Institutional Information Systems Research Articles

Circulation of DENV-3 Genotype 3 during 2017 to 2018 in Delhi: A Single-Center Hospital-Based Study.

Introduction Delhi is hyperendemic for dengue virus (DENV) where all the four DENV have previously been reported. A constant vigilance of circulating DENV serotypes is important in surveillance, since the introduction of a new variant to areas affected by preexisting serotypes constitutes a risk factor for dengue hemorrhagic fever and dengue shock syndrome. Objectives This retrospective study was performed with an objective to determine the circulating serotype and genotype of DENV in acute phase blood samples of patients who have reported to a tertiary liver care hospital in New Delhi during the last 2 years (2017–2018). Methods The data of clinician-initiated testing for dengue nonstructural protein 1 (NS1) antigen (Ag) was searched in the institutional hospital information system. The serum sample of dengue NS1 Ag-positive cases confirmed by enzyme-linked immunosorbent assay (ELISA; PANBIO, Gyeonggi-do, ROK) and a fever duration of less than 5 days were retrieved from the laboratory archive. The DENV serotyping on these sample was performed by reverse transcriptase polymerase chain reaction (RT-PCR). Sequencing and phylogenetic analysis was done for the capsid premembrane (CprM) region to determine the genotype. Results A total of 440 acute-phase samples were received. Twenty one (4.77%) were positive for dengue NS1 Ag with a mean age of 35.1 years and male-to-female ratio of 1.1:1. Eight cases (38.09%) were positive by dengue RT-PCR and all belonged to DENV-3 serotypes. Phylogenetic tree analysis revealed DENV-3 clustered to genotype III with 100% homology with 2008 Indian subcontinent strain. Conclusion This study revealed circulation of DENV-3, genotype III in Delhi from 2017 to 2018, similar to the 2008 viral type. Virological surveillance is an important exercise to be done for viral infections with public threat and outbreak potential.

Staged reflexive artificial intelligence driven testing algorithms for early diagnosis of pituitary disorders

BackgroundSellar masses (SM) frequently present with insidious hormonal dysfunction. We previously showed that, by utilizing a combined reflex/reflecting approach involving a laboratory clinician (LC) on common endocrine test results requested by non-specialists, and subsequently adding further warranted tests, previously undiagnosed pituitary disorders can be identified. However, manually employing these strategies by an LC is not feasible for wider screening of pituitary disorders. ObjectiveThe aim of this study was to compare the accuracy and financial impact of an Artificial Intelligence (AI) based, fully computerized reflex protocol with manual reflex/reflective intervention protocol led by an LC. MethodsWe developed a proof-of-concept AI-based framework to fully computerize multi-stage reflex testing protocols for pituitary dysfunction using automated reasoning methods. We compared the efficacy of this AI-based protocol with a reflex/reflective protocol based on manually curated retrospective data in identifying pituitary dysfunction based on 12 months of laboratory testing. ResultsThe AI-based reflex protocol, as compared with the manual protocol, would have identified laboratory tests for add-on that either directly matched or included all manual add-on tests in 92% of cases, and recommended a similar specialist referral in 90% of the cases. The AI-based protocol would have issued 2.8 times the total number of manual add-on laboratory tests at an 85% lower operation cost than the manual protocol when considering marginal test costs, technical staff and specialist salary. Conclusion/DiscussionOur AI-based reflex protocol can successfully identify patients with pituitary dysfunction, with lower estimated laboratory cost. Future research will focus on enhancing the protocol’s accuracy and incorporating the AI-based reflex protocol into institutional laboratory and hospital information systems for the detection of undiagnosed pituitary disorders.

Architecture of a maturity model for information systems in higher education institutions: multiple case study for dimensions identification

Higher education institutions (HEIs) are complex and dynamic organizations in terms of information management, forcing their information systems to respond to enormous challenges and threats. In order to evaluate the HEIs’ information systems, we propose the development of a maturity model capable of supporting the role of HEI’s managers, as well as accreditation agencies, in the assessment of the maturity of these systems, thus, promoting continuous improvement. In this paper, we present and discuss our proposal for an architecture of the maturity model being developed. This one is based on a two-dimensional architecture composed of vertical and horizontal dimensions. We selected a multi-case study approach, based on five Portuguese HEIs, and reviewed the literature to identify the dimensions. This case study was supported by interviews with experts from the selected HEI. The results of this research work were both encouraging and promising amongst the interviewed experts, revealing a high level of acceptance of the general model architecture, as well as positive expectations about its usefulness in the future. The development of our maturity model is carried out by following a formal methodology specially designed to support the construction of this type of model.

