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BACKGROUND: The application of machine learning (ML) to analyze clinical data with the goal to predict patient outcomes has garnered increasing attention. Ensemble learning has been used in conjunction with ML to improve predictive performance. Although stacked generalization (stacking), a type of heterogeneous ensemble of ML models, has emerged in clinical data analysis, it remains unclear how to define the best model combinations for strong predictive performance. This study develops a methodology to evaluate the performance of "base" learner models and their optimized combination using "meta" learner models in stacked ensembles to accurately assess performance in the context of clinical outcomes. METHODS: De-identified COVID-19 data was obtained from the University of Louisville Hospital, where a retrospective chart review was performed from March 2020 to November 2021. Three differently-sized subsets using features from the overall dataset were chosen to train and evaluate ensemble classification performance. The number of base learners chosen from several algorithm families coupled with a complementary meta learner was varied from a minimum of 2 to a maximum of 8. Predictive performance of these combinations was evaluated in terms of mortality and severe cardiac event outcomes using area-under-the-receiver-operating-characteristic (AUROC), F1, balanced accuracy, and kappa. RESULTS: The results highlight the potential to accurately predict clinical outcomes, such as severe cardiac events with COVID-19, from routinely acquired in-hospital patient data. Meta learners Generalized Linear Model (GLM), Multi-Layer Perceptron (MLP), and Partial Least Squares (PLS) had the highest AUROC for both outcomes, while K-Nearest Neighbors (KNN) had the lowest. Performance trended lower in the training set as the number of features increased, and exhibited less variance in both training and validation across all feature subsets as the number of base learners increased. CONCLUSION: This study offers a methodology to robustly evaluate ensemble ML performance when analyzing clinical data.
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COVID-19 , Humans , Retrospective Studies , Neural Networks, Computer , Algorithms , Machine LearningABSTRACT
This article explores some of the ways in which the COVID-19 pandemic has served as a collective critical event for anthropologists and other social scientists, examining how it has promoted new configurations of the research imagination. We draw on our own experiences of participating in a team of 17 researchers, hailing from anthropology and anthropology-adjacent disciplines, to research social life in Aotearoa/New Zealand during the pandemic, examining how our own research imaginations were transformed during, and via, the process of our collaboration. When our project first began, many of us had doubts reflective of norms, prejudices and anxieties that are common in our disciplines: that the group would be too large to function effectively, or that it would be impossible to develop an approach to authorship that would allow everyone to feel their contributions had been adequately recognised. In practice, the large group size was a key strength in allowing our group to work effectively. Difficulties with authorship did not arise from within the group but from disconnects between our preferred ways of working and the ways authorship was imagined within various professional and publishing bodies. We conclude that large-scale collaborations have many points in their favour, and that the research imaginations of funders, journals, universities and professional associations should be broadened to ensure that they are encouraged, supported and adequately rewarded. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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Background: The COVID-19 pandemic has made neurology clinic waiting times longer. To prevent a build-up of patients waiting, we introduced a neurology advanced referral management system (NARMS) to deal with new referrals from GPs, using advice, investigations, or the telephone, as alternatives to face-to-face (FF) assessment. Methods: For six months, electronic referrals from GPs were triaged to the above categories. We recorded the numbers in each category, patient satisfaction, inter-consultant triage variation, re-referrals, and calculated CO2 emissions. Results: There were 573 referrals. Triage destinations were advice 33%, investigations 27%, telephone 17%, and FF 33%. Of patients referred for MRI, 95% were happy not to be seen if their investigation was normal. Less-experienced consultants triaged 20% and 30% respectively, to advice or investigations, compared with 40% by a triage-experienced neurologist. Four percent were re-referred. Numbers on the waiting list did not increase. CO2 emissions were reduced by 50%. Discussion: Two thirds of neurological referrals from GPs did not need to be seen FF and 50% were dealt with without the neurologist meeting the patient. Carbon emission was halved. This system should be employed more, with FF examination reserved for those patients who need a neurological examination for diagnosis and management.
