Coronavirus disease 2019 (COVID-19) changed healthcare across the world. With this change came an increase in healthcare-associated infections (HAIs) and a concerning concurrent proliferation of MDR organisms (MDROs). In this narrative review, we describe the impact of COVID-19 on HAIs and MDROs, describe potential causes of these changes, and discuss future directions to combat the observed rise in rates of HAIs and MDRO infections. Coronavirus disease 2019 (COVID-19) has changed healthcare delivery as a whole, and infection prevention in particular, in a myriad of ways. Early in the pandemic, many hospitals suffered a shortage of personal protective equipment (PPE) and had to halt or revise standard infection prevention duties to conserve scarce human and equipment resources and to focus on safely caring for patients with this novel pathogen. However, COVID-19 also ushered in changes that had the potential to reduce HAI rates, including heightened awareness of the risk of pathogen transmission, emphasis on hand hygiene, and universal masking. Later in the pandemic, burnout and staffing instability adversely impacted the ability to deliver consistent, reliable care, reversing a decade of reduction in the rates of HAIs. In this narrative review we will describe the impact of COVID-19 on the frequency of HAIs globally, with a focus on MDR organisms (MDROs). We will outline potential causes of these trends and describe potential future initiatives to reduce the occurrence of MDRO HAIs.According to the US CDC, 1 in 31 hospitalized patients develops at least one healthcare-associated infection (HAI) each day.JAC-AMR Online for the full search term. We also reviewed references from included manuscripts to identify other relevant studies.In collaboration with a library informationist, we queried PubMed for articles describing HAIs during the COVID-19 pandemic. A comprehensive literature review was completed for articles investigating MDROs in relation to COVID-19, which yielded 217 results, all of which were reviewed for inclusion. Please see the 3–12 This change was most notable for CLABSIs, which increased in Europe14 and the USA in 2020 and 2021,15–17 with a particularly concerning rise in candidaemia.18–22 In the USA, this rise reversed almost 5 years of reduction in rates of CLABSI.23 The rise in HAIs appeared to be proportional to the number of COVID-19 cases.16 Germany, where only 5% of the country was infected with COVID-19 in early 2020, did not see an increase in HAIs during the first months of the pandemic.24 In contrast, countries such as the USA, where an estimated 13% of the population had COVID-19 in early 2020, noted a concurrent rise in HAIs.24 Similarly, a retrospective study of CLABSIs in the USA found that in hospitals where >10% of admitted patients had COVID-19 there were significantly higher rates of CLABSIs compared with hospitals where COVID-19 accounted for <5% of admissions.25 VAPs increased across Europe26–28 and North17 and Latin America.6 Conversely, in the USA CAUTIs increased only slightly in 2020 and 202117 while Clostridioides difficile infections decreased29 and SSIs remained stable.17HAIs have increased with COVID-19 worldwide.Acinetobacter baumannii (CRAB), antifungal-resistant Candida, ESBL-producing Enterobacterales and VRE.30 Conversely, the overall rates of some infections including carbapenem-resistant Enterobacterales (CRE), MDR Pseudomonas and MRSA remained stable. However, the rates of most hospital-onset infections increased in both 2020 and 2021.17 The CDC reported a 78% increase in hospital-onset CRAB, 35% increase in hospital-onset CRE, 32% increase in hospital-onset ESBL-producing Enterobacterales, 13% increase in hospital-onset MRSA and a 14% increase in hospital-onset VRE.30 This same trend was reflected around the world: endotracheal aspirates obtained from patients in a Turkish ICU showed an increase in MDROs after March 2020 as compared with the year prior,31 a national referral hospital in Indonesia noted an increase in MDRO bloodstream infections from 130.1 cases per 100 000 patient-days in 2019 to 165.5 cases per 100 000 patient-days in 2020 ,32 an ICU in Rome saw a statistically significant association between COVID-19 diagnosis and drug-resistant A. baumannii bloodstream infections33 and France noted an increase in resistance to third-generation cephalosporins among Klebsiella, Enterobacteriaceae and Pseudomonas aeruginosa bloodstream infections in 2020 compared with 2019.34Since the start of the COVID-19 pandemic there has been an increase in many MDROs including carbapenem-resistant 8 and Gram-positive outbreaks were reported in Europe,35–37 the majority of COVID-19-associated MDRO outbreaks consisted of Gram-negative organisms. MDR Gram-negative outbreaks (of both infections and colonization) were reported in Mexico,38 Spain,39 France,40 the USA41 and Iran.42 The majority of outbreaks occurred in ICUs. Ghanizadeh et al.42 found distinct genetic clusters of Klebsiella pneumoniae in tracheal secretions of 70 patients with COVID-19 infections requiring mechanical ventilation in an Iranian ICU, suggestive of many smaller outbreaks within their ward. In a French ICU dedicated to caring for patients with COVID-19, they noted an outbreak of CTX-M-producing K. pneumoniae, including 16 infections between March and June 2020. This same ICU also noted an increase in rates of CRE compared with pre-pandemic levels.40 Some outbreaks were hospitalwide: during the initial months of the pandemic, a Peruvian hospital experienced an outbreak of NDM-producing K. pneumoniae among COVID-19 patients, a pathogen the hospital had never previously identified.43 Similarly, a New York City medical centre identified five patients with COVID-19 who developed secondary infections including bloodstream infections and VAPs from NDM-producing Enterobacter cloacae between March and April 2020, representing a previously unseen cluster of infections.41There have been increased reports of outbreaks of HAIs due to MDROs. Although rates of MRSA increased in many locations44 Similar outbreaks and increases in infections were noted in other US,45 Swiss46 and Brazilian ICUs,47–49 including a Brazilian outbreak mostly driven by International Clone 2, an unusual cause of CRAB in Latin America.49 Eckardt et al.45 described a cluster of six CRAB cases (five infections) in their COVID-19-dedicated ICU in Florida in late 2020 where no prior CRAB had been detected. Thoma et al.46 described two CRAB outbreaks in their Swiss medical and surgical ICUs in late 2020, detected in both clinical and screening isolates. Using WGS, they identified the index patients for both outbreaks, both of whom had been transferred from the Balkans. Although transfers from this region were common prior to 2020, CRAB outbreaks were not, suggesting that factors associated with the COVID-19 pandemic directly contributed to the spread of this MDRO. Outbreaks were noted in both non-ICU and ICU patients with COVID-19 in Italy and Israel.50 The outbreak described in an Israeli hospital, where CRAB is endemic, occurred despite extensive terminal cleaning measures and was postulated to be due to persistent environmental contamination.50CRAB outbreaks were frequently reported. A cluster of 34 CRAB cases were identified between February and July 2020 at a single acute care hospital in New Jersey during a surge of COVID-19 admissions and resolved after returning to usual infection prevention practices.Candida auris outbreaks emerged, including in a COVID-19 unit in Florida,51 as well as in Mexico,52 Italy54 and Lebanon55 (the first described in this country) and in an ICU in India.56 These outbreaks were identified from both clinical and screening isolates, and they occurred in patients with and without COVID-19, and in both ICUs and hospital wards. A rise in the rate of fluconazole-resistant Candida parapsilosis was noted in Europe.57 Outbreaks of this organism were also described in two connected hospitals in Brazil,58 likely resulting from a shared, contaminated CT scanner. Outbreaks were reported in Spain,59 and in Turkey, where the acceleration of an on-going resistant C. parapsilosis outbreak, present since 2015, was confirmed using WGS.60Multiple reports of Factors contributing to the rise in HAIs and MDROs are varied but interrelated and include human factors such as staffing instability, delayed care and increased device use. Similarly, COVID-19 infection itself, therapeutics used to treat patients with COVID-19, along with increased and often inappropriate antibiotic use likely also contributed .41 Dexamethasone was shown early in the pandemic to decrease mortality in patients who required oxygen therapy.75 Unfortunately, dexamethasone also has been shown to lower HLA-DR expression and CD4 cell circulation in COVID-19 patients,76 predisposing them to fungal and bacterial infections.73 Corticosteroid use was associated with increased bloodstream infections and increased the odds of death  in an Italian ICU.33 Similarly, in a case series of hospitalized patients in Brazil, the authors noted that all 11 patients who developed candidaemia did so after receiving steroids and that this infection occurred at a rate 10 times higher than patients without COVID-19 during the same time period.77 Patients with COVID-19 who were treated with dexamethasone were more likely to be diagnosed with a VAP in a propensity-matched ICU cohort in Italy 78 and France ,79 and had an increased risk of MDRO infection in South Korea .80COVID-19 therapeutics increase the risk of HAIs.82 Despite the clinical improvement these drugs can provide, they also increase the risk of bacterial infection, including HAIs. Patients with COVID-19 prospectively studied in an Italian ICU diagnosed with an additional coinfection were more likely to have received tocilizumab or baricitinib .83 A similar result was noted in multiple retrospective observational cohorts in the USA.85 Tocilizumab was associated with an increased risk of Candida bloodstream infections, as described in a case–control study involving two Indian ICUs between August 2020 and January 2021 .86 These findings are not surprising given both drugs’ effects on the immune system, and their previously described association with infection when used for rheumatological diseases.87–91Tocilizumab, an anti-IL-6 medication, and baricitinib, a JAK kinase inhibitor, are used in patients with rapidly progressing COVID-19.92 A cross-sectional survey of Scottish hospitals noted that over 60% of patients admitted for COVID-19 received antibiotics on any given day.93 A review of 126 COVID-19 patients requiring mechanical ventilation in three Seattle-area hospitals found that 97% received antibiotics, although only 55% were diagnosed with a VAP and 20% with a bloodstream infection.94 Early reports from China noted the majority of admitted patients received antibiotics,96 and a subsequent international meta-analysis found that 72% of patients admitted for COVID-19 globally received antibiotics.97 Furthermore, authors of a retrospective cohort of hospitals in South Carolina noted that when compared with the same months in 2019, hospitals that admitted patients with COVID-19 saw increased antibiotic usage between March and June 2020 . Most of the increased usage was in broad-spectrum antibiotics  with a 16.4% increase in agents used for hospital-acquired pathogens. Hospitals that did not admit patients with COVID-19 saw no change in their antibiotic utilization