Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity and mortality worldwide. Although predictive multiparametric screening is being developed, it is not applicable to nulliparous women, and is not applied to low-risk women. As PE is considered a heterogenous disorder, it is unlikely that any single multiparametric screening protocol containing a small group of biomarkers could have the required accuracy to predict all PE subgroups. Given the etiology of PE is complex and not fully understood, it begs the question, whether the search for biomarkers based on the predominant view of impaired placentation involving factors predominately implicated in angiogenesis and inflammation, has been too limiting. Here we highlight the enormous potential of state-of-the-art, high-throughput proteomics, to provide a comprehensive and unbiased approach to biomarker identification. Our literature search identified 1336 articles; after review, 45 studies with proteomic data from PE women that were eligible for inclusion. From 710 proteins with altered abundance, we identified 13 common circulating proteins, some of which had not been previously considered as prospective biomarkers of PE. An additional search of the literature for original publications testing any of the 13 common proteins using non-proteomic techniques was also undertaken. Strikingly, 9 of these common proteins had been independently evaluated in PE studies as potential biomarkers. This study highlights the potential of using high-throughput data sets, which are comprehensive and without bias, to identify a profile of proteins that may improve predictions of PE and understanding of its etiology. We bring to the attention of the medical and research communities that the strengths and advantages of using data from high-throughput studies for biomarker discovery would be increased dramatically, if first and second trimester samples were collected for proteomics, and if standardized guidelines for patient reporting and data collection were implemented.

Background: Patients presenting for major surgery with low cardiorespiratory fitness (deconditioning) and other modifiable risk factors are at increased risk of postoperative complications. This study investigated the feasibility of delivering prehabilitation in high-risk patients scheduled for major abdominal cancer surgery. Methods: Eligible patients in this single-center cohort study included patients with poor fitness (objectively assessed by cardiopulmonary exercise testing, CPET) scheduled for elective major abdominal cancer surgery. Patients were recruited to participate in a prehabilitation program that spanned up to 6 weeks pre-operatively and comprised aerobic and resistance exercise training, breathing exercise, and nutritional support. The primary outcome assessed pre-specified feasibility targets: recruitment >70%, retention >85%, and intervention adherence >70%. Secondary outcomes were assessed for improved pre-operative functional status and health-related quality of life and for postoperative complications. Results: Eighty-two (34%) out of 238 patients screened between April 2018 and December 2019 were eligible for recruitment. Fifty (61%) patients (52% males) with a median age of 71 (IQR, 63–77) years participated in the study. Baseline oxygen consumption the at anaerobic threshold and at peak exercise (mean±SD: 9.8±1.8 and 14.0±2.9 mL/kg/min, respectively) confirmed the deconditioned state of the study cohort. The retention rate within the prehabilitation program was 84%, with 42 participants returning for repeat CPET testing. While >60% of participants preferred to do home-based prehabilitation, adherence to the intervention was low—with only 12 (28%) and 15 (35%) of patients having self-reported compliance >70% with their exercise prescriptions. Conclusion: Our prehabilitation program in high-risk cancer surgery patients did not achieve pre-specified targets for recruitment, retention, and self-reported program adherence. These findings underpin the importance of implementation research and strategies for the prehabilitation programs in major surgery. Trial registration: Australian New Zealand Clinical Trials Registry (ACTRN12620000073909) retrospectively registered.

Background and Purpose: General medical patients often present to the hospital with medical, social, cognitive, and functional issues that may impact discharge destination. The aim of this study was to investigate the association between patient factors at hospital admission and discharge destination in general medical patients. Methods: This was a prospective, single-site observational study conducted on the general medical wards at a tertiary hospital. Inpatients admitted to the general medical unit and referred to physical therapy were included. Patients admitted from residential care were excluded. Main Outcome Measures: Data were collected a median of 2 days (interquartile range: 1-3) from hospital admission and included demographics, comorbidities (Charlson Comorbidity Index), premorbid physical function (Blaylock Risk Assessment Screening Score, BRASS), current function (de Morton Mobility Index, DEMMI and Alpha Functional Independence Measure, AlphaFIM), and cognition (Rowland Universal Dementia Assessment Scale, RUDAS). Results: Between July 2016 and August 2017, 417 patients were recruited (53% female, median age: 81 years (interquartile range: 76-86). Of these, 245 patients were discharged directly home; 172 were not discharged home of whom 140 were discharged to a subacute temporary facility providing further opportunity for therapy and discharge planning. Patients discharged directly home had higher functional, mobility, and cognitive scores. Data were partitioned into training, validation, and test sets to provide unbiased estimates of sensitivity, specificity, receiver operating characteristic curve, and area under the curve. Models best associated with discharge were “DEMMI and toilet transfers” (sensitivity 82.1%, specificity 66.2%, area under the curve 83.8%, 95% confidence interval: 76.4-91.2) and “AlphaFIM and walking independence” (sensitivity: 66.7%, specificity: 83.1%, area under the curve: 81.5, 95% confidence interval: 73.2-89.7). Conclusion: Two models were created that differentiated between discharge home and not home and had similar statistical measures of validity. Although the models require further validation, clinicians should consider whether identification of patients likely to be discharged home or not home is of greater relevance for their clinical setting.

Perfectionism is an important factor in insomnia development and maintenance. Previous studies exploring the relationship between perfectionism and insomnia have predominantly relied on self-reported sleep measures. Therefore, this study sought to assess whether actigraphy-measured sleep parameters were associated with perfectionism. Sixty adults (85% females, mean age 30.18 ± 11.01 years) were sampled from the Australian general population. Actigraphy-derived objective sleep measures, subjective sleep diary measures, the Frost Multidimensional Perfectionism Scale (FMPS), Hewitt-Flett Multidimensional Perfectionism Scale (HFMPS) and Depression, Anxiety and Stress Scale 21 (DASS-21) were collected. High perfectionism levels were associated with poor sleep, but these relationships differed between objective and subjective measures. Perfectionism via FMPS total score and subscales of Concern over Mistakes, Doubts about Actions, Personal Standards and Self-oriented Perfectionism correlated with subjective sleep onset latency and sleep efficiency with moderate effects (r = .26 to .88). In contrast, perfectionism via HFMPS total score and subscales of Socially Prescribed Perfectionism and Parental Expectations predicted objective sleep onset latency and sleep efficiency. Additionally, stress mediated the relationships between objective sleep efficiency and Concern over Mistakes and Doubts about Actions. Perfectionism demonstrated stronger associations with subjective than objective sleep measures. Higher Parental Expectations and Socially Prescribed Perfectionism may increase one's vulnerability to objectively measured poor sleep. Therefore, perfectionism may be important in preventing and treating insomnia.