Abstract
Objectives
Severe maxillofacial space infection (MSI) as an end stage of dentoalveolar diseases or complication of sialadenitis is a potentially life-threatening disease accompanied by complications including airway obstruction, jugular vein thrombosis, descending mediastinitis, sepsis and acute respiratory distress syndrome. The aim of this study was to analyze the incidence and time trends of severe MSI and potentially influencing factors in the German healthcare system over time.
Materials and methods
Nationwide data regarding the national diagnosis-related-group (DRG) inpatient billing system was received from the German Federal Statistical Office. A retrospective analysis of incidence and time trends of MSI-associated procedures classified with the Operation and Procedure Classification System (OPS), were statistically evaluated using Poisson regression analysis between 2005 and 2022 and were associated with different epidemiological factors.
Results
The total standardized incidence rate of MSI-associated procedures in the observational period 2005—2022 was 9.8 (♀8.2; ♂11.4) per 100,000 person years. For all age groups a significant increase of 46.1% in severe MSI – related surgical interventions was registered within the observational period. The largest increase (120.5%) was found in elderly patients over 80 years. There were significant differences of the incidences of MSI-associated surgeries between the different federal states in Germany.
Conclusions
Severe MSI are a growing challenge in German health care especially among elderly patients over 80 years.
Clinical relevance
Severe MSI is a promising target for prevention. There should be more focus in primary dental and medical care especially in groups depending on social support.
Keywords: Epidemiology, Incision, Maxillofacial abscess, Odontogenic abscess, Super octogenarian, Time trends
Introduction
Severe maxillofacial space infections (MSI) are defined as cellulitis or abscess formations of the fascial planes and potential spaces of the head and neck [1]. Early identification and therapy are crucial in prevention of severe potential life-threatening complications such as upper airway obstruction, descending mediastinitis, pleural empyema, pericarditis, jugular vein thrombosis, sepsis or carotid pseudoaneurysm [2]. Even lethal outcomes were documented [3, 4]. Most common primary sources of MSI are end stage of dental disease, complication of sialadenitis, perioperative complication or malignancy [5]. Microbiology typically reveals a mixed bacterial flora, including anaerobic species, that can rapidly progress. Usually, the results of cultures are polymicrobial, and are often caused by oral bacteria. Streptococci are the organisms most commonly cultured from MSI [6]. Since the main symptoms of infection are similar between the different etiologies, clinical diagnosis may be difficult [7]. Identification of causative factors may require radiological examination with ultrasound (US), computed tomography (CT) or magnetic resonance imaging (MRI). Historically, with the introduction and widespread availability of antibiotics the incidence and severity of this disease have declined dramatically. The wide availability of dental care is also an important factor in prevention of MSI [8, 9].
The pillars of treatment are appropriate antimicrobial therapy, sufficient surgical drainage, endodontic or surgical treatment of causative teeth as well as the early management of complications [5, 10]. A calculated empirical antibiotic treatment is necessary until culture-guided antimicrobial therapy is available [11]. Improving the immunological status can have a significantly positive influence on the course of the disease in patients with systemic risk factors such as diabetes mellitus, end stage renal disease or autoimmune disorders [12]. Especially in an aging society with increasing multimorbidity and social imbalance MSI continue to represent a challenge with potentially preventable mortality [13, 14]. However, population-based data about trends in the incidence of severe MSI due to its different causes are limited and may be inconclusive.
Studies from the UK report that the incidence of MSI has increased within the last decades as growing health inequalities are leading to an increase in hospital admissions due to severe odontogenic infections [15, 16]. To our knowledge, there is no conclusive data from any other central European country. The purpose of this study was therefore to investigate the nationwide incidence of severe MSI in Germany. For this purpose, the regional, gender-specific and age-related distribution of patients suffering from severe MSI who required inpatient external incision and drainage in different maxillofacial regions was evaluated.
Materials and methods
The national diagnosis-related groups (DRG) inpatient billing system includes data from all hospitals in Germany that use the DRG system. More than 99% of inpatient treatments are covered. Hospitals are required by law to provide comprehensive information about hospital care, including patient demographics, diagnoses, comorbidities, complications and procedures.
Surgical procedures from the years 2005 to 2022 were coded according to the OPS (Operation and Procedure Classification System), a German modification of the ICPM (International Classification of Medical Procedures). All diagnoses were coded according to the ICD-10GM (German version of the International Classification of Diseases and Related Health Problems, 10th Edition). Detailed lists of all procedures regarding extraoral incision and drainage of severe MSI per year (coded 5–270.0 to 5–270.9; 5–270.x and 5–270.y in the OPS) were provided by the German Federal Statistical Office (Statistisches Bundesamt—Destatis. Genesis-Online. Data license by-2–0). MSI—associated procedures per year (PPY) were calculated and reported. Mean age of patients was calculated. The normality of the distribution of continuous variables was tested by Kolmogorov–Smirnov test. Continuous variables with normal distribution were presented as mean and standard deviation. Means of 2 continuous normally distributed variables were compared by independent samples Student's t-test. The differences were considered significant at p < 0.05. In addition, population-adjusted rates of MSI-associated surgeries per 100,000 person years were calculated using population data also provided by the German Federal Statistical Office and reported with 95% confidence interval. In order to avoid seasonal influences, the MSI-associated infection procedures were analyzed on an annual basis. We performed the main analysis for the entire population and the analyses stratified by sex, age group and federal state. We computed crude and age-sex standardized incidence rates of severe MSI for each calendar year, taking the German population of the latest census 2011 as standard population using 0–14, 15–34, 35–59, 60–79 and ≥ 80 years as age classes to exclude bias due to demographic heterogeneity over time. To ascertain male and female incidence rates, age standardization was performed with the aforementioned age classes using the age distribution of the male and female standard population resulting in different weights for both genders. The calculation of the 95% confidence intervals (95% CI) of crude and standardized incidences was performed by the delta method. Separate Poisson regression models were computed to investigate time trends, fitted with incidence rates of MSI as dependent variables and age group, gender, federal state and year of MSI starting from baseline year 2005 as independent variables. The age class 15–34 years, female sex and federal state of Baden-Württemberg were used as reference group. All models were adapted by descale adjustment to account for overdispersion of the outcome variable. Statistical analysis was performed using IBM SPSS Statistics Version 29.0 (IBM Deutschland GmbH, Böblingen, Germany).
Results
In the observational period 2005—2022 a total of 144,881 MSI-associated procedures were registered in Germany and could be included in the study. The distribution regarding age, gender and year of cases treated for severe MSI is presented in Table 1 and Fig. 1. The majority of cases were older than 35 years (68.4%) and male (57.2%). The mean age increased within this period from 45.0 years between 2005 and 2013 to 48.6 years between 2014 and 2022 (p < 0.01). The age and gender standardized incidence rates of procedures associated with severe MSI are shown in Table 2, Figs. 2 and 3 for the total population and stratified by gender and age. The total standardized incidence rate of MSI-associated procedures in the observational period 2005—2022 was 9.8 per 100,000 person years [95% CI: 9.7–9.8] ranging from 7.6 [7.4–7.8] in 2005 to 11.6 [11.4–11.8] in 2019. In 2022 the incidence was 11.1 [10.9–11.3], an increase of + 45.7% within the observational period. Gender distribution slightly shifted from 59.5% in males and 40.5% in females in 2005 to 56.7% and 43.3% in 2022, respectively. In males the overall incidence was 11.4 [11.3–11.5] spreading from 9.1 [8.8–9.4] in 2005 to 13.6 [13.3–14.0] in 2019, in females the total incidence rate was 8.2 [8.1–8.3] varying between 6.2 [6.0–6.5] in 2005 and 9.7 [9.4–10.0] in 2019.
Table 1.