Cloud Computing-Based Medical Health Monitoring IoT System Design

With the continuous improvement of the national medical system, health monitoring combined with cloud computing and Internet of Things has become a concern. This study mainly discusses the design of the medical health monitoring IoT system based on cloud computing. From the user to the health service provider, there are three devices: sensor terminal, gateway terminal, and service platform. The sensor terminal is used to measure physiological indicators, such as blood pressure, electrocardiogram, blood oxygen saturation, heart rate, and other physiological indicators; the gateway terminal is used to link the sensor terminal to receive physiological indicators and forward them to the business platform; the gateway is also used to receive health information and other instructions issued by the server. In the community service mode, users can be divided into groups according to the community and region, and the corresponding service doctors and agent customer service personnel (nurses) can be assigned. Users can collect personal physiological indicators at home or outside through the medical terminal. These indicators and information are transmitted to the background health platform system through the mobile GSM-TD communication network. Users can also view their own historical health records and opinions of health consultants through the web/WAP website. Through the integration ability of the health cloud platform, relying on the interconnection with HIS, LIS, and other information systems of professional medical institutions, we jointly operate special value-added services, such as appointment registration, maternal and child healthcare, and medical communication (doctor-patient interaction), so that users can enjoy the remote service and guidance of professional medical institutions by subscribing to health value-added services. The CPU utilization rate is 40%, the internal utilization rate is 7.44 G, the memory utilization rate is 11.8%, and the network bandwidth is 591.87 M. During the whole test process, the indicators are stable, and there are no restart, crash, and other phenomena, so the system performance meets the design requirements.

A relevant document search system model using word2vec approaches

USU Repository is an institutional digital information system provided by Universitas Sumatera Utara (USU) that preserves and distributes academic papers, such as thesis and dissertation, from all departments in USU. A search box is provided to help search relevant topics from this repository. However, sometimes the search results returned were irrelevant and did not satisfy the user’s expectations. One of the causes for this situation is that the search engine could not perform optimally, particularly if the query were long and complicated. One approach that can be used to solve the problem is using semantic search. Semantic search is an information retrieval process from a sentence that involves understanding the results returned by natural language processing. In light of this approach, this paper aimed to propose a semantic search to seek the relevance between the user’s input query and academic papers returned as search results. This study implemented word2vec method in converting sentences into vectors. This study indicated average precision scores for small datasets as 46% and 73% for larger datasets.

The value of computed tomography in assessing the risk of death in COVID-19 patients presenting to the emergency room.

ObjectiveThe aims of this study were to develop a multiparametric prognostic model for death in COVID-19 patients and to assess the incremental value of CT disease extension over clinical parameters.MethodsConsecutive patients who presented to all five of the emergency rooms of the Reggio Emilia province between February 27 and March 23, 2020, for suspected COVID-19, underwent chest CT, and had a positive swab within 10 days were included in this retrospective study. Age, sex, comorbidities, days from symptom onset, and laboratory data were retrieved from institutional information systems. CT disease extension was visually graded as < 20%, 20–39%, 40–59%, or ≥ 60%. The association between clinical and CT variables with death was estimated with univariable and multivariable Cox proportional hazards models; model performance was assessed using k-fold cross-validation for the area under the ROC curve (cvAUC).ResultsOf the 866 included patients (median age 59.8, women 39.2%), 93 (10.74%) died. Clinical variables significantly associated with death in multivariable model were age, male sex, HDL cholesterol, dementia, heart failure, vascular diseases, time from symptom onset, neutrophils, LDH, and oxygen saturation level. CT disease extension was also independently associated with death (HR = 7.56, 95% CI = 3.49; 16.38 for ≥ 60% extension). cvAUCs were 0.927 (bootstrap bias-corrected 95% CI = 0.899–0.947) for the clinical model and 0.936 (bootstrap bias-corrected 95% CI = 0.912–0.953) when adding CT extension.ConclusionsA prognostic model based on clinical variables is highly accurate in predicting death in COVID-19 patients. Adding CT disease extension to the model scarcely improves its accuracy.Key Points • Early identification of COVID-19 patients at higher risk of disease progression and death is crucial; the role of CT scan in defining prognosis is unclear. • A clinical model based on age, sex, comorbidities, days from symptom onset, and laboratory results was highly accurate in predicting death in COVID-19 patients presenting to the emergency room. • Disease extension assessed with CT was independently associated with death when added to the model but did not produce a valuable increase in accuracy. Supplementary InformationThe online version contains supplementary material available at 10.1007/s00330-021-07993-9.

