Implementation of Robert's Coping with Labor Algorithm© in a large tertiary care facility

Objectiveto implement use of Roberts’ Coping with Labor Algorithm^© (CWLA) with laboring women in a large tertiary care facility.Designthis was a quality improvement project to implement an alternate approach to pain assessment during labor. It included system assessment for change readiness, implementation of the algorithm across a 6-week period, evaluation of usefulness by nursing staff, and determination of sustained change at one month. Stakeholder Theory (Friedman and Miles, 2002) and Deming's (1982) Plan-Do-Check-Act Cycle, as adapted by Roberts et al (2010), provided the framework for project implementation.Settingthe project was undertaken on a labor and delivery (L&D) unit of a large tertiary care facility in a southwestern state in the USA. The unit had 19 suites with close to 6000 laboring patients each year.Participantsfull, part-time, and per diem Registered Nurse (RN) staff (N=80), including a subset (n=18) who served as the pilot group and champions for implementing the change.Findingsa majority of RNs held a positive attitude toward use of the CWLA to assess laboring women's coping with the pain of labor as compared to a Numeric Rating Scale (NRS). RNs reported usefulness in using the CWLA with patients from a wide variety of ethnicities. A pre-existing well-developed team which advocated for evidence-based practice on the unit proved to be a significant strength which promoted rapid change in practice.Implications for practicethis work provides important knowledge supporting use of the CWLA in a large tertiary care facility and an approach for effectively implementing that change. Strengths identified in this project contributed to rapid implementation and could be emulated in other facilities. Participant reports support usefulness of the CWLA with patients of varied ethnicity. Assessment of change sustainability at 1 and 6 months demonstrated widespread use of the algorithm though long-term determination is yet needed.     

HITCal: a software tool for analysis of video head impulse test responses

Conclusion: The developed software (HITCal) may be a useful tool in the analysis and measurement of the saccadic video head impulse test (vHIT) responses and with the experience obtained during its use the authors suggest that HITCal is an excellent method for enhanced exploration of vHIT outputs. Objective: To develop a (software) method to analyze and explore the vHIT responses, mainly saccades. Methods: HITCal was written using a computational development program; the function to access a vHIT file was programmed; extended head impulse exploration and measurement tools were created and an automated saccade analysis was developed using an experimental algorithm. For pre-release HITCal laboratory tests, a database of head impulse tests (HITs) was created with the data collected retrospectively in three reference centers. This HITs database was evaluated by humans and was also computed with HITCal. Results: The authors have successfully built HITCal and it has been released as open source software; the developed software was fully operative and all the proposed characteristics were incorporated in the released version. The automated saccades algorithm implemented in HITCal has good concordance with the assessment by human observers (Cohen’s kappa coefficient = 0.7).     

Automatic Extraction of Comprehensive Cardiac CT Angiography Parameters: A Novel Program with High Accuracy and Efficiency

We tested the accuracy and efficiency of a novel automated program capable of extracting 15 cardiac computed tomography angiography (CTA) parameters from clinical CTA reports. Five hundred cardiac CTA reports were retrospectively collected and processed. All reports were pre-populated with a structured template per guideline. The program extracted 15 parameters with high accuracy (97.3 %) and efficiency (84 s). This program may be used at other institutions with similar accuracy if its report format follows the Society of Cardiovascular Computed Tomography (SCCT) guideline recommendation.     

