Gestational gigantomastia: a patient case review and literature review

Gestational gigantomastia (GG) or gravidic macromastia is defined as a disorder characterized by a diffuse, extreme and incapacitating enlargement of one or both breast during pregnancy. Gestational Gigantomastia is a very rare condition with a little over a 100cases reported in history. Gigantomastia has been seen to occur in the face of normal hormonal profile. Due to increase in breast mass, the overlying skin is stretched and may undergo necrosis which in the face of pregnancy can cause severe mastitis and haemorrhage.We present a rare case of GG in a 36-year-old para 7 gravida 8, Zambian woman at 28weeks gestation with classical features of typical GG with normal hormonal profile with respect with pregnancy. She was managed conservatively on Bromocriptine 5mg once a day during pregnancy and postpartum until breast size had reduced to near normal prepregnancy size.We report a rare case of “True gigantomastia which develops rapidly during pregnancy, undergoes regression after delivery, and recurs with subsequent pregnancies” in Zambia

Correction: Epidemiology and outcomes of early-onset AKI in COVID-19-related ARDS in comparison with non-COVID-19-related ARDS: insights from two prospective global cohort studies (Critical Care, (2023), 27, 1, (3), 10.1186/s13054-022-04294-5)

Following publication of the original article [1], the authors identified that the collaborating authors part of the collaborating author group CCCC Consortium was missing. The collaborating author group is available and included as Additional file 1 in this article

Stroke in critically ill patients with respiratory failure due to COVID-19: Disparities between low-middle and high-income countries

Purpose: We aimed to compare the incidence of stroke in low-and middle-income countries (LMICs) versus high-income countries (HICs) in critically ill patients with COVID-19 and its impact on in-hospital mortality. Methods: International observational study conducted in 43 countries. Stroke and mortality incidence rates and rate ratios (IRR) were calculated per admitted days using Poisson regression. Inverse probability weighting (IPW) was used to address the HICs vs. LMICs imbalance for confounders. Results: 23,738 patients [20,511(86.4 %) HICs vs. 3,227(13.6 %) LMICs] were included. The incidence stroke/1000 admitted-days was 35.7 (95 %CI = 28.4–44.9) LMICs and 17.6 (95 %CI = 15.8–19.7) HICs; ischemic 9.47 (95 %CI = 6.57–13.7) LMICs, 1.97 (95 %CI = 1.53, 2.55) HICs; hemorrhagic, 7.18 (95 %CI = 4.73–10.9) LMICs, and 2.52 (95 %CI = 2.00–3.16) HICs; unspecified stroke type 11.6 (95 %CI = 7.75–17.3) LMICs, 8.99 (95 %CI = 7.70–10.5) HICs. In regression with IPW, LMICs vs. HICs had IRR = 1.78 (95 %CI = 1.31–2.42, p < 0.001). Patients from LMICs were more likely to die than those from HICs [43.6% vs 29.2 %; Relative Risk (RR) = 2.59 (95 %CI = 2.29–2.93), p < 0.001)]. Patients with stroke were more likely to die than those without stroke [RR = 1.43 (95 %CI = 1.19–1.72), p < 0.001)]. Conclusions: Stroke incidence was low in HICs and LMICs although the stroke risk was higher in LMICs. Both LMIC status and stroke increased the risk of death. Improving early diagnosis of stroke and redistribution of healthcare resources should be a priority. Trial registration: ACTRN12620000421932 registered on 30/03/2020