Fraud Reporting Portal Is Easy And Useful?

The case of fraud is currently a hot topic, according to ACFE in 2018 the rate of fraud in the education sector in the Asia-Pacific region is reached five percent. There are several ways to detect fraud in order to overcome or minimize the occurrence of fraud, one of which is whistleblowing. Based on the ACFE survey in 2020, shows that currently, the form of fraud reporting media tends to be online or electronic. This research aims to explore the ease of use, usefulness, and importance of fraud reporting information systems in educational institutions using the TAM theory. This research method is descriptive qualitative. The results showed that the number of reports submitted to the fraud reporting portal was not driven by the ease and usefulness of the reporting portal service. The results of this study, apart from being able to add insight and literature, can also be used as material for consideration in making improvements related to the use of fraud reporting information systems, especially in educational institutions.

Ground-glass hepatocellular inclusions are associated with polypharmacy

Ground-glass (GG) hepatocytes are classically associated with chronic hepatitis B (HBV) infection, storage disorders, or cyanamide therapy. In a subset of cases, an exact etiology cannot be identified. In this study, we sought to characterize the clinical, histological, and ultrastructural findings associated with HBV-negative GG hepatocytes. Our institutional laboratory information system was searched from 2000 to 2019 for all cases of ground-glass hepatocytes. Ten liver biopsies with GG hepatocellular inclusions and negative HBV serology, no known history of storage disorders, or cyanamide therapy were reviewed. Half of the patients had history of organ transplantation and/or malignancy. These patients took on average 8.1 medications (range: 3–14) with the most common medications being immunosuppressive and health supplements. Histologically, GG hepatocytes show either peri-portal or centrizonal distribution. The inclusions are PAS-positive and diastase sensitive. Electron microscopy showed intracytoplasmic granular inclusions with low electron density, consistent with unstructured glycogen. In summary, GG hepatocytes are a rare finding in liver biopsies, but are more common in patients with hepatitis B. They can also be seen in HBV-negative patients who have polypharmacy. In these cases, they are the result of unstructured glycogen accumulation putatively due to altered cell metabolism.

Prediction of Student Performance Using Rough Set Theory And Backpropagation Neural Networks

With the rise of web-based education systems and the increased use of information systems in education institutions, the amount of data recorded on student performance and behavior has increased exponentially. Thus, bringing about a large number of contributions to the field of educational research, which in itself contributed to the further evolution off the field in the last two decades alone, with terms such as Educational Data Mining (EDM), Learning Analytics, Data-driven Education, Teaching Analytics and others being added to the literature. In this paper, we evaluate the usefulness of a model using Rough Set Theory (RST) and Backpropagation Neural Network (BPNN) in effectively predicting the students’ overall performance. The dataset used consists of 10 different attributes and one decision factor belonging to 53 students collected from a language course which administers in-person education with the aid of an online platform for assignments. RST was implemented in order to reduce the number of attributes used as input in the neural network and the BPNN made an accurate prediction using only 5 of the initial attributes. Thus outperforming a model based solely on BPNN used on the original dataset and reducing computational costs.

Injury incidence and patterns associated with electric scooter accidents in a major metropolitan city

PurposeDespite increased use of e-scooters globally, actionable data around injury incidence and patterns associated with e-scooter accidents are limited. This study aimed to determine the prevalence of imaging exams, injury incidence, and patterns related to e-scooter injuries, with the hope of guiding an appropriate policy response. MethodsThis was a retrospective observational study of imaging exams ordered for injuries related to e-scooters seen in an Emergency Department (ED) setting within our health system from September 2018 through December 2019. Our institutional Radiology Information System (RIS) was searched for the presence of the word “scooter.” Manual query of search results was conducted in the electronic medical record (EMR) and only studies confirmed to be related to e-scooters were included. ResultsA total of 477 radiologic studies performed on 192 unique patients were confirmed to be performed for injuries related to e-scooters. The median patient age was 28 years and 58.3% were male. One hundred forty patients (72.9%) had injuries identified on imaging, with an overall exam positivity rate of 44.4%. The most common injuries were soft tissue and musculoskeletal in nature. Over half (51.9%) of the entries with the keyword “scooter” were excluded because of lack of EMR specificity regarding scooter type. ConclusionWhile this study showed that injuries following e-scooter accidents are common and frequently involve the face and extremities, it is limited by lack of documentation in the EMR. Further research with a standardized documentation protocol will be needed to better understand injuries patterns following e-scooter accidents.