Automatic initial contact detection during overground walking for clinical use

The division of gait into cycles is crucial for identifying deficits in locomotion, particularly to monitor disease progression or rehabilitative recovery. Initial contact (IC) events are often used to separate movement into repetitive cycles yet automatic methods for IC identification in pathological gait are limited in both number and capacity. The aim of this work was to develop a more precise algorithm in IC detection. A projected heel markers distance (PHMD) algorithm is presented here and compared for accuracy to the high pass algorithm (HPA) in IC identification. Kinematic gait data from two clinical cohorts were analyzed and processed automatically for IC detection: (1) unilateral total hip arthroplasty (THA) patients (n = 27) and (2) cerebral palsy pediatric (CPP) patients (n = 20). IC events determined by the two algorithms were benchmarked against the IC events detected manually and from force plates. The PHMD method detected 96.6% IC events in THA patients and 99.1% in CPP patients with an average error of 5.3 ms and 18.4 ms. The HPA method detected 99.1% IC events in THA patients and 97.3% IC events in CPP patients, with an average error of 57.5 ms and 10.2 ms. PHMD identified no superfluous IC events, whereas 51.5% of all THA IC and 47.6% of CPP IC were superfluous events requiring manual deletion with HPA. With the superior comparison against the current gold standard, the PHMD algorithm appears valid for a wide spectrum of clinical data sets and allows for precise, fully automatic processing of kinematic gait data without additional sensors, triggers, or force plates.     

Underutilisation of breast cancer prevention medication in Australia

Increased implementation of proven prevention strategies is required to combat rising breast cancer incidence. We assessed use of risk reducing medication (RRMed) by Australian women at elevated breast cancer risk. Only 2.4% had ever used RRMed. Higher breast cancer risk was statistically significantly associated with use of RRMed (OR 1.82, 95%CI: 1.08–3.07, p = 0.02 for ≥30% lifetime risk compared with 16%–29% lifetime risk), but parity, education level and family history of breast cancer were not. Breast cancer prevention medications are underutilised. Efforts are needed to incorporate breast cancer risk assessment and risk management discussions into routine health assessments for women.     

Falsely elevated human epididymis protein 4 results and Risk of Ovarian Malignancy Algorithm in polymorbid women after solid organ transplantation: A pilot and case‐control study

Background

Cancer prevention is essential after transplantation (Tx). The use of HE4 and Risk of Ovarian Malignancy Algorithm (ROMA) is recommended as a tool for selective ovarian cancer screening; however, creatinine is a known confounder. This study assessed the reliability of HE4, CA125, and ROMA after Tx.

Methods

We matched a total of 202 women without gynecological malignancies and 236 men by age and serum creatinine. Each pair consisted of a patient after Tx (kidney, liver, heart, and pancreas) and a diseased but non‐Tx consecutive patient. Serum HE4, CA125 (Roche Cobas 6000), and creatinine (enzymatic, Abbott Architect) were measured in all patients.

Results

Creatinine correlated with HE4 (women: r = .864, P < .0001; men: r = .848, P < .0001). Age correlated slightly with HE4 in women (r = .250, P < .005) and men (r = .240, P < .0005). HE4 in women after Tx (median of 84.8 pmol/L) was significantly higher than non‐Tx women (53.7 pmol/L, P < .0001) in the reference range of serum creatinine. Neither HE4 nor CA125 correlated with tacrolimus concentration, but anemia, hyperparathyroidism, kidney, liver, and lung diseases were possible confounders for HE4 after transplantation (P < .05).

Conclusion

Human epididymis protein 4 (HE4) was significantly increased in women after solid organ transplantation compared to levels without transplants matched by age and serum creatinine. HE4 results may be misleading in these patients.

     

Massive transfusion prediction in patients with multiple trauma by decision tree: a retrospective analysis

Early initial massive transfusion protocol and blood transfusion can reduce patient mortality, however accurately identifying the risk of massive transfusion (MT) remains a major challenge in severe trauma patient therapy. We retrospectively analyzed clinical data of severe trauma patients with and without MT. Based on analysis results, we established a MT prediction model of clinical and laboratory data by using the decision tree algorithm in patients with multiple trauma. Our results demonstrate that shock index, injury severity score, international normalized ratio, and pelvis fracture were the most significant risk factors of MT. These four indexes were incorporated into the prediction model, and the model was validated by using the testing dataset. Moreover, the sensitivity, specificity, accuracy and area under curve values of prediction model for MT risk prediction were 60%, 92%, 90% and 0.85. Our study provides an easy and understandable classification rules for identifying risk factors associated with MT that may be useful for promoting trauma management.