Prognosis and Strategies to Prevent Colic

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1 Published in IVIS with the permission of the AAEP Close this window to return to IVIS Prognosis and Strategies to Prevent Colic Nathaniel A. White II DVM, MS, Diplomate ACVS Author s Address: Marion Dupont Scott Equine Medical Center, VMRCVM-Virginia Tech, P.O. Box 1938, Leesburg, Virginia nawhite2@vt.edu. Predicting survival in horses with colic is challenging. The prevalence of survival when considering all types of colic is very high making prediction of non-survival difficult in individual cases. For the most part the ability to predict the possibility of death for an episode of colic is needed when horses are unresponsive to the initial treatment and there is a need to determine the chances that a treatment such as surgery will be successful with the needed economic investment. One method of predicting survival is to apply previous knowledge of outcome for specific diseases. Case fatality for specific diseases varies from few deaths in cases of simple colic to as much as 75% in some forms of strangulated intestine. 1 Case fatality of diseases requiring surgery is also related to disease duration prior to surgical correction. Therefore, fatality rates vary between hospitals depending on the time inherent in recognition of the problem and travel time required to reach a surgical facility. Simple obstructions of the large colon such as displacements and impactions have a low case fatality rate (<10%) 1,2 whereas simple obstructions or impactions of the small intestine are somewhat higher case fatality( 30%). 3 Impactions of the cecum have a higher case fatality rate than impactions of the large colon, but overall the fatality rate is relatively low ( 15%). 4 Initial reports of survival of strangulating lesions from was bleak. Small intestinal volvulus, incarcerations in mesenteric rents, and the epiploic foramen had the highest fatality rate (75-95%) followed by volvulus of the large colon (77%). Strangulating lipomas still have a long-term fatality rate of 62%. 5 In recent years reports of fatality rates have decreased with the change subjectively due to early horse referral, improved surgical experience, better anesthesia, 6 and application of critical care during the postoperative period. A recent report states short term case fatality of small intestinal strangulation has decreased from 75% in 1983 to 25% in and 14% for degree small intestinal volvulus. 8 Similarly fatality from large colon volvulus reported as high as 72% is now reported as low as 10-20% in some practices. 9 Long-term follow up has not been completed for many intestinal diseases. The case fatality rate for horses after discharge from the hospital is highest during the first 10 days after discharge with most occurring within the first two months. 10 Only cases of small intestine incarceration in the epiploic foramen had decreased survival more than 2 months after surgery. After 600 days the survival rate was 75%, an improvement compared to previous studies. Furthermore, most horses are able to return to their original use (>90%). 11

2 Though it has been reported that clinicians can reliably predict the outcome after surgery for an acute abdomen, the accuracy suffers from recent experience of the clinician and the complications which arise in individual cases. 12 To try and improve on prognosticating individual cases of colic, several investigations have attempted to use 11, single values, formulas or scoring systems to predict the odds of survival. Parry et al. proved that the cardiovascular values were of the most value in predicting survival. 16 Other studies also identified lactate 13, anion gap, 15 PCV 21, heart rate, 16 mucous membrane color, 26 peritoneal protein concentrations 26 and intraluminal presssure 18 as values which were significantly different in survivors and non-survivors. Unfortunately none of these formulas provide a clear-cut separation between survivors and non-survivors so these values cannot predict absolutely which horse will live and which one will die. Nonetheless some formulas and scores have increased the accuracy of predicting survival by combining those values which each add accuracy to the final prediction. 17 Parry et al. (1983) demonstrated a 93% accurate classification of survival when combining systolic pressure, blood lactate, blood urea and PCV. 17 Furr et al. (1995) used heart rate, lactate concentration, peritoneal protein concentration and mucous membrane color to determine a colic survival score with a 67% sensitivity and a 100% specificity (Figure 1). 26 This score predicted all horses that died but some horses that died were predicted to live. Orsini et al. (1988) developed a predictive model using blood lactate concentration and PCV to achieve a 96% accuracy. Though accurate and useful in a hospital setting, all these formulas suffer from a lack of simple factors which can be used horse side at the farm or stable when the clinician is trying to give an owner an accurate prognosis. Figure 1. Calculation of the Colic Severity Score requires recording heart rate, mucous membrane color and refill, peritoneal fluid protein concentration and blood lactate concentration. 26 A total score > 8 predicts the horse will not survive. This score is based on a prevalence of mortality of 21%. The accuracy when used on horses for a validation was 93%. Some horses predicted live died while the score accurately predicted death in all horses that died. Variable Score Pulse rate < >90 Peritoneal < >4.7 Protein g/dl Lactate mg/dl < >90 MM Normal CTR>3 or cyanotic = Even if these formulas could be used in practice during the initial examination for colic, the high prevalence of survival in a normal population of horses prevents these formulas from improving the predictability compared to the clinicians experience or tossing a coin. However, once a decision is made to classify a horse as a referral candidate, these