Racial Disparities in Sustaining Breastfeeding in a Baby-Friendly Designated Southeastern United States Hospital: An Opportunity to Investigate Systemic Racism.

Background: Racial disparities in breastfeeding rates persist in the United States with Black women having the lowest rates of initiation and continuation. A literature review attributes this to many factors-historical roles, cultural norms, lack of social support, and systemic racism in the health care and lactation support system. The Baby-Friendly Hospital Initiative (BFHI) is an evidence-based program to increase breastfeeding through standardized protocols, and, in a Southeastern U.S. academic center, it was associated with increased breastfeeding, but the effect on racial disparities in breastfeeding was unknown. Methods: Through an institutional Perinatal Information Systems database, breastfeeding rates were compared before and after BFHI implementation. Breastfeeding initiation, sustained breastfeeding 24-hours before discharge, and patient demographics were assessed. Results: After BFHI implementation, mothers were overall 1.17 (95% confidence interval: 1.13-1.19) times more likely to initiate breastfeeding. For Black mothers, breastfeeding initiation increased significantly from 52% to 66%, but they were significantly less likely to sustain in-hospital breastfeeding compared to nonBlack mothers (69.4% versus 84.6%, p < 0.0001). Several demographic and medical comorbidities were significantly associated with failure to sustain breastfeeding to hospital discharge. When controlling for these factors, the racial disparity persisted. Conclusions: Since BFHI implementation, the racial gap in breastfeeding initiation decreased, but a significant disparity remained for sustained in-hospital breastfeeding. This study highlights the success of the BFHI program, but in the context of the current literature, also reveals the need for further work to ensure interventions are culturally competent and delivered equitably to support sustained breastfeeding for Black women.

Renal vein injuries: a 10-year, single institution experience with a rare injury following blunt abdominal trauma.

To determine the incidence, injury type, injury associations, and management of patients with renal vein injuries following trauma. This is a 10-year single-center retrospective observational study of patients with renal vein injuries identified on admission abdominopelvic CT following trauma. Our institutional trauma registry and radiology information system (RIS) was used to identify patients with renal vein injuries. The medical records and imaging exams were reviewed to determine venous injury type, associated injuries, management, and outcomes. Fifteen (15) patients with renal vein injuries (N = 9 right side) were identified out of 36,077 trauma evaluations, for an overall incidence of 0.042%. Eight (53.3%) were male with a mean age of 36.3years (range 9-67years) and a mean Injury Severity Score (ISS) of 32 (range 13-57). The most common imaging findings were pseudoaneurysm formation with or without intimal injury and intraluminal thrombus seen in 86.7% of the cohort. Twelve patients (80.0%) had other acute traumatic renal findings, most commonly an ipsilateral grade 4 or higher renal injury. Angiography was performed in 6 patients (40.0%), however no patients received renal vein specific endovascular evaluation, endovascular treatment, or surgical treatment of their renal vein injuries. Three patients were treated with long-term anticoagulation, of which one received an IVC filter. There were no known renal vein injury specific mortalities. Renal vein injuries are an extremely rare entity but can be detected on admission CT. The most common injury patterns include an intimal injury with intraluminal thrombus and pseudoaneurysm in combination with an intimal injury and intraluminal thrombus. Conservative, nonoperative management was successfully employed in all cases with no renal vein specific mortalities.

Security threats and methods of protecting websites of paid educational services of educational institutions

With the increase in the number of paid educational services of educational institutions, the percentage of fraudulent actions committed, both in relation to web services and in relation to service purchasers, also increases. Therefore, all participants in the process of banking transactions, i.e. the totality of operations that accompany remote interaction between the user and the payment system, must be protected from such actions, which determines the introduction and development of anti-fraud technologies used in the virtual space of the global Internet. Errors in the protection of websites, including websites of paid educational services of educational institutions, continue to be one of the most common shortcomings in ensuring the protection of information. Such errors, i.e. vulnerabilities, are exploited by attackers who attack websites in order to steal valuable information. It also increases the likelihood of subsequent penetration into the corporate information systems of educational institutions. Therefore, there is a need to use specialized tools and methods to protect web applications.

