Accepted Manuscript Alvarado or RIPASA score for diagnosis of acute appendicitis? A meta-analysis of randomized trials Maximos Frountzas, Konstantinos Stergios, Dimitra Kopsini, Dimitrios Schizas, Konstantinos Kontzoglou, Konstantinos Toutouzas PII:
S1743-9191(18)31539-5
DOI:
10.1016/j.ijsu.2018.07.003
Reference:
IJSU 4720
To appear in:
International Journal of Surgery
Received Date: 24 March 2018 Revised Date:
9 June 2018
Accepted Date: 6 July 2018
Please cite this article as: Frountzas M, Stergios K, Kopsini D, Schizas D, Kontzoglou K, Toutouzas K, Alvarado or RIPASA score for diagnosis of acute appendicitis? A meta-analysis of randomized trials, International Journal of Surgery (2018), doi: 10.1016/j.ijsu.2018.07.003. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Alvarado or RIPASA score for diagnosis of acute appendicitis? A metaanalysis of randomized trials. Maximos Frountzas1(MF) MD, Konstantinos Stergios1(KS) MD, Dimitra Kopsini1(DK) MD, Dimitrios Schizas2(DS) MD, PhD, Konstantinos Kontzoglou3(KK) MD, PhD,
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Konstantinos Toutouzas4(KT) MD, PhD
Affiliation
Laboratory of Experimental Surgery and Surgical Research N.S. Christeas,
Athens Medical School, Athens, Greece.
First Department of Surgery, Laiko General Hospital, Athens Medical
School, Athens, Greece. 3
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Second Department of Propaedeutic Surgery, Laiko General Hospital,
School of Medicine, Athens Medical School, Athens, Greece. First Department of Propaedeutic Surgery, Hippocration Hospital,
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Athens Medical School, Athens, Greece.
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Correspondence: Maximos Frountzas, MD, PhD(c) 39, Mikras Asias str. Athens 11527 – GREECE Phone: +0030 6978880045 E-mail:
[email protected],
Disclosure: The authors report no conflict of interest. Source of funding: None to disclose for all authors.
Category: Review (meta-analysis)
Keywords: Alvarado; RIPASA; appendicitis; diagnosis; meta-analysis
ACCEPTED MANUSCRIPT Short title: Alvarado or RIPASA for appendicitis diagnosis? Word counts: abstract: 246, text: 2,729 Number of Figures: 4 Number of Tables: 3
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Number of references: 32
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Abstract
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Backround: The electronic diagnostic tools of acute appendicitis present
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serious disadvantages, thus some clinical scores have been formed in order
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to reach the diagnosis easily and safely. Alvarado and RIPASA scores are the
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most commonly used and the purpose of this meta-analysis is to compare the
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diagnostic accuracy of these two scoring systems.
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Method: We searched MEDLINE (1966-2017), Scopus (2004-2017),
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ClinicalTrials.gov (2008-2017), Google Scholar (2004–2017) and Cochrane
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Central Register of Controlled Trials CENTRAL (1999-2017) databases. We
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selected all observational cohort studies that reported diagnostic parameters
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of Alvarado and RIPASA diagnostic scores on patients with clinical status of
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acute appendicitis. Statistical meta-analysis was performed with Meta Disc 1.4
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software.
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Results: Twelve studies were included in our meta-analysis which enrolled
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2,161 patients. The sensitivity of RIPASA score was 94% (95% CI, 92% to
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95%) and the specificity was 55% (95% CI, 51% to 55%). In addition, the area
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under the Roc Curve (AUC) was 0.9431 and the diagnostic Odds Ratio was
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24.66 (95% CI, 8.06 to 75.43). The sensitivity of Alvarado score was 69%
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(95% CI, 67% to 71%) and the specificity was 77% (95% CI, 74% to 80%).
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Moreover, the AUC was 0.7944 and the diagnostic Odds Ratio was 7.99 (95%
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CI, 4.75 to 13.43).
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Conclusion: RIPASA scoring system is more sensitive than Alvarado one,
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but the low specificity forms the need of a supplementary mean to provide the
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accurate diagnosis. Nevertheless, the wide and safe use of both tests is
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ACCEPTED MANUSCRIPT recommended in health systems that lack electronic diagnostic tests, such us
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developing countries or rural hospitals.
