis or abscess. The aetiology and location of the infections was not recorded. Thus, it is unclear whether this diagnostic tool is useful in the early identification of NSTI in its progression from odontogenic infection. It was hypothesized that the LRINEC score would be positively associated with the risk of NSTI in subjects with odontogenic infection. The specific aims of this study were (1) to estimate the frequency at which odontogenic infection progresses to NSTI in an inpatient cohort, (2) to measure the value of the LRINEC score in predicting this progression, and (3) to estimate the inpatient costs associated with managing patients with NSTIs.

Materials and methods

Study design/sample

After obtaining institutional review board approval, the investigators implemented a retrospective cohort study and enrolled a sample derived from the population of subjects who presented to a medical center for the evaluation and management of odontogenic infections between January 1, 2001 and December 31, 2013. To be included in the study sample, the subjects had to have one of the following discharge diagnoses, according to the International Classification of Diseases, Ninth Revision (ICD-9 codes): cellulitis (528.3), cellulitis and abscess of face/neck (682, 682.1), mediastinitis (519.2), neck swelling/mass (784.2), dental caries (521.09), and necrotizing fasciitis (728.86). Alternatively they could have a Current Procedural Terminology (CPT) code for debridement (11,040–11,044, 41,000–41,008, 41,015–41,018, 42,725, 97,597), intraoral/extraoral incision and drainage (21,501), sternal debridement (21,627), open treatment of sternum fracture with or without skeletal fixation (21,825), thoracoscopy (32,651–32,652), creation of pericardial window (33,025), mediastinotomy with exploration (39,000, 39,010), removal of devitalized tissue from wound(s) (97,602), and negative pressure therapy (97,605). A computer search of the electronic medical records was used to identify potential subjects for inclusion. Exclusion criteria were patient age <18 years, any non-odontogenic infection, and patient not pursuing treatment or for whom data were not complete.


The primary predictor variable was the LRINEC score. The LRINEC score was computed using the parameters described by Wong et al. using admission laboratory values for CRP, WBC count, Hb, sodium, creatinine, and blood glucose. For each patient, the LRINEC score was calculated as the sum of these six laboratory values as per Table 1 .

The primary outcome variable was whether or not the patient developed a NSTI and/or descending necrotizing mediastinitis. This was determined by searching for ICD codes 728.86 (necrotizing fasciitis) and 519.2 (mediastinitis), respectively. These diagnoses were confirmed clinically, operatively, and by biopsy of necrotic tissue. The secondary outcome variable was the total dollar amount billed to each subject derived from billing data. The data were collected in a Microsoft Excel spreadsheet (Microsoft, Redmond, WA, USA).

The other study variables were grouped into the following sets: demographic data, patient history, values on admission, presentation, evaluation, treatment, and outcome. The demographic variables were age (years), race (Caucasian, African American, or other), and sex (male or female). Weight (kg), height (cm), and body mass index (BMI, kg/m 2 ) were also recorded. The patient history variables were history of diabetes (insulin-dependent and non-insulin-dependent), history of dental disease, and other medical/social history (cardiac disease, liver disease, hypertension, chronic obstructive pulmonary disease, asthma, HIV/AIDS, cancer, psychiatric disorder, tobacco use, intravenous drug use, alcohol abuse, and homelessness).

Age was determined by subtracting the date of birth in the demographic information from the date of admission. Sex and race were gathered from the patient demographic information. Weight, height, and BMI were collected from the nursing notes recorded on the day of admission. Medical and social histories were determined from the emergency department notes. Any history of dental disease specifically was determined from the emergency department notes or preoperative notes indicating decay of one or more teeth on admission.

The values recorded on admission were temperature (°C), CRP (mg/l), total WBC count (×10 9 /l), Hb (g/dl), sodium (mmol/l), creatinine (mg/dl), and blood glucose (mg/dl). Temperature on admission was that recorded in the emergency department notes. Admission laboratory data for CRP, WBC, Hb, sodium, creatinine, and blood glucose were obtained from the laboratory results section of the patient’s chart.

The presentation variables were the presence of a draining wound (neck or oral), indication of gas on initial imaging, and whether there was airway compromise. Information on the use of imaging was obtained from the radiology section of the patient’s chart, and the assessment of gas on imaging was obtained from the radiology report and a review of the imaging. Airway compromise was determined by ‘airway involvement’ or ‘airway deviation’ on the radiology report. The evaluation variables were the number and type of imaging modalities used: computed tomography (CT) and magnetic resonance imaging (MRI).