Биоинформатика и искусственный интеллект: геронтологические и гериатрические компоненты медико-социального сопровождения к активному здоровому долголетию

The “cognitive reserve” construct is a set of variables, including intelligence, education, and mental stimulation, that presumably allows the brain to adapt to underlying pathologies, supporting cognitive function despite underlying neural changes. Brain Homo Sapiens also points to resistance to neuropathological damage and can be defined as the ability to optimize or maximize performance through an effective set of neural networks and/or alternative cognitive strategies. Learning in childhood, the level of education and activities for adults — all this independently contributes to the formation of a cognitive reserve. The introduction of biocomputer nanoplatforms and modules consisting of small molecules, polymers, nucleic acids or proteins/peptides, nanoplatforms are programmed to detect and process external stimuli, such as magnetic fields or light, or internal stimuli, such as nucleic acids, enzymes or pH, using three different mechanisms: system assembly, system disassembly or system transformation. Current biocomputer nanoplatforms are invaluable for many applications, including medical diagnostics, biomedical imaging, environmental monitoring, and delivery of therapeutic drugs to target cell populations. The future implementation of systems biology and systems neurophysiology paradigms based on complex analysis of large and deep heterogeneous data sources will be crucial to achieve a deeper understanding of the pathophysiology of Alzheimer’s disease, using current brain-computer and artificial intelligence interface technologies, in order to increase information that can be extracted from preclinical and clinical indicators. Integration of different sources of information will allow researchers to obtain a new holistic picture of the pathophysiological process of the disease, which will cover from molecular changes to cognitive manifestations. The new competencies of psychoneuroimmunoendocrinology and psychoneuroimmunology play a strategic role in interdisciplinary science and interdisciplinary planning and decision-making. The introduction of multi-vector neurotechnologies of artificial intelligence and the principles of digital health care will contribute to the development of modern neuroscience and neuromarketing. Medical and social support for active healthy longevity is possible when synchronizing information systems of medical organizations and social institutions, introducing a single neurophysiological circuit and modern neurointerfaces, a combined and hybrid cluster in the diagnosis, treatment, prevention and rehabilitation of cognitive disorders and cognitive disorders. A key factor in medical and social support is the participation of interdisciplinary business employees and data processing specialists (their support, monitoring), as well as the availability of sufficient staff literacy in data management.

The implementation of e-government in indonesia

This conceptual paper's objectives describe how the utilization of technology and information systems in government institutions developing e-government can improve public service performance and quality. The development of information and technology helps humans and the organization to successfully their operation. The operational system more accurate, useful, and efficient. Most governmental bodies have a low-performance rate in matters of bureaucracy. To repair the quality of bureaucratic performance in government institutions, there is a need to introduce public transparency and accountability to increase the role of public control. The usage of modern technology and systems in government is known as e-government.

A UNIFORM INTERACTION MODEL OF EDUCATIONAL PROCESS AGENTS IN THE UNIFIED MANAGEMENT SYSTEM OF A HIGHER EDUCATION INSTITUTION

One of the most popular classes of educational systems is LMS - Learning Management System, which gives a possibility to implement support for the learning process through E-learning technology. However, such systems do not have sufficient functionality to automate other aspects of the activities of an educational institution. This situation has led to the fact that modern educational institutions are forced to use a whole set of different information systems, each of which solves a certain, strictly specialized range of tasks and complicates the effective use of automation. Thus, the aim of this research is to develop an approach to building a management system for a higher education institution based on a single hardware and software platform, which allows combining all areas of administrative and educational activities within a single system, as well as organizing the management of the educational process and monitoring of the quality of educational services. To achieve this goal, the paper addresses the task of creating a computer system for managing a higher education institution on the basis of a single, widely known platform LMS MOODLE. To accomplish this task, a unified model of interaction between the agents of the educational process has been proposed. This model makes it possible to complement the learning functions of the most popular platform with the solution of organizational tasks in managing a higher education institution and performance of workflow functions. The developed model of interaction between the agents of the educational process was used for processing the system of roles for the users of the system, which made it possible to expand the functionality of work with the database system, as well as to develop a computer based management system for an educational institution on the basis of a single platform. The proposed new technical solutions were introduced during the creation of information systems in such higher education institutions of Ukraine as Donbass State Technical University and Volodymyr Dahl East Ukrainian National University. In addition, the proposed solutions have been successfully applied to create information management systems for several general secondary schools in Lysychansk, Ukraine.

