Frontiers in Medical Technology最新文献

{"title":"To lockdown or not to lockdown: Analysis of the EU lockdown performance vs. COVID-19 outbreak.","authors":"Emanuele Lindo Secco, Stefano Conte","doi":"10.3389/fmedt.2022.981620","DOIUrl":"10.3389/fmedt.2022.981620","url":null,"abstract":"<p><p>The worldwide COVID-19 outbreak has dramatically called for appropriate responses from governments. Scientists estimated both the basic reproduction number and the lethality of the virus. The former one depends on several factors (environment and social behavior, virus characteristics, removal rate). In the absence of specific treatments (vaccine, drugs) for COVID-19 there was a limited capability to control the likelihood of transmission or the recovery rate. Therefore, to limit the expected exponential spread of the disease and to reduce its consequences, most national authorities have adopted containment strategies that are mostly focused on social distancing measures. In this context, we performed an analysis of the effects of government lockdown policies in 5 European Countries (France, Germany, Italy, Spain, United Kingdom). We used phone mobility data, published by Apple Inc. and Google, as an indirect measure of social distancing over time since we believe they represent a good approximation of actual changes in social behaviors. (i) The responsiveness of the governments in taking decisions. (ii) The coherence of the lockdown policy with changes in mobility data. (iii) The lockdown implementation performance in each country. (iv) The effects of social distancing on the epidemic evolution. These data were first analyzed in relation with the evolution of political recommendations and directives to both assess (i) responsiveness of governments in taking decisions and (ii) the implementation performance in each country. Subsequently, we used data made available by John Hopkins University in the attempt to compare changes in people behaviors with the evolution of COVID-19 epidemic (confirmed cases, new and cumulative) in each country in scope. Finally, we made an attempt to identify some key lockdown performance parameters in order to: (i) establish responsiveness, efficiency and effectiveness of the lockdown measures. (ii) model the latency occurring between the changes in social behaviors and the changes in growth rate of the disease.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"981620"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9634555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40669999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of artificial intelligence and precision oncology in Latin America.","authors":"Liliana Sussman,&nbsp;Juan Esteban Garcia-Robledo,&nbsp;Camila Ordóñez-Reyes,&nbsp;Yency Forero,&nbsp;Andrés F Mosquera,&nbsp;Alejandro Ruíz-Patiño,&nbsp;Diego F Chamorro,&nbsp;Andrés F Cardona","doi":"10.3389/fmedt.2022.1007822","DOIUrl":"https://doi.org/10.3389/fmedt.2022.1007822","url":null,"abstract":"<p><p>Next-generation medicine encompasses different concepts related to healthcare models and technological developments. In Latin America and the Caribbean, healthcare systems are quite different between countries, and cancer control is known to be insufficient and inefficient considering socioeconomically discrepancies. Despite advancements in knowledge about the biology of different oncological diseases, the disease remains a challenge in terms of diagnosis, treatment, and prognosis for clinicians and researchers. With the development of molecular biology, better diagnosis methods, and therapeutic tools in the last years, artificial intelligence (AI) has become important, because it could improve different clinical scenarios: predicting clinically relevant parameters, cancer diagnosis, cancer research, and accelerating the growth of personalized medicine. The incorporation of AI represents an important challenge in terms of diagnosis, treatment, and prognosis for clinicians and researchers in cancer care. Therefore, some studies about AI in Latin America and the Caribbean are being conducted with the aim to improve the performance of AI in those countries. This review introduces AI in cancer care in Latin America and the Caribbean, and the advantages and promising results that it has shown in this socio-demographic context.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"1007822"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9608820/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40656778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SARS-CoV-2 variants impact RBD conformational dynamics and ACE2 accessibility.","authors":"Mariana Valério, Luís Borges-Araújo, Manuel N Melo, Diana Lousa, Cláudio M Soares","doi":"10.3389/fmedt.2022.1009451","DOIUrl":"10.3389/fmedt.2022.1009451","url":null,"abstract":"<p><p>Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has killed over 6 million people and is having a devastating social and economic impact around the world. The rise of new variants of concern (VOCs) represents a difficult challenge due to the loss of vaccine and natural immunity, as well as increased transmissibility. All VOCs contain mutations in the spike glycoprotein, which mediates fusion between the viral and host cell membranes. The spike glycoprotein binds to angiotensin-converting enzyme 2 (ACE2) <i>via</i> its receptor binding domain (RBD) initiating the infection process. Attempting to understand the effect of RBD mutations in VOCs, a lot of attention has been given to the RBD-ACE2 interaction. However, this type of analysis ignores more indirect effects, such as the conformational dynamics of the RBD