Importance of routine histopathological examination in appendectomy specimens

Abstract

Background: Acute appendicitis is the most common abdominal emergency. It is a clinical entity with an ongoing diagnostic challenge. Histopathological examinations are the gold standard for the final diagnosis, which has revealed much unusual, unexpected serious underlying pathology. This study is to analyze the histopathological patterns in appendectomy specimens and to establish the role and importance of histopathological examination in diagnosing various serious incidental pathologies. Materials and Methods: This is a retrospective study comprising of 181 patients, carried out at VMKVMCH, Department of Pathology, over a period of 2 years from September 2017 to August 2019. Clinical data of patients were collected for all the appendectomy specimens received at the pathology department and histopathology slides were reviewed. Results: A total of 181 cases were analyzed. Patients' age ranged from 3 to 77 years. The predominant appendectomy finding was acute appendicitis 86 cases (47.51%) followed by chronic appendicitis 58 cases (32.04%). Among the unusual findings, eosinophilic appendicitis was the commonest 4 cases (2.20%), mucocele, carcinoid and parasite 1 case (0.55%) each respectively. Conclusion: Although most of the cases were diagnosed as acute appendicitis, a few of the essential incidental pathologies were missed out pre-operatively and intra-operatively. Hence these serious incidental diagnoses undeniably support the fact that all appendectomy specimens should be sent routinely for histopathological examination, which is not followed in many hospitals in India.

Developing Concept Enriched Models for Big Data Processing Within the Medical Domain

“…Several recent studies have highlighted the growing challenges and importance of Big Data methodologiesandcloudinfrastructurefordataaggregation,knowledgemanagementandconsumption fromheterogeneousmediasourcesbeyondthemedicaldomain.Originatinginapplicationsformedia streamingofultra-highdefinitionvideo,securityforandfeatureextractionfromInternet-of-Things (IoT) networks in cloud computing contexts, and the application of soft computing to Big Data, thesestudieshaverelevanceaswellfordevelopingrobustcognitivecomputingarchitecturesforthe medicaldomain.AsPsannis,Stergiou,andGuptaobserve,"intelligentclouds"canbehelpfulfor compressing,storing,andprocessingstreamingmediaonaBigDatascale(2019).Moreover,another BigDatachallengeconsistsofthevastquantitiesofdatageneratedbynetworkedIoTdevices.These collectionsofnetworkedsensorspresentachallengefordevelopingefficient,sustainableandsecure cloudcomputinginfrastructureforBigDataprocessing,includingmonitoringpatienthealthmetrics (Stergiou,Psannis,Bupta,&Ishibashi,2018;Din,Paul,Ahmad,Gupta,&Rho,2018;Murugan, 2019).Furthermore,duetotheheterogeneityofBigDatasoftcomputingtechniqueswillbeessential (Gupta, Agrawal, Yamaguchi, Sheng 2018). Cognitive-based information retrieval systems will needtoleveragetextminingforbibliometricanalysistoextractgeographic,authorcollaborations, and topical summarization from published medical research (Hao, Chen, Li, & Yan, 2018;Alakashi,2019).Additionally,cognitivesystemswillneedtointerfacewithelectronichealthrecord managementsystemsforpatients (Ziebell,Albors-Garrigos,Schoeneberg,&Marin,2019).Thus, cognitivecomputingsystemsinthemedicaldomainwillneedtouseefficient,sustainablecloud-native architecturesandbecapableofaggregatingandsynthesizingstructuredandunstructuredtextual, AnotherapplicationhasbeencreatedusingIBMWatsonforpersonalizedmedicine.Theidea behindthissystemisthatthebestcancertreatmentistodetect,prevent,andtreatitbeforeitreaches advancedstages.However,notwopeopleorcancersarealike.Thecurrentprocessfortrialmatchingis conductedthroughclinicalcoordinatorswhosortthroughthousandsofpatientrecordsandmatchthe patientwithagivenprotocol.However,eachoneoftheseprotocolshas46requirementsonaverage andrangefromcontainingageneticmarkertoage,tumorstage,growth,andtreatmenthistory.No matterhowmuchofanexpertanyindividualis,thisbecomesahugetasktoconductwithoutadvanced computingcapabilities (Ahmed,Toor,O'Neil,&Friedland,2017).…”