HIV rapidly targets a diverse pool of CD4+ T cells to establish productive and latent infections.

Upon infection, HIV disseminates throughout the human body within 1-2 weeks. However, its early cellular targets remain poorly characterized. We used a single-cell approach to retrieve the phenotype and TCR sequence of infected cells in blood and lymphoid tissue from individuals at the earliest stages of HIV infection. HIV initially targeted a few proliferating memory CD4+ T cells displaying high surface expression of CCR5. The phenotype of productively infected cells differed by Fiebig stage and between blood and lymph nodes. The TCR repertoire of productively infected cells was heavily biased, with preferential infection of previously expanded and disseminated clones, but composed almost exclusively of unique clonotypes, indicating that they were the product of independent infection events. Latent genetically intact proviruses were already archived early in infection. Hence, productive infection is initially established in a pool of phenotypically and clonotypically distinct T cells, and latently infected cells are generated simultaneously.

Generative ß-hairpin design using a residue-based physicochemical property landscape.

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the ß-hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of ß hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial ß-hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

MHC-Fine: Fine-tuned AlphaFold for precise MHC-peptide complex prediction.

The precise prediction of major histocompatibility complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold's capabilities by fine-tuning it with a specialized dataset consisting of exclusively high-resolution class I MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold's original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of class I MHC-peptide interaction prediction. A comparative analysis was conducted against the homology-modeling-based method Pandora as well as the AlphaFold multimer model. Our results demonstrate that our fine-tuned model outperforms others in terms of root-mean-square deviation (median value for Cα atoms for peptides is 0.66 Å) and also provides enhanced predicted local distance difference test scores, offering a more reliable assessment of the predicted structures. These advances have substantial implications for computational immunology, potentially accelerating the development of novel therapeutics and vaccines by providing a more precise computational lens through which to view MHC-peptide interactions.

OpenMDlr: parallel, open-source tools for general protein structure modeling and refinement from pairwise distances.

SUMMARY: Easy-to-use, open-source, general-purpose programs for modeling a protein structure from inter-atomic distances are needed for modeling from experimental data and refinement of predicted protein structures. OpenMDlr is an open-source Python package for modeling protein structures from pairwise distances between any atoms, and optionally, dihedral angles. We provide a user-friendly input format for harnessing modern biomolecular force fields in an easy-to-install package that can efficiently make use of multiple compute cores. AVAILABILITY AND IMPLEMENTATION: OpenMDlr is available at https://github.com/BSDExabio/OpenMDlr-amber. The package is written in Python (versions 3.x). All dependencies are open-source and can be installed with the Conda package management system. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identification of Small-Molecule Inhibitors of Fibroblast Growth Factor 23 Signaling via In Silico Hot Spot Prediction and Molecular Docking to α-Klotho.

Fibroblast growth factor 23 (FGF23) is a therapeutic target for treating hereditary and acquired hypophosphatemic disorders, such as X-linked hypophosphatemic (XLH) rickets and tumor-induced osteomalacia (TIO), respectively. FGF23-induced hypophosphatemia is mediated by signaling through a ternary complex formed by FGF23, the FGF receptor (FGFR), and α-Klotho. Currently, disorders of excess FGF23 are treated with an FGF23-blocking antibody, burosumab. Small-molecule drugs that disrupt protein/protein interactions necessary for the ternary complex formation offer an alternative to disrupting FGF23 signaling. In this study, the FGF23:α-Klotho interface was targeted to identify small-molecule protein/protein interaction inhibitors since it was computationally predicted to have a large fraction of hot spots and two druggable residues on α-Klotho. We further identified Tyr433 on the KL1 domain of α-Klotho as a promising hot spot and α-Klotho as an appropriate drug-binding target at this interface. Subsequently, we performed in silico docking of ∼5.5 million compounds from the ZINC database to the interface region of α-Klotho from the ternary crystal structure. Following docking, 24 and 20 compounds were in the final list based on the lowest binding free energies to α-Klotho and the largest number of contacts with Tyr433, respectively. Five compounds were assessed experimentally by their FGF23-mediated extracellular signal-regulated kinase (ERK) activities in vitro, and two of these reduced activities significantly. Both these compounds were predicted to have favorable binding affinities to α-Klotho but not have a large number of contacts with the hot spot Tyr433. ZINC12409120 was found experimentally to disrupt FGF23:α-Klotho interaction to reduce FGF23-mediated ERK activities by 70% and have a half maximal inhibitory concentration (IC50) of 5.0 ± 0.23 µM. Molecular dynamics (MD) simulations of the ZINC12409120:α-Klotho complex starting from in silico docking poses reveal that the ligand exhibits contacts with residues on the KL1 domain, the KL1-KL2 linker, and the KL2 domain of α-Klotho simultaneously, thereby possibly disrupting the regular function of α-Klotho and impeding FGF23:α-Klotho interaction. ZINC12409120 is a candidate for lead optimization.

