Nomogram for predicting complicated appendicitis and aiding decision-making regarding antibiotic therapy for acute appendicitis

Antibiotic therapy is a feasible treatment option for uncomplicated appendicitis, but the preoperative diagnosis of uncomplicated appendicitis is challenging. This study aimed to develop a nomogram to predict complicated appendicitis based on laboratory data and CT features and to guide antibiotic treatment decision-making. Patients with pathologically conrmed acute appendicitis (AA) were randomly split into the primary and validation cohorts. The nomogram model for predicting complicated appendicitis was constructed based on the results of the multivariate logistic analysis in the primary cohort and transformed into a nomogram risk score. The nomogram was validated in a validation cohort and an independent antibiotic therapy cohort.


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Background Acute appendicitis (AA) is a common cause of abdominal pain and accounts for approximately 7.0-10.0% of emergency visits [1]. AA is divided into uncomplicated appendicitis and complicated appendicitis according to the clinical manifestations and acute in ammatory processes, and complicated appendicitis refers to AA with perforation, gangrene, and abscess [2]. Although appendectomy is a classic and standard treatment for AA, the overall complication rate after postoperative appendectomy is 8.2-31.4%, and the wound infection rate and incidence of pelvic abscess are 3.3-10.3% and 9.4%, respectively [3,4].
Recently, a number of systematic reviews and meta-analyses of random controlled trials (RCTs) have suggested that antibiotic therapy is a feasible treatment option for uncomplicated appendicitis [6][7][8].
Approximately 8.2-12.0% of patients treated with antibiotics experience treatment failure during their rst hospitalization, and 19.2%-22.6% of patients might need a second hospitalization for recurrence during the 1-year follow-up [6,8]. In fact, some RCTs employed computerized tomography (CT) to assess whether appendicitis was complicated. However, whether CT can be used to accurately distinguish complicated appendicitis from uncomplicated appendicitis is still uncertain. Kim et al summarized 23 articles on the CT features distinguishing complicated appendicitis from uncomplicated appendicitis and found that the CT features had a relatively high speci city but low sensitivity [9]. Leeuwenburgh et al. found that ultrasonography and CT features incorrectly classi ed up to half of all patients with perforated appendicitis as having uncomplicated appendicitis [10]. In one of the RCTs, although a preoperative CT assessment was used, 18% of the patients with complicated appendicitis were diagnosed with uncomplicated appendicitis [11]. Therefore, the accurate assessment of patients with complicated appendicitis may improve the targeting of antibiotic treatment. However, the preoperative diagnosis of complicated appendicitis is challenging. In this study, we attempted to determine the factors that can distinguish complicated appendicitis from uncomplicated appendicitis and developed a nomogram to predict complicated appendicitis based on preoperative laboratory data and CT features. Furthermore, the model can be used to guide antibiotic treatment decision-making in patients with AA.

Study population
Surgical therapy cohort (ST cohort) A total of 713 consecutive patients who underwent surgical treatment for pathologically con rmed AA at Beijing Tsinghua Changgung Hospital (BTCH) between January 2016 and December 2019 were recruited. The inclusion criteria were age greater than 18 years, pathological con rmation of AA and performance of an abdominal pelvic CT scan before surgery. The exclusion criteria were age younger than 18 years, no CT scan before surgery, and pregnancy. All patients underwent traditional three-port laparoscopic appendectomy as previously reported [12]. All surgeries were performed by the same group of doctors, who had 3-5 years of experience with laparoscopic appendectomy and performed more than 50 laparoscopic appendectomies per year.
Antibiotic therapy cohort (AT cohort) A total of 242 consecutive patients who were diagnosed with AA at BTCH between January 2016 and January 2019 were recruited. The inclusion criteria were the con rmation of AA based on the medical history, physical examination, laboratory inspection and abdominal pelvic CT scan; the refusal of surgical treatment; and administration of antibiotic therapy. The exclusion criteria were emergency surgical treatment and a diagnosis of appendiceal abscess prior to the initial treatment.
All patients were treated with intravenous antibiotics after diagnosis; the therapeutic options were as follows: ertapenem 1 g + 0.9% NaCl 100 ml 1 time/day; ceftriaxone 2 g + 0.9% NaCl 100 ml 1 time/day and metronidazole or Austrian Nitrazole 0.5 g 2 times/day; cefuroxime 1.5 g + 0.9% NaCl 100 ml 2 times/day and metronidazole or ornidazole 0.5 g 2 times/day; or levo oxacin 0.5 g 1 time/day and metronidazole or ornidazole 0.5 g 2 times/day. After 3 days of treatment, routine blood and CRP tests were performed. If the tests were normal, no further treatment was administered; otherwise, the infusion was continued to reduce in ammation until the tests returned with normal results. Imaging examinations were immediately reviewed if symptoms and signs worsened during treatment, and surgical drainage was performed if there was an abscess around the appendix; the decision to remove the appendix was made based on the intraoperative situation.