Total numbers and mean age of MSI-associated procedures in Germany 2005 – 2022
| All MSI-associated procedures | Total | Male | Female | |
|---|---|---|---|---|
| Number of procedures mean age (years, SD) |
144,881 47.2 (22.2) |
82,825 44.7 (20.7) |
62,053 50.5 (23.8) |
|
| Year | ||||
| 2005 |
number of procedures mean age (years, SD) |
6282 42.1 (21.9) |
3687 40.2 (20.0) |
2594 44.7 (24.2) |
| 2006 |
number of procedures mean age (years, SD) |
6669 43.8 (21.9) |
3866 41.6 (19.9) |
2802 46.9 (24.1) |
| 2007 |
number of procedures mean age (years, SD) |
6630 44.2 (21.9) |
3957 42.2 (20.2) |
2673 47.2 (23.9) |
| 2008 |
number of procedures mean age (years, SD) |
6884 44.3 (21.7) |
3993 42.2 (20.0) |
2891 47.3 (23.5) |
| 2009 |
number of procedures mean age (years, SD) |
7282 44.9 (22.2) |
4094 42.3 (20.5) |
3188 48.4 (23.9) |
| 2010 |
number of procedures mean age (years, SD) |
7199 45.8 (22.2) |
4235 43.3 (20.5) |
2964 49.4 (24.1) |
| 2011 |
number of procedures mean age (years, SD) |
7420 46.7 (22.1) |
4202 44.0 (20.4) |
3218 50.2 (23.6) |
| 2012 |
number of procedures mean age (years, SD) |
7814 46.1 (21.6) |
4539 44.0 (20.0) |
3275 49.0 (23.3) |
| 2013 |
number of procedures mean age (years, SD) |
7970 46.7 (22.3) |
4611 44.5 (20.6) |
3358 49.8 (24.1) |
| 2014 |
number of procedures mean age (years, SD) |
8300 47.5 (22.2) |
4746 45.1 (20.8) |
3554 50.8 (23.7) |
| 2015 |
number of procedures mean age (years, SD) |
8462 47.6 (22.3) |
4803 44.7 (20.7) |
3659 51.3 (23.7) |
| 2016 |
number of procedures mean age (years, SD) |
8739 47.5 (22.6) |
5070 44.7 (21.2) |
3669 51.3 (23.9) |
| 2017 |
number of procedures mean age (years, SD) |
8905 48.4 (22.4) |
5012 45.8 (21.0) |
3893 51.9 (23.7) |
| 2018 |
number of procedures mean age (years, SD) |
9228 48.2 (22.4) |
5234 45.8 (21.1) |
3994 51.5 (23.7) |
| 2019 |
number of procedures mean age (years, SD) |
9710 49.3 (22.5) |
5564 47.1 (21.3) |
4146 52.1 (23.7) |
| 2020 |
number of procedures mean age (years, SD) |
9197 49.9 (22.4) |
5131 47.4 (21.0) |
4066 53.1 (23.7) |
| 2021 |
number of procedures mean age (years, SD) |
8828 50.4 (22.4) |
4924 47.8 (20.7) |
3904 53.7 (23.9) |
| 2022 |
number of procedures mean age (years, SD) |
9362 50.6 (22.3) |
5157 48.2 (21.1) |
4205 53.6 (23.4) |
| Age group | ||||
| 0—14 years | 10,498 | 5914 | 4584 | |
| 15—34 years | 35,222 | 22,276 | 12,946 | |
| 35—59 years | 54,304 | 33,525 | 20,779 | |
| 60—79 years | 32,696 | 17,153 | 15,543 | |
| Over 80 years | 12,158 | 3957 | 8201 | |
Fig. 1.
a Age-gender-diagram of the total number of MSI-associated procedures 2005–2022. b Age-gender-diagram of the German population based on census 2011
Table 2.
Incidence of severe MSI-associated procedures in Germany 2005—2022. Incidence rates (95% confidence interval) per 100,000 person years standardized to the German population based on the Census 2011
| Total | Gender | Age group | ||||||
|---|---|---|---|---|---|---|---|---|
| Male | Female | 0—14 years | 15 – 34 years |
35 – 59 years | 60—79 years | over 80 years |
||
| All years |
9.8 (9.7 – 9.8) |
11.4 (11.3 – 11.5) |
8.2 (8.1 – 8.3) |
5.2 (5.1—5.3) |
10.2 (10.1—10.4) |
10.3 (10.2—10.4) |
10.3 (10.2—10.4) |
13.8 (13.6—14.1) |
| Year | ||||||||
| 2005 |
7.6 (7.4 – 7.8) |
9.1 (8.8—9.4) |
6.2 (6.0—6.5) |
5.6 (5.2—6.0) |
9.2 (8.7—9.6) |
7.5 (7.2—7.9) |
7.1 (6.7—7.5) |
8.3 (7.3—9.2) |
| 2006 |
8.2 (8.0 – 8.3) |
9.6 (9.3—9.9) |
6.8 (6.5 – 7.0) |
5.0 (4.6—5.3) |
9.3 (8.9—9.7) |
8.3 (7.9—8.6) |
7.9 (7.4—8.3) |
10.6 (9.5—11.6) |
| 2007 |
8.1 (7.9 – 8.3) |
9.8 (9.5—10.1) |
6.4 (6.2—6.7) |
5.0 (4.6—5.3) |
9.1 (8.6—9.5) |
8.3 (8.0—8.6) |
7.8 (7.4—8.3) |
10.3 (9.3—11.3) |
| 2008 |
8.4 (8.2 – 8.6) |
9.9 (9.6—10.2) |
7.0 (6.7—7.2) |
5.1 (4.7—5.4) |
9.6 (9.2—10.0) |
8.7 (8.4—9.1) |
8.0 (7.6—8.4) |
10.3 (9.3—11.3) |
| 2009 |
8.9 (8.7 – 9.1) |
10.2 (9.9—10.5) |
7.7 (7.4—7.9) |
5.6 (5.1—5.9) |
9.9 (9.5—10.4) |
9.2 (8.8—9.5) |
8.5 (8.1—8.9) |
12.3 (11.2—13.4) |
| 2010 |
8.8 (8.6 – 9.0) |
10.5 (10.2—10.9) |
7.1 (6.9—7.4) |
5.3 (4.8—5.6) |
9.6 (9.2—10.1) |
8.9 (8.6—9.2) |
9.2 (8.8—9.7) |
11.6 (10.6—12.6) |
| 2011 |
9.2 (9.0 – 9.4) |
10.7 (10.4 – 11.0) |
7.8 (7.6—8.1) |
4.9 (4.5—5.3) |
10.1 (9.6—10.5) |
9.6 (9.2—9.9) |
9.6 (9.1—10.1) |
12.6 (11.5—13.7) |
| 2012 |
9.7 (9.5 – 9.9) |
11.5 (11.2—11.8) |
7.9 (7.7—8.2) |
4.6 (4.2—5.0) |
11.2 (10.7—11.7) |
10.4 (10.0—10.7) |
9.4 (8.9—9.8) |
12.5 (11.5—13.6) |
| 2013 |
9.8 (9.6 – 10.0) |
11.6 (11.3 – 12.0) |
8.1 (7.9—8.4) |
5.7 (5.3—6.1) |
10.5 (10.0—11.0) |
10.2 (9.8—10.6) |
10.2 (9.7—10.7) |
13.8 (12.7—14.9) |
| 2014 |
10.2 (9.9 – 10.4) |
11.9 (11.5—12.2) |
8.5 (8.3—8.8) |
5.5 (5.1—5.9) |
10.7 (10.3—11.2) |
10.6 (10.3—11.0) |
10.7 (10.2—11.2) |
14.8 (13.7—16.0) |
| 2015 |
10.2 (10.0 – 10.4) |
11.8 (11.5—12.2) |
8.7 (8.4 – 9.0) |
5.3 (4.8—5.6) |
10.8 (10.3—11.3) |
10.7 (10.3—11.1) |
11.2 (10.7—11.7) |
14.5 (13.4—15.5) |
| 2016 |
10.5 (10.3 – 10.7) |
12.5 (12.1—12.8) |
8.7 (8.4 – 9.0) |
6.0 (5.5—6.3) |
11.0 (10.6—11.5) |
10.8 (10.4—11.2) |
11.5 (11.0—12.0) |
15.0 (13.9—16.0) |
| 2017 |
10.7 (10.5 – 10.9) |
12.3 (12.0—12.6) |
9.2 (8.9—9.5) |
5.5 (5.1—5.8) |
10.8 (10.3—11.2) |
11.3 (10.9—11.7) |
11.8 (11.3—12.3) |
16.2 (15.1—17.3) |
| 2018 |
11.1 (10.8 – 11.3) |
12.9 (12.5—13.2) |
9.4 (9.1—9.7) |
5.5 (5.0—5.8) |
11.2 (10.7—11.6) |
12.1 (11.7—12.5) |
11.9 (11.4—12.4) |
15.7 (14.7—16.8) |
| 2019 |
11.6 (11.4 – 11.8) |
13.6 (13.3 – 14.0) |
9.7 (9.4—10.0) |
5.8 (5.4—6.2) |
10.9 (10.4—11.4) |
12.6 (12.2—13.0) |
13.2 (12.7—13.8) |
17.1 (16.0—18.2) |
| 2020 |
11.0 (10.8 – 11.2) |
12.6 (12.3 – 13.0) |
9.4 (9.2—9.7) |
4.7 (4.3—5.0) |
10.6 (10.1—11.1) |
12.1 (11.7—12.5) |
12.2 (11.7—12.7) |
17.8 (16.7—18.9) |
| 2021 |
10.5 (10.3 – 10.8) |
12.2 (11.9—12.5) |
9.0 (8.7—9.3) |
4.4 (4.0—4.7) |
9.9 (9.4—10.3) |
11.6 (11.2—12.0) |
12.0 (11.5—12.5) |
17.2 (16.2—18.2) |
| 2022 |
11.1 (10.8 – 11.3) |
12.6 (12.3—12.9) |
9.6 (9.3—9.9) |
4.6 (4.2—4.9) |
10.2 (9.7—10.6) |
12.2 (11.8—12.7) |
12.7 (12.2—13.2) |
18.3 (17.3—19.4) |
Fig. 2.
Standardized overall and gender-specific incidence of MSI-associated procedures, Germany, 2005–2022. *Significant increase (p-value time trend Poisson-Regression model < 0.05)
Fig. 3.
Standardized age-specific incidence of MSI-associated procedures, Germany, 2005–2022. *Significant increase (p value time trend Poisson-Regression model < 0.05)
Among the different age groups children from 0 to 14 years had the lowest incidence rates with a total of 5.2 [5.1–5.3] ranging from 4.4 [4.0–4.7] in 2021 to 6.0 [5.5–6.3] in 2016. Among adolescents and young adults from 15 to 34 years the total incidence rate 10.2 [10.1–10.4] differing between 9.1 [8.6–9.5] in 2007 to 11.2 [10.7–11.7] in 2012. In middle aged adults from 35 to 59 years the overall incidence was 10.3 [10.2–10.4] spreading from 7.5 [7.2–7.9] in 2005 to 12.6 [12.2–13.0] in 2019. Older adults from 60 to 79 years showed an incidence rate of 10.2 (10.1–10.3) varying from 7.1 [6.7–7.5] in 2005 and 13.2 [12.7–13.8] in 2019. Super octogenarians (80 years and older) had the highest total incidence rate with 13.8 [13.6–14.1] ranging from 8.3 [7.3–9.2] in 2005 to 18.3 [17.3–19.4] in 2022 and the strongest increase of 120.5% during this period.
