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Evidence-Based Diabetes Management
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For years, physicians have struggled to predict the postsurgical recovery time of their patients—a variable with unknown causes. Gauging the period of recovery gives patients a sense of how soon they may be up and about, returning to their normal lives and to work. A prolonged recovery time can have multiple consequences, including psychosocial ones for the patient and economic ones for society.
For persons with diabetes, recovery from surgery is particularly complicated. Research has shown that insulin resistance could result from surgery, and its intensity could define the recovery period. These patients also face a greater risk of infection and wounds that do not heal, leading to other health problems and higher hospital costs. Patients who suffer these complications risk being readmitted to the hospital, which brings on the added costs. The need to identify which patients face this risk has never been greater, as the Affordable Care Act (ACA) has brought new penalties for hospitals that see too many readmissions within 30 days of discharge.
Now, a new study from Stanford University has opened up the potential for predictive gene signatures and the development of a diagnostic test that could foretell clinical recovery.1 Such a test could have enormous value when surgical patients have diabetes, for it could help hospitals stratify and target patients for enhanced care to prevent readmission.
Traditional recovery parameters have included metrics such as length of hospital stay, while recent studies have focused on more patient-centered outcomes such as absence of symptoms, ability to perform regular activities, return to work, and quality of life. While there have been attempts to define the process of postoperative recovery, various stakeholders view the matter differently. One such definition attributes the following characteristics to recovery following surgery:
• an energy-requiring process
• a return to a state of normality and wholeness defined by comparative standards
• regaining control of physical, psychological, social, and habitual functions
• returning to preoperative levels of independence in activities of daily living
• regaining one’s optimum level of well-being.2
Although the parameters for measuring recovery have evolved over the years, the available data are not sufficient for drawing predictions on the recovery period. Perioperative methods, such as enhanced recovery protocols, can accelerate recovery and reduce hospital stays,3 but their impact on patient recovery following discharge remains unknown. In an attempt to solve this conundrum, researchers at Stanford University evaluated the molecular signature of patients undergoing surgery to predict patient recovery.4
Using mass spectrometry (MS) as a tool, the scientists measured precise changes in specific molecules of the immune system in patients who had undergone major surgery, including phosphorylation changes in signaling proteins. Whole-blood samples were collected from patients who had undergone hip surgery (primary hip arthoplasty). The samples, collected 1 hour before surgery and at predetermined times after surgery (1 hour, 24 hours, 72 hours, and 6 weeks), were stained with antibodies for cell surface proteins and phosphoepitopes of intracellular proteins, and analyzed by MS.
Researchers discovered that the activithe first 24 hours following surgery could be a predictive signature of how quickly a patient would recover from surgeryinduced pain and fatigue. Simultaneous monitoring of subsets of immune cells provided a global view of immune alterations following surgery in innate and adaptive responses. Additionally, fatigue, pain, and functional impairment of the hip were assessed using 2 different scales: the Surgical Recovery Scale and the Western Ontario and McMaster Universities Arthritis Index.4
Analysis of the results corroborated previous findings: innate immune cells expanded soon after surgery, while the number of cells associated with the adaptive response shrank. As expected, signaling pathways were activated quite early in the process, and the responses were parallel to adaptive and immune cell responses.
A feature of the current study was the evaluation of specific subsets of cells within the immune system, which helped identify and analyze responses that were likely missed in the global immune analysis conducted in earlier investigations.4 When the results of the pain measurements were correlated with the molecular responses, researchers found a 40% to 60% variability in patient recovery rates.
The authors acknowledge that the study population suffered minimal comorbidities and that these patients underwent only 1 type of surgical procedure. Consequently, a likelihood of variation in immune response exists, based on the type of surgical procedure and the influence of comorbidities such as diabetes.
