This study identifies systemic problems in the New Zealand Agricultural Innovation System (AIS) in relation to the AIS capacity to enact a co-innovation approach, in which all relevant actors in the agricultural sector contribute to combined technological, social and institutional change. Systemic problems are factors that negatively influence the direction and speed of co-innovation and impede the development and functioning of innovation systems. The contribution in the paper is twofold. Firstly, it combines both innovation system functions and systemic problems in an integrated analysis to asses an AIS at a country level, which has not been done previously in AIS literature. Secondly, it deepens the generic literature on structural-functional innovation systems analysis by looking at the interconnectedness between systemic problems and how these create core blocking mechanisms linked to the prevalent institutional logics (historically built-up and persistent structures and institutional arrangements) of the AIS. Results indicate that the existing New Zealand AIS has three main blocking mechanisms related to three institutional logics: (i) competitive science in silos, (ii) laissez faire innovation, and (iii) science centered innovation. These findings resemble weaknesses of AIS in other countries, and provide supportive evidence that co-innovation principles in many places have not yet been translated into agricultural innovation policies due to persistent and interlocked blocking mechanism and institutional logics. They point to the absence of effective systemic innovation policy instruments that pro-actively stimulate and support co-innovation. These instruments facilitate the counteracting of individual systemic problems and have a more transformative ambition; tackling the key institutional logics that hinder co-innovation, and hence supporting 'structural system innovation'.
Objective: To develop a prediction model for clinical outcomes after unilateral adrenalectomy for unilateral primary aldosteronism. Summary Background Data: Unilateral primary aldosteronism is the most common surgically curable form of endocrine hypertension. Surgical resection of the dominant overactive adrenal in unilateral primary aldosteronism results in complete clinical success with resolution of hypertension without antihypertensive medication in less than half of patients with a wide between-center variability. Methods: A linear discriminant analysis (LDA) model was built using data of 380 patients treated by adrenalectomy for unilateral primary aldosteronism to classify post-surgical clinical outcomes. The total cohort was then randomly divided into training (280 patients) and test (100 patients) datasets to create and validate a score system to predict clinical outcomes. An online tool (PASO [Primary Aldosteronism Surgical Outcome] predictor) was developed to facilitate the use of the predictive score. Results: Six presurgical factors associated with complete clinical success (known duration of hypertension, sex, antihypertensive medication dosage, body mass index, target organ damage and size of largest nodule at imaging) were selected based on classification performance in the LDA model. A 25-point predictive score was built with an optimal cutoff of greater than 16 points (accuracy of prediction = 79.2%; specificity = 84.4%; sensitivity = 71.3%) with an area under the curve of 0.839. Conclusions: The predictive score and the PASO predictor can be used in a clinical setting to differentiate patients who are likely to be clinically cured after surgery from those who will need continuous surveillance after surgery due to persistent hypertension.
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