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Introduction
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Acute appendicitis (AA) is one of the most common surgical emergencies in
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the world, with 7-12% of the general population being affected (1). Prompt and
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accurate diagnosis, mainly based on clinical assessment and laboratory
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results (2), is of paramount importance in order to reduce complications and
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mortality rates. However, due to the fact that only half of the patients present
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with the typical periumbilical pain followed by nausea, vomiting and migration
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of the pain to the right lower quadrant, as well as the diseases mimicking AA,
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diagnosis of appendicitis is a challenging undertaking (3, 4). Ultrasound, multi-
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detector CT scan and diagnostic laparoscopy have been important, but costly,
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supplements to the differential diagnosis of acute abdominal pain.
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Laparoscopy is a vital tool in the diagnosis and management of lower
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abdominal pain in young and fertile women (5, 6), while CT scan is perceived
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as the best diagnostic tool for AA (7), both reducing the false positive cases
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before the operation.
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However, ionizing radiation and the associated cancer risk especially for the
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pediatric patients, limited availability and high cost are major disadvantages of
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CT scan (8). Surgery is not without risks as well. Negative appendectomy
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(NA) due to early intervention, perforation due to delayed intervention, wound
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infection, hernia development and adhesions are some of the drawbacks of
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appendectomy. Also, the cost of negative appendectomy (NA) to both the
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patient and the health care system, are important things to consider when
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treating patients with a possible appendicitis (9). These facts, have made the
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ACCEPTED MANUSCRIPT need for an assisting tool in diagnosis of AA mandatory and this is how clinical
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scoring systems emerged. Since 1980, more than ten systems have been
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developed, with Alvarado, RIPASA, Fenyo, Tzakis, Eskelinen and Ohmann
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being some of them. These scoring systems stratify patients into scaled
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groups of likelihood to suffer from appendicitis, according to the number of
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symptoms and signs they present. (10).
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The Alvarado score was introduced in 1986 and takes into consideration eight
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parameters that were found to be important in the diagnosis of acute
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appendicitis: localized tenderness in the right lower quadrant, leukocytosis,
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migration of pain, leukocyte shift to the left, temperature elevation, nausea-
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vomiting, anorexia and rebound pain (11). In 2010, a new scoring system
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called RIPASA score was developed. It was thought to have increased
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sensitivity and specificity when applied in Indian population and compared to
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Alvarado’s 8 parameters, it uses 15: age, gender, right iliac fossa (RIF) pain,
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migration of pain to RIF, nausea and vomiting, anorexia, duration of
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symptoms (less or more than 48 hours), RIF tenderness, guarding, rebound
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tenderness, Rovsing's sign, fever, raised white cell count, negative urinalysis
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and foreign national registration identity card (12).
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The aim of our study is to compare these two widely and easily used scoring
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systems, in order to identify which one has the best sensitivity and specificity
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and leads to the most accurate diagnosis of acute appendicitis.
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Material and methods
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Literature search and data collection
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ACCEPTED MANUSCRIPT The present study was designed according to the Preferred Reporting Items
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for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (13).
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Eligibility criteria were predetermined by the authors. Language or date
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restrictions were avoided during the literature search. Case reports and review
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articles were excluded. Two authors (MF, DK) performed the electronic search
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of articles and tabulated data on duplicated pre-structured forms. The data
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where then reviewed by a third author (KS) and every discrepancy regarding
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the evaluation of the methodology, retrieval of articles and statistical analysis
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was resolved by consensus of three authors (DS, KK, KT).
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We used the Medline (1966-2017), Scopus (2004-2017), Clinicaltrials.gov
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(2008-2017), Cochrane Central Register of Controlled Trials CENTRAL
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(1999-2017) and Google Scholar (2004–2017) databases in our primary
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search along with the reference lists of electronically retrieved full-text papers.
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The date of our last search was on December 20th, 2017. The PRISMA flow
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chart of study selection could be found on Figure 1. According to that, 142
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studies excluded selection, due to lack of one diagnostic tool from the
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comparison or due to reference to a different diagnostic tool; the inadequate
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data of some studies about statistical values necessary for our analysis was
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an additional reason for excluding them from selection.
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The search strategy included the keywords “acute”, “appendicitis”, “diagnosis”,
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“score”, in combination with Boolean operators (AND, OR, NOT). The stages
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of article selection are depicted in the PRISMA flow diagram (Figure 1).
