Healthy Eating for Elective Major Orthopedic Surgery: Quality, Quantity, and Timing.

Improvements to enhanced recovery pathways in orthopedic surgery are reducing the time that patients spend in the hospital, giving an increasingly vital role to prehabilitation and/or rehabilitation after surgery. Nutritional support is an important tenant of perioperative medicine, with the aim to integrate the patient's diet with food components that are needed in greater amounts to support surgical fitness. Regardless of the time available between the time of contemplation of surgery and the day of admission, a patient who eats healthy is reasonably more suitable for surgery than a patient who does not meet the daily requirements for energy and nutrients. Moreover, a successful education for healthy food choices is one possible way to sustain the exercise therapy, improve recovery, and thus contribute to the patient's long-term health. The expected benefits presuppose that the patient follows a healthy diet, but it is unclear which advice is needed to improve dietary choices. We present the principles of healthy eating for patients undergoing major orthopedic surgery to lay the foundations of rational and valuable perioperative nutritional support programs. We discuss the concepts of nutritional use of food, requirements, portion size, dietary target, food variety, time variables of feeding, and the practical indications on what the last meal to be consumed six hours before the induction of anesthesia may be together with what is meant by clear fluids to be consumed until two hours before. Surgery may act as a vital "touch point" for some patients with the health service and is therefore a valuable opportunity for members of the perioperative team to promote optimal lifestyle choices, such as the notion and importance of healthy eating not just for surgery but also for long-term health benefit.

Oral Hydration Before and After Hip Replacement: The Notion Behind Every Action.

Introduction: Even though nearly 20 patients undergo hip replacement every hour just in Italy and the United Kingdom, it is unclear what are the most appropriate oral hydration practices that patients should follow before and after surgery. Improper administration can cause postoperative fluid disturbances or exacerbate pre-existing conditions, which are not an uncommon find in older subjects. Significance: Considering that the number of hip operations is expected to increase in the next years as well as the age of patients, it is important to recall the notions behind water balance, especially in light of modern surgical and anesthetic practices. This technical perspective discusses the perioperative changes in the hydration status that occur during hip replacement and provides the concepts that help clinicians to better manage how much water the patient can drink. Results: The points of view of the surgeon, the anesthetist, and the nurse are offered together with the description of mineral waters intended for human consumption. Before surgery, water should be always preferred over caffeinated, sugar-sweetened, and alcoholic beverages. The drinking requirements on the day of surgery should consider the water output from urine, feces, respiration, exudation, and bleeding along with the water input from metabolic production and intravenous administration of fluids and medications. Healthy eating habits provide water and should be promoted before and after surgery. Conclusions: The judgment on which is the most appropriate approach to oral hydration practices must be the responsibility of the multidisciplinary perioperative team. Nevertheless, it is reasonable to argue that, in the presence of a patient with no relevant illness and who follows a healthy diet, it is more appropriate to stay closer to dehydration than liberalizing water intake both prior to surgery and in the early postoperative hours until the resumption of normal physiological functions.

Using Neural Networks with Routine Health Records to Identify Suicide Risk: Feasibility Study.

BACKGROUND: Each year, approximately 800,000 people die by suicide worldwide, accounting for 1-2 in every 100 deaths. It is always a tragic event with a huge impact on family, friends, the community and health professionals. Unfortunately, suicide prevention and the development of risk assessment tools have been hindered by the complexity of the underlying mechanisms and the dynamic nature of a person's motivation and intent. Many of those who die by suicide had contact with health services in the preceding year but identifying those most at risk remains a challenge. OBJECTIVE: To explore the feasibility of using artificial neural networks with routinely collected electronic health records to support the identification of those at high risk of suicide when in contact with health services. METHODS: Using the Secure Anonymised Information Linkage Databank UK, we extracted the data of those who died by suicide between 2001 and 2015 and paired controls. Looking at primary (general practice) and secondary (hospital admissions) electronic health records, we built a binary feature vector coding the presence of risk factors at different times prior to death. Risk factors included: general practice contact and hospital admission; diagnosis of mental health issues; injury and poisoning; substance misuse; maltreatment; sleep disorders; and the prescription of opiates and psychotropics. Basic artificial neural networks were trained to differentiate between the suicide cases and paired controls. We interpreted the output score as the estimated suicide risk. System performance was assessed with 10x10-fold repeated cross-validation, and its behavior was studied by representing the distribution of estimated risk across the cases and controls, and the distribution of factors across estimated risks. RESULTS: We extracted a total of 2604 suicide cases and 20 paired controls per case. Our best system attained a mean error rate of 26.78% (SD 1.46; 64.57% of sensitivity and 81.86% of specificity). While the distribution of controls was concentrated around estimated risks < 0.5, cases were almost uniformly distributed between 0 and 1. Prescription of psychotropics, depression and anxiety, and self-harm increased the estimated risk by ~0.4. At least 95% of those presenting these factors were identified as suicide cases. CONCLUSIONS: Despite the simplicity of the implemented system, the proposed methodology obtained an accuracy like other published methods based on specialized questionnaire generated data. Most of the errors came from the heterogeneity of patterns shown by suicide cases, some of which were identical to those of the paired controls. Prescription of psychotropics, depression and anxiety, and self-harm were strongly linked with higher estimated risk scores, followed by hospital admission and long-term drug and alcohol misuse. Other risk factors like sleep disorders and maltreatment had more complex effects.