The treatment variables were the treatment rendered, use of steroid treatment, type and route of antibiotics given, total number of operating room procedures within 48 h following imaging (including all washouts, which were done exclusively in the operating room), and whether surgery involved the mediastinum. Steroid and antibiotic use was determined from the inpatient medication list. The number and type of surgeries, including mediastinal involvement, was determined from the operative notes and discharge summaries. Comparison of imaging dates and procedure notes allowed the determination of which surgeries occurred within 48 h of imaging as per the imaging recommendations of Freeman et al.

All of the NSTI cases were treated with the same NSTI algorithm, as per the medical center protocol. This included quad antibiotic treatment (penicillin G, vancomycin, clindamycin, and levofloxacin or gentamicin ) until culture results were obtained, emergent debridement, serial washouts, and 48-h CT imaging.

The outcome variables were total days spent in the intensive care unit (ICU), total length of hospital stay, whether imaging was obtained within 48 h of discharge, any complications from the infection or treatment, and whether the patient died during the 90-day postoperative period. ICU use was determined from the discharge summary and inpatient notes. The discharge summary also indicated the total length of hospital stay. If the patient was not admitted overnight, the length of stay was recorded as 0. Imaging dates were compared to the discharge summary to determine whether or not imaging was obtained within 48 h of discharge. Additional information received from the billing department included type of medical coverage, actual payment, and remaining balance.

Data analyses

All data were abstracted from the subjects’ medical records and recorded using a spreadsheet (Microsoft Excel, Redmond, WA, USA). Descriptive statistics including the mean, frequency, range, and standard deviations were computed for each study variable. A Mann–Whitney U -test was used to compare the NSTI and odontogenic infection groups with respect to continuous variables. Fisher’s exact test was used to evaluate differences between groups with respect to categorical variables such as sex and race. To assess the prognostic value of the LRINEC score, diagnostic statistics were computed: sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV); this was done for the subset of patients for whom complete LRINEC laboratory parameters were obtained. To account for the small sample size, binomial proportion confidence intervals (CI) were constructed using Clopper–Pearson intervals rather than relying on the normal approximation to the binomial distribution. Statistical calculations were carried out in R version 3.2.2 (R Development Core Team, Vienna, Austria; ). Statistical significance was set at P = 0.05.


The study population was composed of 988 subjects. Subjects were excluded for the following reasons: non-odontogenic origin of infection, peritonsillar infection, osteomyelitis, and cases involving infected hardware. After applying the exclusion criteria, the final sample was composed of 479 subjects. Table 2 summarizes the results, with a comparison of NSTI to odontogenic infection for all variables analyzed. Five (1.0%) cases of NSTI were identified among the 479 subjects, two of which progressed to descending necrotizing mediastinitis. One of the five NSTI patients died within the 90-day follow-up period from chronic kidney disease for which dialysis was refused, while none of the odontogenic infection patients died within the same follow-up window.