Pathological assessment
The histopathological diagnosis was based on changes in and the density of neutrophils in ltrating the wall of the appendix. The severity of appendicitis can be divided into three histopathological conditions: mucosal, purulent, and gangrenous. The relevant conditions under the microscope are neutrophilin ltrated mucosa/submucosa (mucosal AA); neutrophil-in ltrated mucosa, submucosa and muscularis mucosa (suppurative AA); and penetrating necrosis of the appendix wall and extensive mucosal ulcers.
The de nition of complicated appendicitis includes gangrenous and perforated appendicitis.

Data collection and CT ndings
Data on patients' medical history, physical examinations and laboratory results were collected retrospectively by a case manager on a structured case record form. The following clinical characteristics were obtained for this analysis: age, sex, duration of abdominal pain, presence of shifting pain in the right lower quadrant, vomiting, diarrhoea, peritonitis, temperature (TEMP), history of appendicitis, white blood cell (WBC) count, neutrophil (NEUT) count, neutrophil percentage (NEUT%), lymphocyte (LY) count, lymphocyte percentage (LY%), platelet (PLT) count, albumin (ALB) level, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP) level and the time to operation. CT features associated with complicated appendicitis included appendix diameter, faecalith, pelvic in ammation, and periappendiceal fat stranding (PFS).

Statistical analysis
Statistical analyses were conducted using R software (version 3.5.1, https://www.r-project.org/) for Windows to identify risk factors for complicated appendicitis. For categorical variables, the P value was calculated using Fisher's exact test. Continuous variables are expressed as the means ± standard deviations (SDs) for normally distributed data or as the medians and interquartile ranges (IQRs) for nonnormally distributed data. To improve the clinical applicability of the nomogram, continuous variables were assessed by receiver operating characteristic (ROC) curves and the Youden index. A multivariable logistic regression model with the selected predictors was tted to reduce the use of stepwise backward selection.
The nomogram was formulated based on the results of the multivariate logistic regression analysis with the rms package in R. The performance of the nomogram was measured by the area under the ROC curve (AUC) and the calibration curve. External validation was achieved by applying the nomogram to the validation cohort and evaluating the performance with similar statistics. The nomogram model was transformed into a clinically applicable scoring system called the nomogram risk score. The nomogram was used to calculate each patient's total score. Subsequently, a cutoff value analysis was performed in the primary cohort to demonstrate the ability of the nomogram risk score to select patients with complicated appendicitis. To explore whether the nomogram risk score could be used to guide antibiotic treatment, we obtained a nomogram risk score for each patient in the antibiotic treatment cohort.
According to the cutoff value, patients were divided into the complicated appendicitis group and the uncomplicated appendicitis group, and then the failure rates of antibiotic therapy were calculated for the complicated appendicitis group and the uncomplicated appendicitis group.