Looking at the 16 federal states individually the overall incidence of surgical procedures associated with severe MSI within the observational period ranged from 5.8 [5.6–6.0] in Schleswig–Holstein to 16.3 [15.8–16.9] in Saarland as shown in Table 3. A single year minimum was seen in Schleswig–Holstein in 2006 with 4.2 [3.4–4.9]. A single year maximum was registered in Saarland with 22.3 [19.4–25.2] in 2017.
Table 3.
Regional incidence of severe MSI in all 16 federal states of Germany 2005—2022. Incidence rates (95% confidence interval) per 100,000 person years standardized to the German population based on the Census 2011
| Germany | Baden-Wuerttemberg | Bavaria | Berlin | Brandenburg | Bremen | Hamburg | Hesse | Mecklenburg-Vorpommern | |
|---|---|---|---|---|---|---|---|---|---|
| All years |
9.8 (9.7 – 9.8) |
9.8 (9.6—9.9) |
6.9 (6.8—7.0) |
12.2 (11.9—12.5) |
8.8 (8.5—9.1) |
15.3 (14.6—16.0) |
15.1 (14.7—15.6) |
8.0 (7.9—8.2) |
14.3 (13.9—14.7) |
| 2005 |
7.6 (7.4 – 7.8) |
7.1 (6.6—7.6) |
5.9 (5.5—6.4) |
10.9 (9.8—12.1) |
7.5 (6.4—8.5) |
12.7 (10.0—15.5) |
9.9 (8.4—11.3) |
4.6 (4.1—5.2) |
8.3 (6.9—9.6) |
| 2006 |
8.2 (8.0 – 8.3) |
8.4 (7.9—9.0) |
6.4 (6.0—6.9) |
10.5 (9.4—11.6) |
7.4 (6.3—8.4) |
15.2 (12.2—18.1) |
11.2 (9.6—12.7) |
5.0 (4.4—5.6) |
10.6 (9.1—12.2) |
| 2007 |
8.1 (7.9 – 8.3) |
8.5 (7.9—9.0) |
5.9 (5.5—6.3) |
10.0 (8.9—11.0) |
7.6 (6.6—8.7) |
11.9 (9.3—14.5) |
10.0 (8.5—11.5) |
6.2 (5.5—6.8) |
9.2 (7.8—10.7) |
| 2008 |
8.4 (8.2 – 8.6) |
8.6 (8.1—9.2) |
5.6 (5.2—6.0) |
10.1 (9.0—11.1) |
6.9 (5.9—7.9) |
15.5 (12.5—18.5) |
12.4 (10.7—14.0) |
6.5 (5.9—7.2) |
10.5 (9.0—12.1) |
| 2009 |
8.9 (8.7 – 9.1) |
9.3 (8.7—9.8) |
5.8 (5.4—6.3) |
11.1 (10.0—12.2) |
6.9 (5.9—7.9) |
16.1 (13.1—19.2) |
15.0 (13.2—16.8) |
6.8 (6.1—7.4) |
12.2 (10.5—13.9) |
| 2010 |
8.8 (8.6 – 9.0) |
8.6 (8.0—9.1) |
5.8 (5.4—6.2) |
11.5 (10.4—12.6) |
8.1 (7.0—9.2) |
14.1 (11.3—17.0) |
12.9 (11.3—14.6) |
7.6 (6.9—8.3) |
13.1 (11.3—14.8) |
| 2011 |
9.2 (9.0 – 9.4) |
9.3 (8.7—9.8) |
6.4 (6.0—6.8) |
11.7 (10.5—12.8) |
7.8 (6.7—8.9) |
12.1 (9.4—14.8) |
14.8 (13.0—16.6) |
8.1 (7.4—8.9) |
12.8 (11.1—14.6) |
| 2012 |
9.7 (9.5 – 9.9) |
10.0 (9.4—10.6) |
6.6 (6.1—7.0) |
11.8 (10.6—12.9) |
8.3 (7.2—9.5) |
13.2 (10.4—16.0) |
13.3 (11.6—15.0) |
8.8 (8.1—9.6) |
14.8 (12.9—16.7) |
| 2013 |
9.8 (9.6 – 10.0) |
9.9 (9.3—10.5) |
6.8 (6.4—7.3) |
12.6 (11.5—13.8) |
9.7 (8.4—10.9) |
14.7 (11.8—17.6) |
16.0 (14.2—17.9) |
8.2 (7.5—9.0) |
17.0 (15.0—19.1) |
| 2014 |
10.2 (9.9 – 10.4) |
9.8 (9.2—10.4) |
6.8 (6.4—7.3) |
13.0 (11.8—14.2) |
8.2 (7.1—9.4) |
16.4 (13.3—19.5) |
16.1 (14.2—18.0) |
8.1 (7.4—8.8) |
17.4 (15.4—19.5) |
| 2015 |
10.2 (10.0 – 10.4) |
10.4 (9.8—11.0) |
7.5 (7.0—8.0) |
13.2 (12.0—14.4) |
9.2 (8.0—10.4) |
17.0 (13.9—20.1) |
16.5 (14.6—18.4) |
8.4 (7.7—9.1) |
14.4 (12.6—16.3) |
| 2016 |
10.5 (10.3 – 10.7) |
10.9 (10.3—11.5) |
7.5 (7.0—8.0) |
12.4 (11.2—13.5) |
8.4 (7.2—9.5) |
17.0 (13.9—20.1) |
19.6 (17.5—21.6) |
8.8 (8.1—9.6) |
15.5 (13.6—17.4) |
| 2017 |
10.7 (10.5 – 10.9) |
11.3 (10.7—11.9) |
7.3 (6.8—7.7) |
12.5 (11.3—13.6) |
10.6 (9.3—11.8) |
15.2 (12.2—18.1) |
17.2 (15.3—19.1) |
9.3 (8.5—10.0) |
14.7 (12.9—16.6) |
| 2018 |
11.1 (10.8 – 11.3) |
11.4 (10.8—12.0) |
7.6 (7.2—8.1) |
12.2 (11.1—13.4) |
11.0 (9.7—12.3) |
18.2 (15.0—21.4) |
20.1 (18.0—22.1) |
8.9 (8.2—9.7) |
17.2 (15.1—19.2) |
| 2019 |
11.6 (11.4 – 11.8) |
11.4 (10.7—12.0) |
8.9 (8.4—9.4) |
14.3 (13.1—15.5) |
10.8 (9.6—12.1) |
15.7 (12.7—18.7) |
17.9 (15.9—19.8) |
9.9 (9.1—10.6) |
16.9 (14.9—18.9) |
| 2020 |
11.0 (10.8 – 11.2) |
10.6 (10.0—11.2) |
7.7 (7.3—8.2) |
14.5 (13.3—15.7) |
9.9 (8.6—11.1) |
17.2 (14.1—20.3) |
14.8 (13.1—16.6) |
10.2 (9.4—11.0) |
19.4 (17.3—21.6) |
| 2021 |
10.5 (10.3 – 10.8) |
10.2 (9.6—10.8) |
7.4 (6.9—7.9) |
12.4 (11.2—13.5) |
9.9 (8.7—11.2) |
17.5 (14.4—20.7) |
16.8 (15.0—18.7) |
9.1 (8.4—9.9) |
16.0 (14.1—18.0) |
| 2022 |
11.1 (10.8 – 11.3) |
10.0 (9.5—10.6) |
7.9 (7.4—8.4) |
14.7 (13.5—16.0) |
10.2 (9.0—11.4) |
15.7 (12.7—18.6) |
18.0 (16.1—19.9) |
9.9 (9.2—10.7) |
17.4 (15.3—19.4) |
| Lower Saxony | North Rhine- Westphalia | Rhineland-Palatinate | Saarland | Saxony | Saxony-Anhalt | Schleswig-Holstein | Thuringia | |
|---|---|---|---|---|---|---|---|---|
| All years |
8.9 (8.7—9.0) |
10.8 (10.7—10.9) |
9.8 (9.5—10.0) |
16.3 (15.8—16.9) |
9.0 (8.8—9.3) |
15.0 (14.6—15.4) |
5.8 (5.6—6.0) |
11.1 (10.8—11.5) |
| 2005 |
7.6 (7.0—8.2) |
9.1 (8.7—9.6) |
8.1 (7.2—8.9) |
11.0 (9.0—13.0) |
7.0 (6.2—7.8) |
8.9 (7.7—10.1) |
4.2 (3.4—4.9) |
5.3 (4.4—6.3) |
| 2006 |
7.0 (6.4—7.6) |
9.6 (9.2—10.1) |
8.0 (7.1—8.8) |
14.4 (12.1—16.7) |
6.4 (5.6—7.2) |
10.2 (8.9—11.4) |
5.4 (4.6—6.3) |
6.4 (5.4—7.4) |
| 2007 |
6.8 (6.2—7.4) |
9.4 (8.9—9.8) |
8.8 (7.9—9.7) |
13.1 (10.9—15.3) |
6.0 (5.3—6.8) |
10.9 (9.6—12.2) |
4.8 (4.0—5.6) |
9.0 (7.8—10.3) |
| 2008 |
7.4 (6.8—8.0) |
9.6 (9.1—10.0) |
8.6 (7.7—9.5) |
14.4 (12.0—16.7) |
7.0 (6.2—7.8) |
12.9 (11.4—14.3) |
5.3 (4.4—6.1) |
7.9 (6.7—9.0) |
| 2009 |
8.2 (7.5—8.8) |
10.1 (9.7—10.6) |
9.5 (8.6—10.5) |
14.1 (11.8—16.4) |
5.9 (5.2—6.7) |
14.1 (12.6—15.6) |
5.1 (4.3—5.9) |
8.7 (7.5—9.9) |
| 2010 |
8.6 (8.0—9.3) |
9.5 (9.0—9.9) |
8.5 (7.6—9.4) |
13.7 (11.4—15.9) |
7.6 (6.7—8.4) |
14.6 (13.0—16.1) |
5.0 (4.2—5.8) |
10.2 (8.8—11.5) |
| 2011 |
8.8 (8.2—9.5) |
10.1 (9.6—10.5) |
8.2 (7.3—9.1) |
12.0 (9.9—14.2) |
8.5 (7.6—9.4) |
15.5 (13.9—17.1) |
4.4 (3.6—5.2) |
10.6 (9.3—12.0) |
| 2012 |
8.4 (7.8—9.0) |
10.8 (10.3—11.3) |
9.1 (8.2—10.1) |
14.0 (11.7—16.3) |
8.5 (7.6—9.4) |
17.4 (15.6—19.1) |
5.1 (4.2—5.9) |
12.1 (10.6—13.6) |
| 2013 |
8.5 (7.9—9.2) |
10.6 (10.1—11.1) |
10.7 (9.7—11.8) |
15.0 (12.6—17.4) |
8.9 (8.0—9.8) |
13.1 (11.6—14.6) |
5.3 (4.5—6.2) |
12.2 (10.7—13.6) |
| 2014 |
9.8 (9.1—10.5) |
11.4 (10.9—11.9) |
8.9 (8.0—9.9) |
16.3 (13.8—18.8) |
9.8 (8.8—10.8) |
16.8 (15.1—18.5) |
5.7 (4.8—6.6) |
12.4 (10.9—13.9) |