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) recently emerged as the cause of a global pandemic. Infection with SARS-CoV-2 can result in COVID-19 with both acute and chronic disease manifestations that continue to impact many patients long after the resolution of viral replication. There is therefore great interest in understanding the host factors that contribute to COVID-19 pathogenesis. In this review, we address the role of hyaluronan (HA), an extracellular matrix polymer with roles in inflammation and cellular metabolism, in COVID-19 and critically evaluate the hypothesis that HA promotes COVID-19 pathogenesis. We first provide a brief overview of COVID-19 infection. Then we briefly summarize the known roles of HA in airway inflammation and immunity. We then address what is known about HA and the pathogenesis of COVID-19 acute respiratory distress syndrome (COVID-19 ARDS). Next, we examine potential roles for HA in post-acute SARS-CoV-2 infection (PASC), also known as "long COVID" as well as in COVID-associated fibrosis. Finally, we discuss the potential therapeutics that target HA as a means to treat COVID-19, including the repurposed drug hymecromone (4-methylumbelliferone). We conclude that HA is a promising potential therapeutic target for the treatment of COVID-19.
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COVID-19 , Humans , SARS-CoV-2 , Hyaluronic Acid , Inflammation/pathology , Post-Acute COVID-19 SyndromeABSTRACT
Purpose : Microincision vitrectomy surgery (MIVS) studies have shown low complication rates. In the setting of the COVID-19 pandemic and rural satellite clinics, we investigated the role of telemedicine as an alternative to postoperative visit (POV) regimens after uncomplicated MIVS. Methods : This IRB approved, prospective single-site, and single-surgeon study included patients without any history of glaucoma, ocular trauma, or severe systemic or ocular disease who underwent uncomplicated MIVS for any indication between January-August 2021. Prophylactic topical pressure-lowering drops were prescribed if POV intraocular pressure (IOP) was ≥22 mmHg. POVs included the same day after surgery, week(s) 1, 2, 8, and 12. Patients were randomly assigned (1:1) into two arms: telemedicine (TM) or In-person (IP). Weeks 1 and 8 POV utilized protocol-based and questionnaire guided undilated exams performed by an ophthalmology fellow that were conducted either TM or IP, according to arm assignment. Any patients with concerning symptoms identified at these visits were scheduled for dilated exams with the surgeon. All patients underwent dilated exams performed by the surgeon on the same day after surgery, weeks 2 and 12. Primary endpoint was mean best corrected visual acuity (BCVA). Secondary endpoints included changes in intraocular pressure (IOP), retinal nerve fiber layer thickness, and number of additional visits. Statistical analysis included Mann Whitney U and chi-square tests. Results : Fifty-two eyes from 50 patients (33 female, 17 male;p-value=0.02) with mean ages of 68.4±6.8 years underwent 55 total surgeries with 25 or 27G MIVS platforms. Forty-seven patients have completed all POVs. Mean preop BCVA logMAR was 0.53±0.55 and 0.40±0.45, and at 12 weeks, they were 0.39±0.45 and 0.26±0.33 for the TM and IP groups, respectively. No significant between-group differences were found for primary or secondary outcomes. All cases of abnormal IOP resolved by the following POV with pressure lowering drops. Concerning symptoms were identified in five patients requiring additional visits, revealing two cases of worsening macular edema (1 TM and 1 IP) and one case each of cataract progression (TM), vitreous hemorrhage (IP), and macular hole recurrence (TM). No complications presented at the TM or IP visits. Conclusions : Telemedicine-assisted POV regimens may be a safe and convenient alternative for patients undergoing uncomplicated MIVS.
