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1. Introduction
Appendicitis is a common general-surgical emergency. A lifetime risk of 8.6% in males and 6.7% in females, with a peak incidence during the second decade of life, has been documented for appendicitis [1, 2].
The diagnosis of appendicitis in children is challenging because of the following: (i) often atypical presentation, (ii) misleading symptomatology, (iii) preverbal status of children aged <2 years, and (iv) increased susceptibility to infectious states (e.g., mesenteric lymphadenitis) that mimic appendicitis (especially in younger children) [3]. The prevalence of misdiagnosis of acute appendicitis (AA) can reach 28–57% in children aged >2 years. [4] Moreover, children aged <1 year carry a risk of a perforated appendix (PA) of 86–100%, whereas it is ≤74% in older children with AA [2, 5]. Complications arising from a PA are associated with increased morbidity and include abscess formation, peritonitis, intestinal adhesions, ileus, chronic pain, fertility problems, prolonged duration of hospital stay (DoHS), and additional healthcare expenses [2, 6].
Advances in imaging and increased use of ultrasound (US) in children (which carries a sensitivity of 44–94% and specificity of 47–95%) have led to a decline in the prevalence of unnecessary appendectomies, but the prevalence of a PA has remained relatively unaltered [3]. Those data suggest that imaging improvements are less effective in differentiating a PA from a non-PA, which prompts the need for a diagnostic tool of more predictive value for a PA. If there is no abscess formation or pneumoperitoneum, ultrasound cannot be used to reliably differentiate between a PA and a non-PA, which necessitates surgical exploration. A laboratory parameter of sufficient predictive value for the diagnosis of appendicitis is lacking. However, the level of C-reactive protein (CRP) and white blood cell (WBC) count (including neutrophils) is considered the “gold standard” [7, 8].
Several scoring systems have been used in clinical practice [9–11]. Recently, appendicitis inflammatory score (AIR) has been created to overcome shortcomings of the most commonly used Alvarado score and Pediatric appendicitis score. Recent studies validated the AIR score and reported that the AIR score significantly outperforms the older Alvarado score, especially in distinguishing simple from advanced appendicitis but still not enough to be an exclusive criteria in establishing the diagnosis of acute appendicitis [12].
Recently, hyponatremia has been reported as a very sensitive marker of advanced acute appendicitis in children with sensitivity and specificity of 94.7% and 88.5%, respectively [13].
At our institution, surgery is undertaken on all children with appendicitis regardless of the index of suspicion for a PA. However, according to recent research, a non-PA might undergo spontaneous resolution and seems to be more receptive to conservative antibiotic treatment alone, whereas other types of appendicitis presentation with a PA before hospital admission necessitates surgery [14–16]. In this context, we wished to determine the value of specific parameters in distinguishing AA from a PA in a pediatric cohort.
2. Materials and Methods
2.1. Ethical Approval of the Study Protocol
The study protocol was approved (19-6741-BR) by the Ethics Committee of the Ruhr-University of Bochum (Germany).
2.2. Study Design
In this retrospective, single-center study, we identified 332 consecutive cases aged <18 years with the principal diagnosis of appendicitis on discharge as identified by the ICD-10-GM (International Classification of Diseases, 10th Revision, German Modification) code for appendicitis (K35.) and the OPS (Operation and Procedure Coding System) code for appendectomy (5-470) during study period 01/2014–12/2017. Exclusion criteria were age above 17 years, nonavailability of laboratory (n =3) or histopathological data, and coassociated confounding factors as appendicoliths, infections (e.g., oxyuriasis and enteritis), or hematologic disorders (Figure 1). The remaining 306 cases were considered eligible for further analysis. The primary outcome of this study was the validity of several laboratory factors such as CRP, CLR, and sodium at admission for differentiation of AA from a PA. The secondary outcomes included determination of other predictive factors of PA such as age, temperature on admission, Tzanakis score, duration of the surgical procedure, and DoHS. Data were derived from clinical notes as well as surgical, laboratory, and histopathology reports.