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide-MHC Binding Predictions.

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell-based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2Db are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., K d < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell-based vaccines.

CTL Clonotypes with Higher TCR Affinity Have Better Ability to Reduce the HIV Latent Reservoir.

The success of the shock and kill strategy for the HIV cure depends both on the reactivation of the latent reservoir and on the ability of the immune system to eliminate infected cells. As latency reversal alone has not shown any impact in the size of the latent reservoir, ensuring that effector CTLs are able to recognize and kill HIV-infected cells could contribute to reservoir reduction. In this study, we investigated which functional aspects of human CTLs are associated with a better capacity to kill HIV-infected CD4+ T cells. We isolated Gag- and Nef-specific CTL clones with different TCR sequences from the PBMC of donors in acute and chronic infection. High-affinity clonotypes that showed IFN-γ production preserved even when the CD8 coreceptor was blocked, and clones with high Ag sensitivity exhibited higher efficiency at reducing the latent reservoir. Although intrinsic cytotoxic capacity did not differ according to TCR affinity, clonotypes with high TCR affinity showed a better ability to kill HIV-infected CD4+ T cells obtained from in vivo-infected PBMC and subjected to viral reactivation. Strategies aiming to specifically boost and maintain long-living memory CTLs with high TCR affinity in vivo prior to latency-reversing treatment might improve the efficacy of the shock and kill approach to reduce the latent reservoir.

Continuous Prophylactic Antiretrovirals/Antiretroviral Therapy Since Birth Reduces Seeding and Persistence of the Viral Reservoir in Children Vertically Infected With Human Immunodeficiency Virus.

BACKGROUND: Early antiretroviral therapy (ART) restricts the size of the human immunodeficiency virus (HIV) reservoir in infants. However, whether antiretroviral (ARV) prophylaxis given to exposed vertically infected children exerts similar effects remains unknown. METHODS: We measured total and integrated HIV DNA, as well as the frequency of CD4 T cells producing multiply spliced RNA (msRNA) after stimulation (inducible reservoir) in vertically infected Thai infants. Eighty-five infants were followed longitudinally for up to 3 years. We compared the size of the reservoir in children who received continuous ARV prophylaxis since birth vs those who never received or discontinued prophylaxis before initiating ART. We used samples from a cross-sectional cohort of 37 Thai children who had initiated ART within 6 months of life to validate our findings. RESULTS: Before ART, levels of HIV DNA and the frequencies of cells producing msRNA were significantly lower in infants who received continuous ARV prophylaxis since birth compared to those in whom ARV prophylaxis was discontinued or never initiated (P < .020 and P < .001, respectively). Upon ART initiation, total and integrated HIV DNA levels decayed significantly in both groups (P < .01 in all cases). Interestingly, the initial differences in the frequencies of infected cells persisted during 3 years on ART. The beneficial effect of prophylaxis on the size of the HIV reservoir was confirmed in the cross-sectional study. Importantly, no differences were observed between children who discontinued prophylactic ARVs before starting ART and those who delayed ART initiation without receiving prior prophylaxis. CONCLUSIONS: Neonatal ARV prophylaxis with direct transition to ART durably limits the size of the HIV reservoir.