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Introduction: During theCOVID-19 pandemic we were faced with a large number of critical care discharges recovering from prolonged intensive care admission and severe lung injury at our 500 bed hospital in the South East of England. These patients often had complex rehabilitation needs and rehabilitation of these patients had been challenged by social distancing and the reconfiguration of many outpatient departments. Prior to the covid pandemic our rehabilitation pathway consisted of a nurse led follow up that focussed on psychological recovery and, following initial assessment, physiotherapy that included musculoskeletal therapy, 1:1 or small group exercises and respiratory physiotherapy. We developed a new pathway during the COVID-19 pandemic that united these above services into a one-stop multidisciplinary service that included clinician follow up and utilised smart watch technology from Fitbit watches to aid recovery of our ICU discharges. Method: Prior to discharge patients had a comprehensive set of assessments to identify physical and psychological needs. This included an incremental shuttlewalk test, oneminute sit-to-stand test, patient health questionnaire-9 (PHQ-9), generalized anxiety depression questionnaire -7 and Chelsea critical care physical assessment (CPAX). Patients were offered an exercise programme, depending on level of function, and referred to appropriate community services as required. Patients received Fitbit charge 3watches and were asked towear these as often as they felt able. At three months following discharge patients attended a multidisciplinary clinic consisting of an intensive care clinician, physiotherapist, and nursing staff. Outcome measures were re-assessed, and the patient had access to ongoing physio, nursing and medical input to support their recovery. Fitbit data was reviewed and incorporated into future goal setting. In addition, patients were invited to a relative and patient support group as an opportunity to meet other critical care survivors and for their relatives to share their experiences of recovery. They were also offered the chance to visit the ICU to aid physiological recovery. Results: The one-stop nature of the clinic allowed a resource efficient means for multi disciplinary care to be delivered to patients. The majority of patients found the support group extremely beneficial. Patients reported they found it helpful being able to share experiences, listen to others and see people at different stages in their recovery. Relatives also found the experience useful to deal with the traumatic experience of a critically ill loved one. Smart watches were well received by patients and over 80% of patients felt the watch aided their recovery. The watches also added a unique dimension to the MDT meeting, able to pick up changes in daily activity levels, rapidly alerting the clinician to a potential problem in that patient. Conclusion: The service is continually evolving. Future plans aim;to use smart watches for all ICU discharges with an integrated app to promote recovery and allow remote feedback, to use a Post-ICU Presentation Screen (PICUPS) and rehabilitation prescription to inform rehabilitation needs and to include a psychologist into the clinic to improve patient recovery after ICU admission.
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Purpose of Study Firearm violence comprises a large percentage of pediatric injuries within the United States. Among all highincome countries, 91% of childhood firearm deaths occur in US children younger than 14 years. Coronavirus-19 Pandemic is associated with increased firearm violence, but little is known about the impact on children. Our objective is to evaluate the pediatric rates of firearm-related injuries within the state of Connecticut (CT) before- and during-COVID. Methods Used Data was ed from the Connecticut Health Information Management Exchange (CHIME) datasets from 2016-2020. All cases of firearm related injuries were identified by ICD -10 codes. Two study groups were created using events occurring in 2018 and 2019 (before-COVID) and events occurring in 2020 (during COVID). Before and during COVID groups were compared to assess differences in rates of injuries and any associations by age, sex, race, cause of injury, bodily location of injury, and geographic location of event. Summary of Results A total of 188 encounters were identified. The mean age was 14 years (SD+/- 3.5), 20% girls, 80% boys, 43% White, 37% Black, and 12% Hispanic. The overall rate of firearm injuries before COVID was 1.6 per 100,000 and during COIVD was 2.1/100,000 (p<0.01). Adjusting for population changes, the incidence of firearm injuries in CT increased by 33%. White and Black children accounted for similar proportion of injuries in all time periods. In all years, about 80% were unintentional while half were injured in suburban areas compared to urban and rural (p=0.97). Almost half of all injuries involved an extremity. Conclusions The proportion of children with firearm related injuries significantly increased during COVID compared to the preceding two years. The age, sex and race/ethnicity of injured children was similar before and during the COVID-19 pandemic. Unintentional injury accounted for the majority of injuries. Overall the proportion of White and Black children injured by firearms was similar, and children living in suburban areas were injured more than other areas. (Table Presented).
