Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Regressions for estimating muscle parameters in the thoracic and lumbar trunk for use in musculoskeletal modeling

Musculoskeletal modeling requires information on muscle parameters such as cross-sectional area (CSA) and moment arms. A variety of previous studies have reported muscle parameters in the trunk based on in vivo imaging, but there remain gaps in the available data as well as limitations in the generalizability of such data. Specifically, available trunk muscle CSA data is very limited for older adults, lacking entirely in the thoracic region. In addition, previous studies have made measurements in groups of healthy volunteers or hospital patients who may not be representative of the population in general. Finally, such studies have not reported data for the major muscles connecting the upper limb to the thoracic trunk. In this study, muscle morphology measurements were made for major muscles present in the trunk between vertebral levels T6 and L5 using quantitative computed tomography scans from a community-based sample of 100 men and women aged 36–87. We present regression equations to predict trunk muscle CSA and position relative to the vertebral body in the transverse plane from sex, age, height and weight at vertebral levels T6 to L5. Regressions were also developed for predicting anatomical CSA and muscle moment arms, which were estimated using literature data on muscle line of action. This work thus provides a resource for estimating muscle parameters in the general population for musculoskeletal modeling of the thoraco-lumbar trunk

Specimen size and porosity can introduce error into μCT-based tissue mineral density measurements. Trans 53rd Orthop Res Soc

The accurate measurement of tissue mineral density, ρ m , in specimens of unequal size or quantities of bone mineral using polychromatic μCT systems is important, since studies often compare samples with a range of sizes and bone densities. We assessed the influence of object size on μCT measurements of ρ m using (1) hydroxyapatite rods (HA), (2) precision-manufactured aluminum foams (AL) simulating trabecular bone structure, and (3) bovine cortical bone cubes (BCt). Two beam-hardening correction (BHC) algorithms, determined using a 200 and 1200 mg/cm 3 HA wedge phantom, were used to calculate ρ m of the HA and BCt. Introduction Measurement of equivalent bone tissue mineral density (ρ m ) using polychromatic planar radiography and computed tomography are established techniques whose precision, accuracy, and potential sources of error have been well studied [e.g., 1,2-6]. Polychromatic micro-computed (μCT) tomographic analyses of bone were originally focused only on structural assessments of trabecular and cortical bone tissue [7,8] and not measurements of ρ m . Recently, methods for the measurement of ρ m have been developed for polychromatic μCT and several studies have incorporated these techniques [9][10][11][12][13][14][15][16][17][18][19][20][21][22]. However, only a few published studies of the precision and accuracy of μCT-based equivalent ρ m have been performed to date [23][24][25][26], in contrast to the numerous studies completed for clinical [27][28][29][30][31][32][33][34][35][36][37][38]. The accuracy and precision of μCT-based measurements of ρ m can be affected by factors related to the scan settings, tissue samples, and scan artifacts. Recent studies have examined the influence of factors such as the X-ray tube voltage, current intensity, and sample dimensions [24,25,39,40]. Beam-hardening related artifacts such as streaking [41], dark banding [low attenuation spots between two higher density objects; [42][43][44]], cupping [26,45], as well as ring artifacts [41,46] can introduce errors in measured attenuation values. One topic of specific interest is the effect of sample dimensions or bone mass differences on the accurate measurement of ρ m since (1) object thickness (size) is known to impact linear X-ray attenuation independent of ρ m [1,42,44] and (2) a wide range of orthopedic and bone biology studies incorporate specimens of varying size or quantities of bone including animal models of osteoporosis (disease), bone biomechanics, bone tissue engineering, aging, and interspecies studies of bone structure and function [21,22,[47][48][49][50][51][52][53][54][55][56][57]. For polychromatic computed tomography X-ray systems, the measure

Appendicitis risk prediction models in children presenting with right iliac fossa pain (RIFT study): a prospective, multicentre validation study.

Background Acute appendicitis is the most common surgical emergency in children. Differentiation of acute appendicitis from conditions that do not require operative management can be challenging in children. This study aimed to identify the optimum risk prediction model to stratify acute appendicitis risk in children. Methods We did a rapid review to identify acute appendicitis risk prediction models. A prospective, multicentre cohort study was then done to evaluate performance of these models. Children (aged 5\u201315 years) presenting with acute right iliac fossa pain in the UK and Ireland were included. For each model, score cutoff thresholds were systematically varied to identify the best achievable specificity while maintaining a failure rate (ie, proportion of patients identified as low risk who had acute appendicitis) less than 5%. The normal appendicectomy rate was the proportion of resected appendixes found to be normal on histopathological examination. Findings 15 risk prediction models were identified that could be assessed. The cohort study enrolled 1827 children from 139 centres, of whom 630 (34\ub75%) underwent appendicectomy. The normal appendicectomy rate was 15\ub79% (100 of 630 patients). The Shera score was the best performing model, with an area under the curve of 0\ub784 (95% CI 0\ub782\u20130\ub786). Applying score cutoffs of 3 points or lower for children aged 5\u201310 years and girls aged 11\u201315 years, and 2 points or lower for boys aged 11\u201315 years, the failure rate was 3\ub73% (95% CI 2\ub70\u20135\ub72; 18 of 539 patients), specificity was 44\ub73% (95% CI 41\ub74\u201347\ub72; 521 of 1176), and positive predictive value was 41\ub74% (38\ub75\u201344\ub74; 463 of 1118). Positive predictive value for the Shera score with a cutoff of 6 points or lower (72\ub76%, 67\ub74\u201377\ub74) was similar to that of ultrasound scan (75\ub70%, 65\ub73\u201383\ub71). Interpretation The Shera score has the potential to identify a large group of children at low risk of acute appendicitis who could be considered for early discharge. Risk scoring does not identify children who should proceed directly to surgery. Medium-risk and high-risk children should undergo routine preoperative ultrasound imaging by operators trained to assess for acute appendicitis, and MRI or low-dose CT if uncertainty remains. Funding None