Case of Nigeria-Acquired Human African Trypanosomiasis in United Kingdom, 2016.

Human African trypanosomiasis has not been reported in Nigeria since 2012. Nevertheless, limitations of current surveillance programs mean that undetected infections may persist. We report a recent case of stage 2 trypanosomiasis caused by Trypanosoma brucei gambiense acquired in Nigeria and imported into the United Kingdom

Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: an observational cohort study.

The number of proposed prognostic models for coronavirus disease 2019 (COVID-19) is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation.We independently externally validated the performance of candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at the time of admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictors in univariable analyses.We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78, 95% CI 0.73-0.83), and a novel model for prediction of deterioration <14 days from admission (0.78, 95% CI 0.74-0.82). The most discriminating univariable predictors were admission oxygen saturation on room air for in-hospital deterioration (AUROC 0.76, 95% CI 0.71-0.81), and age for in-hospital mortality (AUROC 0.76, 95% CI 0.71-0.81). No prognostic model demonstrated consistently higher net benefit than these univariable predictors, across a range of threshold probabilities.Admission oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated here offered incremental value for patient stratification to these univariable predictors

AI chatbots not yet ready for clinical use

As large language models (LLMs) expand and become more advanced, so do the natural language processing capabilities of conversational AI, or “chatbots”. OpenAI's recent release, ChatGPT, uses a transformer-based model to enable human-like text generation and question-answering on general domain knowledge, while a healthcare-specific Large Language Model (LLM) such as GatorTron has focused on the real-world healthcare domain knowledge. As LLMs advance to achieve near human-level performances on medical question and answering benchmarks, it is probable that Conversational AI will soon be developed for use in healthcare. In this article we discuss the potential and compare the performance of two different approaches to generative pretrained transformers—ChatGPT, the most widely used general conversational LLM, and Foresight, a GPT (generative pretrained transformer) based model focused on modelling patients and disorders. The comparison is conducted on the task of forecasting relevant diagnoses based on clinical vignettes. We also discuss important considerations and limitations of transformer-based chatbots for clinical use

Implementation and evaluation of a COVID-19 rapid follow-up service for patients discharged from the emergency department.

The COVID-19 pandemic has necessitated rapid adaptation of healthcare providers to new clinical and logistical challenges. Following identification of high levels of emergency department (ED) reattendance among patients with suspected COVID-19 at our centre, we piloted a rapid remote follow-up service for this patient group. We present our service framework and evaluation of our pilot cohort of 192 patients. We followed up patients by telephone within 36 hours of their ED attendance. Pulse oximetry was used for remote monitoring of a subset of patients. Patients required between one and six consecutive telephone assessments, dependent on illness severity, and 23 patients were recalled for in-person assessment. Approximately half of patients with confirmed or probable COVID-19 required onward referral for respiratory follow-up. This framework reduced unplanned ED reattendances in comparison with a retrospective comparator cohort (4.7% from 22.6%). We reproduced these findings in a validation cohort with a high prevalence of acute COVID-19, managed through the clinic in September-October 2020, where we identified an unplanned ED reattendance rate of 5.2%. We propose that rapid remote follow-up is a mechanism by which ambulatory patients can be clinically supported during the acute phase of illness, with benefits both to patient care and to health service resilience

Chest radiograph classification and severity of suspected COVID-19 by different radiologist groups and attending clinicians: multi-reader, multi-case study.