Comparing a clinician-assisted and app-supported behavioral activation intervention to promote brain health and well-being in frontline care.

BACKGROUND: Positive psychiatry offers an unique approach to promote brain health and well-being in aging populations. Minimal interventions through behavioral activation to promote wellness are increasingly available using self-guided apps, yet little is known about the effectiveness of app technology or the difference between clinician-supported behavioral activation versus self-guided app methodologies. OBJECTIVES: Investigate the difference in users and outcomes between two methods of the Fountain of Health (FoH) positive psychiatry intervention for behavioral activation to promote brain health and well-being: (1) clinician-assisted and (2) independent app use for behavioral self-management. DESIGN AND SETTING: As part of a larger knowledge translation intervention in positive psychiatry, two specific methods of a behavioral activation intervention were retrospectively compared. PARTICIPANTS: Two subsets of patients were compared; 254 clinician-assisted patients; 333 independent app users. INTERVENTION: A minimal positive psychiatry intervention in frontline care using the FoH health and behavior change clinical tools. MEASUREMENTS: Main outcomes were changes in psychological (health and resilience, well-being scores) and behavioral indices (goal attainment, items of goal SMART-ness). User profiles (age, sex and completion rates) were also compared. RESULTS: Clinician-assisted patients were more likely to be male, older, and have lower health and resilience scores at baseline. Clinician-assisted patients had notably higher completion rates (99.2% vs. 10.8%). Psychological outcomes (improved health and resilience, and well-being) were similar regardless of intervention method for those who completed the intervention. Behavioral outcomes revealed clinician-assisted patients set goals that better adhered to key goal-setting items. CONCLUSIONS: Clinician-patient relationships appear to be an important factor for intervention completion and behavioral outcomes, while further exploration of best practices for intervention completion using health apps in clinical practice is needed. A preliminary goal-setting methodology for effective behavioral activation, to promote brain health and wellness, is given.

iPNHOT: a knowledge-based approach for identifying protein-nucleic acid interaction hot spots.

BACKGROUND: The interaction between proteins and nucleic acids plays pivotal roles in various biological processes such as transcription, translation, and gene regulation. Hot spots are a small set of residues that contribute most to the binding affinity of a protein-nucleic acid interaction. Compared to the extensive studies of the hot spots on protein-protein interfaces, the hot spot residues within protein-nucleic acids interfaces remain less well-studied, in part because mutagenesis data for protein-nucleic acids interaction are not as abundant as that for protein-protein interactions. RESULTS: In this study, we built a new computational model, iPNHOT, to effectively predict hot spot residues on protein-nucleic acids interfaces. One training data set and an independent test set were collected from dbAMEPNI and some recent literature, respectively. To build our model, we generated 97 different sequential and structural features and used a two-step strategy to select the relevant features. The final model was built based only on 7 features using a support vector machine (SVM). The features include two unique features such as ∆SASsa1/2 and esp3, which are newly proposed in this study. Based on the cross validation results, our model gave F1 score and AUROC as 0.725 and 0.807 on the subset collected from ProNIT, respectively, compared to 0.407 and 0.670 of mCSM-NA, a state-of-the art model to predict the thermodynamic effects of protein-nucleic acid interaction. The iPNHOT model was further tested on the independent test set, which showed that our model outperformed other methods. CONCLUSION: In this study, by collecting data from a recently published database dbAMEPNI, we proposed a new model, iPNHOT, to predict hotspots on both protein-DNA and protein-RNA interfaces. The results show that our model outperforms the existing state-of-art models. Our model is available for users through a webserver: http://zhulab.ahu.edu.cn/iPNHOT/ .

Predicting kinase inhibitors using bioactivity matrix derived informer sets.

