Oral pre-exposure prophylaxis (PrEP) is a highly effective HIV prevention method; however, uptake and persistence have been low among southern African women. A dual prevention pill (DPP) that combines PrEP with oral contraception (OC) may increase PrEP use and better meet women’s sexual and reproductive health needs. We will gauge the DPP’s acceptability in two cross-over clinical trials.

PC952 (Zimbabwe) and PC953 (South Africa) will compare acceptability, adherence and preference for an over-encapsulated DPP versus PrEP and OCs taken separately. HIV-negative, non-pregnant cisgender females in Johannesburg, South Africa (n=96, 16–40 years) and Harare, Zimbabwe (n=30, 16–24 years) will be randomised 1:1 to the order of regimens—DPP or two separate tablets—each used for three 28-day cycles, followed by a 6-month choice period in South Africa. Monthly clinic visits include HIV and pregnancy testing; safety assessments and risk reduction and adherence counselling. We will assess adherence (monthly) based on tenofovir diphosphate drug levels in dried blood spots and by self-report. We will evaluate acceptability (monthly) and preference (end of cross-over) via computer-assisted self-interviewing and in-depth interviews with a subset of participants. Data collection started in September 2022 and ended in January 2024.

PC952 was approved by the Ministry of Health and Child Care, Medical Research Council, Research Council and Medicines Control Authority of Zimbabwe; the Chitungwiza City Health Ethics Committee; and the Joint Research Ethics Committee for the University of Zimbabwe Faculty of Medicine and Health Sciences and Parirenyatwa Group of Hospitals. PC953 was approved by the South African Health Products Regulatory Authority and the University of the Witwatersrand’s Human Research Ethics Committee. The Population Council IRB approved both studies. We will disseminate results in open-access journals, clinical trials registries, and at local and international meetings and conferences.

NCT04778514, NCT04778527.

Conventional prediction models fail to integrate the constantly evolving nature of critical illness. Alternative modelling approaches to study dynamic changes in critical illness progression are needed. We compare static risk prediction models to dynamic probabilistic models in early critical illness.

We developed models to simulate disease trajectories of critically ill COVID-19 patients across different disease states. Eighty per cent of cases were randomly assigned to a training and 20% of the cases were used as a validation cohort. Conventional risk prediction models were developed to analyse different disease states for critically ill patients for the first 7 days of intensive care unit (ICU) stay. Daily disease state transitions were modelled using a series of multivariable, multinomial logistic regression models. A probabilistic dynamic systems modelling approach was used to predict disease trajectory over the first 7 days of an ICU admission. Forecast accuracy was assessed and simulated patient clinical trajectories were developed through our algorithm.

We retrospectively studied patients admitted to a Cleveland Clinic Healthcare System in Ohio, for the treatment of COVID-19 from March 2020 to December 2022.

5241 patients were included in the analysis. For ICU days 2–7, the static (conventional) modelling approach, the accuracy of the models steadily decreased as a function of time, with area under the curve (AUC) for each health state below 0.8. But the dynamic forecasting approach improved its ability to predict as a function of time. AUC for the dynamic forecasting approach were all above 0.90 for ICU days 4–7 for all states.

We demonstrated that modelling critical care outcomes as a dynamic system improved the forecasting accuracy of the disease state. Our model accurately identified different disease conditions and trajectories, with a

Recently, with the rapid development of the perinatal medical system and related life-saving techniques, both the short-term and long-term prognoses of extremely preterm infants (EPIs) have improved significantly. In rapidly industrialising countries like China, the survival rates of EPIs have notably increased due to the swift socioeconomic development. However, there is still a reasonably lower positive response towards the treatment of EPIs than we expected, and the current situation of withdrawing care is an urgent task for perinatal medical practitioners.

To develop and validate a model that is practicable for EPIs as soon as possible after birth by regression analysis, to assess the risk of mortality and chance of survival.

This multicentre prospective cohort study used datasets from the Sino-Northern Neonatal Network, including 46 neonatal intensive care units (NICUs). Risk factors including maternal and neonatal variables were collected within 1 hour post-childbirth. The training set consisted of data from 41 NICUs located within the Shandong Province of China, while the validation set included data from 5 NICUs outside Shandong Province. A total of 1363 neonates were included in the study.

Gestational age, birth weight, pH and lactic acid in blood gas analysis within the first hour of birth, moderate-to-severe hypothermia on admission and adequate antenatal corticosteroids were influencing factors for EPIs’ mortality with important predictive ability. The area under the curve values for internal validation of our prediction model and Clinical Risk Index for Babies-II scores were 0.81 and 0.76, and for external validation, 0.80 and 0.51, respectively. Moreover, the Hosmer-Lemeshow test showed that our model has a constant degree of calibration.

There was good predictive accuracy for mortality of EPIs based on influencing factors prenatally and within 1 hour after delivery. Predicting the risk of mortality of EPIs as soon as possible after birth can effectively guide parents to be proactive in treating more EPIs with life-saving value.

ChiCTR1900025234.

Catecholamine vasopressors such as norepinephrine are the standard drugs used to maintain mean arterial pressure during liver transplantation. At high doses, catecholamines may impair organ perfusion. Angiotensin II is a peptide vasoconstrictor that may improve renal perfusion pressure and glomerular filtration rate, a haemodynamic profile that could reduce acute kidney injury. Angiotensin II is approved for vasodilatory shock but has not been rigorously evaluated for treatment of hypotension during liver transplantation. The objective is to assess the efficacy of angiotensin II as a second-line vasopressor infusion during liver transplantation. This trial will establish the efficacy of angiotensin II in decreasing the dose of norepinephrine to maintain adequate blood pressure. Completion of this study will allow design of a follow-up, multicentre trial powered to detect a reduction of organ injury in liver transplantation.

This is a double-blind, randomised clinical trial. Eligible subjects are adults with a Model for End-Stage Liver Disease Sodium Score ≥25 undergoing deceased donor liver transplantation. Subjects are randomised 1:1 to receive angiotensin II or saline placebo as the second-line vasopressor infusion. The study drug infusion is initiated on reaching a norepinephrine dose of 0.05 µg kg^-1 min^-1 and titrated per protocol. The primary outcome is the dose of norepinephrine required to maintain a mean arterial pressure ≥65 mm Hg. Secondary outcomes include vasopressin or epinephrine requirement and duration of hypotension. Safety outcomes include incidence of thromboembolism within 48 hours of the end of surgery and severe hypertension. An intention-to-treat analysis will be performed for all randomised subjects receiving the study drug. The total dose of norepinephrine will be compared between the two arms by a one-tailed Mann-Whitney U test.

The trial protocol was approved by the local Institutional Review Board (#20–30948). Results will be posted on ClinicalTrials.gov and published in a peer-reviewed journal.

ClinicalTrials.govNCT04901169