during these time periods.98 Increased antibiotic use during COVID-19 has also been described in Portugal,99 the Netherlands,100 elsewhere in the USA101–103 and Singapore,104 often with a specific increase in broad-spectrum antibiotics.105 This increase persisted despite a paucity of data regarding antibiotic efficacy106 and multiple studies showing that less than 7% of patients with COVID-19 had a concomitant bacterial infection upon admission.107–110High rates of antibiotic utilization in patients with COVID-19 contributed to an increase in HAIs caused by MDROs. Diagnostic uncertainty, limited evidence-based treatment options, severity of illness and initial concern for bacterial coinfection all drove increased antibiotic use.P value 0.005) with statistically significant higher rates of antibiotic usage , specifically increased ceftriaxone and carbapenem use.69 A hospital in Rome noted higher rates of MDROs in COVID-19 units than non-COVID-19 units , which they attributed to broader use of antibiotics in the COVID-19 units.111 In a retrospective cohort of patients admitted for COVID-19 to a single hospital in New York between March and April 2020, they noted that 100% of the patients who developed a superinfection with an MDRO had received antibiotics in the prior 30 days compared with only 65% of those with an infection that was not caused by an MDRO.112 Those with an infection caused by an MDRO received antibiotics for a median of 12 days, compared with a median of 8 days for those with an infection caused by a susceptible organism.112 This hospital also noted a shift in their antibiogram between 2018 and 2020 with a greater than 10% decline in susceptibility of K. pneumoniae isolates to many β-lactams including cefepime, meropenem and piperacillin/tazobactam.112 Although antibiotic prescribing patterns have hopefully improved for patients with COVID-19, the sequelae of antibiotic overuse and increase in MDROs continue to plague the global healthcare system.With increased antibiotic use and a shift in infection prevention practices to focus on COVID-19, came an increase in MDROs. A single-centre case–control study conducted in Spain between March and May 2020 found higher rates of CRE in patients admitted for COVID-19 compared with those admitted for other reasons  allowed participating facilities to ease their reporting of HAIs, a metric previously required for reimbursable quality evaluations.114 Enzymatic detergents and isopropyl alcohol, shown to decrease contamination from COVID-19, are also effective against some Gram-negative bacteria,115 and drug-resistant outbreaks have prompted the development of novel disinfecting agents and protocols to eradicate C. auris as well as other MDROs.117 Outbreaks of highly resistant organisms prompted usage of WGS to identify clusters and potential pathways of transmission.60 This approach is becoming more commonplace in infection prevention investigations as the availability of WGS increases and associated costs decrease, which may lead to faster, more accurate identification of MDRO outbreaks.119 Similarly, the rapid diagnostics employed for COVID-19 are comparable to many rapid diagnostics available to identify bacterial resistance. This similarity may encourage hospital authorities to invest in broader deployment of point-of-care resistance tests in clinical microbiology laboratories.114 COVID-19 has ushered in the acceptance of telehealth and opportunities for remote antibiotic stewardship and infection prevention consults in long-term care facilities and smaller community hospitals that were disproportionately affected by a rise in HAIs during COVID-19.12 There has also been renewed focus on antimicrobial stewardship itself, specifically with regard to patients with COVID-19.92 Lastly, novel antibiotics continue to be developed to treat the most drug-resistant bacteria.120Infection prevention practices and antibiotic prescribing have stabilized since the beginning of the pandemic, with a renewed focus on combatting HAIs and MDROs. Hand hygiene was prioritized with the onset of COVID-19, which will hopefully persist as the pandemic’s urgency subsides.121 Conditions that encourage the appropriate use of PPE and decrease opportunities for infection must be hardwired through quality improvement projects and human factors research to control the rise of HAIs.Nevertheless, challenges remain. Hospital staff shortages, which developed during the pandemic due to high turnover, early retirement, burnout and reliance on contract staffing, continue to plague hospitals across the world. The CDC recently recommended that masking requirements could be eased at some healthcare facilities, adding complexity and confusion within many communities.The COVID-19 pandemic has permanently changed healthcare and at least temporarily increased the rates of HAIs and MDRO cases throughout the world. However, with this comes increased recognition of the importance of infection prevention and attention on antimicrobial stewardship. As the world becomes more accustomed to COVID-19, healthcare systems must refocus on preventing HAIs and MDRO infections.dlac130_Supplementary_DataClick here for additional data file.


Kawasaki disease (KD), the most common cause of acquired heart disease in children, can be easily missed as it shares clinical findings with other pediatric illnesses, leading to risk of myocardial infarction or death. KD remains a clinical diagnosis for which there is no diagnostic test, yet there are classic findings on exam that can be captured in a photograph. This study aimed to develop a deep convolutional neural network, KD-CNN, to differentiate photographs of KD clinical signs from those of other pediatric illnesses. To create the dataset, we used an innovative combination of crowdsourcing images and downloading from public domains on the Internet. KD-CNN was then pretrained using transfer learning from VGG-16 and fine-tuned on the KD dataset, and methods to compensate for limited data were explored to improve model performance and generalizability. KD-CNN achieved a median AUC of 0.90 , with a sensitivity of 0.80 (IQR 0.18) and specificity of 0.85 (IQR 0.19) to distinguish between children with and without clinical manifestations of KD. KD-CNN is a novel application of CNN in medicine, with the potential to assist clinicians in differentiating KD from other pediatric illnesses and thus reduce KD morbidity and mortality. As a missed or delayed treatment can lead to an increased risk of myocardial infarction or death of a child, there is a need for accurate and timely diagnosis of KD to improve patient outcomes3. However, KD is often misdiagnosed as it shares clinical findings with other pediatric illnesses4. To date, KD remains a disease for which the etiology is unknown and there is no specific test for diagnosis5. KD clinical diagnosis is based on criteria established by the American Heart Association (AHA): bilateral conjunctival injection, erythema of lips and oral cavity, polymorphous exanthema, erythema/edema of peripheral extremities, and cervical lymphadenopathy6.Kawasaki disease (KD) is an acute childhood vasculitis and the leading cause of acquired pediatric heart disease in children, and has been reported in all continents and over 60 countries to date7 (CNNs) have achieved state-of-the-art performance on a variety of medical tasks10. A key factor contributing to the popularity of deep learning in medicine has been the use of scans such as computed tomography (CT) and magnetic resonance imaging (MRI) for radiology14, and availability of large, annotated datasets for dermatology17. However, there is a lack of a well-established and large image datasets for KD. We explored techniques to apply CNNs towards medical domains with limited data18.In recent years, Convolutional Neural NetworksGiven that KD clinical findings are visual onsets and can be captured in a photograph, a deep learning image analysis algorithm distinguishing KD from other look-alike illnesses has potential to aid in early diagnosis. In this study, we developed a deep convolutional neural network (KD-CNN) for KD diagnosis through clinical photographs. As clinicians assess clinical signs independently, CNNs were constructed for each individual KD sign. We explored methods to improve model performance given a limited photographic dataset and evaluated the potential of deep learning applied towards a challenging diagnosis.The study was conducted using binary classification differentiating between acute Kawasaki Disease (KD) clinical signs and non-KD images. We used a three-step approach of data acquisition and pre-processing, model development and optimization, and statistical evaluation, in order to construct and validate KD-CNN.The dataset was curated from two primary sources: 1) downloading publicly available retrospective images from the Internet using Google search queries  and (2) crowdsourcing from parents of KD patients in collaboration with the KD Foundation . In total, 2,035 images were gathered for the study (1023 KD and 1012 non-KD). The crowdsourcing campaign was launched in August of 2020 through a collaboration with the KD Foundation, who assisted in promotion of the campaign to a large following on social media and KD parent Facebook groups. The project was also presented at the virtual 2020 UCSD KD Parent Symposium with attendees from 17 countries. The guardians/parents of KD patients scanned a QR code to provide informed consent to the KD Foundation and then submitted images online. All photos were uploaded and handled in accordance with the KD Foundation’s guidelines and regulations. We obtained explicit informed consent approved by the UCSD Institutional Review Board for photos in publications, as applicable . Images were then sorted into respective clinical criteria and further adjudicated by a pediatric KD specialist (A.H.T.) to ensure accuracy of labeled data.We applied data augmentation techniques to create a larger training dataset and improve model invariance. Augments were generated from a range of randomly selected values, instead of fixed-value affine and photographic transformations , which introduced an additional factor of randomness between augments. Each of the following three augments was applied once on the original data, using randomly selected values in the range of valid transformations: rotations from − 90° to 90°, brightness adjustments from 50 to 100% , and zooming from 50% zoomed in to 100% .We developed KD-CNN, an 18-layer convolutional neural network, for classification of KD clinical criteria. KD-CNN takes in a photograph of a patient sign as input and outputs a probability of the sign resembling that of KD versus a look-alike disease. The KD-CNN model development process is shown in Fig. 19. Initial layers of the network were frozen for low-level feature representation, while the final fully connected layers were used for KD classification feeding into the decision-making step. All models were constructed sequentially using Tensorflow and Keras21. KD-CNN predictions were compared with the ground truth of labeled classes using categorical cross entropy loss and batch stochastic gradient descent (SGD) with the Adam optimizer22. A second additional fully connected layer provided greater degrees of freedom for fine-tuning with KD and non-KD data, hereby referenced as VGG16+.There are two main components of the KD-CNN model architecture: a pre-trained VGG-16 model with transfer