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Quality assessment
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The methodological quality of the included studies was assessed with the
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ACCEPTED MANUSCRIPT QUADAS-2 tool, which comprises 4 domains: patient selection, index test,
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reference standard, and flow and timing. Each domain is assessed in terms of
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risk of bias, and the first 3 domains are also assessed in terms of concerns
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regarding applicability. Signaling questions are included to help judge risk of
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bias, and the possible answers are “low”, “high” or “unclear”. At the end, a
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summary of the number of studies that had a low, a high, or an unclear risk of
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bias or concerns about applicability for each domain is formed, represented by
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a different color (Figure 2).
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Statistical analysis
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Statistical analysis was performed using the Meta Disc 1.4 software.
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Confidence intervals were set at 95%. Pooled sensitivity, pooled specificity,
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diagnostic Odds Ratios (OR), Summary Receiver Operating Characteristic
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(SROC) curves and 95% confidence intervals (CI) for all outcomes were
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calculated, using the DerSimonian-Laird random effect model due to the
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significant heterogeneity in the methodological characteristics of included
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studies (Table 1). Publication bias was not tested due to the gross
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heterogeneity of included studies, which is a significant confounder that may
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influence the methodological integrity of these tests.
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Definitions
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Alvarado scoring system includes abdominal pain that migrates to the right
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iliac fossa (1 point), anorexia (loss of appetite) or ketones in the urine (1
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point), nausea or vomiting (1 point), tenderness in the right iliac fossa (2
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points), rebound tenderness (1 point), fever of 37.3 °C or more (1 point),
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leukocytosis > 10,000 (2 points), neutrophilia > 70% (1 point). A score of 5 or
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6 is compatible with the diagnosis of acute appendicitis. A score of 7 or 8
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ACCEPTED MANUSCRIPT indicates a probable appendicitis, and a score of 9 or 10 indicates a very
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probable acute appendicitis (14). A score above 7.0 considered as positive for
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appendicitis. All the included studies used classic Alvarado scoring system,
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except from one that used the modified Alvarado test and one that used both
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tests. Nevertheless, all studies considered the same cut-off point (score > 7.0)
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for diagnosis of acute appendicitis.
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RIPASA scoring system includes age (less than 40 years = 1 point; greater
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than 40 years = 0.5 point), gender (male = 1 point; female = 0.5 point), right
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Iliac fossa (RIF) pain (0.5 point), migration of pain to RIF (0.5 point), nausea
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and vomiting (1 point), anorexia (1 point), duration of symptoms (less than 48
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hours = 1 point; more than 48 hours = 0.5 point), RIF tenderness (1 point),
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guarding (2 points), rebound tenderness (1 point), Rovsing's sign (2 points),
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fever (1 point), raised white cell count (1 point), negative urinalysis (1 point)
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and foreign national registration identity card (1 point) (15). A score above 7.5
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considered as positive for appendicitis.
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Results
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Figure 1 shows the process that our study group followed in order to conclude
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to the included studies after search of the literature and evaluation of the
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results. Two studies were excluded, because they referred to Alvarado score
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by itself (12, 16). Another three studies were excluded, because they were
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exclusively associated to the RIPASA score (15, 17) and one study excluded
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due to correlation with an irrelevant scoring system (18).
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studies were included in our meta-analysis which enrolled 2,161 patients (7,
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19-29). All patients that completed the inclusion criteria undergone
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Finally, twelve
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ACCEPTED MANUSCRIPT assessment following both RIPASA and Alvarado diagnostic tests. Table 1
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shows the main characteristics of the studies involved in the present meta-
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analysis. In addition, Table 2 refers to the demographic data of the patients
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that took place in our study, as well as other possible diagnoses that
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confirmed post-operatively. In addition, it presents other means that helped
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the diagnostic procedure (CT, U/S) other than surgery and histopathologic
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analysis, which provided the final diagnostic confirmation in all studies.
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Finally, Table 3 present the statistical parameters of the two tests, which our
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further analysis was based on.
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Quality assessment
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After the quality assessment of the included studies, according to QUADAS-2
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tool, 25% of the studies present a low risk of bias during the patient selection
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process, 50% of the studies present a low risk of bias relative to the index
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test, 15% of the studies have a low risk of bias relative to the reference
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standard and 45% of the studies present a low risk of bias associated with
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timing and flow (Figure 2). In addition, 75% of the included studies present low
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applicability concerns during the patient selection process, 80% of the studies
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have low applicability concerns about the index test and 25% of the studies
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present low applicability concerns correlated to the reference standard (Figure
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2).