| 2015 |
8.7 (8.0—9.3) |
10.8 (10.3—11.3) |
9.7 (8.8—10.7) |
19.0 (16.3—21.7) |
10.5 (9.5—11.5) |
16.2 (14.6—17.9) |
6.7 (5.7—7.6) |
13.2 (11.6—14.7) |
| 2016 |
9.1 (8.5—9.8) |
11.3 (10.8—11.8) |
9.7 (8.8—10.7) |
20.7 (17.8—23.5) |
10.5 (9.5—11.5) |
16.7 (15.0—18.4) |
7.1 (6.1—8.1) |
11.9 (10.4—13.3) |
| 2017 |
9.9 (9.2—10.6) |
11.4 (10.9—11.9) |
9.9 (8.9—10.8) |
22.3 (19.4—25.2) |
11.3 (10.3—12.4) |
17.0 (15.3—18.7) |
7.7 (6.7—8.7) |
11.3 (9.9—12.8) |
| 2018 |
9.2 (8.5—9.8) |
12.1 (11.6—12.6) |
11.9 (10.8—12.9) |
18.9 (16.2—21.6) |
10.5 (9.6—11.5) |
17.7 (16.0—19.5) |
6.5 (5.5—7.4) |
16.2 (14.5—17.9) |
| 2019 |
10.9 (10.2—11.6) |
12.6 (12.1—13.1) |
10.6 (9.6—11.6) |
20.9 (18.1—23.8) |
12.1 (11.0—13.1) |
18.1 (16.4—19.9) |
7.0 (6.1—8.0) |
13.2 (11.6—14.7) |
| 2020 |
9.9 (9.2—10.6) |
11.9 (11.4—12.4) |
11.2 (10.2—12.3) |
19.3 (16.5—22.0) |
10.9 (9.9—11.9) |
15.5 (13.9—17.2) |
6.4 (5.5—7.3) |
14.5 (12.9—16.1) |
| 2021 |
10.7 (10.0—11.5) |
11.3 (10.8—11.7) |
11.6 (10.6—12.7) |
17.5 (14.8—20.1) |
10.6 (9.6—11.6) |
16.8 (15.1—18.5) |
5.8 (5.0—6.7) |
11.9 (10.4—13.4) |
| 2022 |
9.9 (9.2—10.5) |
12.2 (11.7—12.7) |
12.5 (11.4—13.5) |
17.7 (15.1—20.3) |
10.6 (9.6—11.6) |
17.5 (15.8—19.3) |
6.1 (5.2—7.0) |
13.5 (11.9—15.0) |
The results of the time trend of incidence from the fully adjusted Poisson models are shown in Table 4, Table 5 and Fig. 4. We observed a marked increase in the incidence of MSI-associated procedures with a significant annual percentage increase of 2.8% in the observational period (relative risk per calendar year 1.028; 95% CI: 1.027–1.030, p-value < 0.001). The increase was slightly weaker in males (2.6% per year, RR: 1.026; 1.024–1.028; p-value < 0.001) than in females (3.2% per year, RR:1.032; 1.029–1.034; p < 0.001), although the baseline incidence was higher in males. Significant increases were observed in age groups 15–34 years (1.6% per year, RR: 1.016; 1.012 – 1.019; p < 0.001), 35–59 years (2.9% per year, RR: 1.029; 1.027 – 1.032; p < 0.001), 60–79 years (3.4% per year, RR: 1.039; 1.035 – 1.042; p < 0.001) and over 80 years (4.5% per year, RR: 1.045; 1.040 – 1.049; p < 0.001). In contrast no significant change was seen in children from 0 to 14 years (− 0.2% per year, RR: 0.998; 0.992 – 1.005; p = 0.63). A significant increase of MSI-associated procedures was found in all 16 federal states ranging from 1.7% per year in Bremen (RR: 1.017; 1.012–1.022; p < 0.001) to 4.0% per year in Saxony (RR: 1.040; 1.033–1.047; p < 0.001) and Thuringia (RR: 1.040; 1.034–1.046; p < 0.001).
Table 4.
Results of the Poisson models for total population and stratified by gender and age group (Germany, 2005–2022)
| Total population | Gender | Age group | ||||||
|---|---|---|---|---|---|---|---|---|
| Male | Female | 0–14 | 15–34 | 35–59 | 60–79 | 80 + | ||
| Risk factor | ||||||||
| Calendar year |
1.028 (1.027—1.030)* |
1.026 (1.024—1.028)* |
1.032 (1.029—1.034)* |
0.998 (0.992—1.005) |
1.016 (1.012—1.019)* |
1.029 (1.027—1.032)* |
1.039 (1.035—1.042)* |
1.045 (1.040—1.049)* |
| Gender a |
1.435 (1.413—1.458)* |
- | - |
1.226 (1.147—1.31)* |
1.688 (1.631—1.748)* |
1.684 (1.643—1.727)* |
1.256 (1.213—1.301)* |
0.883 (0.846—0.922)* |
| Age group | ||||||||
| 0–14 |
0.503 (0.485—0.522)* |
0.441 (0.42—0.464)* |
0.608 (0.574—0.643)* |
- | - | - | - | - |
| 15–34 | 1.000a | 1.000a | 1.000a | - | - | - | - | - |
| 35–59 |
0.957 (0.938—0.977)* |
0.956 (0.932—0.982)* |
0.959 (0.927—0.992)* |
- | - | - | - | - |
| 60–79 |
0.919 (0.898—0.942)* |
0.815 (0.79—0.841)* |
1.096 (1.055—1.138)* |
- | - | - | - | - |
| 80 + |
1.194 (1.162—1.227)* |
0.891 (0.858—0.926)* |
1.704 (1.637—1.774)* |
- | - | - | - | - |
| Federal state | ||||||||
| Baden-Württemberg | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a |
| Bavaria |
0.709 (0.674—0.746)* |
0.706 (0.661—0.755)* |
0.714 (0.66—0.772)* |
0.645 (0.522—0.798)* |
0.724 (0.642—0.818)* |
0.71 (0.655—0.77)* |
0.706 (0.635—0.785)* |
0.721 (0.633—0.821)* |
| Berlin |
1.232 (1.179—1.287)* |
1.254 (1.184—1.328)* |
1.2 (1.121—1.285)* |
1.217 (1.017—1.456)* |
1.458 (1.317—1.615)* |
1.349 (1.26—1.446)* |
1.066 (0.969—1.172) |
0.922 (0.817—1.042) |
| Brandenburg |
0.868 (0.827—0.911)* |
0.892 (0.838—0.949)* |
0.835 (0.775—0.9)* |
0.866 (0.713—1.053) |
1.279 (1.152—1.42)* |
0.864 (0.8—0.933)* |
0.65 (0.583—0.725)* |
0.738 (0.648—0.839)* |
| Bremen |
1.582 (1.518—1.650)* |
1.556 (1.473—1.644)* |
1.619 (1.519—1.726)* |
1.217 (1.017—1.456)* |
1.724 (1.562—1.903)* |
1.741 (1.631—1.859)* |
1.34 (1.224—1.466)* |
1.521 (1.365—1.696)* |
| Hamburg |
1.526 (1.463—1.591)* |
1.506 (1.426—1.592)* |
1.552 (1.455—1.656)* |
1.516 (1.277—1.8)* |
1.651 (1.494—1.823)* |
1.545 (1.445—1.653)* |
1.473 (1.349—1.61)* |
1.414 (1.267—1.579)* |
| Hesse |
0.824 (0.785—0.865)* |
0.825 (0.775—0.88)* |
0.823 (0.763—0.887)* |
0.622 (0.502—0.771)* |
0.933 (0.833—1.044) |
0.872 (0.808—0.942)* |
0.774 (0.698—0.859)* |
0.732 (0.643—0.833)* |
| Mecklenburg-Vorpommern |
1.439 (1.379—1.501)* |
1.556 (1.473—1.644)* |
1.276 (1.193—1.365)* |
1.028 (0.852—1.239) |
2.038 (1.852—2.243)* |
1.545 (1.445—1.653)* |
1.15 (1.048—1.263)* |
1.072 (0.954—1.205) |
|
Lower Saxony |
0.904 (0.862—0.947)* |
0.896 (0.842—0.954)* |
0.914 (0.85—0.983)* |
0.954 (0.789—1.154) |
1.103 (0.989—1.229) |
0.918 (0.851—0.99)* |
0.791 (0.714—0.877)* |
0.789 (0.695—0.896)* |
| North Rhine-Westphalia |
1.103 (1.054—1.153)* |
1.071 (1.009—1.136)* |
1.147 (1.071—1.229)* |
0.788 (0.645—0.963)* |
1.298 (1.169—1.441)* |
1.162 (1.082—1.248)* |
1.002 (0.91—1.104) |
1.002 (0.889—1.129) |
| Rhineland-Palatinate |
1.002 (0.957—1.049) |
1.001 (0.942—1.063) |
1.004 (0.935—1.078) |
0.783 (0.641—0.958)* |
1.192 (1.072—1.326)* |
1.051 (0.977—1.131) |
0.898 (0.813—0.992)* |
0.902 (0.798—1.019) |
| Saarland |
1.637 (1.571—1.706)* |
1.69 (1.601—1.783)* |
1.565 (1.467—1.669)* |