Baseline characteristics of patients undergoing appendectomy
According to the inclusion and exclusion criteria, 543 patients who received surgical therapy (appendectomy) (ST cohort) were enrolled. The ST cohort dataset was split into the primary and validation cohorts with repeated random sampling until there were no signi cant differences (P value ≥ 0.10) between the two cohorts in any variables (Table 1). Ultimately, 375 patients were included in the primary cohort, and 168 patients were included in the validation cohort.
The baseline characteristics of the primary cohort (n=375) and validation cohort (n=168) are summarized in Table 1. The baseline characteristics were similar between the primary and validation cohorts. In the primary cohort, 117 (31.2%) patients were diagnosed with complicated appendicitis, and 258 (69.8%) patients were diagnosed with uncomplicated appendicitis. The primary cohort population consisted of 188 men (188/375, 50.1%) and 76 women (187/375, 49.9%), with a median age of 36 years (IQR: 28-52 years). The median age in the complicated appendicitis group was older than that in the uncomplicated appendicitis group (43.0 vs 35.0, p=0.005). There was no difference in the male to female ratio between the two groups ( Table 2).

Nomogram construction and predictive performance
In the univariate analysis, the factors associated with complicated appendicitis in the primary cohort were as follows: age, duration of abdominal pain, shifting pain in the right lower quadrant, vomiting, peritonitis, TEMP, WBC count, CRP level, NEUT count, NEUT%, LY count, LY%, PLT count, ALB level, the NLR, appendix diameter, pelvic in ammation and PFS. However, in the multivariate analysis, the data were compared between the uncomplicated appendicitis group and the complicated appendicitis group using inverse stepwise logistic regression analysis, and PFS (p<0.001, OR=67.80), a CRP level ≥38 mg/L (p<0.001, OR=5.77) and a NLR≥7 (p<0.001, OR=3.51) were statistically sig ni cant independent risk factors ( Table 3). The cut-offs for the CRP level and the NLR in the primary cohort were 38 mg/L and 7, respectively ( Figure 1).
The nomogram for predicting complicated appendicitis was constructed based on the results of the multivariate analysis in the primary cohort. The PFS, CRP and NLR scores were 10.0, 4.0 and 3.0, respectively ( Figure 1). In the primary cohort, the predictive accuracy for complicated appendicitis as measured by the AUC value was 0.890 (95% CI: 0.854-0.920, Figure 3A-B). The nomogram risk score was calculated for each patient. The best cutoff value for the nomogram risk score was 11.0 points, and nomogram risk scores greater than 11 were predictive of complicated appendicitis. In the primary cohort, fourteen patients (3.7%, 14/375) with complicated appendicitis were classi ed as having uncomplicated appendicitis, and the sensitivity and speci city were 0.880 and 0.748, respectively. The calibration plot for the probability of complicated appendicitis showed a good correlation between the actual observed outcome and the outcome predicted by the nomogram ( Figure 3C).

Validation of the nomogram for the prediction of complicated appendicitis
The nomogram was validated by the calibration plot and the AUC in an independent validation cohort of 168 patients. The AUC in the validation cohort was 0.890 (95% CI: 0.832-0.933, Figure 3D-E), which demonstrated that the model had good distinguishing ability. In the validation cohort, seven patients (4.2%, 7/168) with complicated appendicitis were classi ed as having uncomplicated appendicitis, and the sensitivity and speci city were 0.868 and 0.696, respectively. The calibration plot for the probability of having complicated appendicitis showed a good correlation between the actual observed outcome and the outcome predicted by the nomogram (Figure F).
Prediction of the failure of antibiotic therapy during the rst 30 days by the nomogram risk score To evaluate whether the nomogram risk score could predict the e cacy of antibiotic treatment for AA during the rst 30 days, we enrolled 169 patients who received antibiotic treatment after refusing to undergo surgery between January 2016 and January 2019. The de nition of treatment failure was the formation of a pelvic or abdominal abscess that required an operation within 30 days of antibiotic treatment. Of the 169 antibiotic treatment patients, 23.7% (40/169) underwent appendectomy due to the failure of antibiotic treatment.
In the univariate analysis, the data were compared between the failure group and the success group and demonstrated that age, TEMP, CRP level, the NLR, appendix diameter, PFS, use of cephalosporin, antibiotic therapy time and the nomogram risk score were statistically sig ni cant risk factors. Multivariate analysis showed that a nomogram risk score >11 points (p=0.001, OR=5.045) was a statistically sig ni cant independent risk factor (Table 5). When the nomogram risk score was greater than 11, the failure rate of antibiotic treatment was 49.2%; when the nomogram risk score was less than 11, the failure rate of antibiotic treatment was only 5.3%. Furthermore, the predictive accuracy of the nomogram risk score for antibiotic treatment failure as measured by the AUC was 0.823 (95% CI: 0.757 -0.878, Figure 4B).