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Outcomes
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The sensitivity of RIPASA score among the included studies was 94% (95%
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CI, 92% to 95%) (Fig. 3a). On the other hand, the specificity of RIPASA score
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was 55% (95% CI, 51% to 55%) (Fig. 3b). In addition, the area under the Roc
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Curve (AUC) was 0.9431 for the RIPASA score (Fig. 3c). Finally, the
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ACCEPTED MANUSCRIPT diagnostic Odds Ratio for the RIPASA score was 24.66 (95% CI, 8.06 to
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75.43) (Fig. 3d).
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The sensitivity of Alvarado score was 69% (95% CI, 67% to 71%) among the
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included studies (Fig. 4a). The specificity of the same test was 77% (95% CI,
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74% to 80%) (Fig. 4b). Moreover, the AUC for the Alvarado test was found to
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be 0.7944 (Fig. 4c). Finally, the diagnostic Odds Ratio of the Alvarado test
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was 7.99 (95% CI, 4.75 to 13.43) (Fig. 4d).
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Discussion
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Acute appendicitis is the most frequent cause of abdominal pain, excluding
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the cases, where no cause will be identified (30). Most of the surgeons, at
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some point of their practice, will face an important dilemma, between
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performing an unnecessary appendectomy and delaying one, requesting
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further diagnostic tests and finally operating when perforation occurs. Our
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study revealed that the RIPASA score has a very high sensitivity but low
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specificity, lower than the Alvarado one. On the other hand, the Alvarado
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system presents a low sensitivity. Moreover, the RIPASA presents a higher
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diagnostic Odds Ratio and a greater AUC. Overall, both systems can help the
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physicians diagnose acute appendicitis, but the RIPASA one is more sensitive
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and provides better statistical parameters than the Alvarado one.
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A wide range of diagnostic tests, such as CT scan and ultrasonography, are
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today available and present high sensitivity and specificity rates, although
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their use is importantly limited by different factors, such as the prompt
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availability, the costs, the ionizing radiation risk of developing cancer, the
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national guidelines and the common sense among healthcare professionals
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ACCEPTED MANUSCRIPT that an equivocal scan has nothing to offer, which would change the patient’s
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management (31). On the other hand, identifying a normal appendix during
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the laparoscopy, carries the risks of an operation under general anesthesia,
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the overall cost is high and the surgeon will face again a dilemma between
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performing or not an appendectomy. At the end of the day most surgeons will
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remove the appendix, making all the diagnostic work up at this stage looking
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not very useful. The fact that the complications rate is the same irrespective of
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the inflammation or not of the appendix, complicates further the patient’s
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management and makes the implementation of a prediction scoring system
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necessary (32). Different clinical diagnostic scoring systems have been
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proposed in the past, the last one by Sammalkorpi et al. (32), but the RIPASA
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followed the Alvarado Score, as the most frequently used and studied. The
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Alvarado scoring system has been found in a recent study to have a low
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negative appendectomy rate of 18.9%, comparing to Izbicki and Christian
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scoring systems (33). Alvarado and RIPASA are accurate, simple rapid,
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reliable and of low cost.
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The main advantage of our study is that it deals with a very common medical
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emergency, whose incidence is very high in all age groups and the diagnosis
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is very simple, despite the extremely serious complications that may occur to
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the misdiagnosed cases. These complications would be eliminated by the
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accurate and precise diagnosis, which the present study attribute to.
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Furthermore, our study focuses on two scoring systems that could be
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available to every physician even at the most remote health units and require
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very low cost to perform. The extensive search of the literature and the
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collection of all the available studies that were relative to the subject of our
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ACCEPTED MANUSCRIPT meta-analysis led to precise and useful conclusions, that could directly apply
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to the clinical practice. On the other hand, the two scoring systems that our
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study refers to are mainly based on the clinical presentation, and that fact
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makes the diagnosis difficult for some groups of patients, such as the elderly,
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the diabetics and the children. In addition, very few of the studies included in
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our meta-analysis have been originated in western health systems, such us
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Western Europe or America; the explanation of that is the overuse of
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electronic diagnostic means in such health systems, like ultrasound and CT.