[figure omitted; refer to PDF]2.3. Patient Grouping
Based on the histopathology classification, data were dichotomized into AA (
Hematology parameters were obtained upon hospital admission: WBC (109/L), lymphocytes (109/L), CRP (mg/dL), CRP level-to-lymphocyte-count ratio (CLR; [mg/dL]/[109/L]), and sodium (mmol/L). The Tzanakis scoring system was utilized for improving the predictive value of single factors in the diagnosis of appendicitis [9]. It comprises four independent clinical-laboratory variables (6 points for ultrasound demonstrating appendicitis; 4 points for tenderness in the right lower quadrant; 3 points for rebound tenderness; 2 points for WBC count
2.4. Data and Statistical Analyses
The sampling and analyses of data were done using Excel™ (Microsoft, Redmond, WA, USA). Statistical analyses were undertaken with OriginPro™ 2021b (OriginLab, Northampton, MA, USA) and SPSS 27 (IBM, Armonk, NY, USA) for binary regression analysis.
Data are the arithmetic
3. Results
3.1. Basic Data
Basic clinical, laboratory, and procedural characteristics are given in Table 1. A total of 306 patients with appendicitis confirmed by histology were evaluated. The study cohort had a male preponderance (females,
Table 1
Clinical, laboratory, and procedural parameters regarding acute appendicitis versus a perforated appendix.
Acute appendicitis | Perforated appendicitis | ||||
Number | 237 | 69 | |||
Female : male ( | 110 : 127 | 22 : 47 | |||
Female (%) | 46 | 32 | |||
Age (years) | 10 (7–12) | 237 | 6 (4–10) | 69 | <0.001† |
Temperature (°C) | 37.4 (37.0–38.0) | 188 | 38.2 (37.6–38.9) | 59 | <0.001† |
Tzanakis score | 10 (6–12) | 237 | 12 (9–15) | 69 | <0.001† |
Laboratory data | |||||
CRP (mg/dL) | 1.0 (0.2–3.3) | 236 | 10.8 (5.7–18.7) | 69 | <0.001† |
CLR (mg/dL/109/L) | 0.6 (0.2–2.5) | 111 | 10,3 (4.3–14.1) | 33 | <0.001† |
Lymphocytes (109/L) | 112 | 33 | 0.26‡ | ||
WBC (109/L) | 237 | 68 | <0.001‡ | ||
Sodium (mmol/L) | 140.0 (138.0–142.0) | 120 | 135.5 (133.0–138.3) | 54 | <0.001† |
Procedural data | |||||
DoHS (days) | 4 (3–4) | 237 | 7 (5–9) | 69 | <0.001† |
Procedure duration (min) | 50 (40–65) | 237 | 80 (60–104) | 69 | <0.001† |
Mode of surgery | |||||
Laparoscopy/conversion/open ( | 234/1/2 | 54/12/3 |
CRP: C-reactive protein; WBC: white blood cell. CLR: C-reactive protein-to-lymphocyte ratio; DoHS: Duration of hospital stay. †Mann–Whitney
[figures omitted; refer to PDF]
3.2. ROC Characteristics
ROC analyses for differentiation of AA from a PA (Table 2; Figures 3(a) and 3(b)) revealed moderate diagnostic accuracy (
Table 2
Analyses of ROC curves for selected variables.
AUC (±SE) | Cutoff | Sensitivity | Specificity | 95% CI | PPV | NPV | OR (95% CI) | ||
Age ( | 6,5 | 52% | 84% | 0.66–0.79 | <0.001 | 49% | 86% | 5.9 (3.3–10.6) | |
Temperature (°C) | 38.0 | 68% | 75% | 0.68–0.82 | <0.001 | 46% | 88% | 6.1 (3.3–11.6) | |
Tzanakis score | 12.5 | 49% | 91% | 0.63–0.77 | <0.001 | 63% | 86% | 10.0 (5.2–19.2) | |
CRP (mg/dL) | 4.1 | 86% | 79% | 0.83–0.93 | <0.001 | 55% | 95% | 22.5 (10.7–47.2) | |
CLR (mg/dL/109/L) | 1.9 | 97% | 72% | 0.82–0.96 | <0.001 | 42% | 94% | 27.0 (7.7–95.1) | |
WBC (109/L) | 13.4 | 79% | 59% | 0.65–0.80 | <0.001 | 38% | 95% | 12.4 (5.4–28.2) | |
Sodium (mmol/L) | 137.5 | 69% | 80% | 0.72–0.86 | <0.001 | 61% | 85% | 8.7 (4.2–18.0) |
AUC: area under the curve; SE: standard error; PPV: positive predictive value; NPV: negative predictive value; OR: odds ratio; CI: confidence interval; CRP: C-reactive protein; WBC: white blood cell. CLR: C-reactive protein-to-lymphocyte ratio.
