Early prediction of ventilator-associated pneumonia with machine learning models: A systematic review and meta-analysis of prediction model performance✰.

BACKGROUND: Machine learning-based prediction models can catalog, classify, and correlate large amounts of multimodal data to aid clinicians at diagnostic, prognostic, and therapeutic levels. Early prediction of ventilator-associated pneumonia (VAP) may accelerate the diagnosis and guide preventive interventions. The performance of a variety of machine learning-based prediction models were analyzed among adults undergoing invasive mechanical ventilation. METHODS: This systematic review and meta-analysis was conducted in accordance with the Cochrane Collaboration. Machine learning-based prediction models were identified from a search of nine multi-disciplinary databases. Two authors independently selected and extracted data using predefined criteria and data extraction forms. The predictive performance, the interpretability, the technological readiness level, and the risk of bias of the included studies were evaluated. RESULTS: Final analysis included 10 static prediction models using supervised learning. The pooled area under the receiver operating characteristics curve, sensitivity, and specificity for VAP were 0.88 (95 % CI 0.82-0.94, I2 98.4 %), 0.72 (95 % CI 0.45-0.98, I2 97.4 %) and 0.90 (95 % CI 0.85-0.94, I2 97.9 %), respectively. All included studies had either a high or unclear risk of bias without significant improvements in applicability. The care-related risk factors for the best performing models were the duration of mechanical ventilation, the length of ICU stay, blood transfusion, nutrition strategy, and the presence of antibiotics. CONCLUSION: A variety of the prediction models, prediction intervals, and prediction windows were identified to facilitate timely diagnosis. In addition, care-related risk factors susceptible for preventive interventions were identified. In future, there is a need for dynamic machine learning models using time-depended predictors in conjunction with feature importance of the models to predict real-time risk of VAP and related outcomes to optimize bundled care.

Doctors' and Nurses' Attitudes of Acupuncture and Acupressure use in Perioperative Care: An Australian National Survey.

BACKGROUND: Acupuncture and acupressure are not being systematically used in the management of postoperative nausea and vomiting and pain, despite being included in the guidelines. AIM: To examine the beliefs, attitudes, and knowledge of Australian nurses/midwives and doctors toward the perioperative use of AA for the management of postoperative nausea and vomiting and pain; to explore the barriers and enablers influencing acupuncture and acupressure integration into hospital setting. METHODS: A mixed-mode approach was undertaken for data collection. An online approach was used to recruit respondents from Australian College of Perioperative Nurses. Three hospitals from three different Australian states were selected via convenience sampling. RESULTS: A total of 421 usable surveys were included in data analysis. The respondents comprised 14.3% doctors and 72.9% nurses/midwives. Overall, 69.4% were female, 85% were trained in Australia with 35% and 51.4% having knowledge or personal exposure to AA in general respectively. Over 60% of the respondents agreed AA should be routinely integrated into perioperative care, and over 80% would recommend AA to their patients if it was provided at their hospital, and, 75% would be willing to receive further education. The three main reported barriers included: perceived lack of scientific evidence (80.9%), unavailability of credentialed provider (77.2%) and lack of reimbursement (60.4%). CONCLUSIONS: Positive attitudes are reported by Australian doctors and nurses toward AA. This is despite of low levels of knowledge or personal exposure to AA. Further studies are required to explore the implementation of barriers and address respondent calls for further education.

Healthcare Professionals' Attitudes to Integration of Acupuncture in Western Medicine: A Mixed-Method Systematic Review.

BACKGROUND: Acupuncture is practiced in many Western countries with increasing evidence supporting its use across the healthcare system. However, this nonpharmacological intervention is yet to be widely integrated into hospitals. Fundamental to the integration of any innovation into healthcare systems is the attitudes of healthcare professionals. AIMS: To explore healthcare professionals' attitudes towards acupuncture and identify the enablers and barriers to integration in the hospital setting. DESIGN: This review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines; we conducted a mixed-method systematic review following Joanna Briggs Institute Reviewer's Manual 2017. DATA SOURCES: PubMed, CINAHL, AMED, EMBASE, Cochrane Library, and SCOPUS were searched from their inception to December 2019 using different combination of keywords. METHODS: Attitude and perception data were extracted from the articles and constructs were categorized as barriers and enablers. A convergent integrated approach was adopted whereby qualitative data themes were integrated with quantitative data constructs to generate descriptive codes around enablers and barriers at intrapersonal, interpersonal, and environmental levels according to the framework proposed by Manias et al. (2014). RESULTS: Twenty-six studies comprising 19 survey and seven interview studies were identified, with 24 articles (92%) reporting positive attitudes, supporting the integration of acupuncture into Western medicine. Enablers identified were prior positive experience, belief in the treatment's efficacy, and patient demand. Barriers were lack of evidentiary knowledge or experience; lack of resources such as time, providers, and funding; and paradigm differences. Twenty studies (77%) focused on medical doctors or medical student perceptions. A conceptual framework for implementing and integrating acupuncture into Western medicine is proposed. CONCLUSION: Healthcare professionals' attitudes to acupuncture are positive. Barriers to integrating acupuncture into the hospital system exist at intrapersonal, interpersonal, and external levels, with lack of resources being the key barrier. Nurses' role in facilitating integration into Western medical pain management practice provides an avenue for future research. The proposed conceptual framework provides guidance for nursing researchers interested in the role of acupuncture and integrated medicine in patient-centric, value-based healthcare.

The digital patient journey solution for patients undergoing elective hip and knee arthroplasty: Protocol for a pragmatic randomized controlled trial.

AIM: To describe a randomized controlled trial (RCT) protocol that will evaluate the effectiveness of a digital patient journey (DPJ) solution in improving the outcomes of patients undergoing total hip and knee arthroplasty. BACKGROUND: There is an urgent need for novel technologies to ensure sustainability, improve patient experience, and empower patients in their own care by providing information, support, and control. DESIGN: A pragmatic RCT with two parallel arms. METHODS: The participants randomized assigned to the intervention arm (N = 33) will receive access to the DPJ solution. The participants in the control arm (N = 33) will receive conventional care, which is provided face to face by using paper-based methods. The group allocations will be blinded from the study nurse during the recruitment and baseline measures, as well as from the outcome assessors. Patients with total hip arthroplasty will be followed up for 8-12 weeks, whereas patients with total knee arthroplasty will be followed up for 6-8 weeks. The primary outcome is health-related quality of life, measured by the EuroQol EQ-5D-5L scale. Secondary outcomes include functional recovery, pain, patient experience, and self-efficacy. The first results are expected to be submitted for publication in 2020. IMPACT: This study will provide information on the health effects and cost benefits of using the DPJ solution to support a patient's preparation for surgery and postdischarge surgical care. If the DPJ solution is found to be effective, its implementation into clinical practice could lead to further improvements in patient outcomes. If the DPJ solution is found to be cost effective for the hospital, it could be used to improve hospital resource efficiency.