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The COVID-19 pandemic has increased the worldwide production and use of disposable plastic face masks (DPFMs). The release of micro- and nanopollutants into the environment is one of the impacts derived from regulated and unregulated disposal of DPFMs. This study focuses on the emission of pollutants from medical-grade DPFMs when submerged in deionized water, simulating regulated and unregulated disposal of these masks. Three brands of FFP2 and three brands of Type IIR medical masks, produced in various countries (UK, EU, and non-EU), were investigated. Field emission gun scanning electron microscopy (FEG-SEM) was used to obtain high-resolution images of the micro- and nanoparticles, and 0.02 µm pore size inorganic membranes were used to retain and subsequently analyze smaller particle size nanoparticles (>20 nm) released from the DPFMs. Particles and fibers in the micro- and nanoscale were found in all six DPFM brands. SEM with energy-dispersive spectroscopy analysis revealed the presence of particles containing different heavy metals like lead, mercury, and arsenic. Inductively coupled plasma mass spectrometry analysis confirmed the leaching of trace heavy metals to water (antimony up to 2.41 µg/L and copper up to 4.68 µg/L). Liquid chromatography-mass spectrometry analysis identified polar organic species related to plastic additives and contaminants such as polyamide-66 monomers and oligomers.
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Background. Patient and treatment-related factors have been used to stratify COVID-19 outcomes;however, studies in the general population and specifically veterans have yielded variable results. This study was designed to assess how baseline characteristics and interventions correlate with clinical outcomes in patients admitted with COVID-19 at a large academic Veterans Affairs hospital. Methods. Retrospective chart review was conducted on veterans admitted to the hospital with COVID-19 between March 1 to December 31, 2020. Veterans without respiratory symptoms attributed to COVID-19 or enrolled in a COVID-19 clinical trial were excluded. Primary outcome was in-hospital mortality up to 28 days. Secondary outcomes were 90-day mortality, discharge to higher level of care or remained in the hospital within 28 days, and discharge with new oxygen requirement within 28 days. Patient characteristics and therapeutic interventions were assessed for correlation with primary and secondary outcomes. Results. Of 497 hospitalized patients reviewed, 293 were included for analysis;94% were male;average age was 68 years with 64.9% of veterans greater than 65 years of age;43.7% were Black;17.4% were Hispanic. In-hospital mortality at 28-days and 90-day mortality were 18.1% and 21.5%, respectively. At discharge, 34.1% had a new oxygen requirement and 17.5% went to a higher level of care. Patients that died in-hospital were more likely to be greater than 65 years of age (p< 0.001), Hispanic (p=0.007), have chronic kidney disease (CKD) (p=0.005), be admitted to ICU (p< 0.001);receive dexamethasone (p< 0.001), convalescent plasma (p< 0.001), or antibiotics (p< 0.001);require mechanical ventilation (p< 0.001);or have new onset atrial fibrillation (p< 0.001). Veterans also had higher levels of inflammatory markers within 48 hours of hospital admission (see Table 2) and longer length of hospital stay (< 0.001). There was a trend for patients that died in the hospital within 28-days to be less likely to be Black (p=0.06). Conclusion. Patients were more likely to die in-hospital within 28-days if they were greater than 65 years of age, Hispanic and had CKD. Veterans that died in-hospital within 28-days had higher inflammatory marker levels and were more likely to receive COVID-19 treatments.
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When Covid-19 appeared in the USA at the beginning of 2020, there was no treatment or vaccine. The only way to deal with the virus was containment, which resulted in business and agency closures. The impact on the economy was enormous, particularly on the lives of minorities and financially vulnerable people. The present study investigated the impact of COVID-19 on the lives of vulnerable people through qualitative interviews of major social service and healthcare agencies. The results show how the pandemic furthered existing disparities in access to a variety of services and supports.