itself. Observing that some mutations occur in residues that are not in direct contact with ACE2, we hypothesized that they could affect the RBD conformational dynamics. To test this, we performed long atomistic (AA) molecular dynamics (MD) simulations to investigate the structural dynamics of <i>wt</i> RBD, and that of four VOCs (Alpha, Beta, Delta, and Omicron). Our results show that the <i>wt</i> RBD presents two distinct conformations: an \"open\" conformation where it is free to bind ACE2; and a \"closed\" conformation, where the RBM ridge blocks the binding surface. The Alpha and Beta variants shift the open/closed equilibrium towards the open conformation by roughly 20%, likely increasing ACE2 binding affinity. Simulations of the Delta and Omicron variants showed extreme results, with the closed conformation being rarely observed. The Delta variant also differed substantially from the other variants, alternating between the open conformation and an alternative \"reversed\" one, with a significantly changed orientation of the RBM ridge. This alternate conformation could provide a fitness advantage due to increased availability for ACE2 binding, and by aiding antibody escape through epitope occlusion. These results support the hypothesis that VOCs, and particularly the Omicron and Delta variants, impact RBD conformational dynamics in a direction that promotes efficient binding to ACE2 and, in the case of Delta, may assist antibody escape.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"1009451"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40677055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical decision support system using weakly-labeled lung CT scans.","authors":"Alejandro Murillo-González, David González, Laura Jaramillo, Carlos Galeano, Fabby Tavera, Marcia Mejía, Alejandro Hernández, David Restrepo Rivera, J G Paniagua, Leandro Ariza-Jiménez, José Julián Garcés Echeverri, Christian Andrés Diaz León, Diana Lucia Serna-Higuita, Wayner Barrios, Wiston Arrázola, Miguel Ángel Mejía, Sebastián Arango, Daniela Marín Ramírez, Emmanuel Salinas-Miranda, O L Quintero","doi":"10.3389/fmedt.2022.980735","DOIUrl":"10.3389/fmedt.2022.980735","url":null,"abstract":"<p><strong>Purpose: </strong>Determination and development of an effective set of models leveraging Artificial Intelligence techniques to generate a system able to support clinical practitioners working with COVID-19 patients. It involves a pipeline including classification, lung and lesion segmentation, as well as lesion quantification of axial lung CT studies.</p><p><strong>Approach: </strong>A deep neural network architecture based on DenseNet is introduced for the classification of weakly-labeled, variable-sized (and possibly sparse) axial lung CT scans. The models are trained and tested on aggregated, publicly available data sets with over 10 categories. To further assess the models, a data set was collected from multiple medical institutions in Colombia, which includes healthy, COVID-19 and patients with other diseases. It is composed of 1,322 CT studies from a diverse set of CT machines and institutions that make over 550,000 slices. Each CT study was labeled based on a clinical test, and no per-slice annotation took place. This enabled a classification into Normal vs. Abnormal patients, and for those that were considered abnormal, an extra classification step into Abnormal (other diseases) vs. COVID-19. Additionally, the pipeline features a methodology to segment and quantify lesions of COVID-19 patients on the complete CT study, enabling easier localization and progress tracking. Moreover, multiple ablation studies were performed to appropriately assess the elements composing the classification pipeline.</p><p><strong>Results: </strong>The best performing lung CT study classification models achieved 0.83 accuracy, 0.79 sensitivity, 0.87 specificity, 0.82 F1 score and 0.85 precision for the Normal vs. Abnormal task. For the Abnormal vs COVID-19 task, the model obtained 0.86 accuracy, 0.81 sensitivity, 0.91 specificity, 0.84 F1 score and 0.88 precision. The ablation studies showed that using the complete CT study in the pipeline resulted in greater classification performance, restating that relevant COVID-19 patterns cannot be ignored towards the top and bottom of the lung volume.</p><p><strong>Discussion: </strong>The lung CT classification architecture introduced has shown that it can handle weakly-labeled, variable-sized and possibly sparse axial lung studies, reducing the need for expert annotations at a per-slice level.</p><p><strong>Conclusions: </strong>This work presents a working methodology that can guide the development of decision support systems for clinical reasoning in future interventionist or prospective studies.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"980735"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33514830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An artificial intelligence-enabled smartphone app for real-time pressure injury assessment.","authors":"Chun Hon Lau,&nbsp;Ken Hung-On Yu,&nbsp;Tsz Fung Yip,&nbsp;Luke Yik Fung Luk,&nbsp;Abraham Ka Chung Wai,&nbsp;Tin-Yan Sit,&nbsp;Janet Yuen-Ha Wong,&nbsp;Joshua Wing Kei Ho","doi":"10.3389/fmedt.2022.905074","DOIUrl":"https://doi.org/10.3389/fmedt.2022.905074","url":null,"abstract":"<p><p>The management of chronic wounds in the elderly such as pressure injury (also known as bedsore or pressure ulcer) is increasingly important in an ageing population. Accurate classification of the stage of pressure injury is important for wound care planning. Nonetheless, the expertise required for staging