Diabetes Can Complicate Surgical Recovery, Extend Hospital Stays, and Incur Additional Costs
Because insulin resistance increases during surgery, a person who already has elevated blood glucose can experience problems when non insulin-sensitive cells rapidly absorb glucose. This could result in infections and cardiovascular complications, while a reduced glucose uptake in muscle could reduce muscle function and impair mobility.5
Diabetes-associated peripheral arterial disease can reduce blood flow to the surgical area, resulting in delayed recovery. Additionally, in patients who have poor control of their blood sugar levels, surgical wounds stand a higher chance of being infected, further delaying recovery. Taken together, surgical stress boosts the blood sugar levels in the body, which can develop into diabetic ketoacidosis and complicate the process even further.6
Those with type 1 diabetes mellitus (T1DM), the so-called juvenile or insulin-dependent form of the disease, appear to be at higher risk of surgical complications than those with type 2 diabetes mellitus (T2DM). A study conducted at the Duke University Medical Center evaluated surgical recovery and perioperative complications in patients who had undergone orthopedic procedures for joint replacement between 1988 and 2003. The analysis compared patients with T1DM with those suffering from T2DM, and found that T1DM patients had significantly longer hospital stays, and increased incidence of myocardial infection, pneumonia, urinary tract infection, postoperative hemorrhage, wound infection, and death, resulting in a significant uptick in the cost of care.7
Research presented at the 21st annual meeting of the American Association of Clinical Endocrinologists compared the length of stay following elective surgery in patients with diabetes and those without, and analyzed the influence of comorbidities and perioperative complications on healthcare costs. Using data from the Healthcare Cost and Utilization Project, the researchers found that patients with diabetes had a higher number of chronic conditions and comorbidities when admitted for surgery, compared with those without (7.6 vs 3.6 diagnoses). Additionally, diabetes nearly doubled the patient stay in hospitals: 9.08 days for those with diabetes versus 4.76 days for those without; the associated costs per patient were $19,547 versus $15,873.8
The study results point to increased complications in patients with diabetes undergoing surgery, resulting in longer hospital stays and, thereby, higher costs.8 The longer stays are a drain on hospital revenue, so greater attention to maintaining the glycemic levels of these patients could have a tremendous impact on patient outcomes as well as healthcare costs.
CMS Challenges Hospital Vigilance
Complicated recoveries translate into higher readmission rates for surgical patients with diabetes. Findings ways to trim the length of hospital stays and prevent readmissions could lead to significant cost savings. The Healthcare Cost and Utilization Project, a federal-state-industry partnership, identified diabetes, mood disorders, and schizophrenia as conditions with the highest number of 30-day all-cause hospital readmissions for Medicaid. Complications associated with diabetes cost Medicaid $251 million in readmissions in 2011, accounting for 3.3% of the total cost of Medicaid readmissions.9
Both T1DM and T2DM were identified as risk factors for readmission in patients undergoing lumbar fusion surgery. While T2DM patients had longer hospital stays, T1DM patients had several complications post surgery, including sepsis, ventilator-associated respiration, wound-related infection, urinary tract infection, and pneumonia. These resulted in more extended hospital stays and readmissions within 30 days.10 Medicare patients receiving a kidney transplant had a 29% increased incidence of 30-day readmissions in women with diabetes and a 12% increase in men with diabetes.11
EBDM
With this kind of evidence, Medicare, through provisions of the ACA, established the Hospital Readmissions Reduction Program (effective October 2012), which mandates reduced reimbursement to hospitals participating in the inpatient prospective payment systems that have higher readmissions.12 CMS hopes that these penalties will prod hospitals to take steps to better monitor patients at high risk of readmission, including those with diabetes. References
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5. Ljungqvist O, Jonathan E. Rhoads lecture 2011: insulin resistance and enhanced recovery after surgery. JPEN J Parenter Enteral Nutr. 2012;36(4):389-398.
6. Kim J. Surgical complications in diabetic patients. Livestrong website. http://www.livestrong.com/article/69142-complications-surgery-diabetic/. Reviewed October 9, 2013. Accessed October 20, 2014.
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8. Figaro MK, Jung K, Lim D, BeLue R. The impact of diabetes on length of stay and hospital costs after elective surgical procedures. Presented at the American Association of Clinical Endocrinologists 21st Annual Scientific and Clinical Congress; May 23-27, 2012; Philadelphia, PA. Abstract 232. https://www.aace.com/files/abstracts-2012.pdf. Accessed October 21, 2014.
9. Hines AL, Barrett ML, Jiang HJ, Steiner CA. Conditions with the largest number of adult hospital readmissions by payer, 2011. Healthcare Cost and Utilization Project: Statistical Brief #172. Agency for Healthcare Research and Quality website. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb172-Conditions-Readmissions-Payer.pdf. Published April 2014. Accessed October 21, 2014.
10. Golinvaux NS, Varthi AG, Bohl DD, Basques BA, Grauer JN. Complication rates following elective lumbar fusion in patients with diabetes: insulin dependence makes the difference. Spine (Phila Pa 1976). 2014;39(21):1809-1816.
11. McAdams-Demarco MA, Grams ME, Hall EC, Coresh J, Segev DL. Early hospital readmission after kidney transplantation: patient and center-level associations. Am J Transplant. 2012;12(12):3283-3288.
12. Readmissions Reduction Program. CMS website. http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Readmissions-Reduction-Program.html. Accessed October 20, 2014.