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This article reports on the findings of a study that explored the benefits and challenges for women of working at an Australian regional university in early 2020 before the COVID-19 pandemic. It examines whether living and working at a regional university with dispersed campuses presented particular challenges for women and whether it had an impact on their career progression. Twenty-one women supplied written responses to a list of questions provided by the researchers. The main finding was that women enjoyed working in teams and preferred flexibility, autonomy and positive teamwork environments. To address challenges identified in the study about working across dispersed campuses and the limitations of virtual communication, particularly in the current pandemic, the article investigates the feasibility of a blended approach to teamwork using the concept of a third space.
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Introduction: One of the major impacts of the COVID-19 pandemic on healthcare has been the increased utilization of technology. When face-to-face visits pose a public health concern, providers across various specialties have become increasingly reliant on virtual visits, phone calls, and MyChart messages to provide care. With this shift in healthcare delivery, an analysis of the impact on healthcare is needed. The objective of this study is to determine how increasing telemedicine utilization affects the care provided to pediatric gastroenterology patients with a focus on inpatient acuity and the care methods prior to admission. Methods: A retrospective chart review of patients admitted under the care of the pediatric gastroenterology team at Doernbecher Children's Hospital was performed for April - June 2019, 2020, and 2021. Length of stay and requirement of intensive care (PICU) admission were used as measures of inpatient acuity with secondary outcomes being the number of clinic visits, telephone calls, and MyChart messages in the 3 months preceding admission. Descriptive statistics were used for demographic data and T-tests were used for continuous variables and Fischer's Exact test for binary variables. Results: The average length of stay per patient was 4.14 days in 2019 compared to 3.88 days in 2021, which was not significantly different (Table 1). There was no significant difference in the percentage of patients admitted to the PICU. In 2021, 70.6% of admitted patients were seen in the GI clinic in the 3 months prior to admission with an average of 2.67 visits per patient compared to 42.9% in 2019 (p-value 0.04) with an average of 1.33 visits per patient. 67.6% of patients called the provider in the 3 months prior to admission in 2021 with an average of 3.57 calls per patients compared to 35.7% in 2019 (p-value 0.02) with an average of 3.8 calls per patient. In 2021, 50% of patients used MyChart with an average of 6.53 messages, compared to 31.4% with an average of 2.67 messages in 2019 (p-value 0.03). Discussion: With the transition to the telemedicine platform in response to the COVID-19 pandemic, a potential concern was that providers would not be able to provide as effective of medical care. Thereby, patients might end up being sicker at the time of hospital admission. Notably, inpatient acuity as measured by length of stay or PICU admissions did not significantly change between 2019, 2020, and 2021. This observation suggests that despite potential limitations of the telemedicine platform, such as communication challenges or an in ability to conduct a live physical exam, patients and providers have been able to adjust and effectively share their medical concerns. Since the introduction of the telemedicine platform, patient healthcare seeking behaviors have changed as there have been a significant increase percentage of admitted patients utilizing virtual visits, telephone calls, and MyChart messages prior to admission. In addition, for patients using these methods of communication, there was a noticeable increase in the frequency of use of both virtual visits and MyChart messages, suggesting that patients may becoming more comfortable and potentially reliant on these communication methods. As this increase in utilization has not decreased length of hospitalization, it is possible that telemedicine has lowered the barrier to contacting providers, thus changing patient healthcare access behaviors. Limitations to this study include small sample size and the generalizability of this study as this is a single center study. Conclusion: The COVID-19 pandemic has forced providers to shift how they deliver care, with increased reliance on remote methods such as virtual visits, phone calls, and MyChart messages. We expected that limitations to in person care would mean that pediatric GI patients would be coming to the hospital sicker than before the pandemic. What was found instead was that adaptations were made to provide care virtually with an increase in non-in-person clinical contact while there was no change in length of inpatient stay. Future analysis will focus on longer term data and seek to determine if there are any differences in acuity based on diagnosis.