Discussion
In this study, we constructed a nomogram for the prediction of complicated appendicitis. This nomogram can be used to estimate the probability of complicated appendicitis based on the results of a logistic regression analysis. The nomogram includes one CT feature and two clinical features that are routinely obtained. This model can accurately predict complicated appendicitis, and furthermore, this model can be used to guide decision-making regarding antibiotic therapy in AA.
AA is one of the most common abdominal emergencies in the world, and the cause of the condition is still unclear; in addition, there has been little progress in this eld in the past few decades [2]. To stratify patients based on the necessary clinical management, AA is divided into uncomplicated and complicated appendicitis; however, many patients still have ambiguous diagnoses, which is one of the most challenging problems. Recently, several systematic reviews and meta-analyses have shown that most uncomplicated appendicitis patients can be treated with antibiotics rst [7][8][9]. Therefore, the World Society of Emergency Surgery (WES) guidelines recommend the use of antibiotic therapy as a safe alternative to surgery for patients with uncomplicated appendicitis and without appendicolith. Notably, the guidelines also indicate the possibility of treatment failure and the misdiagnosis of complicated appendicitis [13].
A recent meta-analysis by Podda et al. showed that the failure rate of antibiotic treatment and the recurrence rate at the 1-year follow-up were 8.5% and 19.2%, respectively. However, the failure rate of antibiotic therapy in the Vons et al study was 12% (14/120). Notably, in this study, despite CT-scan assessment, 21 (18%) of 119 patients were unexpectedly identi ed as having complicated appendicitis during surgery [11]. Salminen et al showed that 4 (1.5%) of 237 patients were identi ed as having complicated appendicitis during surgery [14]. This may be due to inaccurate CT scans or the progression of uncomplicated appendicitis to perforation.
Neither CT nor emergency MRI can be used to discriminate between nonperforated and perforated appendicitis. Leeuwenburgh et al. found that both methods incorrectly classi ed more than half of the patients with perforated appendicitis as having uncomplicated appendicitis [10]. A systematic review and meta-analysis of 10 CT features (extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal uid collection, ascites, intraluminal air, intraluminal appendicolith and PFS) for the diagnosis of complicated appendicitis showed that PFS was the only feature that had a high sensitivity (94%; 95% CI: 86%-98%), although it had a low speci city (40%; 95% CI: 23%, 60%) [9]. Another study showed that the pooled sensitivity of the presence of any of the 10 CT features was higher than that of individual assessments (92% vs 64%; p < 0.001), although the pooled speci city was lower (43% vs 76%; p < 0.001). In our study, the AUC, sensitivity and speci city of PFS were 79.2%, 98.7% and 59.7%, respectively. However, sensitivity, rather than speci city, should be given priority in the diagnosis of complicated appendicitis. Low speci city may lead to appendectomy in some patients who could be treated with antibiotics.
To improve the predictive ability, our nomogram includes clinical features and imaging features. Clinical features, especially when two or more are combined, have been suggested as being valuable in the diagnosis of complicated appendicitis. The NLR is a simple clinical in ammatory marker, and the NLR provides information about two different immune and in ammatory pathways, which may make it a good marker for predicting appendicitis and its severity [15][16][17]. In our study, the optimal cutoff value for the NLR was 7, and an NLR greater than 7 indicated the presence of complicated appendicitis. Similar to other studies, the AUC, sensitivity, and speci city of the NLR for predicting complex appendicitis were 0.667, 0.735, and 0.535, respectively. In the early stage of AA, the sensitivity of CRP is low. CRP may be more sensitive for the detection of perforation of the appendix and the formation of an abscess, although the positive predictive value of traditional in ammatory markers is relatively lower [18]. A systematic review and meta-analysis demonstrated that the CRP level was more accurate (AUC = 0.75, 95% CI: 0.71 to 0.78) than the WBC count and procalcitonin level [19]. In our study, the AUC, sensitivity, and speci city of CRP for predicting complicated appendicitis were 0.741, 0.573, and 0.841, respectively.
