Incidence of Appendicitis over Time: A Comparative Analysis of an Administrative Healthcare Database and a Pathology-Proven Appendicitis Registry

<div><p>Importance</p><p>At the turn of the 21^st century, studies evaluating the change in incidence of appendicitis over time have reported inconsistent findings.</p><p>Objectives</p><p>We compared the differences in the incidence of appendicitis derived from a pathology registry versus an administrative database in order to validate coding in administrative databases and establish temporal trends in the incidence of appendicitis.</p><p>Design</p><p>We conducted a population-based comparative cohort study to identify all individuals with appendicitis from 2000 to2008.</p><p>Setting & Participants</p><p>Two population-based data sources were used to identify cases of appendicitis: 1) a pathology registry (n = 8,822); and 2) a hospital discharge abstract database (n = 10,453).</p><p>Intervention & Main Outcome</p><p>The administrative database was compared to the pathology registry for the following <i>a priori</i> analyses: 1) to calculate the positive predictive value (PPV) of administrative codes; 2) to compare the annual incidence of appendicitis; and 3) to assess differences in temporal trends. Temporal trends were assessed using a generalized linear model that assumed a Poisson distribution and reported as an annual percent change (APC) with 95% confidence intervals (CI). Analyses were stratified by perforated and non-perforated appendicitis.</p><p>Results</p><p>The administrative database (PPV = 83.0%) overestimated the incidence of appendicitis (100.3 per 100,000) when compared to the pathology registry (84.2 per 100,000). Codes for perforated appendicitis were not reliable (PPV = 52.4%) leading to overestimation in the incidence of perforated appendicitis in the administrative database (34.8 per 100,000) as compared to the pathology registry (19.4 per 100,000). The incidence of appendicitis significantly increased over time in both the administrative database (APC = 2.1%; 95% CI: 1.3, 2.8) and pathology registry (APC = 4.1; 95% CI: 3.1, 5.0).</p><p>Conclusion & Relevance</p><p>The administrative database overestimated the incidence of appendicitis, particularly among perforated appendicitis. Therefore, studies utilizing administrative data to analyze perforated appendicitis should be interpreted cautiously.</p></div

Clinical characteristics of patients with appendicitis derived from a pathology-proven registry and from an administrative healthcare database.

<p>Clinical characteristics of patients with appendicitis derived from a pathology-proven registry and from an administrative healthcare database.</p

Comparative analysis in incidence and temporal trends between cohorts of appendicitis patients derived from a pathology-proven registry and an administrative healthcare database.

<p>Comparative analysis in incidence and temporal trends between cohorts of appendicitis patients derived from a pathology-proven registry and an administrative healthcare database.</p

Flow-chart of the study populations derived for the pathology proven registry and the administrative healthcare database.

<p>Flow-chart of the study populations derived for the pathology proven registry and the administrative healthcare database.</p

Positive predictive value of coding in the administrative healthcare database as compared to the pathology-proven registry stratified overtime.

<p>Positive predictive value of coding in the administrative healthcare database as compared to the pathology-proven registry stratified overtime.</p

Incidence of Appendicitis over Time: A Comparative Analysis of an Administrative Healthcare Database and a Pathology-Proven Appendicitis Registry - Fig 2

<p>Annual incidence of appendicitis stratified by perforated and non-perforated from cohorts derived by A) a pathology proven registry; and B) an administrative healthcare database.</p

Sarcopenia and myosteatosis are accompanied by distinct biological profiles in patients with pancreatic and periampullary adenocarcinomas

<div><p>Introduction</p><p>Pancreatic and periampullary adenocarcinomas are associated with abnormal body composition visible on CT scans, including low muscle mass (sarcopenia) and low muscle radiodensity due to fat infiltration in muscle (myosteatosis). The biological and clinical correlates to these features are poorly understood.</p><p>Methods</p><p>Clinical characteristics and outcomes were studied in 123 patients who underwent pancreaticoduodenectomy for pancreatic or non-pancreatic periampullary adenocarcinoma and who had available preoperative CT scans. In a subgroup of patients with pancreatic cancer (n = 29), <i>rectus abdominus</i> muscle mRNA expression was determined by cDNA microarray and in another subgroup (n = 29) ¹H-NMR spectroscopy and gas chromatography-mass spectrometry were used to characterize the serum metabolome.</p><p>Results</p><p>Muscle mass and radiodensity were not significantly correlated. Distinct groups were identified: sarcopenia (40.7%), myosteatosis (25.2%), both (11.4%). Fat distribution differed in these groups; sarcopenia associated with lower subcutaneous adipose tissue (P<0.0001) and myosteatosis associated with greater visceral adipose tissue (P<0.0001). Sarcopenia, myosteatosis and their combined presence associated with shorter survival, Log Rank P = 0.005, P = 0.06, and P = 0.002, respectively. In muscle, transcriptomic analysis suggested increased inflammation and decreased growth in sarcopenia and disrupted oxidative phosphorylation and lipid accumulation in myosteatosis. In the circulating metabolome, metabolites consistent with muscle catabolism associated with sarcopenia. Metabolites consistent with disordered carbohydrate metabolism were identified in both sarcopenia and myosteatosis.</p><p>Discussion</p><p>Muscle phenotypes differ clinically and biologically. Because these muscle phenotypes are linked to poor survival, it will be imperative to delineate their pathophysiologic mechanisms, including whether they are driven by variable tumor biology or host response.</p></div

Biological functions associated with differentially abundant genes for muscle radiodensity and sarcopenia.

<p>Biological functions associated with differentially abundant genes for muscle radiodensity and sarcopenia.</p

Kaplan-Meier plots.

<p>(A) Disease-free survival (DFS) as a function of sarcopenia. (B) Overall survival (OS) as a function of sarcopenia. (C) DFS as a function of myosteatosis. (D) OS as a function of myosteatosis. (E) DFS in individuals with both sarcopenia and myosteatosis. (F) OS in individuals with both sarcopenia and myosteatosis.</p

Metabolomic models that distinguish body composition phenotypes in pancreatic cancer patients.

<p>(A) OPLS-DA scores plots and metabolite lists for NMR and GC-MS metabolites: sarcopenia vs. no sarcopenia or myosteatosis. (B) OPLS-DA scores plots and metabolite lists for NMR and GC-MS metabolites: myosteatosis vs. no sarcopenia or myosteatosis. For the metabolite lists: metabolites in <b>bold</b> are shared in 1H-NMR spectroscopy and GC-MS datasets; metabolites in red have a VIP>1.</p