1.903 (1.615—2.243)* |
2.167 (1.971—2.382)* |
1.722 (1.612—1.838)* |
1.34 (1.224—1.466)* |
1.153 (1.028 – 1.294)* |
| Saxony |
0.917 (0.874—0.961)* |
0.945 (0.889—1.005) |
0.877 (0.815—0.944)* |
0.793 (0.649—0.968)* |
1.147 (1.031—1.277)* |
0.969 (0.899—1.044) |
0.772 (0.696—0.856)* |
0.786 (0.692—0.892)* |
| Saxony-Anhalt |
1.470 (1.410—1.534)* |
1.529 (1.447—1.616)* |
1.389 (1.3—1.484)* |
1.175 (0.981—1.408) |
2.263 (2.059—2.486)* |
1.591 (1.488—1.701)* |
1.039 (0.944—1.143) |
1.018 (0.905 – 1.147) |
| Schleswig–Holstein |
0.576 (0.546—0.608)* |
0.595 (0.554—0.638)* |
0.55 (0.505—0.598)* |
0.585 (0.47—0.729)* |
0.769 (0.683—0.866)* |
0.599 (0.55—0.653)* |
0.483 (0.429—0.544)* |
0.429 (0.368—0.500)* |
| Thuringia |
1.136 (1.086—1.188)* |
1.184 (1.117—1.255)* |
1.069 (0.997—1.147) |
0.949 (0.785—1.149) |
1.423 (1.285—1.576)* |
1.173 (1.093—1.26)* |
0.951 (0.863—1.049) |
1.063 (0.945—1.195) |
Relative risk for severe MSI (95% Confidence interval). * p-value < 0.05;
a Baseline: gender: female, age:15–34 years, federal state: Baden-Württemberg
Table 5.
Results of the Poisson models stratified by federal state (Germany, 2005–2022). Relative risk for severe MSI (95% Confidence interval)
| Federal state | ||||||||
| Baden-Württemberg | Bavaria | Berlin | Brandenburg | Bremen | Hamburg | Hesse | Mecklenburg-Vorpommern | |
| Risk factor | ||||||||
| Calendar year |
1.023 (1.016—1.029)* |
1.026 (1.018—1.033)* |
1.021 (1.015—1.026)* |
1.026 (1.019—1.033)* |
1.017 (1.012—1.022)* |
1.033 (1.027—1.038)* |
1.038 (1.030—1.045)* |
1.035 (1.030—1.041)* |
| Gender a |
1.382 (1.294—1.477)* |
1.367 (1.264—1.479)* |
1.444 (1.360—1.533)* |
1.476 (1.374—1.585)* |
1.329 (1.261—1.400)* |
1.341 (1.272—1.415)* |
1.387 (1.290—1.492)* |
1.685 (1.593—1.783)* |
| Age group | ||||||||
| 0–14 |
0.696 (0.596—0.812)* |
0.619 (0.512—0.749)* |
0.58 (0.506—0.665)* |
0.471 (0.402—0.552)* |
0.491 (0.429—0.561)* |
0.639 (0.564—0.723)* |
0.464 (0.385—0.559)* |
0.351 (0.304—0.404)* |
| 15–34 | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a |
| 35–59 |
1.128 (1.027—1.240)* |
1.106 (0.990—1.236) |
1.044 (0.965—1.130) |
0.762 (0.697—0.833)* |
1.139 (1.061—1.224)* |
1.056 (0.981—1.138) |
1.055 (0.956—1.164) |
0.855 (0.798—0.917)* |
| 60–79 |
1.321 (1.190—1.465)* |
1.288 (1.139—1.456)* |
0.965 (0.879—1.059) |
0.672 (0.602—0.749)* |
1.026 (0.943—1.116) |
1.179 (1.085—1.281)* |
1.096 (0.980—1.227) |
0.745 (0.685—0.811)* |
| 80 + |
1.734 (1.545—1.946)* |
1.726 (1.507—1.976)* |
1.097 (0.983—1.223) |
1.000 (0.887—1.128) |
1.530 (1.397—1.675)* |
1.485 (1.353—1.631)* |
1.361 (1.198—1.546)* |
0.912 (0.827—1.006) |
| Federal state | ||||||||
| Lower Saxony | North Rhine-Westphalia | Rhineland-Palatinate | Saarland | Saxony | Saxony-Anhalt | Schleswig–Holstein | Thuringia | |
| Risk factor | ||||||||
| Calendar year |
1.026 (1.020—1.033)* |
1.019 (1.013—1.026)* |
1.028 (1.021—1.034)* |
1.031 (1.026—1.036)* |
1.04 (1.033—1.047)* |
1.029 (1.024—1.035)* |
1.024 (1.016—1.033)* |
1.040 (1.034—1.046)* |
| Gender a |
1.355 (1.264—1.452)* |
1.290 (1.212—1.374)* |
1.378 (1.290—1.472)* |
1.492 (1.417—1.572)* |
1.489 (1.389—1.596)* |
1.522 (1.441—1.608)* |
1.495 (1.37—1.632)* |
1.531 (1.438—1.630)* |
| Age group | ||||||||
| 0–14 |
0.602 (0.515—0.703)* |
0.422 (0.358—0.498)* |
0.457 (0.387—0.540)* |
0.611 (0.547—0.682)* |
0.48 (0.407—0.567)* |
0.361 (0.316—0.413)* |
0.529 (0.435—0.643)* |
0.464 (0.399—0.54)* |
| 15–34 | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a | 1.000a |
| 35–59 |
0.939 (0.856—1.030) |
1.010 (0.928—1.099) |
0.995 (0.911—1.086) |
0.896 (0.839—0.958)* |
0.953 (0.87—1.043) |
0.793 (0.742—0.848)* |
0.879 (0.786—0.983)* |
0.930 (0.857—1.009) |
| 60–79 |
0.948 (0.851—1.055) |
1.020 (0.926—1.124) |
0.995 (0.898—1.101) |
0.817 (0.754—0.884)* |
0.888 (0.798—0.988)* |
0.606 (0.557—0.66)* |
0.829 (0.726—0.947)* |
0.883 (0.802—0.972)* |
| 80 + |
1.241 (1.100—1.401)* |
1.338 (1.200—1.492)* |
1.312 (1.170—1.470)* |
0.923 (0.840—1.015) |
1.187 (1.053—1.339)* |
0.780 (0.707—0.861)* |
0.967 (0.826—1.131) |
1.295 (1.166—1.438)* |
* p-value < 0.05; a Baseline: gender: female, age:15–34 years
Fig. 4.
a Increase of the incidence of MSI-associated procedures. Annual percentage increase as result from the fully adjusted Poisson models stratified by federal state. Germany, 2005–2022. b Baseline incidence of MSI-associated procedures standardized for age and gender, Germany, 2005. c Latest Incidence of MSI-associated procedures standardized for age and gender, Germany, 2022. *Significant increase (p-value time trend Poisson-Regression model < 0.05); SH: Schleswig Holstein; MV: Mecklenburg-Vorpommern; HH: Hamburg; HB: Bremen; NI: Lower saxony; BE: Berlin; BB: Brandenburg; ST: Saxony-Anhalt; NW: North Rhine-Westphalia; HE: Hesse; TH: Thuringia; SX: Saxony; RP: Rhineland-Palatinate; SL: Saarland; BW: Baden-Wurttemberg; BY: Bavaria
Discussion
Despite good access to dental care, availability of antibiotic therapy and good socioeconomic conditions, severe MSI is a persistent challenge in general and oral healthcare. Its main cause is end stage dentoalveolar disease leading from caries, periodontal disease to cellulitis and abscess formation. It is still an important cause of hospitalization in oral and maxillofacial surgery departments [13]. However, reliable population-based data about long-term trends, age and gender distributions in the incidence of severe MSI are limited and may be inconclusive due to its different causes and clinical presentations. Most available data were collected from single center case series and therefore may not be representative. To our knowledge, this is the first population-based study to investigate the incidence of severe MSI using Germany’s DRG inpatient billing data base, which includes data on the entire population of Germany.
