Digital approaches to reducing TB treatment loss to follow-up.

Poor adherence to TB treatment leads to adverse clinical outcomes. A range of digital technologies to support adherence have been developed and the COVID-19 pandemic considerably accelerated the implementation of digital interventions. Here, we review the current evidence on digital adherence support tools and update the findings of a previous review, with evidence published from 2018 to date. Interventional and observational studies, as well as primary and secondary analyses were included, and we summarised available evidence on effectiveness, cost-effectiveness and acceptability. The studies were heterogenous and varied in outcome measures and approaches used. Overall, our findings show that digital approaches, such as digital pillboxes and asynchronous video-observed treatment, are acceptable and have the potential to improve adherence and be cost-effective over time if implemented at scale. Digital tools should be part of multiple strategies to support adherence. Further research to integrate behavioural data on reasons for non-adherence will help to determine how to best implement these technologies in different settings.

The Influence of the Corona Virus Pandemic on Sustainable Development Goal 13 and United Nations Framework Convention on Climate Change Processes

Apart from many social and economic problems worldwide, the COVID-19 pandemic has also led to sudden halt in face-to-face climate-related meetings. Moreover, it has also negatively influenced the works related to the preparations for the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) and organizing the 26th Conference of the Parties of the UN Framework Convention on Climate Change (UNFCCC), namely COP26 to be held in Glasgow, which was postponed to November 2021. This article presents a global study undertaken among UNFCCC contact points and other climate experts, to ascertain the impacts of the pandemic on the implementation of SDG13 and UNFCCC processes. The methodological approach entails an bibliometric analysis, online survey, and authors’ expert judgment. Results of the bibliometric analysis show that the most common terms associated with this theme are COVID-19, climate change, CO2, energy, “pandemic-related,” and “adaptation-related.” In addition, the survey revealed some difficulties associated with online participation in the processes from many developing countries. The study concluded that there is negative impact of COVID-19 pandemic on the UNFCCC process, more minor government priorities regarding climate action, loss of traction of the process, and a challenge to achieve the Paris Agreement, with less significant support from the respondents from less developed countries. The findings suggest that urgent action is needed, to make up for the lost time, and place climate issues more prominently on the global agenda. Copyright © 2022 Filho, Hickmann, Nagy, Pinho, Sharifi, Minhas, Islam, Djalanti, García Vinuesa and Abubakar.

Disease severity and patient recovery in COVID-19: an observational study comparing first and second wave admissions in London

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.

The impact of ethnicity on the long-term sequelae of COVID-19: follow-up from the first and second waves in North London

P137 Table 1Demographics, admission severity and follow-up symptomsVariable White N = 603 Asian N = 252 Black N = 130 Other N = 122 p-value Age 65 ± 16.5 59 ± 15.4 59 ± 13.9 59 ± 14.7 <0.001 Male (%) 372 (62) 148 (59) 72 (55) 81 (66) 0.28 Index of deprivation* 6 (3–7) 6 (4–8) 5 (3–7) 5 (3–7) 0.03 Body mass index 27.1 (23.5–30.5) 26.0 (23.7 – 29.2) 28.9 (25.9 – 34.7) 26.7 (25.1 – 30.9) <0.001 Hypertension (%) 244/583 (42) 113/247 (46) 72/125 (58) 40/119 (34) 0.001 Cardiovascular disease (%) 133/415 (32) 45/166 (27) 15/86 (17) 16/73 (22) 0.02 Diabetes (%) 122/583 (21) 80/247 (32) 45/125 (36) 40/119 (34) <0.001 Respiratory disease (%) 124/416 (30) 39/167 (23) 21/91 (23) 16/70 (23) 0.25 Chronic kidney disease (%) 61/583 (11) 29/247 (12) 27/125 (22) 9/119 (8) 0.002 Any mental health (%) 77/583 (13) 23/247 (9) 8/125 (6) 17/119 (14) 0.08 Smoking history (%) 250/587 (43) 43/244 (18) 44/127 (35) 44/118 (37) <0.001 Clinical frailty score 3 (2–4) 2 (2–4) 3 (2–4) 3 (2–3) 0.11 NEWS2 4 (2–6) 4.5 (3–6) 5 (3–6) 5 (3–7) 0.3 Respiratory support 80/564 (14) 47/236 (20) 23/116 (20) 21/118 (18) 0.15 Follow-up symptoms MRC score* 2 (1–3) 2 (1–3) 2 (1–3) 2 (1–2) 0.61 Cough improved (%) 414/553 (75) 177/232 (76) 85/118 (72) 87/113 (77) 0.8 Fatigue improved (%) 451/552 (82) 193/228 (85) 109/122 (89) 88/115 (77) 0.05 Sleep improved (%) 342/536 (64) 155/228 (68) 76/117 (65) 68/112 (61) 0.57 Burden of symptoms* 1 (0–2) 1 (0–2) 1 (0–2) 1 (0–2) 0.78 Returned to work (%) 142/256 (56) 77/139 (55) 29/64 (45) 41/71 (58) 0.45 Felt back to normal (%) 256/439 (55) 112/186 (60) 62/103 (60) 43/78 (55) 0.87 Positive PHQ-2 (depression screening) 65/580 (11) 40/242 (17) 12/126 (10) 11/116 (10) 0.09 Positive TSQ (post-traumatic stress screening) 42/601 (7) 16/248 (7) 13/130 (10) 8/122 (7) 0.6 *Non-parametric data presented as median ± interquartile range, all other data presented as mean ± standard deviation.DiscussionOur data demonstrate that despite having more co-morbidities associated with worse outcomes, adults from BAME backgrounds who are discharged from hospital following COVID-19 are no more likely to experience symptoms consistent with ‘Long CO ID’. However, given the increased risk of infection among BAME communities, we must ensure that reducing health inequalities remain central to the UK health agenda.ReferenceSze, et al. EClinicalMedicine 2020. doi:10.1016/j.eclinm.2020.100630