is often not available in a residential care home setting. Artificial-intelligence (AI)-based computer vision techniques have opened up opportunities to harness the inbuilt camera in modern smartphones to support pressure injury staging by nursing home carers. In this paper, we summarise the recent development of smartphone or tablet-based applications for wound assessment. Furthermore, we present a new smartphone application (app) to perform real-time detection and staging classification of pressure injury wounds using a deep learning-based object detection system, YOLOv4. Based on our validation set of 144 photos, our app obtained an overall prediction accuracy of 63.2%. The per-class prediction specificity is generally high (85.1%-100%), but have variable sensitivity: 73.3% (stage 1 vs. others), 37% (stage 2 vs. others), 76.7 (stage 3 vs. others), 70% (stage 4 vs. others), and 55.6% (unstageable vs. others). Using another independent test set, 8 out of 10 images were predicted correctly by the YOLOv4 model. When deployed in a real-life setting with two different ambient brightness levels with three different Android phone models, the prediction accuracy of the 10 test images ranges from 80 to 90%, which highlight the importance of evaluation of mobile health (mHealth) application in a simulated real-life setting. This study details the development and evaluation process and demonstrates the feasibility of applying such a real-time staging app in wound care management.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"905074"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9541137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33516717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Orchestrating the fecal microbiota transplantation: Current technological advancements and potential biomedical application.","authors":"Manisha Nigam,&nbsp;Abhaya Shikhar Panwar,&nbsp;Rahul Kunwar Singh","doi":"10.3389/fmedt.2022.961569","DOIUrl":"https://doi.org/10.3389/fmedt.2022.961569","url":null,"abstract":"<p><p>Fecal microbiota transplantation (FMT) has been proved to be an effective treatment for gastrointestinal disorders caused due to microbial disbalance. Nowadays, this approach is being used to treat extragastrointestinal conditions like metabolic and neurological disorders, which are considered to have their provenance in microbial dysbiosis in the intestine. Even though case studies and clinical trials have demonstrated the potential of FMT in treating a variety of ailments, safety and ethical concerns must be answered before the technique is widely used to the community's overall benefit. From this perspective, it is not unexpected that techniques for altering gut microbiota may represent a form of medication whose potential has not yet been thoroughly addressed. This review intends to gather data on recent developments in FMT and its safety, constraints, and ethical considerations.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"961569"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535080/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33516716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-throughput and automated screening for COVID-19.","authors":"Nestor Jonguitud-Borrego,&nbsp;Koray Malcı,&nbsp;Mihir Anand,&nbsp;Erikan Baluku,&nbsp;Calum Webb,&nbsp;Lungang Liang,&nbsp;Carlos Barba-Ostria,&nbsp;Linda P Guaman,&nbsp;Liu Hui,&nbsp;Leonardo Rios-Solis","doi":"10.3389/fmedt.2022.969203","DOIUrl":"https://doi.org/10.3389/fmedt.2022.969203","url":null,"abstract":"<p><p>The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"969203"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521367/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40391421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acoustocerebrography in septic patients: A randomized and controlled pilot study.","authors":"Martin Sauer,&nbsp;Anika Sievert,&nbsp;Miroslaw Wrobel,&nbsp;Paul Schmude,&nbsp;Georg Richter","doi":"10.3389/fmedt.2022.920674","DOIUrl":"https://doi.org/10.3389/fmedt.2022.920674","url":null,"abstract":"<p><p>Sepsis-associated encephalopathy (SAE) is a common organ dysfunction in patients with severe sepsis or septic shock and leads to higher mortality and longer hospital stay. The diagnosis remains an exclusion process; none of the available measurements are specific for SAE. The aim of the presented prospective and controlled clinical study was to evaluate the possible role of molecular acoustics in determining acute brain injury in septic patients using an acoustocerebrography (ACG) system. ACG is a multifrequency, transcranial ultrasound method that measures the attenuation and time of flight to detect changes in the brain tissue. After approval from the local research ethics committee (of the University Hospital of Rostock: Reg. No.: A 2016-0026), 20 patients were included in two study groups: septic shock group (SG) and control group (CG; postoperative nonseptic patients). All patients were screened several times with the ACG on different days. Blood parameters of organ function, sepsis-related organ failure assessment score, and delirium scores [Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC)] were obtained as well. A neurologist examined all patients at inclusion. Predictive analysis was done using a data-driven statistical method and by deriving a parameter from the ACG data. The study was registered under \"clinicaltrials.gov\" (Reg. No.: NCT03173196). All patients in the SG were CAM-ICU-positive at inclusion (ICDSC: in mean 4.0) and had clinical signs of SAE. In contrast, all patients in the CG were CAM-ICU-negative, with an ICDSC score of 0. Predictive analysis using the ACG data presented an accuracy of 83.4% with a specificity of 89.0% and a sensitivity of 75.1%. The ACG method may be helpful for the monitoring and diagnosing acute brain injury; however, the results of this first report should be verified by further clinical studies. Further investigations should include long-established instruments of SAE diagnosis, e.g., electroencephalography, MRI, and biomarkers, to compare the results with the ACG measurements.