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P97 Table 1Demographics and clinical characteristics of participants at hospital admission and follow up for wave 1 and 2 admissions Wave 1 Wave 2 p-value N = 400 N = 400 Demographics and Lifestyle Age (years) (Median, IQR) 61 (50 -74) 61 (51 - 74) 0.59 Male gender (N,%) 247 (61.8%) 237 (59.3%) 0.47 Ethnicity (White) (N,%) 200 (50.0%) 195 (48.8%) 0.001* Smoking status – Never smoker (N,%) 215 (53.8%) 219 (54.8%) 0.58 BMI (kg/m2) (Median, IQR) 26.8 (24.1 - 29.4) 27.7 (24.3 - 31.6) 0.015 Underlying clinical status Clinical Frailty Score (Median, IQR) 2 (2, 4) N = 332 3 (2, 3) N = 384 0.001 Shielding Status (N,%) Extremely vulnerable HCP issued letter 32 (10.1%) 23 (7.2%) 39 (11.2%) 5 (1.4%) 0.001 Covid Admission Severity Parameters Total number of symptoms (Median, IQR) 4 (3 - 6) 3 (2 - 3) <0.0001 NEWS2 score (Median, IQR) 5 (2 - 7) N = 372 4 (3 - 6) N = 379 0.60 TEP status – For full escalation (N,%) 284/365 (77.8%) 361/400 (90.3%) <0.0001 Maximum respiratory support (N,%) CPAP NIV N= 377 10 (2.7%) 2 (0.5%) N = 400 32 (8.0%) 5 (1.3%) <0.0001 Received anti-viral or immunosuppressive drugs (N,%) 23/374 (6.2%) 127/400 (31.8%) <0.0001 ITU admission (N,%) 62/377 (16.5%) 43/400 (10.8%) 0.02 Intubation (N,%) 49/364 (13.5%) 19/400 (4.8%) <0.0001 Pulmonary Embolus (N,%) 22/360 (6.1%) 24/395 (6.1%) 0.98 Follow-up Outcomes N = 322 N = 365 Mental Health Outcomes PHQ2 score ≥ 3 (N,%) 47 (15.4%) 34 (9.9%) 0.04 TSQ score ≥ 5 (N,%) 44 (14.9%) 12 (3.3%) <0.0001 Physical Recovery and Symptoms Not returned to work (N,%) 76 (24.8%) 114 (33.6%) 0.03 Improved Sleep quality (N,%) 168 (61.5%) 265 (78.4%) <0.0001 Improved Fatigue (N,%) 241 (87.6%) 307 (88.7%) 0.91 Improved Cough (N,%) 194 (69.5%) 291 (84.8%) <0.0001 Improved Breathlessness (N,%) 213 (76.1%) 311 (89.6%) <0.0001 Total Number of Symptoms (Median, IQR) 1 (0 - 2) N=314 0 (0 – 1) N=364 Radiology outcomes (N,%) Normalised Significantly Improved Not significantly improved Worsened N=309 211 (68.3%) 55 (17.8%) 2 (0.7%) 30 (9.7%) N=279 187 (67.0%) 65 (23.3%) 13 (4.7%) 14 (5.0%) <0.0001 *p value likely attributable to differences in unknown ethnicityConclusionThese data suggest second wave pa ients, although frailer, presented with fewer symptoms and experienced improved hospital admission trajectory. They demonstrated improved self-reported mental health and physical recovery outcomes despite earlier follow-up, possibly attributed to improved in-hospital treatment. Supporting recovery remains a clinical priority given many patients had not returned to work.ReferenceSaito S, et al. First and second COVID-19 waves in Japan: comparison of disease severity and characteristics. J Infect. 2021;82(4):84-123.
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Chatbots have the potential of being used as dialogical argumentation systems for behaviour change applications. They thereby offer a cost-effective and scalable alternative to in-person consultations with health professionals that users could engage in from the comfort of their own home. During events like the global COVID-19 pandemic, it is even more important than usual that people are well informed and make conscious decisions that benefit themselves. Getting a COVID-19 vaccine is a prime example of a behaviour that benefits the individual, as well as society as a whole. In this paper, we present a chatbot that engages in dialogues with users who do not want to get vaccinated, with the goal to persuade them to change their stance and get a vaccine. The chatbot is equipped with a small repository of arguments that it uses to counter user arguments on why the user is reluctant to get a vaccine. We evaluate our chatbot in a study with participants. © 2021, Springer Nature Switzerland AG.