[figures omitted; refer to PDF]
3.3. Regression Analysis
The independent regression parameters were identified by AUC values ≥0.7 from ROC analysis and were considered eligible for binary logistic regression analysis (Enter method) if the variance inflation factor (VIF; as a measure of multicollinearity between variables) was within the threshold of 2.5, as proposed by Midi and colleagues [21]. Due to VIF levels of 4.011 and 3.452 for CRP and CLR, respectively, two regression models with either CRP or CLR included together with the following variables were performed: age, Tzanakis score, body temperature on admission, levels of sodium, and WBC. In brief, the CRP-controlled model slightly outperformed the CLR-controlled model. In the CRP-controlled model, among all included variables, levels of sodium (OR 0.858, 95% CI 0.737–1.000,
4. Discussion
We wished to evaluate the value of basic clinical–laboratory parameters in differentiating a PA from AA in a pediatric cohort. An increased CRP level and Tzanakis score, together with hyponatremia, were of independent predictive value for a PA. Moreover, in this context, the value of CLR might be equal to, or greater than, that of CRP. This information could foster decision-making towards the treatment of AA and PA cases.
The present study had several limitations. First, it was retrospective. Second, it was from a single center. Third, the study cohort was relatively small. Fourth, longitudinal laboratory data were lacking, so conclusions on possible dynamic variations in the investigated parameters could not be drawn. Fifth, the validity of data on body temperature may have been compromised by the preceding use of antipyretic medication because documentation of this issue was not part of our study protocol.
We observed reduced levels of sodium in the PA group (Table 1 and Figure 2(f)), and similar results were reported in a prospective study by Lindestam and coworkers [22]. Moreover, they found that increased concentrations of vasopressin in PA cases compared with those in patients without a PA. In this context, conditions as vomiting, pain, fever, physiological stress, and hypovolemia are often associated with a PA and may constitute nonosmotic stimuli for vasopressin release with consecutive hyponatremia [23]. The pathogenesis of hyponatremia in PA is incompletely understood, but an interleukin- (IL-) 6- and vasopressin-mediated response in early systemic inflammation might have a pivotal role [24–26]. Of note, hyponatremia (sodium <136 mmol/L) is not only associated with a PA but also with an increased morbidity and mortality [27–29]. In this context, hyponatremia has been hypothesized to have predictive value in detection of perforation in sigmoid diverticulitis in older patients undergoing emergency surgery [29] and anastomotic leakage in patients following colorectal surgery [30]. Compared to the results of a prospective study by Pogorelić et al. [13], the discriminatory accuracy of our data on sodium was lower regarding differentiation of a PA from AA. Noteworthy, cutoff was set at a lower level and also mean levels of their PA group were markedly lower. However, our finding of sodium as an independent factor using regression analysis underlines its importance as a surrogate for a PA.
In our series, the CRP level was more sensitive than the WBC count for detecting a PA (Table 2 and Figure 3(a)). Accordingly, the CRP level has been reported being more sensitive than the WBC count for detecting a PA [31]. However, these data must be interpreted with caution because each parameter follows a characteristic time course. Hence, the timepoint of sampling has considerable influence on the obtained value. Upon the onset of inflammation, the number of circulating leukocytes is increased following their decrease secondary to sequestration within inflamed tissues after ≥48 h. Serum CRP levels start to increase within 6 h from the initial insult and reach a peak at ~40 h, with a decrease thereafter [6, 31, 32].