Oil war a brewin’: rubber suppliers to oil, gas sector likely to be hit by downturn

Academic Analytics enables an analysis of data that is very important for making decisions in the educational institutional environment, aggregating valuable information in the academic research activity and providing easy to use business intelligence tools. This article shows a proposal for creating an information system based on Academic Analytics, designing a model that is supported by Academic Analytics for the collection and analysis of data from the information systems of educational institutions. The idea that was conceived proposes a system that is capable of displaying statistics on the historical data of students and teachers taken over academic periods, with the purpose of gathering the information that the director, the teacher, and finally the student need for making decisions. The model was validated with information taken from students and teachers during the last five years, and the export format of the data was pdf, csv, and xls files. The findings allow us to state that it is extremely important to analyze the data that is in the information systems of the educational institutions for making decisions. After the validation of the model, it was established that it is a must for students to know the reports of their academic performance in order to carry out a process of self-evaluation, as well as for teachers to be able to see the results of the data obtained in order to carry out processes of self-evaluation, and adaptation of content and dynamics in the classrooms.

Systems change in UK HEIs: how do culture, management, users and systems align?

PurposeThe purpose of the study is to assess the implementation of integrated information systems in UK higher education institutions (HEIs) via multiple internal stakeholders.Design/methodology/approachThe approach analyses the implementation strategy of two HEIs and assesses the impact of new systems on working practices. This involves interviews with various stakeholder groups from the HEIs, capturing 35 interviews.FindingsResults indicate that growth of alternative power bases emerge within both HEIs, as well as new roles and responsibilities for administrative staff, and different working practices for academics. Varying levels of importance are given to people and culture, management support, user involvement and clarity of communication and systems' requirements at project pre-implementation, implementation and post-implementation stages.Practical implicationsThis study provides lessons of HEIs planning to undertake significant change by implementing integrated information systems. Challenges emerge around fit, complexity, training, communication and consultation. Benefits gained and emerging challenges show some commonality between the two case HEIs, pointing the way forward for other “large” (student number determined) HEIs embarking on similar change.Originality/valueThe UK HEI sector is experiencing major change emphasising cost reduction and operational efficiency. Understanding challenges relating to significant systems change in complex settings with varying stakeholder demands has considerable sectoral value.

Feasibility on the development of maternal and child cohorts, based on the maternal and child care network

Under the limitation of cross-sectional studies, more researchers are turning their attention to maternal and child cohort studies. However, some problems do exist in the traditional maternal and child cohort studies, if data is only gathered from the hospitals. The limitation would include the contents of research and the high rate of loss to follow-up. With the integration of different medical traits and the progress in big data, the development of maternal and child related cohorts, with characteristics of dynamic follow-up and data sharing, through combining the information and health service systems of different institutions, seem in urgent need. This paper aims to provide some basic achievements in conducting maternal and child cohorts that can serve the related health problems through full-life cycle, and provide new references on conducting cohort studies, aiming at special population or diseases.

Rectal stump management in inflammatory bowel disease: a cohort study, systematic review and proportional analysis of perioperative complications.

The aim of this study was to analyse local single-institution data and perform a systematic review of the literature to calculate precise risk estimates of rectal stump-related morbidity and mortality following subtotal colectomy in patients with inflammatory bowel disease (IBD), including Crohn's colitis, ulcerative colitis and indeterminate colitis. Institutional information systems were interrogated to obtain local patient data. A systematic review of MEDLINE and EMBASE was performed to identify relevant articles. Fixed-effects or random-effects meta-analysis of proportions was performed to calculate pooled incidence estimates, including local data. Sixty-one patients were included locally and all had their rectal stump closed intra-abdominally. Four patients (8.3%) had a rectal stump perforation and 30-day mortality was 0. Fourteen papers were included in our review alongside local data, with a total of 1330 patients included. Pooled mortality was 1.7% (95% confidence interval, CI 1.0-2.8), pooled incidence of pelvic abscess/sepsis, stump leak and wound infection was 5.7% (95% CI 4.4-7.3), 4.9% (95% CI 3.7-6.6) and 11.3% (95% CI 7.8-16), respectively. Subcutaneous placement of the stump was associated with the highest incidence of stump leak (12.6%, 95% CI 8.3-18.6), and closure of the stump with both staples and suture was associated with the highest incidence of pelvic abscess (11.1%, 95% CI 5.8-20.3). Mortality and the incidence of wound infection were similar across stump closure techniques. There was evidence suggesting considerable heterogeneity and publication bias among studies. This study provides estimates of morbidity associated with the rectal stump after subtotal colectomy for IBD. A closed intra-abdominal stump seems to be associated with the highest rate of pelvic abscess/sepsis. Further work in form of an international collaborative project would allow individual patient data analysis and identification of risk factors for complications.