3 prognostic systems can be helpful. With the advent of laptop computers and hand held devices these formulas can be rapidly utilized to provide the odds that a horse will survive or need surgery. Reeves et al. (1989) developed a model to predict the need for surgery and death using readily available clinical values and included the ability to specify the prevalence of death in the population being examined (Figure 2). 31 Though no formula can be 100% accurate, this system can provide confidence in one s medical judgment while accounting for the prevalence of surgery and survival in a particular practice. Figure 2. Model to predict death based on the age, sex, breed, pulse strength, heart rate, treatment medical or surgical, PCV, evidence of trauma, CRT and prevalence of death from colic in the population. 31 A) This example shows a low odds for death based on a horse needing medical treatment. Eight of 100 horses with these values are predicted to die. Enter VARIABLES data Age in years 12 Sex s Breed qtr Peripheral pulse strength 1 Heart rate beats/min 50 Surgical or medical treatment? med Packed cell volume % 58 Self-inflicted trauma 0 Capillary refill time /sec 3.0 Prevalence of death (%) 5 Likelihood ratio for death 1.67 Post-test odds of death 0.09 Post-test probability of death 0.08 DATA CODING INFORMATION - PROGNOSIS MODEL AGE: Enter age in years SEX: Type "S" for stallion, "G" for gelding or "F" for female BREED: Type "Arab" for Arabian = 1 "App" for Appaloosa = 2 "AmSB" for American Saddlebred = 3 "Morg" for Morgan = 4 "Qtr" for Quarterhorse = 5 "STB" for Standardbred = 6 "TB" for Thoroughbred = 7 "Other" for any other breed = 8 PERIPHERAL PULSE STRENGTH: normal= 0, weak= 1 TREATMENT?: Type "med" for medical or "surg" for surgical SELF-INFLICTED TRAUMA: absent= 0, present= 1

4 B) This example shows the odds for death based on a disease predicted to require surgery. Seventy-two out of 100 horses with these values are predicted to die. FOR DATA ENTRY HELP HIT <Pg Dn> VARIABLES Enter data Age in years 12 Sex g Breed tb Peripheral pulse strength 1 Heart rate beats/min 85 Surgical or medical treatment? surg Packed cell volume % 50 Self-inflicted trauma 1 Capillary refill time /sec 3.0 Prevalence of death (%) 20 Likelihood ratio for death Post-test odds of death 2.63 Post-test probability of death 0.72 DATA CODING INFORMATION - PROGNOSIS MODEL AGE: Enter age in years SEX: Type "S" for stallion, "G" for gelding or "F" for female BREED: Type "Arab" for Arabian = 1 "App" for Appaloosa = 2 "AmSB" for American Saddlebred = 3 "Morg" for Morgan = 4 "Qtr" for Quarterhorse = 5 "STB" for Standardbred = 6 "TB" for Thoroughbred = 7 "Other" for any other breed = 8 PERIPHERAL PULSE STRENGTH: normal= 0, weak= 1 TREATMENT?: Type "med" for medical or "surg" for surgical SELF-INFLICTED TRAUMA: absent= 0, present= 1 Unless one is proficient in estimating or calculating prevalence of death and using a validated formula of easily obtained values from the physical examination, the safest way to help owners decide about the chance of survival is to provide a prognosis based on the disease classification. If the disease process can be categorized (simple colic, obstruction, strangulation, eneritis, ulceration, peritonitis), it is usually possible to give a reasonable estimate of the chance for survival. One important factor is the disease duration, which can alter the outcome of any disease depending on the severity of shock. Furthermore,

5 as treatments and critical care have improved case fatality rates including long-term outcome. Prevention of Colic Two factors should be considered when trying to prevent colic; farm factors and horse 1, 32 factors. Farm factors include management, use, feeding, and environment. The associated risks on farms with high rates of colic include poor parasite control, high concentrate levels in the diet, multiple sources of concentrates (including supplements which contain higher than suspected amounts of soluble carbohydrates), chronic deficiency in water, excessive use of NSAIDS, acute changes in hay or grain, and horses in training that are confined and fed large amounts of carbohydrates and lesser amounts of roughage. Altering these risks with management has decreased the incidence of colic on farms with a higher than average annual colic rate. Based on these known factors, colic prevention should start by making sure horses have a constant source of fresh water, ensuring that forage makes up at least 60% or more of the diet, and that concentrates (soluble carbohydrates) are fed at the minimal level required to maintain weight and performance. The turn out and exercise routines should be regular and consistent. Changes in feed should be completed over a 7-10 day period. Parasite control must be optimal. Parasite control starts with fecal egg counts several times during the year or more often when horses are moved on and off farms or stables. Though interval worming would seem to be sufficient to control common parasites, small strongyles and tapeworms have both been linked to increased colic risk and may not be totally controlled by some 33, 34 programs. Control of small stronglye infection on farms was reported to decrease the incidence of colic. 33 On farms with a high incidence of colic (>10 colic cases per 100 horses per year) careful monitoring of the daily management and measurement of the energy, protein and fiber in the diet should be the first steps in assessing the farm for colic risk. An example of the need for this type of feed analysis is the unrealized carbohydrate overload, which can occur from feeding bran. Unbeknown to many owners or managers, bran can have a high soluble carbohydrate content. If fed as a laxative in addition to a regular grain diet, the soluble carbohydrate intake in a horse s diet can be doubled (Figure 3). When considering individual horse colic, internal factors are potential contributors as well as the diet and environment. Known factors, which affect individual horses, include acute confinement due to injury, lack of turn out, gastric ulceration due to performance, and aerophagia. These factors are often associated with simple colic with no other diagnosis. Horse factors may be impossible to control, although some horses respond to turn out 24 hours a day and a total forage diet. This arrangement may not be compatible with certain types of performance, but often this ad lib exercise and feeding system can decrease recurrent colic. Other horse factors include diseases which are not related to management including intestinal accidents such as lipomas or incarcerations in internal hernias. Factors, which affect these this type of intestinal disease, have not been widely investigated.