Previously, Atema et al. constructed a model for predicting complicated appendicitis based on clinical and imaging characteristics. The model includes ve clinical indicators (age, TEMP, duration of symptoms, WBC count, and CRP level) and three CT-based parameters (presence of extraluminal free air, periappendiceal uid and appendicolith). Nonetheless, scores > 6 points are not speci c for complicated appendicitis; instead, other complex diseases, such as perforated diverticulitis and Crohn's disease, may also be indicated [20]. These limitations and the time needed to calculate up to 22 points per patient may limit its daily use. In addition, the study lacked a validation group. Avanesov et al. constructed a model for predicting complicated appendicitis based on a combination of clinical and CT features called the appendicitis severity index (ASPI) [21]. A score ≥ 4 points predicted complicated appendicitis with a positive predictive value of 92% and a negative predictive value of 83%. Again, the study lacked a validation group. In our study, evaluation of the nomogram showed that a score greater than or equal to 11 points indicated the presence of complicated appendicitis, and fourteen patients (3.7%, 14/375) and seven patients (4.2%, 7/168) with complicated appendicitis were classi ed as having uncomplicated appendicitis in the primary and validation cohorts, respectively. The false-negative classi cation of complicated appendicitis patients who then receive antibiotic treatment may result in an increased rate of treatment failure. In this study, we used an independent cohort who received antibiotic therapy to test whether this nomogram risk score could guide decision-making with regard to antibiotic therapy. When the nomogram risk score was more than 11 points, the failure rate of antibiotic treatment was 49.2%; in contrast, when the nomogram risk score was less than 11 points, the failure rate of antibiotic treatment was only 5.3%, which was lower than previously reported. This suggests that the nomogram risk score not only accurately predicts complicated appendicitis but can also be used to guide the use of antibiotic treatment in patients with AA.
Several limitations of this study need to be addressed. First, this study was retrospective and included a relatively limited number of patients from only one hospital. Although the model was validated in an independent validation cohort, there was no external validation to ensure that the results support universal application. The second is the de nition of complicated appendicitis in this study. The de nition of complicated appendicitis is not yet clear. The de nition of complicated appendicitis in this study included gangrenous and perforated appendicitis, which are determined based on postoperative pathological results. Patients with appendiceal abscesses or in ammatory masses were excluded because this subgroup of appendicitis requires special treatment.

Conclusion
In conclusion, we found that the proposed nomogram risk score based on clinical and CT features not only enables the accurate identi cation of complicated appendicitis patients before surgery but can also be used to guide management decisions.

Declarations
Yiting Meng, data collection. Yuanxin Li: design, writing and revision. All authors read and approved the nal manuscript.

Funding
No funding has been provided to support this manuscript.
Availability of data and materials The authors state that all data generated or analyzed during this study are included in this published article.

Figure 2
Nomogram for complicated appendicitis based on clinical and CT features. Each variable value is assigned a score, and the sum of scores is converted to a probability in the total points axis. Calculated probabilities are assigned to uncomplicated and complicated appendicitis.Abbreviations: NLR, neutrophilto-lymphocyte ratio; CRP, C-reactive protein, PFS, Periappendiceal fat stranding