During the observational period from 2005–2022 we were able to detect a significant increase in the incidence of severe MSI requiring external incision and drainage in Germany. The phenomenon of rising incidence of severe MSI affects the entire society and is not limited to distinct regions, genders or age groups. These results were in accordance with other data describing an increase in maxillofacial infections. Robertson et al. report an increasing number of hospital admissions due to odontogenic infections in the hospitals of National Health System in the United Kingdom rising from 1.71 per 100,000 person years in the year 2000 to 5.36 per 100,000 person years in 2020 [15]. Similar data for the UK were published by Thomas et al. in 2008 [16]. Allareddy et al. analyzed 29,228 hospitalizations due to oral infections between 2004 and 2010 in the USA with an increasing number over time [17]. Seppänen et al. describe an increase of maxillofacial space infections requiring hospital care in the Helsinki and Uusimaa Hospital District in Finland representing more than 25% of the population in Finland with an increase from 5.3 per 100,000 inhabitants in 1995 to 7.2 per 100,000 inhabitants in 2005 [18]. Yang et al. saw a slight increase in head and neck space infections in Taiwan from 2.47 per 100,000 person years in 2007 to 3.71 per 100,000 person years 2016 [19].
Odontogenic infections are the main cause of MSI and can usually be found in more than 80% of all cases [20–22]. The caries experience among younger adults (35–44 years) in Germany has declined from 16.1% in 1997 and 14.6% in 2005 to 11.2% in the last national oral health study in 2014 [23–25]. Also caries experience in younger seniors (65–74 years) has declined from 23.6% in 1997 and 22.1% in 2005 to 17.7% in 2014 [23–25]. At first sight the improvement in societal oral health is contractionary to the increase in severe MSI. The increase might be more associated to individual social subgroups. Caries prevalence, number of missing teeth and edentulism as measures of oral health are significantly associated with lower income and lower education in Germany [26]. The association of these social factors with oral health and reduced utilization patterns increased over the last decades [27]. This may lead to a social disparity in oral health and, as a result, to an increase in severe infections in most disadvantaged groups. This is in alignment with data from the UK by Moles et al. reporting an increasing incidence of dental abscesses which is mostly driven by poorer people and strongly associated with the relative deprivation of the area of residence [28].
The phenomenon of rising incidence of severe MSI s not limited to individual genders or age groups. Nevertheless, some epidemiological factors are more predisposing than others. Male gender is an important predisposing factor as there is a consistent male preponderance in every study year which is in accordance with the literature showing that odontogenic infection are more prevalent in males [21, 29–31]. We also found incidence differences between age groups that were observed consistently over the 18-year observational period. Elderly people over 80 years of age have the highest incidence rates of severe MSI and they also share the strongest increase over time followed by older adults between 60 und 79 years. Seemingly contradictory at first glance, dental diseases including caries, tooth loss and edentulism decline in the German society as well as globally [32, 33]. This means a higher number of teeth is preserved in elderly people. There they are “teeth at risk” for dental disease and may act as a source of infection, especially when accompanied by systemic diseases associated with age such as dementia, tremor, diabetes, which have a negative impact on personal oral hygiene and oral health [34]. Together with a lower level of medical utilization due to limited mobility, this may result in a situation that is predisposing to advanced maxillofacial infections. This could be possibly a contributing factor for the increase in the number of MSI in these age groups. In patients with systemic diseases, the spread of the odontogenic infection requiring inpatient treatment and the occurrence of complications during the course of the disease are more common than in patients without systemic diseases [12, 18, 35, 36]. As systemic risk factors and comorbidities like diabetes, obesity, cardiovascular disease and mental disorders are on the rise, the risk for severe MSI may also increase over time especially in the age groups most affected by these conditions [37–40]. Further studies are needed to identify potential risk factors and risk groups for severe odontogenic infections [41].
MSI are usually caused by a polymicrobial variety of aerobic and anaerobic bacteria [20, 21, 42, 43]. A shift in the microbiological composition within odontogenic infections have been determined in preceding studies [42, 44]. Streptococcus species are the most frequently identified bacteria in MSI followed by Prevotella species and Staphylococcus species [45–47]. Antibiotic resistance is a common phenomenon in odontogenic infections with prevalence of more than 40% to at least one antibiotic agent [45, 48]. Accordingly, increased attention must be paid to the initial empiric antibiotic therapy. Penicillin-group antibiotics continue to be highly effective against Streptococci, Prevotella and Staphylococci while Clindamycin could not be shown to be effective as an empirical drug of choice for a high number of odontogenic infections [20, 29, 49]. In a recent study on antimicrobial resistances in oral- and maxillofacial infections in more than 20,000 clinical isolates from dental and oral-maxillofacial clinical settings in Germany Meinen et al. found high clindamycin and macrolide resistance proportions (> 17%) in Streptococcus spp. and Staphylococcus aureus isolates [48]. Moreover increasing resistance against clindamycin is an emerging problem in different bacteria and along different clinical settings [50–55]. The German S3-guideline on odontogenic infections recommends clindamycin only as a second-line antibiotic in the presence of an allergy to penicillin group antibiotics [56]. Nevertheless clindamycin is with more than 23.4% of all antibiotic prescriptions still the second most prescribed antibiotic among dentists in Germany [57]. In contrast to Germany clindamycin is rarely dentally prescribed in other industrialized countries like Great Britain, Norway or Canada [58–60]. Increased resistance rates for clindamycin require clarification among dentists in order to prescribe antibiotics according to national and international guidelines and the current scientific knowledge.
Increasing number of MSI requiring inpatient treatment with external incision leads to an increasing burden for the health system. There is only scarce data on costs caused by odontogenic infections in Germany [61]. Most Studies on this topic were conducted in the USA and Great Britain [62–64]. Due to the differences in the health systems, it is only insufficiently possible to transfer the results to Germany. Nevertheless, with an increasing incidence of inpatient treatments of MSI a relevant increase in financial expenditure for these conditions seems likely. Since reimbursement by statutory health insurance cannot fully cover the costs of treating these patients, this type of disease represents an economic burden not only for the cost bearer but also for the treating department [61].
This study is subject to certain strengths and limitations, which are mainly related to the dataset that was available for analysis. First, the specific reimbursed OPS codes from the national DRG system database only represent MSI treated by external incision and drainage in the analyzed years. MSI treated non-surgically are not included in the dataset. Second, the study only includes MSI cases requiring a hospital admission that led to the billing of a DRG. Patients treated as outpatients or who use other reimbursement schemes could not be included.
Since statutory health insurance in Germany provides a fully accessible and affordable healthcare system for every citizen and MSI is a serious and progressive disease that requires immediate medical attention and hospitalization, we assume that we can cover the vast majority of the German population and provide a comprehensive overview. Selection bias in MSI determination due to socioeconomic status is limited by the population-based approach. The completeness of our description is only limited by the dataset itself, which provides information at only an aggregated level and in limited detail without information about a specific cause or severity of the infection; therefore, a more advanced analysis including anamnestic and diagnostic information was not possible. This would, however, be interesting to evaluate the reasons for the increasing rate of severe MSI further. Nevertheless, the DRG inpatient billing data base provides an excellent tool for German researchers to perform large-scale clinical epidemiology investigations on procedures and diseases. The use of claims data also avoided recall bias and misclassification bias that may result from studies based on self-reported data.
To the best of our knowledge, as initially aimed, this study is the first to examine the incidence, time trends and epidemiological distribution of severe MSI at a national level in Germany after more than twenty years. It can contribute to an analysis on the influence of population structure and oral health care on the occurrence of severe MSI. The description of negative effects can contribute to the future addressing of risk groups who may take profit from early oral health care motivation or intervention. For this purpose, the investigation of the direct influence of social background should be expanded.
Conclusion
The study suggests an increasing incidence rate of severe MSI in Germany over the last decades. This is not limited to certain regions, genders or age groups. Elderly patients over 80 years of age represent the social group that poses the greatest challenge. They present the highest increase in incidence over time and are beyond this the fastest growing age group in an aging society. Thus, severe MSI is an increasing challenge even in countries with comprehensive health care like Germany. As severe MSI is a promising target for prevention there have to be more focus on early detection and management of odontogenic infections.
Acknowledgements
We thank the Federal Statistical Office of Germany (Destatis) for their support of this work.
Author contributions
Conceptualization and methodology: A.M., A.N., F.H.; formal and statistical analysis: A.M. and S.P.; writing-original draft preparation A.M. and S.P.; writing—review and editing, A.M., S.P., F.D., A.N., F.H.; visualization: A.M. All authors have read and agreed to the published version of the manuscript.