Prediction of compounds that are active against a desired biological target is a common step in drug discovery efforts. Virtual screening methods seek some active-enriched fraction of a library for experimental testing. Where data are too scarce to train supervised learning models for compound prioritization, initial screening must provide the necessary data. Commonly, such an initial library is selected on the basis of chemical diversity by some pseudo-random process (for example, the first few plates of a larger library) or by selecting an entire smaller library. These approaches may not produce a sufficient number or diversity of actives. An alternative approach is to select an informer set of screening compounds on the basis of chemogenomic information from previous testing of compounds against a large number of targets. We compare different ways of using chemogenomic data to choose a small informer set of compounds based on previously measured bioactivity data. We develop this Informer-Based-Ranking (IBR) approach using the Published Kinase Inhibitor Sets (PKIS) as the chemogenomic data to select the informer sets. We test the informer compounds on a target that is not part of the chemogenomic data, then predict the activity of the remaining compounds based on the experimental informer data and the chemogenomic data. Through new chemical screening experiments, we demonstrate the utility of IBR strategies in a prospective test on three kinase targets not included in the PKIS.

Oral Vitamin C (500 mg/d) to Pregnant Smokers Improves Infant Airway Function at 3 Months (VCSIP). A Randomized Trial.

Rationale: We reported a randomized trial demonstrating daily supplemental vitamin C to pregnant smokers significantly improved newborn pulmonary function tests. The current study tests these results in a new cohort using infant pulmonary function tests. Objectives: To determine if infants of pregnant smokers randomized to daily supplemental vitamin C would have improved forced expiratory flows (FEFs) at 3 months of age compared with those randomized to placebo, and to investigate the association of the α5 nicotinic acetylcholine receptor. Methods: A randomized, double-blind, placebo-controlled trial was conducted at three centers. Two hundred fifty-one pregnant smokers were randomized at 13-23 weeks of gestation: 125 randomized to vitamin C (500 mg/d) and 126 to placebo. Measurements and Main Results: The primary outcome was FEF75 at 3 months of age performed with the raised volume rapid thoracic compression technique (Jaeger/Viasys). FEF50 and FEF25-75 obtained from the same expiratory curves were prespecified secondary outcomes. The infants of pregnant smokers randomized to vitamin C (n = 113) had the following FEFs at 3 months of age compared with those randomized to placebo (n = 109) as measured by FEF75 (200.7 vs. 188.7 ml/s; adjusted 95% confidence interval [CI] for difference, -3.33 to 35.64; P = 0.10), FEF50 (436.7 vs. 408.5 ml/s; adjusted 95% CI for difference, 6.10-61.30; P = 0.02), and FEF25-75 (387.4 vs. 365.8 ml/s; adjusted 95% CI for difference, 0.92-55.34; P = 0.04). Infant FEFs seemed to be negatively associated with the maternal risk alleles for the α5 nicotinic acetylcholine receptor (rs16969968). Conclusions: Although the primary outcome of FEF75 was not improved after vitamin C supplementation to pregnant smokers, the predetermined secondary outcomes FEF50 and FEF25-75 were significantly improved. These results extend our previous findings and demonstrate improved airway function (FEF50 and FEF25-75) at 3 months of age in infants after vitamin C supplementation to pregnant smokers. Clinical trial registered with www.clinicaltrials.gov (NCT01723696).

Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey.

