Case Report: Respiratory Management With a 47-Day ECMO Support for a Critical Patient With COVID-19

This paper reports a complete case of severe acute respiratory distress syndrome (ARDS) caused by coronavirus disease 2019 (COVID-19), who presented with rapid deterioration of oxygenation during hospitalization despite escalating high-flow nasal cannulation to invasive mechanical ventilation. After inefficacy with lung-protective ventilation, positive end-expiratory pressure (PEEP) titration, prone position, we administered extracorporeal membrane oxygenation (ECMO) as a salvage respiratory support with ultra-protective ventilation for 47 days and finally discharged the patient home with a good quality of life with a Barthel Index Score of 100 after 76 days of hospitalization. The purpose of this paper is to provide a clinical reference for the management of ECMO and respiratory strategy of critical patients with COVID-19-related ARDS.

A complete case of Cantrell's Pentalogy with isolated left ventricular diverticulum

The congenital left ventricular diverticulum is a rare cardiac malformation, and it may associate with Cantrell’s Pentalogy with other cardiac defects. However, isolated ventricular diverticulum without any other cardiac defect in complete Cantrell’s syndrome is very rare. We describe a 6-year-old male patient with a complete Cantrell’s syndrome with isolated left ventricular diverticulum.

Prosthetic rehabilitation of maxillary lateral incisors agenesis using dental mini-implants: a multicenter 10-year follow-up

Objectives Implants are used to replace congenitally missing lateral incisors but often the space across the alveolar crest is too narrow to permit their use. This multicenter study (Dental Clinic of the University of Foggia, Odontostomatology Clinic of the University of L’Aquila) evaluated the efficacy of mini-implants in cases of maxillary lateral incisor agenesis with severe osseous atrophy in 10-year follow-up. Materials and methods Forty-seven mini-implants have been inserted in 35 patients affected by lateral incisors agenesis (23 single and 12 bilateral ageneses). All patients underwent orthodontic opening of the space of the upper lateral incisors. After the insertion of the implants, the immediate, non-functional loading, positioning of crowns, presence of pain during percussion and mini-implant function, horizontal and vertical movement when a force of 5 N was applied, ridge loss, and plaque index have been evaluated 1 month after loading, 1 year after loading, and then every 5 years in the following 10 years. Little’s test was used to evaluate the assumption that data of loss to follow-up implants are missing completely at random (MCAR) and that a complete-case scenario could be adopted. Wilcoxon test was carried out to look statistically significant differences between the various parameters resulting in the complete-case scenario and those assumed for the worst scenario. The software R (v. 3.6.1, 2019) was employed to perform the statistical analysis. Results The results obtained over 10 years range from 89% of success rate in a worst-case scenario to the 100% using a complete-case analysis with satisfactory values of marginal bone resorption and good conditions of the peri-implant tissue. Ten-year follow-up using complete-case analysis shows survival rates of 100% for implants with no signs of peri-implantitis, stability of the marginal bone levels and soft tissue around the dental implants. Conclusions The data collected show very good implant stability, absence of progressive peri-implantitis, and satisfactory aesthetical results in time (no signs of infraocclusion). Clinical relevance Mini-implants can be considered a valid and stable over time solution in the restorative treatment of maxillary lateral incisors agenesis.

Complete case logistic regression with a dichotomised continuous outcome: a simulation study

Background A complete case logistic regression will give a biased estimate of the exposure odds ratio only if there is a multiplicative interaction between the exposure and outcome with respect to the probability of missingness – whereas linear regression with a continuous outcome is biased in more scenarios, including when only the outcome causes missingness. It is not clear whether a complete case logistic regression will give a biased estimate of the odds ratio if missingness depends on a continuous outcome but this outcome is dichotomised for the analysis – a common situation in epidemiology. Methods We investigated this using a simulation study and data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a UK birth cohort. We also examined whether any bias could be reduced by including a proxy for the binary outcome as an auxiliary variable in multiple imputation. Results There was negligible bias in the exposure odds ratio when the probability of being a complete case was independently associated with the exposure and (continuous) outcome but important bias in the presence of an interaction, particularly at high levels of missing data. Inclusion of the proxy led to significant bias reductions when this had high sensitivity and specificity in relation to the study outcome. Conclusions The robustness of logistic regression to missing data is maintained even when the outcome is a binary version of a continuous outcome. Bias due to an interaction between the exposure and outcome in their effect on selection could be reduced by including proxies for the missing outcome as auxiliary variables in MI. If such proxies are available, we would recommend using MI over a complete case analysis because, in practice, it would be difficult to rule out an interaction.