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Background: Persons living with HIV (PLWH) face a number of nutritional issues including dyslipidaemia, non-alcoholic steatohepatitis, diabetes, and obesity that can be attributed to HIV infection/medications. Poor management of these complications can reduce quality of life and increase health costs. We implemented a dietetic service within our HIV clinic for 6 months and evaluated the outcomes. Method: Twice weekly dietetic clinics were established. Eligible patients were offered group, face-to- face or telephone consultations. Medical records and our database were used to obtain demographics, treatments and co-morbidities. Cholesterol markers were measured along with weight, height, and body mass index (BMI). Results: 84 (total clinic cohort 3308) PLWH were referred. 61/84 attended their appointment;36 selected face-to- face, 25 selected telephone for their first appointment. Patients did not opt for group sessions. DNA rates were similar in both groups (31% and 28% respectively). In attendees median age was 54y, 59% male, 34% Black African origin. Eighty-five per cent of patients were diagnosed before 2010. 95.1% had undetectable viral load and 82% had CD4 count ≥400 cells/mm3 at most recent consultation. 82% of patients were on ≥1 NRTI and 36% were on a PI. Major reason for referral (40/61) was weight management;other reasons included type II diabetes management (7/61), irritable bowel syndrome (IBS) (8/61) and poor appetite (5/61). 15% of patients had an HbA1c of ≥48mmol/L and 11% of patients were pre-diabetic (HbA1c 42-48 mmol/L), 50% had TChol>5.0mmol/L, 11% had TChol:HDL ratio >5 and 38% had a LDL level >3mmol/L. Of the patients with available BMI, 32% (13/41) were classed as overweight and 56% (23/41) were classed as obese. 18% of attendees were ≥55y female and post-menopause could have been a contributing factor for weight gain. 28% of telephone and 31% of face-to- face consultations were scheduled for at least one follow up. Conclusion: PLWH are at risk of complex metabolic conditions, which can be difficult to manage. A dietician was able to provide expert and personalised advice to our patients and helped to empower them to take care of their own health. Patients engaged with both telephone and face-to- face consultations. Due to the short-term funding available in addition to the COVID-19 pandemic, longer term impact could not be evaluated.
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Background: At the start of the UK national lockdown in March 2020, many of the most vulnerable patients with HIV were encouraged to shield, and HIV outpatient services were forced to remodel. We aimed to look at: first, how emergency admissions for patients with HIV had changed in 2020 in comparison with previous years and during/after lockdown;second, to examine whether any fall in admissions related to vulnerability factors (new diagnoses, CD4<350, other HIV-related presentations). Finally, to see if the spectrum of presentations had changed. Method: Retrospective analysis of databases covering HIV admissions for two hospital sites in our urban trust was performed for matched time period (March -August) for 2017-2020. Elective and maternity admissions were excluded, as well as patients who did not have a recorded CD4 count either during the relevant admission or in the 18 months prior. Results: Admissions fell for the period of March to August 2020 compared with previous years (see table). There were 7 covid admissions. A spike in admissions was seen in June, but admissions fell again in July and August. Patients with low CD4 counts (<350) accounted for a similar proportion of total admissions in 2020 (47.8%) compared with previous years (47.0%). Although admissions directly related to HIV fell slightly in 2020 (11, compared with an average of 16), they came to represent a slightly higher proportion of admissions (16.4%) compared with previous years (average 13.8%). This was one of only two admission categories which proportionately increased in 2020. Conclusion: The fall in admissions during lockdown was to be expected. However, although numbers rebounded in June, this did not continue in July and August. There are numerous potential explanations for this. The reduction in emergency admissions for patients with a low CD4 count is of particular concern;the impact of this on morbidity or mortality remains to be seen. (Table Presented).