BACKGROUND: Heart age calculators are used worldwide to engage the public in cardiovascular disease (CVD) prevention. Experimental studies with small samples have found mixed effects of these tools, and previous reports of population samples that used web-based heart age tools have not evaluated psychological and behavioral outcomes. OBJECTIVE: This study aims to report on national users of the Australian heart age calculator and the follow-up of a sample of users. METHODS: The heart age calculator was launched in 2019 by the National Heart Foundation of Australia. Heart age results were calculated for all users and recorded for those who signed up for a heart age report and an email follow-up over 10 weeks, after which a survey was conducted. CVD risk factors, heart age results, and psychological and behavioral questions were analyzed using descriptive statistics and chi-square tests. Open responses were thematically coded. RESULTS: There were 361,044 anonymous users over 5 months, of which 30,279 signed up to receive a heart age report and 1303 completed the survey. There were more women (19,840/30,279, 65.52%), with an average age of 55.67 (SD 11.43) years, and most users knew blood pressure levels (20,279/30,279, 66.97%) but not cholesterol levels (12,267/30,279, 40.51%). The average heart age result was 4.61 (SD 4.71) years older than the current age, including (23,840/30,279, 78.73%) with an older heart age. For the survey, most users recalled their heart age category (892/1303, 68.46%), and many reported lifestyle improvements (diet 821/1303, 63.01% and physical activity 809/1303, 62.09%). People with an older heart age result were more likely to report a doctor visit (538/1055, 51.00%). Participants indicated strong emotional responses to heart age, both positive and negative. CONCLUSIONS: Most Australian users received an older heart age as per international and UK heart age tools. Heart age reports with follow-up over 10 weeks prompted strong emotional responses, high recall rates, and self-reported lifestyle changes and clinical checks for more than half of the survey respondents. These findings are based on a more engaged user sample than previous research, who were more likely to know blood pressure and cholesterol values. Further research is needed to determine which aspects are most effective in initiating and maintaining lifestyle changes. The results confirm high public interest in heart age tools, but additional support is needed to help users understand the results and take appropriate action.

DBSI server: DNA binding site identifier.

UNLABELLED: : Protein-nucleic acid interactions are among the most important intermolecular interactions in the regulation of cellular events. Identifying residues involved in these interactions from protein structure alone is an important challenge. Here we introduce the webserver interface to DNA Binding Site Identifier (DBSI), a powerful structure-based SVM model for the prediction and visualization of DNA binding sites on protein structures. DBSI has been shown to be a top-performing model to predict DNA binding sites on the surface of a protein or peptide and shows promise in predicting RNA binding sites. AVAILABILITY AND IMPLEMENTATION: Server is available at http://dbsi.mitchell-lab.org CONTACT: jcmitchell@wisc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The D0 Ig-like domain plays a central role in the stronger binding of KIR3DL2 to B27 free H chain dimers.

We proposed that the killer cell Ig-like receptor KIR3DL2 binding more strongly to HLA-B27 (B27) ß2-microglobulin free H chain (FHC) dimers than other HLA-class I molecules regulates lymphocyte function in arthritis and infection. We compared the function of B27 FHC dimers with other class I H chains and identified contact residues in KIR3DL2. B27 FHC dimers interacted functionally with KIR3DL2 on NK and reporter cells more strongly than did other class I FHCs. Mutagenesis identified key residues in the D0 and other Ig-like domains that were shared and distinct from KIR3DL1 for KIR3DL2 binding to B27 and other class I FHCs. We modeled B27 dimer binding to KIR3DL2 and compared experimental mutagenesis data with computational "hot spot" predictions. Modeling predicts that the stronger binding of B27 dimers to KIR3DL2 is mediated by nonsymmetrical complementary contacts of the D0 and D1 domains with the α1, α2, and α3 domains of both B27 H chains. In contrast, the D2 domain primarily contacts residues in the α2 domain of one B27 H chain. These findings provide novel insights about the molecular basis of KIR3DL2 binding to B27 and other ligands and suggest an important role for KIR3DL2-B27 interactions in controlling the function of NK cells in B27(+) individuals.

Breast Cancer Screening and Prevention.

This issue provides a clinical overview of breast cancer screening and prevention, focusing on risk assessment, screening, prevention, and practice improvement. The content of In the Clinic is drawn from the clinical information and education resources of the American College of Physicians (ACP), including MKSAP (Medical Knowledge and Self-Assessment Program). Annals of Internal Medicine editors develop In the Clinic in collaboration with the ACP's Medical Education and Publishing divisions and with the assistance of additional science writers and physician writers.

Mitochondrial COQ9 is a lipid-binding protein that associates with COQ7 to enable coenzyme Q biosynthesis.