Funding
Open Access funding enabled and organized by Projekt DEAL. This study received no external funding.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Institutional review board statement
Ethical approval was granted by the ethics committee of the faculty of medicine university Marburg (24–5 RS; January 03rd, 2024). The study was conducted in accordance with the Declaration of Helsinki. No administrative permission was required to access the analyzed dataset. The data was anonymized before its use.
Consent to participate
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Marra S, Hotaling AJ. Deep neck infections. Am J Otolaryngol. 1996;17:287–298. doi: 10.1016/s0196-0709(96)90013-7. [DOI] [PubMed] [Google Scholar]
- 2.Gallo O, Mannelli G, Lazio MS, Santoro R. How to avoid life-threatening complications following head and neck space infections: an algorithm-based approach to apply during times of emergency. When and why to hospitalise a neck infection patient. J Laryngol Otol. 2018;132:53–59. doi: 10.1017/S0022215117002201. [DOI] [PubMed] [Google Scholar]
- 3.Ma C, Zhou L, Zhao JZ, Lin RT, Zhang T, Yu LJ, Shi TY, Wang M. Multidisciplinary treatment of deep neck infection associated with descending necrotizing mediastinitis: a single-centre experience. J Int Med Res. 2019;47:6027–6040. doi: 10.1177/0300060519879308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Opitz D, Camerer C, Camerer DM, Raguse JD, Menneking H, Hoffmeister B, Adolphs N. Incidence and management of severe odontogenic infections-a retrospective analysis from 2004 to 2011. J Craniomaxillofac Surg. 2015;43:285–289. doi: 10.1016/j.jcms.2014.12.002. [DOI] [PubMed] [Google Scholar]
- 5.Vieira F, Allen SM, Stocks RM, Thompson JW. Deep neck infection. Otolaryngol Clin North Am. 2008;41(459–83):vii. doi: 10.1016/j.otc.2008.01.002. [DOI] [PubMed] [Google Scholar]
- 6.Jung J, Oh Y, Cha S, Ohe J. An analysis of contributing factors of head and neck space infections of odontogenic origin: a long-term retrospective clinical study (including COVID-19 pandemic period) Med Oral Patol Oral Cir Bucal. 2023 doi: 10.4317/medoral.26018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Brito TP, Hazboun IM, Fernandes FL, Bento LR, Zappelini CEM, Chone CT, Crespo AN. Deep neck abscesses: study of 101 cases. Braz J Otorhinolaryngol. 2017;83:341–348. doi: 10.1016/j.bjorl.2016.04.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gates GA. Deep neck infection. Am J Otolaryngol. 1983;4:420–421. doi: 10.1016/s0196-0709(83)80052-0. [DOI] [PubMed] [Google Scholar]
- 9.Kauffmann P, Cordesmeyer R, Troltzsch M, Sommer C, Laskawi R. Deep neck infections: a single-center analysis of 63 cases. Med Oral Patol Oral Cir Bucal. 2017;22:e536–e541. doi: 10.4317/medoral.21799. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Uluibau IC, Jaunay T, Goss AN. Severe odontogenic infections. Aust Dent J. 2005;50:S74–81. doi: 10.1111/j.1834-7819.2005.tb00390.x. [DOI] [PubMed] [Google Scholar]
- 11.Huang TT, Tseng FY, Yeh TH, Hsu CJ, Chen YS. Factors affecting the bacteriology of deep neck infection: a retrospective study of 128 patients. Acta Otolaryngol. 2006;126:396–401. doi: 10.1080/00016480500395195. [DOI] [PubMed] [Google Scholar]
- 12.Rasteniene R, Aleksejuniene J, Puriene A. Determinants of length of hospitalization due to acute odontogenic maxillofacial infections: a 2009–2013 retrospective analysis. Med Princ Pract. 2015;24:129–135. doi: 10.1159/000370073. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Reynolds SC, Chow AW. Life-threatening infections of the peripharyngeal and deep fascial spaces of the head and neck. Infect Dis Clin North Am. 2007;21:557–576. doi: 10.1016/j.idc.2007.03.002. [DOI] [PubMed] [Google Scholar]
- 14.Palladino R, Pennino F, Finbarr M, Millett C, Triassi M. Multimorbidity and health outcomes in older adults in ten European health systems, 2006–15. Health Aff (Millwood) 2019;38:613–623. doi: 10.1377/hlthaff.2018.05273. [DOI] [PubMed] [Google Scholar]
- 15.Robertson DD, Smith AJ. Significant increase in hospital admissions for the management of severe dental infection in England 2000–2020. J Infect. 2021;83:496–522. doi: 10.1016/j.jinf.2021.07.009. [DOI] [PubMed] [Google Scholar]
- 16.Thomas SJ, Atkinson C, Hughes C, Revington P, Ness AR. Is there an epidemic of admissions for surgical treatment of dental abscesses in the UK? BMJ. 2008;336:1219–1220. doi: 10.1136/bmj.39549.605602.BE. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Allareddy V, Rampa S, Nalliah RP, Allareddy V. Longitudinal discharge trends and outcomes after hospitalization for mouth cellulitis and Ludwig angina. Oral Surg Oral Med Oral Pathol Oral Radiol. 2014;118:524–531. doi: 10.1016/j.oooo.2014.06.003. [DOI] [PubMed] [Google Scholar]
- 18.Seppanen L, Rautemaa R, Lindqvist C, Lauhio A. Changing clinical features of odontogenic maxillofacial infections. Clin Oral Investig. 2010;14:459–465. doi: 10.1007/s00784-009-0281-5. [DOI] [PubMed] [Google Scholar]
- 19.Yang TH, Xirasagar S, Cheng YF, Wu CS, Kao YW and Lin HC (2021) A nationwide population-based study on the incidence of parapharyngeal and retropharyngeal abscess-a 10-year study. Int J Environ Res Public Health 18. 10.3390/ijerph18031049 [DOI] [PMC free article] [PubMed]
- 20.Al-Nawas B, Maeurer M. Severe versus local odontogenic bacterial infections: comparison of microbial isolates. Eur Surg Res. 2008;40:220–224. doi: 10.1159/000110864. [DOI] [PubMed] [Google Scholar]
- 21.Sanchez R, Mirada E, Arias J, Pano JR, Burgueno M. Severe odontogenic infections: epidemiological, microbiological and therapeutic factors. Med Oral Patol Oral Cir Bucal. 2011;16:e670–e676. doi: 10.4317/medoral.16995. [DOI] [PubMed] [Google Scholar]
- 22.Sato FR, Hajala FA, Freire Filho FW, Moreira RW, de Moraes M. Eight-year retrospective study of odontogenic origin infections in a postgraduation program on oral and maxillofacial surgery. J Oral Maxillofac Surg. 2009;67:1092–1097. doi: 10.1016/j.joms.2008.09.008. [DOI] [PubMed] [Google Scholar]
- 23.Jordan RA, Bodechtel C, Hertrampf K, Hoffmann T, Kocher T, Nitschke I, Schiffner U, Stark H, Zimmer S, Micheelis W, Group DVSI The Fifth German Oral Health Study (Funfte Deutsche Mundgesundheitsstudie, DMS V) - rationale, design, and methods. BMC Oral Health. 2014;14:161. doi: 10.1186/1472-6831-14-161. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Holtfreter B, Berg MH, Kocher T, Schiffner U, Hoffmann T, Micheelis W. Change in FS-T index in adults in the German national oral health surveys between 1989 and 2005. Community Dent Oral Epidemiol. 2013;41:251–260. doi: 10.1111/j.1600-0528.2012.00739.x. [DOI] [PubMed] [Google Scholar]
- 25.Schiffner U, Hoffmann T, Kerschbaum T, Micheelis W. Oral health in German children, adolescents, adults and senior citizens in 2005. Community Dent Health. 2009;26:18–22. [PubMed] [Google Scholar]
- 26.Heilmann A, Sheiham A, Watt R, Jordan R. Common risk factor approach – Ein integrierter bevölkerungsbezogener und evidenzbasierter Ansatz zum Ausgleich sozialer Ungleichheiten in der Mundgesundheit. Das Gesundheitswesen. 2015;78:672–677. doi: 10.1055/s-0035-1548933. [DOI] [PubMed] [Google Scholar]
- 27.Geyer S, Micheelis W. Changes in problem-based and routine-based healthcare attendance: a comparison of three national dental health surveys. Community Dent Oral Epidemiol. 2012;40:459–467. doi: 10.1111/j.1600-0528.2012.00690.x. [DOI] [PubMed] [Google Scholar]
- 28.Moles DR. Epidemic of dental abscesses?: dental abscesses have increased most among poorer people. BMJ. 2008;336:1323. doi: 10.1136/bmj.39605.430243.3A. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Eckert AW, Just L, Wilhelms D, Schubert J. Odontogene Infektionen – Teil I. Wien Med Wochenschr. 2012;162:316–320. doi: 10.1007/s10354-012-0103-2. [DOI] [PubMed] [Google Scholar]
- 30.Walia IS, Borle RM, Mehendiratta D, Yadav AO. Microbiology and antibiotic sensitivity of head and neck space infections of odontogenic origin. J Maxillofac Oral Surg. 2014;13:16–21. doi: 10.1007/s12663-012-0455-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Chunduri NS, Madasu K, Goteki VR, Karpe T, Reddy H. Evaluation of bacterial spectrum of orofacial infections and their antibiotic susceptibility. Ann Maxillofac Surg. 2012;2:46–50. doi: 10.4103/2231-0746.95318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Jordan AR, Stark H, Nitschke I, Micheelis W, Schwendicke F. Epidemiological trends, predictive factors, and projection of tooth loss in Germany 1997–2030: part I. missing teeth in adults and seniors. Clin Oral Invest. 2020;25:67–76. doi: 10.1007/s00784-020-03266-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Kassebaum NJ, Bernabe E, Dahiya M, Bhandari B, Murray CJ, Marcenes W. Global burden of severe tooth loss: a systematic review and meta-analysis. J Dent Res. 2014;93:20S–28S. doi: 10.1177/0022034514537828. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Fries JF. Aging, natural death, and the compression of morbidity. N Engl J Med. 1980;303:130–135. doi: 10.1056/NEJM198007173030304. [DOI] [PubMed] [Google Scholar]