6 Identifying horses at high-risk may help determine if there is a generalized colic risk on the farm or if specific individuals are responsible for a majority of colic episodes. Often the problem may be a basic diet or management issue such as lack of fresh water, feeding large amounts concentrates with insufficient forage intake in the diet, or excessive use of medications such as NSAIDs. These factors will not always be apparent in the history of the farm or the owner s assessment of management. Therefore, careful observations and record keeping are often prerequisites to understanding the colic risk factors on a farm. Figure 3. Analysis of bran from a farm, which routinely fed a bran mash to all horses daily. The energy content of the bran was as high as corn and in sufficient amounts could significantly increase the carbohydrate content of the diet. This increase lowers consumption of forage and causes dehydration of ingesta in the colon. References 1. White NA. Epidemiology and etiology of colic. In: White NA, ed. The Equine Acute Abdomen. Philadelphia: Lea and Febiger; 1990: Dabareiner DM, White NA. Large Colon Impaction In Horses: 147 cases ( ). J. Am. Vet. Med. Assoc. 1995;206: Parks AH, Doran RE, White NA, Allen D, Baxter GM. Ileal impaction in the horse: 75 cases. Cornell Veterinarian. 1989;79(1): Colatos C, Romano S. Cecal impaction in horses: Causes, diagnosis, and medical treatment. Compend Contin Educ Pract Vet. 1993;15: Edwards GB, Proudman CJ. An analysis of 75 cases of intestinal obstruction caused by pedunculated lipomas. Equine Vet J. Jan 1994;26(1): Trim CM, Adams JG, Cowgill LM, Ward SL. A retrospective survey of anaesthesia in horses with colic. Equine Vet J Suppl. Jun 1989(7): Freeman DE, Hammock P, Baker GJ, et al. Short- and long-term survival and prevalence of postoperative ileus after small intestinal surgery in the horse. Equine Vet J Suppl. Jun 2000(32):42-51.

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8 25. Milne EM, Woodman MP, Doxey DL. Use of clinical measurements to predict the outcome in chronic cases of grass sickness (equine dysautonomia). Vet Rec. Apr ;134(17): Furr MO, Lessard P, White NA, 2nd. Development of a colic severity score for predicting the outcome of equine colic. Vet Surg. Mar-Apr 1995;24(2): Sandholm M, Vidovic A, Puotunen-Reinert A, Sankari S, Nyholm K, Rita H. D- dimer improves the prognostic value of combined clinical and laboratory data in equine gastrointestinal colic. Acta Vet Scand. 1995;36(2): Proudman CJ, Smith JE, Edwards GB, French NP. Long-term survival of equine surgical colic cases. Part 2: modelling postoperative survival. Equine Vet J. Jul 2002;34(5): Ihler CF, Venger JL, Skjerve E. Evaluation of clinical and laboratory variables as prognostic indicators in hospitalised gastrointestinal colic horses. Acta Vet Scand. 2004;45(1-2): Saulez MN, Cebra CK, Tornquist SJ. The diagnostic and prognostic value of alkaline phosphatase activity in serum and peritoneal fluid from horses with acute colic. J Vet Intern Med. Jul-Aug 2004;18(4): Reeves MJ, Curtis CR, Salman MD, Reif JS, Stashak TS. A multivariable prognostic model for equine colic patients. Preventive Veterinary Medicine. 1990;9(4): Tinker MK, White NA, Lessard P, et al. Prospective study of equine colic risk factors. Equine Vet J. Nov 1997;29(6): Uhlinger C. Effects of three anthelmintic schedules on the incidence of colic in horses. Equine Veterinary Journal. 1989;7: Proudman CJ, Holdstock NB. Investigation of an outbreak of tapewormassociated colic in a training yard. Equine Vet J Suppl. Jun 2000(32):37-41.