Table 2
Study variables grouped by necrotizing soft tissue infection status (odontogenic infection vs. necrotizing soft tissue infection). a
Variables Odontogenic infection Necrotizing soft tissue infection P -value b
Demographic variables
Age, years 37.7 ± 14.4 48.8 ± 15.7 0.094
Race 0.647
African American 13.9% 20%
Caucasian 67.7% 80%
Other 18.4% 0%
Sex, male 62.0% 80% 0.656
Weight, kg 80.7 ± 24.6 84.8 ± 19.7 0.572
Height, cm 172.4 ± 10.4 181.8 ± 8.3 0.067
BMI, kg/m 2 27.2 ± 7.8 26.2 ± 9.14 0.344
Temperature, °C 37.22 ± 0.99 37.42 ± 0.82 0.612
Hypertension 14.4% 40% 0.026
Tobacco 58.0% 40% 0.722
Alcohol 11.8% 0% 1.0
HIV 1.48% 0% 1.0
Hepatitis C 2.74% 0% 1.0
Intravenous drug use 7.2% 0% 1.0
Cancer 1.69% 0% 1.0
Psychiatric illness 9.28% 0% 1.0
Renal disease 0.63% 20% 0.023
Diabetes 11.6% 40% 0.110
Dental disease 93.80% 100% 1.0
Homelessness 0.6% 0% 1.0
Laboratory variables
CRP, mg/l 116.46 ± 96.6 101.52 ± 96.69 0.919
Total WBC count, ×10 9 /l 13.68 ± 4.63 14.59 ± 5.68 0.555
Hb, g/dl 13.36 ± 2.75 10.9 ± 1.12 0.004
Sodium, g/dl 135.79 ± 2.98 135 ± 2.65 0.395
Creatinine, mg/dl 0.90 ± 0.63 1.92 ± 1.8 0.387
Glucose, mg/dl 126.24 ± 62.4 127 ± 71.1 0.947
Hospital course
Gas on imaging 12.60% 80% 0.001
Draining wound 96.83% 100% 1.00
Airway compromise 22.40% 60% 0.081
Number of CTs 1.14 ± 1.01 2.4 ± 3.71 0.988
Number of MRIs 0.006 ± 0.08 0 0.042
Mediastinal involvement 1.47% 40% 0.003
Total number of surgeries 1.3 ± 0.757 7.6 ± 6.43 <0.001
ICU, days 0.56 ± 2.26 14.6 ± 11.8 <0.001
LOS, days 4.18 ± 4.54 24.2 ± 10.4 <0.001
Imaging within 48 h of discharge 58.50% 20% 0.166
Amount billed, US$ 19,291 ± 25,915 319,337 ± 271,506 0.051
Amount collected, US$ 8975 ± 14,663 177,329 ± 248,915 0.2
BMI, body mass index; HIV, human immunodeficiency virus; CRP, C-reactive protein; WBC, white blood cell; Hb, haemoglobin; CT, computed tomography; MRI, magnetic resonance imaging; ICU, intensive care unit; LOS, length of stay.

a The results are presented as the number and percentage, or the mean ± standard deviation.

b P < 0.05 significant.

Of the 479 patients, 297 (62.0% ) of the odontogenic infection and four (80%) of the NSTI patients were male. The mean age of odontogenic infection patients was 37.7 years (range 18–93 years) and of NSTI patients was 48.8 years (range 28–66 years) ( P = 0.094). The mean BMI of the NSTI patients was 26.2 kg/m 2 (range 20.5–42.5 kg/m 2 ), while the mean BMI for odontogenic infection patients was 27.2 kg/m 2 (range 15.1–57 kg/m 2 ) ( P = 0.344). Fifty-five of the 474 odontogenic infection patients (11.6%) had a history of diabetes, either insulin-dependent or non-insulin-dependent. Of the five NSTI patients, one had non-insulin-dependent diabetes and one had insulin-dependent diabetes mellitus. Two hundred and seventy-five of the 474 odontogenic infection patients (58.0%) reported a history of tobacco use in any form. Of the five NSTI patients, two reported tobacco use. Thirty-four of the 474 (7.2%) admitted to intravenous drug use (IVDU) currently or in the past. None of the five NSTI patients admitted to IVDU, chronic alcohol abuse, or homelessness.

Three of the five NSTI patients received intravenous antibiotics prior to arrival at the medical center, one of whom received quad antibiotic therapy. All bacterial cultures for the five NSTI patients were polymicrobial oral flora. Only one NSTI patient presented with bacterial resistance; culture grew Bacteroides fragilis with clindamycin resistance. Table 3 shows a comparison of the bacterial isolates from the NSTI cases and odontogenic infection cases, as per Dillon et al.

Table 3
Frequency of pathogens isolated, in descending order of occurrence.
Necrotizing soft tissue infection (of five total) Odontogenic infection (from Dillon et al., 2012)
Streptococcus milleri ( n = 5) Anaerobic Gram-negative rods
Coagulase-negative Staphylococcus species ( n = 3) α-Hemolytic Streptococcus species
Anaerobic Gram-negative rods ( n = 3) Streptococcus milleri
α-Hemolytic Streptococcus species ( n = 2) Anaerobic non-spore-forming Gram-positive rods
Propionibacterium ( n = 1) Coagulase-negative Staphylococcus species
Eikenella species ( n = 1) Anaerobic Gram-positive cocci
Pseudomonas species ( n = 1) Neisseria species
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Dec 14, 2017 | Posted by in Oral and Maxillofacial Surgery | Comments Off on Can progression of odontogenic infections to cervical necrotizing soft tissue infections be predicted?
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