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Another disadvantage of our study is that it does not compare the two scoring
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systems with other diagnostic tests, like CT scan or ultrasonography, due to
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lack of relevant studies from the literature. Finally, the two scoring systems
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that are included in our study use a wide number of criteria, which require
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accurate recall of the ranges and the point system, a fact that may cause
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confusions and wrong diagnoses at the very noisy and messy environment of
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the emergency rooms.
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An ideal prediction tool would aid to avoid unnecessary operations, and
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missing out real appendicitis which finally perforates, keeping low the negative
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appendicectomy rate, the missing out of appendiceal perforations and the
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possibility of perforation in case of conservative treatment. In addition, since
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the incidence of acute appendicitis depends on the sex, future studies should
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provide stratified data according to sex, in order a subgroup analysis to
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become possible and a correlation between the diagnostic value of each
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scoring system and the sex of each patient to be investigated. In fact, we are
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still far from having an ideal scoring system and definitely more studies with
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strict implementation of a scoring system are necessary, in order to obtain
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ACCEPTED MANUSCRIPT more robust evidence. Comparing the available diagnostic tools, we conclude
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that RIPASA scoring system is more sensitive than Alvarado one, but the lack
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of high specificity for the RIPASA scoring system, forms the need of a
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supplementary mean to provide the accurate diagnosis, depending on the
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clinical case each time. In addition, the wide and safe use of both tests could
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be extremely crucial in health systems of developing countries, in which
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electronic diagnostic tests are not widely available, or in distant rural health
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units, where the available equipment limits the diagnostic potentials.
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Acknowledgements
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We would like to thank Dr. VP for his critical evaluation of the meta-analysis
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and his useful remarks during the writing of the present manuscript.
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25. Verma M, Chanchal K, Vashisht M, Goyal K, Yadav P. Comparison of Alvarado and RIPASA scoring systems in diagnosis of acute appendicitis paripex. Indian J Res. 2015;4(8):55-7. 26. Walczak DA, Pawełczak D, Żółtaszek A, Jaguścik R, Fałek W, Czerwińska M, et al. The Value of Scoring Systems for the Diagnosis of Acute Appendicitis. Polish Journal of Surgery. 2015;87(2):65-70. 27. Golden SK, Harringa JB, Pickhardt PJ, Ebinger A, Svenson JE, Zhao Y-Q, et al. Prospective evaluation of the ability of clinical scoring systems and physiciandetermined likelihood of appendicitis to obviate the need for CT. Emerg Med J. 2016:emermed-2015-205301. 28. Singla A, Singla S, Singh M, Singla D. A comparison between modified Alvarado score and RIPASA score in the diagnosis of acute appendicitis. Updates in surgery. 2016;68(4):351-5. 29. Sinnet P, Chellappa PM, Kumar S, Ethirajulu R, Thambi S. Comparative study on the diagnostic accuracy of the RIPASA score over Alvarado score in the diagnosis of acute appendicitis. Journal of Evidence Based Medicine and Healthcare. 2016;3(80):4318-21. 30. Cervellin G, Mora R, Ticinesi A, Meschi T, Comelli I, Catena F, et al. Epidemiology and outcomes of acute abdominal pain in a large urban Emergency Department: retrospective analysis of 5,340 cases. Annals of translational medicine. 2016;4(19):362. 31. Ozkan S, Duman A, Durukan P, Yildirim A, Ozbakan O. The accuracy rate of Alvarado score, ultrasonography, and computerized tomography scan in the diagnosis of acute appendicitis in our center. Nigerian journal of clinical practice. 2014;17(4):413-8. 32. Shogilev DJ, Duus N, Odom SR, Shapiro NI. Diagnosing appendicitis: evidence-based review of the diagnostic approach in 2014. The western journal of emergency medicine. 2014;15(7):859-71.
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339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366
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Figure 1. The PRISMA flow chart of study selection.
Figure 2. The methodological assessment of the included studies according to the QUADAS-2 TOOL.
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0,2
0,4 0,6 Sensitivity
Pooled Sensitivity = 0,94 (0,92 to 0,95) Chi-square = 59,97; df = 11 (p = 0,0000) 1 Inconsistency (I-square) = 81,7 %
0,8
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Figure 3a. Pooled sensitivity of the RIPASA test. CI, confidence intervals.