In search of a more sensitive marker that reflects systemic inflammation and the immunological response, the CLR was applied (Tables 1 and 2, Figure 2(e) and 3(a)). To our knowledge, this is the first study to use the CLR to differentiate a PA from AA, and the first to recruit a pediatric population for its application. The hypothetical advantage of the CLR over the CRP level alone or lymphocyte number alone lies in its unified reflection of two opposing immune pathways, with a possibly more accurate consideration of temporal variations of each integrated parameter. The CLR has been proposed as an indicator of systemic inflammation in malignancies [33, 34] or intestinal ischemia [35]. With regard to appendicitis, the CLR has been applied only once, in a recent study by Daldal and Dagmura [36]. They utilized the reciprocal value, the lymphocyte-to-CRP ratio (LCR) in the context of a possibly related appendix diameter and complete blood count parameters by comparing AA with lymphoid hyperplasia (normal appendix) in adults with an appendix diameter >6 mm. However, even though the WBC count, neutrophil count, and neutrophil-to-lymphocyte ratio were altered, the LCR remained unchanged. In contrast to those results, the CLR was increased in our PA cohort (Table 1 and Figure 2(e)) and displayed among the highest discriminatory accuracy according to ROC analyses (Table 2 and Figure 3(a)). This discrepancy in results could be explained by a lower prevalence of a PA in the AA cohort in the abovementioned study by Daldal and Dagmura. Conversely, the CLR might not be applicable in adults with appendicitis. Due to the observed multicollinearity regarding the CRP level and CLR, two regression models, including either CRP or CLR, were calculated with highest accuracy in the CRP-controlled model. Perhaps longitudinal measurements instead of a single measurement might have demonstrated the superiority of the CLR over CRP in terms of a truer and more dynamic depiction of the underlying inflammatory state.
Our applied Tzanakis score served as an internal control regarding the clinical validity of laboratory results. In accordance with the literature [9], the Tzanakis score was increased in the PA group compared with that in the AA group, thereby reflecting inter alia clinical progression of appendiceal inflammation. Although the Tzanakis score displayed only moderate discriminatory ability (Table 2 and Figure 3(a)), together with the CRP and sodium level, it was an independent predictor for a PA in the CRP-controlled regression model.
In accordance with the literature, male sex was associated with a PA (Table 1). Also, the sex distribution in the AA group was evenly matched [37]. In line with the literature, a PA was associated with a younger age compared with AA [5]. The value of body temperature as a cofactor in predicting a PA has been described by van den Bogaard and colleagues [38]. However, apart from being higher in the PA group (Table 1), body temperature upon hospital admission was not retained in our final regression model as being independently predictive for a PA.
5. Conclusions
Our study provides data on the potential of using the CLR to distinguish a PA from AA in children. Also, it underlines the importance of an increased CRP level, hyponatremia, and high Tzanakis score as predictors for a PA. These factors might be helpful if clinical and imaging investigations are inconclusive. Moreover, if applicable, these factors might support decision-making towards a hypothetical conservative (antibiotic) treatment in AA or surgery to treat a PA.
Additional Points
Key Messages. (i) Acute appendicitis (AA) might be amenable to conservative treatment while a perforated appendix (PA) necessitates surgery. (ii) Although distinctive and reliable markers for a PA or AA are lacking, our data indicate that a raised C-reactive protein (CRP), hyponatremia, and Tzanakis score may predict a PA. (iii) The value of the newly applied CRP-to-lymphocyte ratio might be similar to that for CRP.
Disclosure
The funding source had no involvement in study design, data collection/analyses/interpretation, writing of the report, or decision to submit the article for publication.
Authors’ Contributions
R.-B.T. contributed to the study design, data collection, and critical revision of the manuscript. M.N. contributed to the study design, data collection, statistical analyses, and manuscript writing.
Acknowledgments
M.N. is receiving a research fellowship from the Ruhr University Bochum (grant number K133-19).
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Abstract
Background. Acute appendicitis (AA) might be amenable to conservative antibiotic treatment, whereas a perforated appendix (PA) necessitates surgery. We investigated the value of clinical–laboratory markers in distinguishing AA from a PA. Methods. Retrospectively obtained preoperative parameters for 306 consecutive patients (<18 years) with histologically confirmed appendicitis (AA (
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