learning, and additional fully connected layers fine-tuned for classification on the KD and non-KD dataset. To compensate for a small dataset, transfer learning with pre-trained VGG-16 was used to instantiate model weights for efficient training24. Early stopping with callbacks of loss and accuracy (maximum of 50 epochs and patience of 5) automatically searched for an optimal halting place during training, instead of manually configurating the number of training epochs. A dropout layer of rate 20% was added before the final VGG16 + fully connected layer to prevent too much co-adaptation. A combination of downsampling the majority class and an adaptive weighted loss function was implemented on a per-criteria basis to help reduce class imbalance26, e.g., for the Peeling class which had a proportion of 1:4 KD to non-KD images and Extremities class which had 1:2 KD to non-KD images.Hyperparameters of mini-batch size and steps per epoch, number of epochs, and learning rate were optimized for more efficient model training. We used a small mini-batch size of 4 samples and a default Keras learning rate of 0.001 to trade-off between fast convergence and overshooting minima. To prevent overfitting, we applied regularization steps of early stopping and dropoutSuppose 27. Each sample was used in nine separate folds for training and one time for testing (90–10 train-test split), and performance was measured on previously unseen samples during testing. Other methods used to evaluate model performance were area under the receiver operating characteristic curves (AUC)28, confusion matrices29, and true class probability (TCP) charts30. TCP charts plot a distribution of raw probability predictions by removing the final softmax activation, instead of the typical maximum class probability (MCP) output of binary classifications. Samples which were incorrectly classified with high probability (> 70% threshold) based on TCP were flagged for human review to further examine misclassified images. From the confusion matrix, additional metrics not dependent on prevalence used to evaluate model performance were sensitivity, specificity, and diagnostic odds ratio (DOR)31.We evaluated KD-CNN performance using tenfold cross validation, typically a less biased and less optimistic performance estimate compared to a single realization of a train-test splitThe KD-CNN dataset gathered from Internet sources and crowdsourcing is shown in Table We built the KD-CNN model and evaluated optimization techniques through the statistical methods shown in Fig. From the tenfold cross validation testing results, KD-CNN achieved a median AUC of 0.90 (IQR 0.10) with a sensitivity of 0.80 (IQR 0.18) and specificity of 0.85 (IQR 0.19) to distinguish between children with and without clinical manifestations of KD Table . Based o17, there are few studies applying deep learning for clinical diagnosis of pediatric diseases. A few studies have been conducted for neural networks for KD assessment and prediction34. To our knowledge, our study is the first to develop image-based deep learning methods for KD.We developed a convolutional neural network that can distinguish with high sensitivity and specificity between the clinical signs of KD and signs of other pediatric illnesses through patient photographs. KD-CNN is the first application of deep learning to the diagnosis of KD, achieving an overall AUC of 0.90. While deep learning has been previously investigated for the detection of skin disorders using photographsKD-CNN utilizes photographs of patient clinical features, which can be easily taken on a smartphone device, to classify KD from look-alike diseases. We used an innovative combination of Internet downloads and crowdsourcing from parents of KD patients for data collection. Given the lack of a pre-existing dataset and publicly available images on the Internet alone, we leveraged unique crowdsourcing methods to incorporate data from a variety of different geographical locations and generalize across a larger population. To improve model training, we applied pre-training and transfer learning to inherit weights from VGG-16, and added second fully connected layer (VGG16 + architecture) to allow greater fine-tuning on the KD and non-KD dataset. Additional layers beyond VGG16 + did not yield significant improvement in performance, most likely due to the limited data available to train models of increasing complexity and the advent of overfitting. Since some clinical signs included a greater proportion of non-KD images than KD, an adaptive weighted loss function was created to mitigate class imbalance, through applying class weights proportional to the relative number of samples per class.There are both strengths and limitations to this study. A primary limitation is the size of the dataset, given the absence of a well-established and pre-existing image database for KD. The uncommon nature of the disease prevented collection of a high volume of images, such as thousands of samples per class typical for deep learning studies. Furthermore, despite the geographical diversity of crowdsourced data, the exact demographic information and breakdown of the patient population such as race was not collected, which limited our ability to assess association of patient characteristics with model predictions. Additional testing with well-characterized patient data from, as well as greater investigation into potential algorithmic bias, will help further validate KD-CNN during our next stage of research. Development of a composite score integrating multiple patient photographs, demographic information, and initial laboratory values would also be worth exploring in future work.KD-CNN is a novel application of CNN image classification for KD clinical sign diagnosis. This study highlights methods of data crowdsourcing and deep learning methodologies towards new applications of AI and provides support that a deep learning algorithm can help distinguish between photographs of the clinical signs of KD and other pediatric illnesses.


Ocln knockout mice as well as a combined omics analysis and immunofluorescent labelling. Our results showed that the epididymis of Ocln-null mice displayed a phenomenon resembling epididymal sperm granuloma, which occurred especially in the junctional region between caput and corpus epididymidis. Sperm motility and fertilisation capacity were also impaired in these Ocln-null mice, accompanied by enlarged tubules in the proximal regions and degeneration in the distal regions of epididymis. Cellular localization analysis showed that OCLN immunofluorescence was enriched only in the apical junction of epithelial principal cells in the proximal regions of epididymis. Integrative omics analysis revealed the downregulation of gene clusters enriched in acid secretion and fatty acid metabolism in the Ocln-null epididymis, especially the enzymes related to the unsaturated arachidonic acid pathway. The number of proton-pump V-ATPase-expression clear cells, a key player of luminal acidification in the epididymis, declined drastically from prepubertal age before sperm arrival but not in the early postnatal age. This was accompanied by programmed cell death of clear cells and increased pH in the epididymal fluid of OCLN-deficient mice. The lipidomics results showed significantly increased levels of specific DAGs conjugated to unsaturated fatty acids in the Ocln-mutant. Immunofluorescent labelling showed that the arachidonic acid converting enzyme PTGDS and phospholipase PLA2g12a were prominently altered in the principal cells and luminal contents of the Ocln-mutant epididymis. Whereas the carboxylate ester lipase CES1, originally enriched in the WT basal cells, was found upregulated in the Ocln-mutant principal cells. Overall, this study demonstrates that OCLN is essential for maintaining caput-to-corpus epithelial integrity, survival of acid-secreting clear cells, and unsaturated fatty acid catabolism in the mouse epididymis, thereby ensuring sperm maturation and male fertility.Occludin (OCLN) is a tight junction protein and Ocln deletion mutation causes male infertility in mice. However, the role of OCLN in male reproductive system remains unknown. In this study, we used an interdisciplinary approach to elucidate the underlying mechanism of male infertility in related to OCLN function, including  The epididymis is a post-testicular male reproductive organ to provide a region-specific and optimal luminal microenvironment for sperm maturation and storage before sperm transport to the vas deferens for ejaculation –3. Such citation –13, and citation . Thus, sertility , 15, 16.ertility –8, 17. Mertility . All theOcln knockout (Ocln-KO) male mice are infertile  in the transcriptomes and proteomes of Ocln-KO compared to WT mice. The cellular expression of the significantly downregulated DEGs, including proton-pump V-ATPase and fatty acid catabolic enzymes PTGDs and CES1, were found to be altered in specific epithelial cell types. Overall, our study demonstrated the important role of OCLN in acid-base balance and metabolism in the epididymis.Occludin (OCLN) is an epithelial tight junction protein and nfertile ; howeverOcln-KO and B1-V-ATPase-EGFP mice were provided by Prof. Eveline E. Schneeberger and Prof. Sylvie Breton from MGH/Harvard Medical School. The background of these mice has been published previously  mice (C57BL/6) for maintenance. All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of ShanghaiTech University.eviously , 24. AllOcln-KO male mice aged 6, 9, 12, 20, 40 and 60 weeks were mated with two female wild-type mice. At least three pairs of mice of each age were mated for at least two weeks. To determine male mice mating behavior, the female mice (12-week-old) from the mating cage were examined for the plugs and the vaginal plugs were smeared, and the spermatozoa were observed under microscopy.WT and in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) assays, sperms were directly obtained from caput or cauda epididymis of WT and Ocln-KO males, the assays were performed as previously reported , embedded in O.C.T. compound (Sakura) and sectioned at −18°C or −20°C (Leica Microsystems GmbH), as described previously . Images were acquired using laser scanning confocal microscopy  and analyzed with the original software before imported into Adobe Photoshop for typesetting. Details of the antibodies used in this study are listed in The immunofluorescent labelling procedure was performed as described previously . BrieflyWestern blot was performed as published previously . Cell ly2 with Full-IMDM supplemented with 1 nM 5α-dihydrotestosterone and containing 10% (v/v) FBS, penicillin and streptomycin, as described previously (Ocln-KO cells were generated in DC2 cells by using the CRISPR/Cas9 system. The Ocln sequence in the second exon 5′-CGGCTGAGAGAGCATCGGC-3′ (Ocln–sgRNA) was targeted with pGL3-U6-sgRNA-PGK-Puro (Addgene). DC2 cells were then co-transfected with Ocln–sgRNA-expressing vector and Cas9 expressed vector pST1374-NLS-flag-linker-Cas9 (Addgene) by Lipofectamine 2000 and selected with puromycin and blasticidin for 24  h. Single cells were isolated by cell sorting. The single clones were validated by immunoblotting analysis and DNA sequencing. The two plasmids were gifts from Xingxu Huang  and recorded it by video. Data values were measured on captured images 10- second after the sample liquid touched the pH paper and the different standards in grey scale were used for calibration using Fiji