375 376
EP
0,2
0,4 0,6 Specificity
0,8
1
0,81 0,62 0,85 0,25 0,28 0,91 0,74 0,11 0,09 0,65 0,80 0,36
(0,72 - 0,89) (0,52 - 0,71) (0,55 - 0,98) (0,01 - 0,81) (0,14 - 0,45) (0,71 - 0,99) (0,64 - 0,82) (0,00 - 0,48) (0,02 - 0,23) (0,41 - 0,85) (0,28 - 0,99) (0,29 - 0,43)
Pooled Specificity = 0,55 (0,51 to 0,59) Chi-square = 150,42; df = 11 (p = 0,0000) Inconsistency (I-square) = 92,7 %
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Specificity (95% CI)
2011; Chong 2012; Alnjadat 2012; Garcia 2012; Ferlengez 2013; Erdem 2014; Nanjundaiah 2015; Liu 2015; Verma 2015; Walczak 2016; Sinnet 2016: Singla 2016; Golden
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(0,93 - 1,00) (0,91 - 0,95) (0,81 - 0,97) (0,77 - 0,97) (0,95 - 1,00) (0,92 - 0,98) (0,91 - 0,98) (0,96 - 1,00) (0,76 - 0,95) (0,89 - 0,99) (0,85 - 0,99) (0,68 - 0,86)
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0,98 0,93 0,91 0,90 1,00 0,96 0,95 1,00 0,88 0,96 0,96 0,78
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2011; Chong 2012; Alnjadat 2012; Garcia 2012; Ferlengez 2013; Erdem 2014; Nanjundaiah 2015; Liu 2015; Verma 2015; Walczak 2016; Sinnet 2016: Singla 2016; Golden
Figure 3b. Pooled sensitivity of RIPASA test. CI, confidence intervals.
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SROC Curve
Symmetric SROC AUC = 0,9431 SE(AUC) = 0,0433 Q* = 0,8814 SE(Q*) = 0,0558
0,9
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Figure 3c. The area under the roc curve (AUC) for the RIPASA test.
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1 Diagnostic Odds Ratio
2011; Chong 2012; Alnjadat 2012; Garcia 2012; Ferlengez 2013; Erdem 2014; Nanjundaiah 2015; Liu 2015; Verma 2015; Walczak 2016; Sinnet 2016: Singla 2016; Golden
Diagnostic OR (95% CI) 215,47 (48,28 - 961,63) 22,05 (12,98 - 37,45) 57,20 (9,80 - 333,85) 3,08 (0,26 - 37,09) 61,42 (3,48 - 1.084,40) 252,86 (49,14 - 1.301,02) 55,24 (25,00 - 122,04) 32,29 (1,22 - 855,56) 0,67 (0,16 - 2,78) 39,46 (10,13 - 153,77) 86,00 (6,32 - 1.169,48) 1,93 (1,10 - 3,41)
Random Effects Model Pooled Diagnostic Odds Ratio = 24,66 (8,06 to 75,43) Cochran-Q = 112,74; df = 11 (p = 0,0000) 100,0 Inconsistency (I-square) = 90,2 % Tau-squared = 3,0828
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Figure 3d. The pooled diagnostic odds ratio for the RIPASA test.
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Figure 4a. The pooled sensitivity of the Alvarado test. CI, confidence intervals.
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Figure 4b. The pooled specificity of the Alvarado test. CI, confidence intervals.
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SROC Curve
Symmetric SROC AUC = 0,7944 SE(AUC) = 0,0265 Q* = 0,7310 SE(Q*) = 0,0229
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Figure 4c. The area under the roc curve (AUC) for the Alvarado test.
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Figure 4d. The pooled diagnostic odds ratio for the Alvarado test.
