Throughout this case, health analytics are referenced that help physicians make an early leptospirosis diagnosis. Other analytics referenced aid in diagnosis, assessment, and disease management. When integrated into clinical decision making, medical algorithms can lead to better outcomes for patients and physicians.
Sandeep is a 60-year old internist who was diagnosed with type 2 diabetes at the age of 58. He traditionally turned to food as a source of comfort and relief during times of stress. Because of stress at work he did not recognize the early signs of diabetes for some time.
He developed a diabetic foot ulcer that became infected with MRSA earlier this year. This foot ulcer was followed by osteomyelitis necessitating amputation of his left hallux, or “big toe.” He was discouraged and depressed due to this amputation, and was worried about his chances of coronary and peripheral arterial disease. He was determined to get in shape and reverse his diagnosis of type 2 diabetes. Once Sandeep successfully recovered from surgery, he began physical therapy and decided to begin a vigorous exercise program. After being cleared by his physician he started with biking but soon extended to running.
Sandeep grew deeply committed to his exercise and diet regimen, often spending hours perusing fitness periodicals and experimenting with Atkins, South Beach and Weight Watchers. Several of his attempts to dedicate wholly to a fad diet failed, so he consulted with a local clinical nutritionist to find an ideal solution.
He eventually began to eat a balanced, nutritious diet high in protein and low in fat. An intense daily exercise regimen resulted in the normalization of his hemoglobin A1c. His levels fell to 5.3% from 7.2% within a relatively short period of time. Sandeep soon took his dedication to fitness to the next level and began to train for an ironman competition, which for a person of his age required completion of a 2.4-mile swim, 112-mile bicycle ride and 26.2-mile run within seventeen hours.
Though Wisconsin is known for its severe winters, the summers can be unusually warm. Sandeep completed the triathlon during one of the hottest weeks in August; the course ran through a state park and he swam across Lake Monona. He completed the course in sixteen hours with the title of “ironman.”
Presentation, Examination & Diagnosis
One week after the triathlon, Sandeep developed a high fever, headache, chills, muscle aches, diarrhea and abdominal pain. One of his colleagues mentioned that he looked jaundiced, which prompted Sandeep to visit the emergency room. The astute ER physician considered several infections, including leptospirosis.
Serologic testing showed a positive IgM ELISA assay against Leptospira, supporting the diagnosis. Antibiotic therapy was started and the patient made a full recovery.
Leptospirosis results from contact with water, soil, or food contaminated with the urine of infected animals. The bacteria can enter the body through skin or mucous membranes (eyes, nose or mouth). It is likely the case that Sandeep contracted the illness during his swim through the lake.
Analytics: Easily Implemented Methods of Diagnosis & Tools for Predicting Risk
Medical algorithms can save lives and assist with diagnosis as showcased here. The Medical Algorithms Company (TMAC) is a world-leading digital resource of more than 21,000 health analytics physicians can use to address many of the complications that arose in this case.
The case study highlights algorithms for diagnosing type 2 diabetes, identifying factors that contribute to a delay in the diagnosis of diabetes, identifying peripheral arterial disease, diabetic foot ulcer, and diabetic foot osteomyelitis. The leptospirosis evaluation tool, available at MedicalAlgorithms.com reviews the following clinical features: headache of sudden onset, fever, conjunctival suffusion, meningism, muscle pain, presence of conjunctival suffusion, jaundice, and albuminuria or nitrogen retention. Sandeep’s ER physician could have used this tool for more accurate patient assessment.
- Leptospirosis can be caught early on with the implementation of analytics in clinical practice.
- Medical algorithms, if used strategically and appropriately, can be instrumental in diagnosis, assessment and disease management.
- The medical algorithms highlighted in this case study are available at The Medical Algorithms Company and also on apervita.net.
Apervita is the leading health analytics community and marketplace, where prominent health professionals and enterprises from around the globe are transforming the world’s health knowledge into thousands of health analytics.
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About the Authors
Farva Jafri is a manager at Apervita, Inc. on the Content & Authoring and Legal teams. She has a Juris Doctorate and MBA from University of Illinois at Urbana-Champaign, and a Masters of Public Health from the University of Southern California Keck School of Medicine. Farva has an extensive background in consulting, marketing, research and legal fields. She works closely with TMAC to bring many of their high-quality algorithms onto Apervita’s platform.
Dr. Chad Rudnick, MD, FAAP is a board-certified pediatrician in Boca Raton, FL. He is the Medical Director of The Medical Algorithms Company. A proponent of incorporating medical technology into his practice, Dr. Rudnick uses telemedicine and medical algorithms from The Medical Algorithms Company in his daily practice to better serve his patients and their families. An accomplished medical writer, he maintains a popular pediatric blog, All Things Pediatric, and has written for numerous online and print publications including KevinMD.com.
John Svirbely, MD is a founder and Chief Medical Officer of The Medical Algorithms Company and the primary author of its medical algorithms. John is a co-founder of the Medical Algorithms Project and has developed its medical content for nearly 20 years. He has a BA degree from the Johns Hopkins University and his MD from the University of Maryland. He is a board-certified pathologist with a fellowship in medical microbiology and biomedical computing at Ohio State University. Currently he is in private practice in Cincinnati, Ohio. He has authored multiple books and articles on medical algorithms.
Note: This case study is fictional and based on actual events.