software.For pH measurement in vas deferens of adult WT and Ocln-KO mice were pooled into one sample. The distal epididymidum was treated the same way. Three samples per group were used in this study. Lipids were extracted using a modified version of the Bligh and Dyer’s method as described previously (https://www.cloudtutu.com/).For lipid extraction, the proximal epididymides from three WT or eviously . Lipidomeviously . GlyceroOcln-KO mice whole epididymis by lysis buffer (50 mM (NH4)2CO3, 8 M urea, 1 mM DTT and protease inhibitor) separately and quantitation using BCA protein assay kit. After alkylated by iodoacetamide and digested by trypsin, the peptide was labeled by TMTs label regent following the manufacturer’s protocol. The resulting peptides were separated and analyzed on an Easy-nLC 1000 system coupled to a Q Exactive HF (Thermo Scientific). The LC-MS/MS procedure and data analysis were performed as reported previously  and kept at -80°C.The RNA with RIN >6.0 is about to undergo rRNA depletion. cDNA libraries were constructed for each pooled RNA sample by using the NEBNext® Ultra™ Directional RNA Library Prep Kit for Illumina according to the manufacturer’s instructions. The tagged cDNA libraries were pooled in equal ratio and used for 150 bp paired-end sequencing in a single lane of the Illumina HiSeqXTen. Before read mapping of pair-ends, clean reads were obtained from the raw reads by removing the adaptor sequences, reads with >5% ambiguous bases (noted as N) and low-quality reads containing more than 20 percent of bases with qualities of<20. The clean reads were then aligned to mouse genome (version: GRCm38 NCBI) using hisat2. Differential gene and transcript expression analysis of RNA-seq experiments with HTseq  analysis were obtained from the following criteria  was used for all statistical analyses.Comparisons were performed using the 2-tailed paired or unpaired Student’s t-test for only two groups, or one-way or 2-way-ANOVA for the comparisons of more than two groups at one- or two-levels, respectively. Significance was defined as a Ocln-KO male mice were reported to be infertile , which confirmed their sterility after 9-week-old. However, at juvenile ages of about 8 weeks, 1 out 8 Ocln-KO male mice was able to fertilize female mice to give birth to live pups  mice, although no difference in proportional size of the epididymis or other organs was found  of principal cells of the initial segment (IS) and CPT epididymidis, as well as the lateral membranes of WT or Ocln-KO leads to the observed epididymal defected, we profiled the transcriptomes and proteomes of the whole epididymis from adult Ocln-KO mice in comparison to those of WT mice to find differentially expressed genes (DEGs). An integrative approach was applied to the analysis of DEGs obtained by combining RNAseq and proteomic datasets. Through the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the results showed that the gene clusters enriched in the acid secretion, and metabolic pathways, including lipid and amino acid metabolic pathways, were the main nodes of downregulation , such as arachidonic acid , a key player in luminal acidification of epididymis, keeping sperm in a quiescent stage . In the luminal contents, the apoptotic index was decreased from CPT to CD epididymidis, whereas the apoptotic index was increased in the epithelial cells of epithelium , but it obviously decreased at puberty and in adulthood  and their derivatives diacylglycerols (DAG) in the epididymis  and triacylglycerols (TAGs) did not differ between the two groups , energy (e.g. ATP) and water. In the epididymis, it has been known that both luminal acidification and regulation of metabolism play essential roles in sperm maturation, as illustrated in the proposed model in 2 hydrolyses spontaneously in water to become bicarbonate, and CO2-bicarbonate equilibrium is an essential process contributing to acid-base balance in the epididymis , was converted to other forms in the distal versus proximal epididymis. However, this conversion remained effective in the Ocln-null epididymis, suggesting that releasing unsaturated long fatty acid chains from TAG58:7(22:6) was independent of the loss of OCLN and/or there is a compensation conversion pathway upregulated. Consistent with both speculations, the content of TAG58:7(22:6) in the caput epididymidis was slightly decreased, indicating a net reduction in the synthesis of this TAG component, and triglyceride lipase Lpl expression was slightly upregulated in Ocln-null epididymis.Fatty acid chains conjugated to DAG and/or TAG are an important source of arachidonic acid and thus are important upstream precursors of lipid-mediated signaling pathways. Arachidonic acid is a 20-carbon unsaturated fatty acid chain containing four double-bonds. Our results showed that impaired release of free long-chain fatty acids, such as arachidonic acid, from DAG is one of the major defects in the OCLN-deficient epididymis. This notion is supported by our lipidomic data, in which DAG38:5(16:0/22:5) with long fatty acid unsaturated chains in the proximal epididymis and arachidonate-conjugated DAG38:4(18:0/20:4) in the distal epididymis were significantly accumulated in the OCLN-deficient epididymis. In addition, the enzymes known to be involved in this process were all downregulated, including Ocln-KO. Our immunofluorescent labelling results showed that, in the WT epididymis, CES1 is predominantly expressed in basal cells from proximal to distal regions, and only in principal cells in distal regions. However, CES1 was significantly upregulated in principal cells but decreased in basal cells of caput epididymidis of OCLN-deficient mice. A potential role for basal cells in epididymal lipid homeostasis has been reported . The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the iProX partner repository, with the dataset identifier PXD037690 .The original contributions presented in the study are publicly available. This data can be found here: The RNA-sequencing data have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO series accession number GSE166141  of ShanghaiTech University. Written informed consent was obtained from the owners for the participation of their animals in this study.WS conceptualized, experimental designed, data analysis, curation, and interpretation. WS and BL wrote the manuscript. BL and BZ performed most of the experiments. DG performed the animal phenotypic analysis as well as some omics and imaging experiments. XX performed some imaging experiments. QL participated in experiments of IVF and ICSI experiments. All authors contributed to the article and approved the submitted version.This work was financially supported by the National Natural Science Foundation of China , and ShanghaiTech University.The authors thank all the staff of ShanghaiTech core facilities for their technical support, especially Dr. Xiao-Ming Li of Imaging Core Facility Dr Pi-Liang Hao of Mass Spectrometry Core Facility and Dr Ying Xiong of Cell & Molecular Core Facility.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Work-related factors can contribute to risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, and subsequent COVID-19–attributable outcomes, including death. Comparing COVID-19 metrics across industries can help identify workers at highest risk. Elevated COVID-19 mortality rates have been reported among all transportation workers, as well as specifically in public transportation industries  was 1.4 times as high as that for all industries (24.7) . Among iThe cumulative crude mortality rate for all public transportation industries was 174 per 100,000 workers, 1.5 times as high as the rate across all industries . CumulatCOVID-19 outbreak incidence and mortality rates are higher in public transportation industries in California compared with all industries combined. Workers in these industries have continued to report to work throughout the pandemic, and many have jobs involving close, frequent contact with coworkers and the public. Among New York City transit workers who died of COVID-19 early in the pandemic, 57% worked in public-facing positions  and the challenges of case and outbreak ascertainment with independent contractor work arrangements. Conversely, elevated outbreak incidence in air transportation relative to other transportation industries might partially reflect this industry’s enhanced outbreak identification and contact tracing capability, in addition to other work-related factors, such as duration and intensity of contact with others.Previous reports of excess all-cause mortality and COVID-19 mortality across occupational groups in California identified elevated mortality rates among non-Hispanic Black and Hispanic workers compared with non-Hispanic White workers in transportation occupations  might also affect outbreak and mortality rates and could not be adjusted for in this analysis. Fourth, although the industries analyzed here are public transportation industries, they include some workers who are not in public-facing roles; distinguishing these workers from public-facing workers was not possible in this analysis, and transmission might have occurred between coworkers as well as between workers and members of the public. Fifth, workers could not be distinguished from nonworkers in outbreak-associated case counts and, although death counts were limited to working-age persons and excluded those identified as unemployed or retired, some misclassification of working status remains possible. Decedents were classified by “usual industry,” which might also have led to misclassification of persons with more than one source of employment. Finally, identifying a specific source of COVID-19 exposure for individual patients is challenging because of the occurrence of presymptomatic and asymptomatic transmission and limitations in contact tracing, particularly for workers who come into frequent close contact with many persons; therefore, determining whether and how COVID-19 exposures occurred in the workplace can be difficult, particularly when analyzing aggregate data.The elevated outbreak incidence identified in public transportation industries suggests higher risk for SARS-CoV-2 workplace exposure among public transportation workers, and elevated mortality rates suggest increased risk for dying from COVID-19. Regardless of whether exposures occur from interactions with the public, coworkers, or other sources, these observations indicate that public transportation workers represent a vulnerable group who should be prioritized for COVID-19 prevention strategies. Such strategies can include targeted vaccination efforts, access to antiviral treatments, public health messaging, and enhanced workplace protection measures, such as improved ventilation and use of well-fitted masks or respirators  by workers and members of the public (Workers who perform in-person work and come into close, frequent contact with other workers or the public might be at increased risk for SARS-CoV-2 exposure and infection.Public transportation industries in California experienced cumulative COVID-19 outbreak incidence and mortality rates 1.5 times as high as that for all industries; outbreak incidence was 5.2 times as high, and mortality was 1.8 times as high in bus and urban transit industries as in all industries.Public transportation workers should be prioritized for COVID-19 prevention strategies, including vaccination and enhanced workplace protection measures.