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"920674"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531262/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33492823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MemoBox: A mechanical follow-the-leader system for minimally invasive surgery.","authors":"Costanza Culmone,&nbsp;David J Jager,&nbsp;Paul Breedveld","doi":"10.3389/fmedt.2022.938643","DOIUrl":"https://doi.org/10.3389/fmedt.2022.938643","url":null,"abstract":"<p><p>With the increase in Natural Orifice Transluminal Endoscopic Surgery procedures, there is an increasing demand for surgical instruments with additional degrees of freedom, able to travel along tortuous pathways and guarantee dexterity and high accuracy without compromising the surrounding environment. The implementation of follow-the-leader motion in surgical instruments allows propagating the decided shape through its body and moving through curved paths avoiding sensitive areas. Due to the limited operational area and therefore the instrument size, the steerable shaft of these instruments is usually driven by cables that are externally actuated. However, a large number of degrees of freedom requires a great number of actuators, increasing the system complexity. Therefore, our goal was to design a new memory system able to impose a follow-the-leader motion to the steerable shaft of a medical instrument without using actuators. We present a memory mechanism to control and guide the cable displacements of a cable-driven shaft able to move along a multi-curved path. The memory mechanism is based on a programmable physical track with a mechanical interlocking system. The memory system, called MemoBox, was manufactured as a proof-of-concept demonstration model, measuring 70 mm × 64 mm × 6 mm with 11 programmable elements and featuring a minimum resolution of 1 mm. The prototype shows the ability to generate and shift complex 2D pathways in real-time controlled by the user.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"938643"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632848/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40670001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infections and hospital bed-days among aging adults: A five-year retrospective study in a Belgian general hospital.","authors":"Anne-Marie De Cock,&nbsp;Danielle Strens,&nbsp;Peter Van Osta,&nbsp;Baudouin Standaert","doi":"10.3389/fmedt.2022.912469","DOIUrl":"https://doi.org/10.3389/fmedt.2022.912469","url":null,"abstract":"<p><strong>Background: </strong>Infectious disease in aging adults (≥61 years) often occurs in combination with other health conditions leading to long hospital stays. Detailed studies on infection in aging adults investigating this problem are sparse.</p><p><strong>Aim: </strong>To quantify the effect of primary and secondary diagnosed infections on hospitalization bed-days among aging adult patients.</p><p><strong>Design: </strong>Retrospective patient-file study.</p><p><strong>Setting: </strong>Ziekenhuis Netwerk Antwerpen (ZNA) Hospital, a 1,858-bed general hospital in Belgium, with 364 beds allocated to geriatric patients.</p><p><strong>Data source: </strong>Database of hospitalized adult patients aged ≥61 years.</p><p><strong>Methods: </strong>All adult patients aged ≥61 years hospitalized on two wards, Geriatrics and Pulmonology, from 2010 to 2014 were included. Primary diagnosed infections were defined as infections known at entry to be treated first. Secondary diagnosed infections included infections known at entry but treated in parallel to primary non-infectious causes of entry, infections unknown at entry, and hospital-acquired (nosocomial) infections. Data were analyzed by patient age, gender, year, ward type, bed-days of hospitalization, infection rates, and seasonality.</p><p><strong>Results: </strong>There were 3,306 primary diagnosed infections (18%) and 14,758 secondary infections (82%) identified in the two wards combined (54.7% of all hospital stays at those 2 wards). Secondary diagnosed infections accounted for a significantly higher proportion of hospitalizations in both wards (+40% for Geriatric ward; +20% for Pulmonology ward; <i>p</i> < 0.001) and were associated with a significantly longer average hospital stay (+4 days for Geriatric ward; +5 days for Pulmonology ward; <i>p</i> < 0.001). Nosocomial infections (12% for Geriatric ward; 7% for Pulmonology ward) were associated with particularly high bed-days of hospitalization, at approximately +15 days and +12 days on Geriatric and Pulmonology wards, respectively. Both wards showed marked seasonality for respiratory infections with winter peaks.</p><p><strong>Conclusion: </strong>Real-world data showed that secondary diagnosed infections in aging adults imposed a high burden on hospital care along with longer hospital stays. This hampered bed availability during peak seasons.</p>","PeriodicalId":12599,"journal":{"name":"Frontiers in Medical Technology","volume":" ","pages":"912469"},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40670000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}