OBJECTIVES: To quantify reader agreement for the British Society of Thoracic Imaging (BSTI) diagnostic and severity classification for COVID-19 on chest radiographs (CXR), in particular agreement for an indeterminate CXR that could instigate CT imaging, from single and paired images. METHODS: Twenty readers (four groups of five individuals)-consultant chest (CCR), general consultant (GCR), and specialist registrar (RSR) radiologists, and infectious diseases clinicians (IDR)-assigned BSTI categories and severity in addition to modified Covid-Radiographic Assessment of Lung Edema Score (Covid-RALES), to 305 CXRs (129 paired; 2 time points) from 176 guideline-defined COVID-19 patients. Percentage agreement with a consensus of two chest radiologists was calculated for (1) categorisation to those needing CT (indeterminate) versus those that did not (classic/probable, non-COVID-19); (2) severity; and (3) severity change on paired CXRs using the two scoring systems. RESULTS: Agreement with consensus for the indeterminate category was low across all groups (28-37%). Agreement for other BSTI categories was highest for classic/probable for the other three reader groups (66-76%) compared to GCR (49%). Agreement for normal was similar across all radiologists (54-61%) but lower for IDR (31%). Agreement for a severe CXR was lower for GCR (65%), compared to the other three reader groups (84-95%). For all groups, agreement for changes across paired CXRs was modest. CONCLUSION: Agreement for the indeterminate BSTI COVID-19 CXR category is low, and generally moderate for the other BSTI categories and for severity change, suggesting that the test, rather than readers, is limited in utility for both deciding disposition and serial monitoring. KEY POINTS: • Across different reader groups, agreement for COVID-19 diagnostic categorisation on CXR varies widely. • Agreement varies to a degree that may render CXR alone ineffective for triage, especially for indeterminate cases. • Agreement for serial CXR change is moderate, limiting utility in guiding management

COVID-19-associated hyperinflammation and escalation of patient care: a retrospective longitudinal cohort study.

BACKGROUND: A subset of patients with severe COVID-19 develop a hyperinflammatory syndrome, which might contribute to morbidity and mortality. This study explores a specific phenotype of COVID-19-associated hyperinflammation (COV-HI), and its associations with escalation of respiratory support and survival. METHODS: In this retrospective cohort study, we enrolled consecutive inpatients (aged ≥18 years) admitted to University College London Hospitals and Newcastle upon Tyne Hospitals in the UK with PCR-confirmed COVID-19 during the first wave of community-acquired infection. Demographic data, laboratory tests, and clinical status were recorded from the day of admission until death or discharge, with a minimum follow-up time of 28 days. We defined COV-HI as a C-reactive protein concentration greater than 150 mg/L or doubling within 24 h from greater than 50 mg/L, or a ferritin concentration greater than 1500 μg/L. Respiratory support was categorised as oxygen only, non-invasive ventilation, and intubation. Initial and repeated measures of hyperinflammation were evaluated in relation to the next-day risk of death or need for escalation of respiratory support (as a combined endpoint), using a multi-level logistic regression model. FINDINGS: We included 269 patients admitted to one of the study hospitals between March 1 and March 31, 2020, among whom 178 (66%) were eligible for escalation of respiratory support and 91 (34%) patients were not eligible. Of the whole cohort, 90 (33%) patients met the COV-HI criteria at admission. Despite having a younger median age and lower median Charlson Comorbidity Index scores, a higher proportion of patients with COV-HI on admission died during follow-up (36 [40%] of 90 patients) compared with the patients without COV-HI on admission (46 [26%] of 179). Among the 178 patients who were eligible for full respiratory support, 65 (37%) met the definition for COV-HI at admission, and 67 (74%) of the 90 patients whose respiratory care was escalated met the criteria by the day of escalation. Meeting the COV-HI criteria was significantly associated with the risk of next-day escalation of respiratory support or death (hazard ratio 2·24 [95% CI 1·62-2·87]) after adjustment for age, sex, and comorbidity. INTERPRETATION: Associations between elevated inflammatory markers, escalation of respiratory support, and survival in people with COVID-19 indicate the existence of a high-risk inflammatory phenotype. COV-HI might be useful to stratify patient groups in trial design. FUNDING: None

Clinical features and management of individuals admitted to hospital with monkeypox and associated complications across the UK: a retrospective cohort study.