To examine how the COVID-19 pandemic affected the demographic and clinical characteristics, in-hospital care, and outcomes of long-term care residents admitted to general medicine wards for non-COVID-19 reasons.We conducted a retrospective cohort study of long-term care residents admitted to general medicine wards, for reasons other than COVID-19, in four hospitals in Toronto, Ontario between January 1, 2018 and December 31, 2020. We used an autoregressive linear model to estimate the change in monthly admission volumes during the pandemic period (March-December 2020) compared to the previous two years, adjusting for any secular trend. We summarized and compared differences in the demographics, comorbidities, interventions, diagnoses, imaging, psychoactive medications, and outcomes of residents before and during the pandemic.Our study included 2,654 long-term care residents who were hospitalized for non-COVID-19 reasons between January 2018 and December 2020. The crude rate of hospitalizations was 79.3 per month between March-December of 2018–2019 and 56.5 per month between March-December of 2020. The was an adjusted absolute difference of 27.0  fewer hospital admissions during the pandemic period, corresponding to a relative drop of 34%. Residents admitted during the pandemic period had similar demographics and clinical characteristics but were more likely to be admitted for delirium  and were less likely to be admitted for pneumonia . Residents admitted during the pandemic were more likely to be prescribed antipsychotics  and more likely to die in-hospital Better integration between long-term care and hospitals systems, including programs to deliver urgent medical care services within long-term care homes, is needed to ensure that long-term care residents maintain equitable access to acute care during current and future public health emergencies. The COVID-19 pandemic had a dramatic impact on the use of hospital services in Canada, with significant drops in hospital occupancy rates beginning in March of 2020 . While mExisting research on the frequency of long-term care residents admitted to hospital during the COVID-19 pandemic in Canada has been restricted to aggregate analysis at the population level , 7. In pWe conducted a retrospective cohort study within four hospital sites in Toronto, Ontario, Canada.All data for the study was accessed through the GEMINI research database. GEMINI is a hospital research collaborative  that colWe included all residents living in long-term care homes admitted to general internal medicine wards for non-COVID-19 reasons at the study sites between January 1, 2018 and December 31, 2020. Participants were restricted to those residents admitted to general medicine wards to enable consistent data capture and avoid selection bias across the three years of the study. We excluded admissions for COVID-19 based on the ICD-10-CA code U07.1 (“COVID-19 diagnosis confirmed by a laboratory test”) [The pandemic period was defined as March-December 2020 . To avoiWe described the residents’ age, sex, and comorbidity profile. We reported the Elixhauser comorbidity index  and specWe characterized the in-patient care that residents received based on pre-specified categories of clinical management and resource use. For interventions, we reported the proportion of residents that received mechanical ventilation, any modality of dialysis, bronchial or gastrointestinal endoscopy, and red blood cell transfusions. We also reported the use of imaging studies, including plain radiography, computed tomography, magnetic resonance imaging, and ultrasonography. We examined in-hospital use of antidepressants , antipsychotics , and benzodiazepines . We chose these medication classes given evidence of increased use of psychotropic medications in long-term care homes in Ontario across 2020 .Outcomes examined included hospital length of stay, admission to an intensive care unit, and in-patient mortality.We plotted the monthly count of admissions from January 2018 to December 2020. We fit an autoregressive linear model to estimate the change in the average monthly count of admissions during the pandemic period. To achieve this, we included an interaction term between year (2020 vs. 2018–2019) and month category (January-February vs. March-December) while also controlling for a linear secular trend. This allowed us to compare 2020 to the previous years separately for the portions of the year before and during the pandemic.For residents admitted between March and December, we reported summary statistics for all demographic characteristics, clinical characteristics, outcomes, and in-hospital care measures across the two periods. We examined differences between periods using the Wilcoxon rank-sum test for continuous variables and Fisher’s exact test for categorical variables. All analysis was done using R 3.4.4 .Some patients may have contracted COVID-19 after hospital admission. We sought to identify these patients using post-admission comorbidities diagnoses U07.1 and U07.2 in the Discharge Abstract Database, and examined the effects of excluding these individuals on our findings. We also tabulated descriptive data on patients admitted for COVID-19.Ethics approval was obtained from Clinical Trials Ontario (1394) and Mount Sinai Hospital (15-0075-C). Waiver of informed consent was obtained as this was a large retrospective study with minimal risk. All records were full anonymized prior to access.Our study included 2,654 long-term care residents who were admitted to one of the study hospitals for non-COVID-19 reasons between January 2018 and December 2020; 2,150 of whom were admitted between March and December. The count of admissions between March and December was 791 (crude rate 79.1 per month) in 2018, 794 (crude rate 79.4 per month) in 2019, and 565 (crude rate 56.5 per month) in 2020. There were 57 COVID-19 positive admissions that were excluded from the pandemic period, 24 (52%) of which were in April 2020. Had the COVID-19 admissions been included, the crude March-December 2020 admission rate would have been 62.2 per month.The times series of monthly hospital admissions indicates a drop in admissions during the pandemic period with little recovery by December 2020 . The monIn the pre-pandemic period, admitted residents had a median age of 84 years and 47% of residents were female. . In the The five most frequent most responsible diagnoses among pre-pandemic residents were Congestive Heart Failure (I50), Aspiration Pneumonia (J69), Pneumonia (J18), Urinary Tract Infection (N39), and Sepsis (A41). Among pandemic residents, Delirium (F05) was also a top five most responsible diagnosis, displacing Pneumonia (J18).Intervention rates were similar across both groups. Nearly all residents in both groups received radiographs . Pandemic residents were more likely to receive computed tomography, although the difference was small . Use of magnetic resonance imaging and ultrasonography where similar between the groups. Antipsychotic medications were more frequently dispensed in-hospital during the pandemic period (37%) compared to the pre-pandemic period . Antidepressants  and benzodiazepines  were not significantly different.Hospital length of stay was longer for pandemic residents, who had a median stay of 6.2 days compared to 4.8 days for pre-pandemic residents (p <0.001). While the rates of ICU admission were similar, pandemic residents were more likely to die in hospital (14%) compared to 10% for pre-pandemic residents (p = 0.04).Only three residents were identified with post-admit COVID-19. Their exclusion did not meaningfully alter any results. Descriptive data on the COVID-19 admissions excluded from the main analysis is provided in We found that non-COVID-19 related admissions of long-term care residents to hospital dropped by over one-third during the pandemic, compared to the previous two years, and did not exhibit signs of recovery through the end of 2020. Residents admitted during the pandemic period for non-COVID-19 reasons were similar in most demographic and clinical characteristics to those admitted during the pre-pandemic period, but had longer hospital stays and were more likely to die in-hospital. Pandemic residents were less likely to be admitted for pneumonia but more likely to be admitted for delirium. Residents received similar care in-hospital between the periods, but pandemic residents were more likely to be prescribed antipsychotic medications.The drop in hospital admissions starting in April of 2020 mirrors the drops in health care use more broadly in the system at that time . Our stuThe care provided to residents in long-term care homes was inevitably affected by the COVID-19 pandemic. Notably, visits by essential caregivers were heavily restricted and a pre-existing staffing shortage escalated into a staffing crisis , 21. TheMortality rates for long-term care residents were significantly higher than normal between March-May and November-December of 2020  and new The demographic and clinical characteristics of pre-pandemic and pandemic residents admitted to hospitals were similar in most respects. Pneumonia was a considerably less frequent reason for hospitalization during the pandemic period, which is likely related to lower levels of circulating respiratory viruses resulting from public health restrictions to contain the COVID-19 pandemic , 27. ResCare in the hospital was similar between pandemic and pre-pandemic residents with the exception of higher use of antipsychotic medications during the pandemic period. Increased use of psychotropic medications during the pandemic has been previously noted with concern within long-term care homes in Ontario , 28 and The enduring drop in hospitals admissions raises questions regarding the on-going access of long-term care home residents to acute care services. While not all hospital transfers may be necessary, our data do not suggest that residents transferred during the pandemic were of higher acuity, as might be expected if only the more urgent transfers were taking place. Concerns have been raised in the broader population about “missing” hospital admissions and emergency department visits during the early portions of the pandemic for serious conditions necessitating hospital-based care , 38. OurOur study only included four hospitals in Toronto, Ontario which limited our study size and may impact generalizability. Additionally, we only could consider residents admitted to general medicine wards rather than surgical or other types of wards due to data availability. For our classification of admissions as COVID-19 related, we did not have access to PCR testing results but relied on the diagnoses provided in the hospital record. It is possible that more patients acquired COVID-19 in-hospital than we were able to identify using our data sources. Finally, we were unable to accurately measures changes to the long-term care population in the surrounding homes to analytically adjust for its influence on hospitalization rates.The COVID-19 pandemic resulted in an enduring drop in the volume of long-term care residents admitted to hospital. The characteristics of non-COVID-19 residents admitted before and during pandemic were similar, although those admitted during the pandemic were more likely to die in hospital, had differences in case mix, and had higher rates of antipsychotic use. Preparing Ontario’s long-term care system to weather the remainder of the COVID-19 pandemic and to plan for future public health emergencies will require better integration across the hospitals and long-term care systems, to ensure that frail and vulnerable long-term care residents do not experience interruptions in access to acute care.S1 Table(DOCX)Click here for additional data file.


