Transthyretin cardiac amyloidosis: A treatable form of heart failure with a preserved ejection fraction

Cardiac amyloidosis (CA) is considered a rare disease with poor prognosis and limited therapeutic options. However, non-biopsy diagnostic modalities as well as emerging therapies are challenging this long-held belief. Radionuclide bone scintigraphy is increasingly being used in the diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CA). As such, it is expected that the number of patients diagnosed with ATTR-CA will continue to rise. Emerging therapies decrease the progressive morbidity and mortality associated with ATTR-CA. The importance of early recognition of ATTR-CA is imperative as prompt initiation of these novel agents is essential to maximize their therapeutic potential. Herein, we outline the current approach to diagnosis of ATTR-CA and review the therapeutic management of the disease.     

Splenic Artery Embolization after Delayed Splenic Rupture Following Blunt Trauma: Is Nonoperative Management Still an Option in This Cohort?

Patients treated with splenic artery embolization (SAE) >48 hours after a blunt injury for a delayed splenic rupture (DSR) were assessed for the need for a subsequent splenectomy. Thirty-four patients underwent SAE for DSR over 10 years at our level 1 trauma center, performed at a median of 4.5 days after the injury (interquartile range = 5.5), and the patients were followed up for a median of 11 months (interquartile range = 31). There were 3 occurrences of rebleeds, and 2 patients required splenectomy (5.9%). This study showed that treatment with SAE after DSR results in splenic salvage in 94.1% of patients.     

Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.     

Exploring the impact of COVID-19 pandemic lockdown on informal settlements in Tshwane Gauteng Province,South Africa

ABSTRACT

Informal settlements remain a public health problem as they lack basic infrastructure. Furthermore, it is challenging to enforce public health regulations and protocols to prevent the spread of infection during a pandemic. This paper was set out to explore the impact of lockdown during COVID-19 among people living in informal settlements. An exploratory qualitative design was utilised. Purposive sampling was used to select research participants. In-depth one-to-one interviews were held involving 30 research participants through a WhatsApp online telephone platform. A thematic approach underpinned by the four stages of data analysis in interpretive phenomenological analysis was utilised to analyse the data. The study found that during the the research participants were affected by lack of space to practice social distancing, over-burdened infrastructure, lack of savings, loss of income and shortage of food, hunger and diseases, anxiety and depression and poor access to education. There is a need to prioritise the needs of informal settlers and endeavour to establish permanent homes. Health promotion and communication initiatives and pandemic awareness programmes are needed to mitigate the impact of lockdown during a pandemic in informal settlements.