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Table 1. Study characteristics No of patients
Inclusion criteria
Exclusion criteria
2011; Chong
Prospective
192
Patients of all age groups presenting with RIF pain and suspicion of AA
2012; Alnjadat
Prospective
600
2012; Garcia
Prospective
70
2012; Ferlengez 2013; Erdem
Prospective
45
All patients >14 years old who underwent appendectomy Patients with abdominal pain suggesting AA N/A
Patients presenting with non-RIF pain and those who had been previously admitted for other complaints but subsequently developed RIF pain during their admission episodes N/A
Prospective
113
2014; Nanjundaiah 2015; Liu
Prospective
206
Retrospective cohort
297
Patients eligible to calculate RIPASA and Alvarado scores + patients with abdominal pain
2015; Verma
Prospective
100
Prospective Prospective
92 109
Patients of all age groups with RIF pain suspected to have AA N/A All patients with RIF pain, vomiting and fever. All patients presenting with RIF pain
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Patients admitted at the hospital due to suspected AA All patients with RIF pain
N/A
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Children <15 years old, pregnant women, patients with RIF mass, h/x urolithiasis, h/x PID Children (<18 years old), pregnant female patients, patients allergic to iodinated contrast material, cases of AA with appendectomy performed >24 h following CT examination N/A
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N/A <12years old, complications of AA (appendicular mass and malignancy, perforated appendix, elective appendectomy) 2016; Singla Prospective 50 Multiple co-morbid diseases, coagulation disorders, adverse anesthetic history, suspected/proven malignancy 2016; Golden Prospective 287 Patients > 11 years old and a CT Patients who were incarcerated, pregnant, post-appendectomy, unable to ordered to evaluate for appendicitis. have intravenous contrast, unable to speak or read English, or who lacked capacity to provide informed consent/assent were excluded. Table 1. The characteristics of the studies that were included in the present meta-analysis. N/A, data were not available; RIF, right iliac fossa; AA, acute appendicitis; PID, pelvic inflammatory disease 2015; Walczak 2016; Sinnet
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Mal e 92
Sex Femal e 100
Confirmed AA Histologically 101
Other Diagnoses
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Table 2. Patients’ demographics Age
25,1 ± 12,7
2012; Alnjadat
360
240
498
102 NA. Mesenteric lymphadenitis (3), Ruptured ovarian cyst (4), Ectopic pregnancy (4), Crohn’s disease (3), Cecal tumors (3)
36 27
34 18
57 41
N/A N/A
2013; Erdem
Mean: 26,52 26,15 (M) 27,08 (F) 33,8 30,64+12,09 30,2 ± 10,1
62
51
77
N/A
2014; Nanjundaiah 2015; Liu
27,82 ± 9,262 47,9 ± 17,6
127
79
184
Operated: Ruptured Ovarian cyst (3) IBD (2), Carcinoid tumor (1) Non-operated: Urinary system disease (8), Gastroenteritis (4), Mesenteric lymphadenitis (1), IND (1), Gynecologic problem (1) N/A
158
139
187
Yes
2015; Verma
28,10 ± 10,887 38
67
33
91
Crohn’s disease (2) Gastrointestinal perforation (3) Inflammation of caecum and/or ascending colon (9) Adhesive ileus (5) Intussusception (2) Volvulus (4) Right ureter tumor (3) Right ureter calculus (8) Right accessory tumor (12) Right pelvic endometrioma (2) Uterine myoma (3) Appendiceal tumor (3) Gastrointestinal tumor (44) N/A
46
46
N/A (US done) N/A
N/A N/A
N/A
N/A
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2011; Chong
2012; Garcia 2012; Ferlengez
Normal appendix (23), periappendicitis (7)
Performed CT
Mesenteric lymphadenitis (6), Ruptured Ovarian cyst (2), extra-uterine pregnancy (1), acute No pancreatitis (1), necrotic omental fragment (1) 2016; Sinnet 28 40 69 89 N/A N/A 2016; Singla 25,74 32 18 45 N/A N/A 2016; Golden 33 ± 15,2 115 172 94 N/A Yes Table 2. The characteristics of the patients that were included in the present meta-analysis and other diagnoses that were confirmed post-operatively. Data are mean ± SD or median (range) unless otherwise specified. N/A, data were not available; M, male; F, female. Age in years. 2015; Walczak
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Table 3. Diagnostic values of the scoring tests
2013; Erdem 2014; Nanjundaiah 2015; Liu 2015; Verma 2015; Walczak 2016; Sinnet 2016; Singla 2016; Golden
85,34% vs 86,25% 92,2% vs 92% 96,3% vs 92,7% Ν/Α
97,37% vs 71,43% 64,9% vs 34,8% 68,8% vs 60% Ν/Α
28% vs 75%
75% vs 88%
96,2% vs 58,9% 95,2% vs 63,1% 100% vs 82,42% 88% vs 85%
90,5% vs 85,7% 73,6% vs 80,9% 11,11% vs 44,44% 9% vs 16%
98,9% vs 97,3% N/A
100% vs 66% 73,1% vs 19,1% N/A
91,92% vs 93,75% 68% vs 74%
95,51% vs 65,16% 95,6% vs 53,3% 78% vs 61%
65% vs 90%
92,39% vs 96,67% 97,7% vs 100% 39% vs 53%
80% vs 100% 36% vs 74%
AUC
PLR
NLR
N/A
N/A
15,7% vs 18,3%
0,9183 vs 0,8651 0,9149 vs 0,7432 0,93 vs 0,89
Ν/Α
Ν/Α
2,4368% vs 2,0880% 5,93% vs 2.908% Ν/Α
0,1105% vs 0,4065% 10,4% vs 15,2% Ν/Α
77% vs 80%
25% vs 12%
N/A
N/A
96,2% vs 58,9%
N/A
N/A
N/A
87,2% vs 69,7%
N/A