BACKGROUND The scale of the 2022 global mpox (formerly known as monkeypox) outbreak has been unprecedented. In less than 6 months, non-endemic countries have reported more than 67 000 cases of a disease that had previously been rare outside of Africa. Mortality has been reported as rare but hospital admission has been relatively common. We aimed to describe the clinical and laboratory characteristics and outcomes of individuals admitted to hospital with mpox and associated complications, including tecovirimat recipients. METHODS In this cohort study, we undertook retrospective review of electronic clinical records and pathology data for all individuals admitted between May 6, and Aug 3, 2022, to 16 hospitals from the Specialist and High Consequence Infectious Diseases Network for Monkeypox. The hospitals were located in ten cities in England and Northern Ireland. Inclusion criteria were clinical signs consistent with mpox and MPXV DNA detected from at least one clinical sample by PCR testing. Patients admitted solely for isolation purposes were excluded from the study. Key outcomes included admission indication, complications (including pain, secondary infection, and mortality) and use of antibiotic and anti-viral treatments. Routine biochemistry, haematology, microbiology, and virology data were also collected. Outcomes were assessed in all patients with available data. FINDINGS 156 individuals were admitted to hospital with complicated mpox during the study period. 153 (98%) were male and three (2%) were female, with a median age of 35 years (IQR 30-44). Gender data were collected from electronic patient records, which encompassed full formal review of clincian notes. The prespecified options for data collection for gender were male, female, trans, non-binary, or unknown. 105 (71%) of 148 participants with available ethnicity data were of White ethnicity and 47 (30%) of 155 were living with HIV with a median CD4 count of 510 cells per mm (IQR 349-828). Rectal or perianal pain (including proctitis) was the most common indication for hospital admission (44 [28%] of 156). Severe pain was reported in 89 (57%) of 156, and secondary bacterial infection in 82 (58%) of 142 individuals with available data. Median admission duration was 5 days (IQR 2-9). Ten individuals required surgery and two cases of encephalitis were reported. 38 (24%) of the 156 individuals received tecovirimat with early cessation in four cases (two owing to hepatic transaminitis, one to rapid treatment response, and one to patient choice). No deaths occurred during the study period. INTERPRETATION Although life-threatening mpox appears rare in hospitalised populations during the current outbreak, severe mpox and associated complications can occur in immunocompetent individuals. Analgesia and management of superimposed bacterial infection are priorities for patients admitted to hospital

Non-communicable disease clinics in rural Ethiopia: why patients are lost to follow-up

Objective: Providing effective medical care for non-communicable diseases (NCD) in rural sub-Saharan Africa has proved to be difficult because of poor treatment adherence and frequent loss to follow-up (LTFU). As the reasons are poorly understood, we have investigated LTFU in a rural Ethiopian community among patients with two contrasting, but common NCDs.Method: The study was based in five health centres in southern Ethiopia providing services for surrounding rural populations where NCD clinics run by nurses and health officers were initiated in 1998. Samples of LTFU patients with epilepsy and hypertension were identified and traced through health extension workers. A questionnaire enquiring about the reasons for LTFU was administered to LTFU patients and non-LTFU, comparison patients.Results: Of 268 LTFU patients, the current status of 147(54.9%) was ascertained. Of these 62 had died, moved away or were continuing medical care at other facilities. The remaining patients (48 with epilepsy and 37 with hypertension) were compared with 113 non-LFTU patients with epilepsy and 98 with hypertension attending the same clinics. The major factors associated with LTFU were distance from the clinic, associated costs and a preference for traditional treatments together with misunderstanding as to the nature of NCD management.Conclusions: We conclude that the delivery of low cost, affordable care closer to the patients’ homes has the greatest potential to address the problem of LTFU. Also needed are increased levels of patient education and interaction with traditional healers to explain the nature of NCDs and the need for life-long management.<br/

Table1_AI chatbots not yet ready for clinical use.docx

As large language models (LLMs) expand and become more advanced, so do the natural language processing capabilities of conversational AI, or “chatbots”. OpenAI's recent release, ChatGPT, uses a transformer-based model to enable human-like text generation and question-answering on general domain knowledge, while a healthcare-specific Large Language Model (LLM) such as GatorTron has focused on the real-world healthcare domain knowledge. As LLMs advance to achieve near human-level performances on medical question and answering benchmarks, it is probable that Conversational AI will soon be developed for use in healthcare. In this article we discuss the potential and compare the performance of two different approaches to generative pretrained transformers—ChatGPT, the most widely used general conversational LLM, and Foresight, a GPT (generative pretrained transformer) based model focused on modelling patients and disorders. The comparison is conducted on the task of forecasting relevant diagnoses based on clinical vignettes. We also discuss important considerations and limitations of transformer-based chatbots for clinical use.</p