Coenzyme Q (CoQ) is an isoprenylated quinone that is essential for cellular respiration and is synthesized in mitochondria by the combined action of at least nine proteins (COQ1-9). Although most COQ proteins are known to catalyze modifications to CoQ precursors, the biochemical role of COQ9 remains unclear. Here, we report that a disease-related COQ9 mutation leads to extensive disruption of the CoQ protein biosynthetic complex in a mouse model, and that COQ9 specifically interacts with COQ7 through a series of conserved residues. Toward understanding how COQ9 can perform these functions, we solved the crystal structure of Homo sapiens COQ9 at 2.4 Å. Unexpectedly, our structure reveals that COQ9 has structural homology to the TFR family of bacterial transcriptional regulators, but that it adopts an atypical TFR dimer orientation and is not predicted to bind DNA. Our structure also reveals a lipid-binding site, and mass spectrometry-based analyses of purified COQ9 demonstrate that it associates with multiple lipid species, including CoQ itself. The conserved COQ9 residues necessary for its interaction with COQ7 comprise a surface patch around the lipid-binding site, suggesting that COQ9 might serve to present its bound lipid to COQ7. Collectively, our data define COQ9 as the first, to our knowledge, mammalian TFR structural homolog and suggest that its lipid-binding capacity and association with COQ7 are key features for enabling CoQ biosynthesis.

Expression patterns of Ikaros family members during positive selection and lineage commitment of human thymocytes.

The Ikaros family of transcription factors is essential for normal T-cell development, but their expression pattern in human thymocytes remains poorly defined. Our goal is to determine how protein levels of Ikaros, Helios and Aiolos change as human thymocytes progress through the positive selection and lineage commitment stages. To accomplish this goal, we used multi-parameter flow cytometry to define the populations in which positive selection and lineage commitment are most likely to occur. After human thymocytes express CD3 and receive positive selection signals, the cells down-regulate expression of CD4 to become transitional single-positive (TSP) CD8+ thymocytes. At this stage, there was a transient increase in the Ikaros, Helios and Aiolos protein levels. After the TSP CD8+ developmental stage, some thymocytes re-express CD4 and become CD3hi double-positive thymocytes before down-regulating CD8 to become mature single-positive CD4+ thymocytes. Except for regulatory T cells, Helios protein levels declined and Aiolos protein levels transiently increased during CD4+ T-cell maturation. For thymocytes progressing toward the CD8+ T-cell lineage, TSP CD8+ thymocytes increase their expression of CD3 and maintain high levels of Aiolos protein as the cells complete their maturation. In summary, we defined the TSP CD8+ developmental stage in human T-cell development and propose that this stage is where CD4/CD8 lineage commitment occurs. Ikaros, Helios and Aiolos each undergo a transient increase in protein levels at the TSP stage before diverging in their expression patterns at later stages.

Challenges of intra-institutional transfer of care from paediatric to adult congenital cardiology: the need for retention as well as transition.

BACKGROUND: Transferring patients with CHD from paediatric to adult care has been challenging, especially across institutions. Within a single institution, some issues such as provider interaction, information exchange, or administrative directives should not play a significant role, and should favour successful transfer. OBJECTIVE: We studied patients who were eligible for transfer to the adult congenital heart disease service within our institution in order to identify factors associated with successful transfer to adult care providers versus failure to transfer. METHODS: Patients above18 years of age with CHD who were seen by paediatric cardiologists before January, 2008 were identified through a patient-care database. Records were reviewed to determine follow-up between 2008 and 2011 and to determine whether the patient was seen in the adult congenital cardiology clinic, paediatric cardiology clinic, or had no follow-up, and statistical comparisons were made between groups. RESULTS: After reviewing 916 records, 229 patients were considered eligible for transition to adult congenital cardiology. Of these, 77 (34%) were transferred successfully to adult congenital cardiology, 47 (21%) continued to be seen by paediatric cardiologists, and 105 (46%) were lost to follow-up. Those who transferred successfully differed with regard to complexity of diagnosis, insurance, and whether a formal referral was made by a paediatric care provider. Only a small fraction of the patients who were lost to follow-up could be contacted. CONCLUSION: Within a single institution, with shared information systems, administrations, and care providers, successful transfer from paediatric to adult congenital cardiology was still poor. Efforts for successful retention are just as vital as those for transfer.