- 35.Seppanen L, Lauhio A, Lindqvist C, Suuronen R, Rautemaa R. Analysis of systemic and local odontogenic infection complications requiring hospital care. J Infect. 2008;57:116–122. doi: 10.1016/j.jinf.2008.06.002. [DOI] [PubMed] [Google Scholar]
- 36.Lee JK, Kim HD, Lim SC. Predisposing factors of complicated deep neck infection: an analysis of 158 cases. Yonsei Med J. 2007;48:55–62. doi: 10.3349/ymj.2007.48.1.55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Rowley WR, Bezold C, Arikan Y, Byrne E, Krohe S. Diabetes 2030: insights from yesterday, today, and future trends. Popul Health Manag. 2017;20:6–12. doi: 10.1089/pop.2015.0181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Kramer M. The rising pandemic of mental disorders and associated chronic diseases and disabilities. Acta Psychiatr Scand. 2007;62:382–397. doi: 10.1111/j.1600-0447.1980.tb07714.x. [DOI] [Google Scholar]
- 39.Collaborators GBDMD. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9:137–150. doi: 10.1016/S2215-0366(21)00395-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Amini M, Zayeri F and Salehi M (2021) Trend analysis of cardiovascular disease mortality, incidence, and mortality-to-incidence ratio: results from global burden of disease study 2017. BMC Public Health 21. 10.1186/s12889-021-10429-0 [DOI] [PMC free article] [PubMed]
- 41.Schmalz G, Brauer L, Haak R, Ziebolz D. Evaluation of a concept to classify anamnesis-related risk of complications and oral diseases in patients attending the clinical course in dental education. BMC Oral Health. 2023;23:609. doi: 10.1186/s12903-023-03343-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Robertson D, Smith AJ. The microbiology of the acute dental abscess. J Med Microbiol. 2009;58:155–162. doi: 10.1099/jmm.0.003517-0. [DOI] [PubMed] [Google Scholar]
- 43.Singh M, Kambalimath DH, Gupta KC. Management of odontogenic space infection with microbiology study. J Maxillofac Oral Surg. 2014;13:133–139. doi: 10.1007/s12663-012-0463-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Sobottka I, Wegscheider K, Balzer L, Boger RH, Hallier O, Giersdorf I, Streichert T, Haddad M, Platzer U, Cachovan G. Microbiological analysis of a prospective, randomized, double-blind trial comparing moxifloxacin and clindamycin in the treatment of odontogenic infiltrates and abscesses. Antimicrob Agents Chemother. 2012;56:2565–2569. doi: 10.1128/AAC.06428-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Heim N, Jurgensen B, Kramer FJ, Wiedemeyer V. Mapping the microbiological diversity of odontogenic abscess: are we using the right drugs? Clin Oral Investig. 2021;25:187–193. doi: 10.1007/s00784-020-03350-0. [DOI] [PubMed] [Google Scholar]
- 46.Kityamuwesi R, Muwaz L, Kasangaki A, Kajumbula H, Rwenyonyi CM. Characteristics of pyogenic odontogenic infection in patients attending Mulago Hospital, Uganda: a cross-sectional study. BMC Microbiol. 2015;15:46. doi: 10.1186/s12866-015-0382-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Fowell C, Igbokwe B, MacBean A. The clinical relevance of microbiology specimens in orofacial abscesses of dental origin. Ann R Coll Surg Engl. 2012;94:490–492. doi: 10.1308/003588412X13373405385539. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Meinen A, Reuss A, Willrich N, Feig M, Noll I, Eckmanns T, Al-Nawas B, Markwart R. Antimicrobial resistance and the spectrum of pathogens in dental and oral-maxillofacial infections in hospitals and dental practices in Germany. Front Microbiol. 2021;12:676108. doi: 10.3389/fmicb.2021.676108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Cachovan G, Boger RH, Giersdorf I, Hallier O, Streichert T, Haddad M, Platzer U, Schon G, Wegscheider K, Sobottka I. Comparative efficacy and safety of moxifloxacin and clindamycin in the treatment of odontogenic abscesses and inflammatory infiltrates: a phase II, double-blind, randomized trial. Antimicrob Agents Chemother. 2011;55:1142–1147. doi: 10.1128/AAC.01267-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Heim N, Faron A, Wiedemeyer V, Reich R, Martini M. Microbiology and antibiotic sensitivity of head and neck space infections of odontogenic origin. Differences in inpatient and outpatient management. J Craniomaxillofac Surg. 2017;45:1731–1735. doi: 10.1016/j.jcms.2017.07.013. [DOI] [PubMed] [Google Scholar]
- 51.Alexander AJ, Richardson SE, Sharma A, Campisi P. The increasing prevalence of clindamycin resistance in Staphylococcus aureus isolates in children with head and neck abscesses. Can J Infect Dis Med Microbiol. 2011;22:49–51. doi: 10.1155/2011/261519. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.White BP, Siegrist EA. Increasing clindamycin resistance in group A streptococcus. Lancet Infect Dis. 2021;21:1208–1209. doi: 10.1016/S1473-3099(21)00456-4. [DOI] [PubMed] [Google Scholar]
- 53.Braun L, Craft D, Williams R, Tuamokumo F, Ottolini M. Increasing clindamycin resistance among methicillin-resistant Staphylococcus aureus in 57 northeast United States military treatment facilities. Pediatr Infect Dis J. 2005;24:622–626. doi: 10.1097/01.inf.0000171175.76673.64. [DOI] [PubMed] [Google Scholar]
- 54.Asmah N, Eberspacher B, Regnath T, Arvand M. Prevalence of erythromycin and clindamycin resistance among clinical isolates of the Streptococcus anginosus group in Germany. J Med Microbiol. 2009;58:222–227. doi: 10.1099/jmm.0.001560-0. [DOI] [PubMed] [Google Scholar]
- 55.DeMuri GP, Sterkel AK, Kubica PA, Duster MN, Reed KD, Wald ER. Macrolide and clindamycin resistance in group a streptococci isolated from children with pharyngitis. Pediatr Infect Dis J. 2017;36:342–344. doi: 10.1097/INF.0000000000001442. [DOI] [PubMed] [Google Scholar]
- 56.Al-Nawas B, Karbach J (2017) S3-Leitlinie Odontogene Infektionen [S3-Guideline Odontogenic infections]. German Society of Oral- and Maxillofacial-Surgery AWMF-Registernummer: 007–006
- 57.Albrecht H, Schiegnitz E, Halling F. Facts and trends in dental antibiotic and analgesic prescriptions in Germany, 2012–2021. Clin Oral Investig. 2024;28:100. doi: 10.1007/s00784-024-05497-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Al-Haroni M, Skaug N. Incidence of antibiotic prescribing in dental practice in Norway and its contribution to national consumption. J Antimicrob Chemother. 2007;59:1161–1166. doi: 10.1093/jac/dkm090. [DOI] [PubMed] [Google Scholar]
- 59.Karki AJ, Holyfield G, Thomas D. Dental prescribing in Wales and associated public health issues. Br Dent J. 2011;210:E21. doi: 10.1038/sj.bdj.2010.1179. [DOI] [PubMed] [Google Scholar]
- 60.Halling F, Neff A, Heymann P, Ziebart T. Trends in antibiotic prescribing by dental practitioners in Germany. J Craniomaxillofac Surg. 2017;45:1854–1859. doi: 10.1016/j.jcms.2017.08.010. [DOI] [PubMed] [Google Scholar]
- 61.Doll C, Carl F, Neumann K, Voss JO, Hartwig S, Waluga R, Heiland M, Raguse JD. Odontogenic abscess-related emergency hospital admissions: a retrospective data analysis of 120 children and young people requiring surgical drainage. Biomed Res Int. 2018;2018:3504727. doi: 10.1155/2018/3504727. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Kim MK, Nalliah RP, Lee MK, Allareddy V. Factors associated with length of stay and hospital charges for patients hospitalized with mouth cellulitis. Oral Surg Oral Med Oral Pathol Oral Radiol. 2012;113:21–28. doi: 10.1016/j.tripleo.2011.01.012. [DOI] [PubMed] [Google Scholar]
- 63.Eisler L, Wearda K, Romatoski K, Odland RM. Morbidity and cost of odontogenic infections. Otolaryngol Head Neck Surg. 2013;149:84–88. doi: 10.1177/0194599813485210. [DOI] [PubMed] [Google Scholar]
- 64.Burnham R, Bhandari R, Bridle C. Changes in admission rates for spreading odontogenic infection resulting from changes in government policy about the dental schedule and remunerations. Br J Oral Maxillofac Surg. 2011;49:26–28. doi: 10.1016/j.bjoms.2009.10.033. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.