We specifically assessed the relationship between changes in subjective well-being and changes in functional connectivity (FC) with the bilateral anterior insula from before to after exercise training. Cardiorespiratory fitness, subjective well-being, and resting-state fMRI were measured before and after a 12-week moderate-intensity walking intervention. A seed-based correlation analysis was conducted using the bilateral anterior insula as a priori seed regions of interest. The associations between bilateral anterior insula FC with other brain regions and subjective well-being were computed before and after exercise training, respectively, and the statistical difference between the correlations (before vs after exercise training) was evaluated. There was a significant Group (MCI vs CN) × Time (before vs after exercise training) interaction for subjective well-being, such that while those with MCI demonstrated significantly increased subjective well-being after exercise training, no changes in subjective well-being were observed in CN. Participants with MCI also showed an exercise training-related increase in the bilateral anterior insula FC. While there was no significant correlation between subjective well-being and bilateral anterior insula FC before exercise training, a positive association between subjective well-being and bilateral anterior insula FC was found in the MCI group after exercise training. Our findings indicate that 12 weeks of exercise training may enhance subjective well-being in older adults diagnosed with MCI and, further, suggest that increased bilateral anterior insula FC with other cortical regions may reflect neural network plasticity associated with exercise training-related improvements in subjective well-being.While it is well known that exercise training is associated with improvement in subjective well-being among older adults, it is unclear if individuals with cognitive impairment experience the same effects elicited by exercise on subjective well-being. We further explored whether the bilateral anterior insula network may be an underlying neural mechanism for the exercise training-related improvements in subjective well-being. We investigated the effects of exercise training on subjective well-being in older adults (78.4 ± 7.1 years) with mild cognitive impairment (MCI;  Sixteen million American older adults  are currently living with mild cognitive impairment (MCI) . MCI is Exercise training has well-established positive effects on cardiovascular, muscular, and metabolic health . EmerginImportantly, the neural foundations of subjective well-being related to ET are unknown. Thus, we sought to address this gap in the literature in healthy older adults and older adults diagnosed with MCI by examining ET-related changes in functional connectivity (FC) within a brain network known to be associated with subjective well-being. Resting-state FC analysis assesses the patterns of functional interaction between remotely located brain regions  by usingDespite the converging evidence, little is known about the association between anterior insula connectivity and subjective well-being after exercise training. This is particularly important and unstudied in individuals at risk for subjective well-being decline, such as older adults diagnosed with MCI. To address this knowledge gap, the second purpose of this study was to compare the association between the anterior insula FC and subjective well-being before and after the ET intervention. Based on separate pieces of evidence showing both increased intra-salience network connectivity (one of the primary seeds included anterior insula)  and enhaOur prior investigation reported detailed information about the recruitment, eligibility screening, enrollment, and withdrawals . BrieflyPhysically inactive older individuals  were included in the present study. A detailed description about the eligibility criteria and recruitment was previously reported . BrieflyA team of clinical investigators made determinations for each participant’s cognitive status using the core clinical criteria for the diagnosis of MCI by the National Institute of Aging-Alzheimer’s Association criteria for diagnosis of MCI . The folSubjective well-being was assessed using the satisfaction with life scale. The satisfaction with life scale is a short five-item unidimensional measure designed to assess psychometric properties related to satisfaction with life . The sat2) consumption, rate of carbon dioxide (CO2) production, and the respiratory exchange ratio  using a calibrated metabolic measurement system . The ratings of perceived exertion (RPE) scale (2peak), a measure of cardiorespiratory fitness, and at age-predicted maximal heart rate.Participants completed a modified submaximal stress test to assess aerobic fitness before and after the 12-week walking exercise intervention. A modified Balke-Ware protocol  was used on a General Electric (GE) motorized treadmill . We assessed breath-by-breath measures (expressed as a 15-s average) of ventilation, rate of oxygen (OE) scale  was usedAll participants were assessed with a comprehensive neuropsychological battery before and after the exercise intervention. The neuropsychological test battery evaluated several aspects of cognition including episodic memory, executive function, and processing speed, and a full report can be found in our previous study . The neuA 12-week treadmill walking intervention was administered to the study participants. All exercise sessions were administered under the supervision of a certified personal trainer or exercise physiologist. Each exercise session was conducted with no more than two participants. The duration of each exercise session was a total of 50 min including a 30-min exercise session, and 10-min warm-up and cool-down sessions. Each exercise session was administered 4 times/week in local recreation centers. With the goal of achieving a moderate intensity during each session, an HR monitor  and the RPE scale  were useAll MRI data were acquired on a 3.0 Tesla GE  MR scanner. A high-resolution T1-weighted anatomical image was acquired for co-registration with the following sequence parameters: 3D Spoiled Gradient Recalled at steady-state protocol (SPGR), field of view (FOV) = 240 mm, voxel size = 0.94 × 0.94 × 1.00 mm, number of excitations (NEX) = 1, slice thickness = 1 mm, repetition time (TR) = 9.6 ms, echo time (TE) = 3.9 ms, inversion recovery preparation time = 450 ms, flip angle = 12°, resolution = 256 × 224, and sequence duration = 6 min. The resting-state BOLD data were acquired using the following sequence parameters: gradient echo planar images, 4.0 mm isotropic voxels, FOV = 240 mm, NEX = 1 mm, slice thickness = 1.0 mm, TR/TE = 2,000/25 ms, axial slices = 36, flip angle = 77°, resolution = 64 × 64, and sequence duration = 6 min. During the resting-state scan, participants were instructed to stay still and to keep their eyes on a fixation cross projected on the screen.p = 0.062; paired t-test). We also did not find significant differences in motion between groups , and there was not a significant Time × Group interaction  on removed TRs. Thus, the effects of head movement were not included as a covariate in the fMRI data analysis.Using FreeSurfer’s (version 5.3.0) automated processing stream , the T1-weighted anatomical volumes were processed to generate cortical and subcortical reconstructions based on tissue-specific intensities and atlas probabilities . The resa priori seed regions of interest. To accomplish this, left and right anterior insula masks . Normality of satisfaction with life scale and the geriatric depression scale (GDS) were also computed using the Shapiro–Wilk test. We used repeated-measures ANOVA to test the main effects of Time , Group , and Group × Time interaction on the satisfaction with life scale score and GDS. We also tested the main effects of Time within each group. The association between the satisfaction with life scale score and anterior insula FC was subsequently investigated before and after ET, respectively. To accomplish this, partial correlation analysis was used. Prior to this test, we conducted bivariate correlation tests to evaluate relationships between age and variables of interest . There were no significant correlations between age and variables of interest (p ≥ 0.199). We did not find significant correlations between sex and variables of interest (p ≥ 0.104). Furthermore, there were no significant correlations between motion metric and variables of interest (p ≥ 0.497). Therefore, the correlation analyses were unadjusted. After computing the correlation between satisfaction with life scale score and anterior insula FC before and after ET, respectively, the statistical difference between correlation  was computed. The “cocor”  package within R software  were evaluated using independent sample software  was used2peak , and GDS ; these participants are included in all analyses not involving these variables. The demographic data for the 28 participants are shown in 2peak, and Lawton Instrumental Activities of Daily Living  were excluded from analysis due to missing satisfaction with life scale data. The remaining 28 participants were included in the final analyses (14 MCI and 14 CN). Data were missing for some participants for V̇Oy Living .2peak from before to after ET in both groups  . There was a significant Group × Time  for satisfaction with life scale data (see p = 0.003), but no subjective well-being change occurred in the CN group after ET (p = 0.382). Yet, no main effects of Time  and Group  were found in satisfaction with life scale. While there was a significant main effect of Group for the GDS  indicating higher depression scores in the MCI, there were no significant effects of Time  or Group × Time  . There were group differences (CN > MCI), as well as significant Time main effects and one Time by Group interaction effect on multiple cognitive tasks. See There was a significant increase in V̇Odata see , such th3] was found in the MCI group , BA 7, 19, 1,128 mmCI group ; Panel Awith MCI ; Panel B MCI , the association between subjective well-being and bilateral anterior insula FC was only assessed in the MCI group. To examine the association between subjective well-being and bilateral anterior insula FC, average z-scored connectivity within the regions shown in R = 0.123, 2R = 0.015, p = 0.675] and after ET . While there was no significant correlation between the subjective well-being and bilateral anterior insula FC with bilateral precuneus before ET  , suggesting that the correlation between subjective well-being and bilateral anterior insula-bilateral precuneus FC became significantly different after ET compared to before ET in participants with MCI.As a significant change in subjective well-being was only found in the MCI group  across participants. Those with MCI had lower subjective well-being at baseline, which increased to equal that of the CN group over the 12 weeks; CN older adults maintained subjective well-being over