0,857 vs 0,818 (?) 0,982 vs 0,849 N/A
N/A
N/A
100% vs 20% 20% vs 29%
92% vs 79%
8,1% vs 6,3%
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
76,47% vs 36,73% 66,7% vs 19,2% 76% vs 79%
89,9% vs 69,73% 94% vs 58%
7,61% vs 3,33%
N/A
N/A
N/A
N/A
N/A
N/A
0,943 vs 0,862 0,960 vs 0,580 0,67 vs 0,0,72
130% vs 220%
50% vs 60%
Ν/Α
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81.32% vs 87,91% 61,8% vs 68,6% 84,6% vs 69,2% 25% vs 75%
Negative appendicitis rate 14,7% vs 13,8% 7,8% vs 8%
SC
98,02% vs 68,32% 93,2% vs 73,7% 91,2% vs 89,5% 90,2% vs 34,1% 100% VS 82 %
Diagnostic accuracy 91,83% vs 86,51% 91,5% vs 74,3%
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NPV
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PPV
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2012; Alnjadat
Specificity
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2011; Chong
Sensitivity
2% vs 0%
Table 3. The diagnostic parameters of the two scoring tests (RIPASA vs Alvarado) among the included studies. N/A, data were not available; PPV, positive predictive value; NPV, negative predictive value; AUC, area under the roc-curve; PLR, positive likelihood ratio; NLR, negative likelihood ratio.
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RIPASA test had greater sensitivity than Alvarado test
•
Alvarado test had greater specificity than RIPASA test
•
RIPASA test presented greater Area Under the Roc Curve (AUC) than Alvaradi test
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PRISMA 2009 Checklist Section/topic
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# Checklist item
Title
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TITLE 1
Identify the report as a systematic review, meta-analysis, or both.
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Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.
3
Rationale
3
Describe the rationale for the review in the context of what is already known.
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Objectives
4
Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).
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Protocol and registration
5
Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
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Eligibility criteria
6
Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.
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Information sources
7
Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.
5
Search
8
Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.
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Study selection
9
State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
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Structured summary
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Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
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Data items
11
List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
6
Risk of bias in individual studies
12
Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
6
Summary measures
13
State the principal summary measures (e.g., risk ratio, difference in means).
7
Synthesis of results
14
Describe the methods of handling data and combining results of studies, if done, including measures of consistency 2 (e.g., I ) for each meta-analysis.
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PRISMA 2009 Checklist Page 1 of 2
Reported on page #
# Checklist item
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Section/topic Risk of bias across studies
15
Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
6
Additional analyses
16
Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
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Study selection
17
Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
Study characteristics
18
For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
8
Risk of bias within studies
19
Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).
9
Results of individual studies
20
For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
9
Synthesis of results
21
Present results of each meta-analysis done, including confidence intervals and measures of consistency.
9
Risk of bias across studies
22
Present results of any assessment of risk of bias across studies (see Item 15).
9
Additional analysis
23
Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]).
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Summary of evidence
24
Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).
11
Limitations
25
Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).
11
Conclusions
26
Provide a general interpretation of the results in the context of other evidence, and implications for future research.
12
27
Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.
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FUNDING Funding
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From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097. doi:10.1371/journal.pmed1000097
For more information, visit: www.prisma-statement.org. Page 2 of 2