Screening for Predictors of Chronic Ciguatera Poisoning: An Exploratory Analysis among Hospitalized Cases from French Polynesia

Ciguatera poisoning is a globally occurring seafood disease caused by the ingestion of marine products contaminated with dinoflagellate produced neurotoxins. Persistent forms of ciguatera, which prove to be highly debilitating, are poorly studied and represent a significant medical issue. The present study aims to better understand chronic ciguatera manifestations and identify potential predictive factors for their duration. Medical files of 49 patients were analyzed, and the post-hospitalization evolution of the disease assessed through a follow-up questionnaire. A rigorous logistic lasso regression model was applied to select significant predictors from a list of 37 patient characteristics potentially predictive of having chronic symptoms. Missing data were handled by complete case analysis, and a survival analysis was implemented. All models used standardized variables, and multiple comparisons in the survival analyses were handled by Bonferroni correction. Among all studied variables, five significant predictors of having symptoms lasting ≥3 months were identified: age, tobacco consumption, acute bradycardia, laboratory measures of urea, and neutrophils. This exploratory, hypothesis-generating study contributes to the development of ciguatera epidemiology by narrowing the list from 37 possible predictors to a list of five predictors that seem worth further investigation as candidate risk factors in more targeted studies of ciguatera symptom duration.

1230Should multiple imputation be stratified by exposure group when estimating causal effects via outcome regression?

Background Outcome regression remains widely applied for estimating causal effects in observational studies, in which causal inference is conceptualised as emulating a randomized controlled trial (RCT). Multiple imputation (MI) is a commonly used method for handling missing data, but while in RCTs it has been shown that MI should be conducted by treatment group to reduce bias, whether imputation should be conducted by exposure group in observational studies has not been studied. Methods We conducted a simulation study to evaluate the performance of seven methods for handling missing data: Complete-case analysis (CCA), MI of main effect, MI with interactions (between exposure and: outcome, a strong confounder, outcome and a strong confounder, all incomplete), and MI conducted by exposure group. We simulated data based on an example from the Victorian Adolescent Health Cohort Study. Three exposure prevalences and seven outcome generation models were considered, the latter ranging from no interaction to strong-positive or negative exposure-confounder interaction. Various missingness scenarios were examined: with incomplete outcome only or also incomplete confounders, and three levels of complexity regarding the missingness mechanism. Results For all scenarios, MI by exposure led to the least bias, followed by MI approaches that included exposure-confounder interactions. Conclusions If MI is adopted in outcome regression, we recommend conducting MI by exposure group and, when not feasible, including exposure-confounder interactions in the imputation model. Key messages Similar to RCTs, MI should be conducted by exposure group when estimating average causal effects using outcome regression in observational studies.

1202Examining the mental health effect of caring among adolescents using augmented inverse probability treatment weighting

Background Caring exerts significant impacts on the lives of those providing care, however there has been limited quantitative analysis of the mental health impacts on young carers. This research aimed to estimate the effect of informal caring at age 14/15 years on mental health at age 18/19 years. Methods Data was drawn from Waves 5, 6, 8 (2012-2018) of the Longitudinal Study of Australian Children. Effects of caring on mental health were assessed using augmented inverse probability treatment weighting, with adjustment for potential confounders. Caring was assessed with both a binary (any caring vs none), and a three-category variable (no caring, less than daily caring, daily caring). Results In complete case models, binary caring at age 14/15 years was associated with poorer mental health at age 18/19 years, with an average treatment effect (ATE) of 1.10 (95%CI 0.37, 1.83). The ATE of daily caring compared to no caring at age 14/15 years of age was 1.94 (95%CI 0.48, 3.39), and caring less than daily (compared to no caring) was associated with a treatment effect of 0.83(95%CI 0.06, 1.61). Associations were robust to several sensitivity analyses. Conclusions These results suggest there is a mental health impact of caring in adolescence on mental health four years later. Key messages These results highlight the need for support for young carers. Such support is particularly essential for those providing more intensive caring.

High risk groups for severe COVID-19 in a whole of population cohort in Australia

Background Increasing age is the strongest known risk factor for severe COVID-19 disease but information on other factors is more limited. Methods All cases of COVID-19 diagnosed from January–October 2020 in New South Wales Australia were followed for COVID-19-related hospitalisations, intensive care unit (ICU) admissions and deaths through record linkage. Adjusted hazard ratios (aHR) for severe COVID-19 disease, measured by hospitalisation or death, or very severe COVID-19, measured by ICU admission or death according to age, sex, socioeconomic status and co-morbidities were estimated. Results Of 4054 confirmed cases, 468 (11.5%) were classified as having severe COVID-19 and 190 (4.7%) as having very severe disease. After adjusting for sex, socioeconomic status and comorbidities, increasing age led to the greatest risk of very severe disease. Compared to those 30–39 years, the aHR for ICU or death from COVID-19 was 4.45 in those 70–79 years; 8.43 in those 80–89 years; 16.19 in those 90+ years. After age, relative risks for very severe disease associated with other factors were more moderate: males vs females aHR 1.40 (95%CI 1.04–1.88); immunosuppressive conditions vs none aHR 2.20 (1.35–3.57); diabetes vs none aHR 1.88 (1.33–2.67); chronic lung disease vs none aHR 1.68 (1.18–2.38); obesity vs not obese aHR 1.52 (1.05–2.21). More comorbidities was associated with significantly greater risk; comparing those with 3+ comorbidities to those with none, aHR 5.34 (3.15–9.04). Conclusions In a setting with high COVID-19 case ascertainment and almost complete case follow-up, we found the risk of very severe disease varies by age, sex and presence of comorbidities. This variation should be considered in targeting prevention strategies.