the 12 weeks. Moreover, opposite patterns of anterior insula FC were found between the groups after ET, such that there was an ET-induced increase in the FC between the bilateral anterior insula and other brain regions in MCI, but there was decreased FC between the bilateral anterior insula and other brain regions in the CN group. Finally, in the MCI group, we observed a positive association between anterior insula FC with the bilateral precuneus and subjective well-being after exercise training; an association that was not observed before ET.The present study investigated the effects of a 12-week walking intervention on subjective well-being and bilateral anterior insula FC in older adults with MCI and normal cognition. The walking exercise intervention resulted in an approximately 10% increase in cardiorespiratory fitness  . Accordip = 0.183). One possible factor driving the lack of ET-related changes in subjective well-being among the CN group could be a relatively high baseline subjective well-being. That is, the CN group had higher subjective well-being than the MCI group at baseline, indicating a possible ceiling effect that would not permit increased scores in the CN group but would allow greater opportunity for the participants with MCI to experience ET-related enhancement in subjective well-being. Indeed, exercise is likely to elicit greater effects on aspects of health-related quality of life among individuals experiencing age/pathology-related decline in brain function  . FurtherNotably, the correlation between the anterior insula-precuneus connectivity and subjective well-being became significantly positive after ET in the MCI group. The relationship between anterior insula FC and subjective well-being presented in this study is supported by the work of Although the neurophysiological mechanisms underpinning the ET-related increase in FC among individuals with MCI are not completely understood, consistent exercise is associated with increased skeletal muscle capillarization and enhanced mitochondrial function in the brain . This ETAnother possible mechanism involves changes in cerebrovascular reactivity, especially due to the location of the anterior insula and middle cerebral artery. The main arterial source for the insula is the M2 segment of the middle cerebral artery , which h2peak). Furthermore, the psychological benefits of ET were examined in older adults with an objective diagnosis of MCI, who have been understudied. Despite these strengths, the present study should be interpreted with caution until it is replicated in a larger randomized controlled trial due to the lack of a non-exercise (or active) control group. Next, we used a relatively short intervention ; thus, we may have missed potential effects that could manifest after a longer exercise intervention . Nevertheless, the present study suggests that ET-related effects on subjective well-being and anterior insula FC may emerge within 3 months. Thus, it may be useful for longer interventions to document the time course of these effects in addition to measurements before and after the intervention. In addition, the present study employed a relatively small sample (n = 28) with homogeneous demographic characteristics . Therefore, our results may not be generalizable to the entire older adult population. An important additional direction for future research is to recruit a larger sample with diverse fitness levels to further assess the effects of exercise training on subjective well-being in individuals with MCI. Lastly, the ceiling effect may have occurred in the subject well-being scale for the CN group, which may have impeded capturing the intervention effect in CN older adults.A major strength of the present study was the well-attended (compliance rate of ∼96%) and well-supervised intervention, which may have driven the increase in cardiorespiratory fitness after ET (10.5% increase in V̇OIn conclusion, a 12-week walking intervention improved subjective well-being in older adults with impaired cognition, which occurred independently of changes in cognitive function. Hence, the present study suggests that improvement in subjective well-being after exercise training may be an independent construct from cognition in older adults with MCI. Our results also suggest that the increase in FC between the anterior insula and precuneus may be an important neural basis for the ET-induced enhancements in subjective well-being among older adults diagnosed with MCI. Consistent with our previous studies using the same MCI cohort that showed the ET-related effects were evident in the insula , our worThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Medical College of Wisconsin. The patients/participants provided their written informed consent to participate in this study.JW and JS developed the study idea and collectively developed the analytic strategy. JS and KN developed the overall study protocol and collected data. JW processed and analyzed imaging data, drafted the manuscript, and created the figures. All authors interpreted the data, edited the manuscript, reviewed, revised, and approved the final manuscript.The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This cohort study assesses the association of incident delirium, days of delirium, days of coma, and delirium- and coma-free days with short-term mortality and hospital length of stay among adult patients with critical illness receiving mechanical ventilation. Are incident delirium, days of delirium, days of coma, and delirium- and coma-free days (DCFDs) associated with short-term mortality and hospital length of stay?In this prospective cohort study of 267 patients with critical illness receiving mechanical ventilation, delirium was not associated with short-term mortality, despite being associated with longer hospital stays. Days spent in coma were associated with an increased hazard of dying within a given 14-day period and during hospitalization, whereas the number of DCFDs was a protective factor.The findings of this study support adoption of interventions  to maximize DCFDs, thereby potentially increasing in-hospital survival of patients receiving mechanical ventilation. Intensive care unit (ICU)–acquired delirium and/or coma have consequences for patient outcomes. However, contradictory findings exist, especially when considering short-term  mortality and length of stay (LOS).To assess whether incident delirium, days of delirium, days of coma, and delirium- and coma-free days (DCFDs) are associated with 14-day mortality, in-hospital mortality, and hospital LOS among patients with critical illness receiving mechanical ventilation.This single-center prospective cohort study was conducted in 6 ICUs of a university-affiliated tertiary hospital in Taiwan. A total of 267 delirium-free patients (aged ≥20 years) with critical illness receiving mechanical ventilation were consecutively enrolled from August 14, 2018, to October 1, 2020.Participants were assessed daily for the development of delirium and coma status over 14 days (or until death or ICU discharge) using the Confusion Assessment Method for the Intensive Care Unit and the Richmond Agitation-Sedation Scale, respectively.Mortality rates  and hospital LOS using electronic health records.Of 267 participants , 149 patients (55.8%) developed delirium for a median (IQR) of 3.0 (1.0-5.0) days at some point during their first 14 days of ICU stay, and 105 patients (39.3%) had coma episodes also lasting for a median (IQR) of 3.0 (1.0-5.0) days. The 14-day and in-hospital mortality rates were 18.0% (48 patients) and 42.1% (112 of 266 patients [1 patient withdrew from the study]), respectively. The incidence and days of delirium were not associated with either 14-day mortality  or in-hospital mortality , whereas days spent in coma were associated with an increased hazard of dying during a given 14-day period  and during hospitalization . The number of DCFDs was a protective factor; for each additional DCFD, the risk of dying during the 14-day period was reduced by 11% , and the risk of dying during hospitalization was reduced by 7% . Incident delirium was associated with longer hospital stays  when compared with no incident delirium.In this study, despite prolonged LOS, ICU delirium was not associated with short-term mortality. However, DCFDs were associated with a lower risk of dying, suggesting that future research and intervention implementation should refocus on maximizing DCFDs to potentially improve the survival of patients receiving mechanical ventilation. Delirium is also associated with longer hospital length of stay (LOS),9 but there are inconsistent findings for the association between ICU delirium and LOS.11Delirium, a form of acute brain dysfunction, occurs in up to 80% of patients receiving mechanical ventilation in the intensive care unit (ICU).12 are adopted into critical care practice, the association of ICU delirium with short-term mortality and LOS may change. In addition, coma  has been suggested to be a greater risk factor than ICU delirium for short-term mortality.8 In general, the delirium-mortality association (up to 18 months) has been confined to patients with coma.14 As a negative surrogate, delirium- and coma-free days (DCFDs) provide an estimate of the duration of normal brain function and have been used as an outcome in previous high-impact studies.17As new guidelines providing recommendations for the prevention and management of agitation, sedation, and delirium18 Thus, we conducted a prospective cohort study to evaluate the association of incident delirium, days of delirium, days of coma, and DCFDs with short-term  mortality and hospital LOS to verify the relevant outcomes for delirium prevention and management.In hospitals in Taiwan, acute brain dysfunction is presenting as a hidden and increasing epidemic, especially in the ICU setting. In a national effort, Taiwan released guidelines to facilitate the adoption of protocolized delirium monitoring and other evidence-based delirium interventions.STROBE) reporting guideline for cohort studies.This prospective cohort study of patients receiving mechanical ventilation was approved by the National Taiwan University Hospital Research Ethics Committee. Written informed consent was obtained from all participants or their surrogates. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology , (2) were confined to bed for a prolonged period before index hospitalization (based on our study aim of monitoring patient recovery through activities of daily living [ADL]), or (3) were placed on contact and droplet precautions . Exclusion criteria, defined a priori, are shown in the patient flow diagram  admitted to 6 medical ICUs  of a university-affiliated tertiary hospital in Taiwan. Qualified patients for the study included those who were delirium or coma free and received mechanical ventilation with an expected ICU stay exceeding 24 hours. Patients were excluded if they (1) could not respond to the questions or evaluation protocol  was applied using the most abnormal values obtained during the first 24 hours of ICU stay. The Charlson Comorbidity Index (CCI)21  was calculated to represent the sum of weighted preexisting comorbid conditions at ICU admission. Sepsis (yes or no) was defined as a Sequential Organ Failure Assessment (SOFA)22 score of 2 or higher at ICU admission. The SOFA evaluates 6 organ systems, with a total score ranging from 0 (best) to 24 (worst).22Two trained research nurses (H.C.L. and Y.J.X.) evaluated participants by collecting cohort demographic (age in years and sex) and clinical characteristics. The Acute Physiology and Chronic Health Evaluation II19 . Participant ADL function before the index hospitalization was assessed using the Barthel Index.24 The Barthel Index measures independence in feeding, bathing, grooming, dressing, bowel or bladder function, toilet use, transfers, mobility, and climbing stairs; scores were classified into 3 functional categories: severely to fully dependent (0-60 points), slightly to moderately dependent (61-99 points), and fully independent (100 points)).24The research nurses also rated the presence and extent of dementia using the CDR scaleThe ICU admission diagnoses  were abstracted from medical records. Delirium and coma were assessed once daily by trained research nurses until ICU discharge or for a maximum of 14 days, whichever occurred first. All research nurses had at least 1 year of ICU experience and received 1:1 training on delirium evaluation from 2 intensivists (T.Y.C.Y. and S.C.K.), an experienced nurse practitioner (C.C.H.C.), and a psychiatrist. Nurse ICU delirium screening was calibrated with an experienced psychiatrist during the study.25 partnered with the RASS to measure the level of consciousness. Coma was defined as a RASS score of −4 or −5, making those participants ineligible for CAM-ICU screening.13 We considered the fact that brain function fluctuates during an ICU stay, contributing to different outcomes; thus, the data were codified into delirium days, coma days, and DCFDs. We did not exclude individuals with persistent coma from our analyses . Therefore, the measure of coma days reflected the cumulative consequences of the comatose state. Delirium- and coma-free days  provided an estimate of the duration of normal brain function. Any remaining study days were recorded as 0 for patients who died or were discharged from the ICU before day 14 . Rather than recording 0 DCFDs when patients died within the study period,17 we counted the DCFDs the same way regardless of whether participants died within the study period.Delirium (yes or no) was measured using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU)Mortality  was evaluated at 14 days and at the time of hospital discharge. Hospital and ICU LOS days were abstracted from the electronic health records. Both mortality and LOS data were collected by an independent outcome assessor blinded to the study hypothesis and delirium assessment results.P < .05 considered significant. Sample characteristics were reported as numbers with percentages or medians with IQRs. Survival time associations of incident delirium, days of delirium, days of coma, and DCFDs with 14-day and in-hospital mortality were estimated using Cox proportional hazards regression analysis. Because the proportionality of the hazards is an important assumption of Cox proportional hazards analysis, we evaluated the assumption using scaled Schoenfeld residuals.26 Once this assumption was met, we reported our results as adjusted hazard ratios (aHRs) with 95% CIs. Five confounders  known to be associated with mortality in adults with critical illness were identified a priori and subsequently forced into each model. Multivariable linear regression analysis was used to assess hospital LOS.All data were entered into a Research Electronic Data Capture (REDCap) database, and analyses were performed using statistical packages of IBM SPSS Statistics software, version 22 (IBM Corporation), with all tests being 2-tailed and Among 267 participants, the median (IQR) age was 65.9 (57.4-75.1) years; 140 participants (52.4%) were 65 years and older, 171 (64.0%) were male, and 96 (36.0%) were female . All parDuring the first 14 days in the ICU, 149 participants (55.8%) developed delirium, and 105 participants (39.3%) spent 1 or more days with coma . The medThe Cox proportional hazards regression analysis reavealed that neither incident delirium nor days of delirium were associated with 14-day mortality  or in-hospital mortality  . Days of9 , days of coma , nor DCFDs  were associated with hospital LOS . Only inBecause we suspected that increased mortality among participants with coma (or persistent coma) masked the association with LOS, we reanalyzed the data. First, we excluded participants with persistent coma (n = 246) and found that results remained similar; only incident delirium was significantly associated with longer LOS   mortality, but days spent in coma increased the odds of 28- and 90-day mortality. There are 3 possible explanations for the contradictory findings of delirium-associated mortality in the literature.27 First, patients who presented with delirium before ICU admission were excluded from our study and the Dutch study . Second, improvements in ICU care may have resulted in more recent cohort studies of patients with critical illness reporting a lower delirium incidence, with an increasing pattern of negative findings for short-term mortality after ICU delirium compared with previous investigations.29 Third, the current practice of excluding individuals with coma (RASS score of −4 or −5) from delirium screening may result in potential underestimation of the rate of delirium and overestimation of the role of coma within the sample. We acknowledge that delirium and coma exist on a spectrum of acute brain dysfunction. Thus, the traditional approach of separating the 2 variables when evaluating their individual associations with mortality might not be clinically warranted. It may also inadequately account for the fact that they are on a continuum.In our study, delirium alone was not associated with short-term mortality, and the number of days spent in coma was significantly associated with the risk of 14-day and in-hospital mortality. These results build on those of a previous Dutch study,30 The Hospital Elder Life Program (HELP) has been reported to be effective in preventing delirium in hospitalized older adults.31 The HELP provides a multiple component protocol targeting risk factors for delirium. The ABCDEF  bundle is a multicomponent guideline-recommended model that coordinates the people, processes, and technologies in the ICU to result in patients who are awake, cognitively engaged, and physically active.33 Despite its efficacy in reducing next-day delirium and coma, the bundle is still underused in ICUs worldwide.34 The findings of this study support bundle adoption to maximize DCFDs, thus potentially increasing in-hospital survival of patients receiving mechanical ventilation.We found that DCFDs were associated with lower odds of 14-day and in-hospital mortality. Because delirium and coma are closely related and both are associated with adverse outcomes, targeting improvement in DCFDs as the basis of outcomes and quality measures in ICUs to improve short-term survival is clinically warranted. As a means to facilitate the implementation of recent critical care guidelines to improve outcomes, bundled nonpharmacological interventions have been increasingly studied.35 Thus, the finding of protective benefit should be interpreted with caution and replicated by more independent assessments.This study has several limitations. First, as in any observational study, this study is not designed to assess causality. Moreover, we acknowledge the limitation of using DCFDs to estimate in-hospital mortality. Similar to ventilator-free days, such failure-free day concepts, which combine survival and ventilation duration or delirium and coma (in the case of this study), penalize nonsurvivors.36 supported a combination of patient assessment, medical record review, and medication administration record review to improve the sensitivity of delirium identification for research purposes. Researchers in the Netherlands have also identified a 5-step algorithm to classify mental status based on the CAM-ICU.37 Future studies might incorporate those tools to enhance the sensitivity of delirium identification.Second, we did not measure the timing of delirium evaluation and daily sedation cessation. Not measuring those factors could have overestimated delirium incidence while participants were receiving sedative medications . In addition, delirium and coma incidence and duration may be underestimated because we performed once-daily delirium assessment for 14 days (or until death or ICU discharge), potentially missing rapid fluctuations in mental status. We specifically chose a 14-day ICU delirium evaluation period because it represents the best balance for covering the dynamic ICU course to gain important data while maximizing resource use, given the median (IQR) LOS in the participating ICUs was 9.0 (5.0-15.0) days. Findings from a previous studyThird, no data on sedative or antipsychotic medication use were collected, and we generally included confounding factors at baseline. Because many factors can change over time , residual confounding in the associations of delirium and coma with mortality cannot be excluded. Lack of use of time-varying cofounders is also acknowledged.Fourth, this study was conducted in a single center, and the exclusion criteria of a CDR score of 2 or higher and preexisting delirium at ICU admission likely resulted in a cohort with better cognitive reserve (97.4% of participants had scores of 0 on the CDR); thus, the results are restricted to those without preexisting acute or chronic cognitive impairment and may not generalize to all ICU populations. Moreover, although we did not enroll individuals with COVID-19, our study spans the COVID-19 period from March to October 2020, which may have impacted the study results and mortality rates.38 Future studies with larger samples from representative sites and with careful design in delirium evaluation are warranted to detangle the complex interplay between delirium (or motoric subtypes) and coma and, most important, to examine whether maximizing ICU DCFDs would improve hospital survival.Fifth, we did not collect data on delirium subtypes and are thus unable to verify previous findings that only mixed delirium  is associated with mortality.This cohort study found that delirium in patients with critical illness receiving mechanical ventilation was not consistently associated with short-term  mortality. Nonetheless, ICU DCFDs may be a protective factor. With each additional DCFD, the risk of dying within 14 days or during hospitalization was independently reduced. Future research and intervention implementation might refocus on maximizing DCFDs, thus potentially improving the survival of patients receiving mechanical ventilation.