Every time a cow leaves the hospital pen, it’s a chance to reflect. What does a successful treatment really mean in the dairy industry? How should we evaluate the cure rate in cows?
These are important questions because both labor and treatment costs for hospital cows are not trivial. Understanding these outcomes is critical for effective dairy herd health management.
In this article, I’ll present a case study to discuss the factors that influence cow health outcomes. And, we can evaluate what “success” truly means when treating cows in the hospital. The topic may seem complex, but here’s a summary of what I will talk about:
- When a cow is added to the hospital pen, what performance metrics can we use to evaluate its recovery beyond treating the infection?
- Why is it essential to consider a long-term perspective when evaluating treatment success after hospitalization?
- A review of an actual case study on mastitis in cows treatment.
- Why is defining both the treatment timing—or non-treatment— and success metrics critical to effective dairy herd health analysis?
Evaluating Dairy Cow Recovery: Performance Metrics Beyond Treating the Infections
Some animals leave the hospital cow pen only to leave the herd due to other complications. Commonly, these are not getting bred or are too low in milk. These results are common because mastitis in cows often occurs just before peak milk production and just when the animal is being bred.
As a result, these cows are sometimes left out of the systematic reproduction program. Additionally, the ration provided during their hospital stay is usually not formulated for milk production. This further impacts their performance.
The Importance of a Long-Term Perspective in Dairy Herd Health Analysis
Here we’ll examine some examples using the DHI-Plus software Rx tools to compare treatment outcomes for mastitis in dairy cows. These examples focus on animals that remained in the herd after completing the withdrawal period. Study the tables below to see the impact of taking a long-term perspective on dairy cow health monitoring.
Herd One: 1,585 Cases in One Year
| Days After Withdrawal | Still in the Herd | Sold | Died |
| 14 | 95% | 4% | 1% |
| 28 | 92% | 9% | 1% |
| 60 | 85% | 14% | 2% |
| 150 | 70% | 26% | 3% |
| 210 | 54% | 42% | 4% |
Herd Two: 2,181 Cases in One Year
| Days After Withdrawal | Still in the Herd | Sold | Died |
| 14 | 91% | 7% | 2% |
| 28 | 87% | 12% | 2% |
| 60 | 80% | 18% | 2% |
| 150 | 68% | 28% | 4% |
| 210 | 62% | 33% | 4% |
As you can see, time does make a difference. If we only look at what happened just after getting out of the hospital, I would say Herd One had the most treatment success. However, Herd Two achieved greater long-term success because they did a better job of keeping the Hospital cows in the herd. This demonstrates the critical role of dairy cow health management and using data to evaluate both short and long-term outcomes.
Case Study: Using Somatic Cell Count to Evaluate Dairy Cow Mastitis Treatments
When measuring treatment success, it’s important to define what “success” looks like. From my perspective, one valuable tool to determine a successful treatment is a drop in Somatic Cell Count (SCC). However, I find that analyzing quarter samples individually provides the most insights.
For the following example, I have used an advanced animal diagnostic machine that measure both SCC by quarter and a white blood cell differential. Below, Cow 3280 was diagnosed with mastitis in the left rear quarter with the following organisms.
| LR | 3/20/2020 | Enterococcus sp. (including faecalis and faecium) (27.5 Ct) |
| LR | 3/20/2020 | Staphylococcus sp. (33.3 Ct) |
| LR | 3/20/2020 | Str. uberis (36.4 Ct) |
She was treated for Enterococcus sp., and she also had a case of mastitis in the right front quarter.
| RF | 3/20/2020 | S. marcescens (39.2 Ct) |
Here are the SCC and white blood cell differential results:
Q Scout 3/4/2020
| 3280 | 3/4/20 | LF | Negative | 52 | 28 | 53.2% | <10 | 15.2% | 16 | 31.6% |
| 3280 | 3/4/20 | LR | Positive | 359 | 209 | 58.2% | 48 | 13.4% | 102 | 28.4% |
| 3280 | 3/4/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 3/4/20 | RF | Positive | 389 | 219 | 56.5% | 73 | 18.7% | 97 | 24.8% |
Q Scout taken 3/11/2020
| 3280 | 3/11/20 | LF | Negative | 37 | 13 | 33.9% | <10 | 7.1% | 22 | 58.9% |
| 3280 | 3/11/20 | LR | Positive | 459 | 304 | 66.2% | 35 | 7.6% | 120 | 26.1% |
| 3280 | 3/11/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 3/11/20 | RF | Negative | 323 | 173 | 53.8% | 32 | 9.8% | 117 | 36.4% |
Q Scout taken 3/30/2020
| 3280 | 3/30/20 | LF | Negative | 38 | 18 | 46.4% | 12 | 30.4% | <10 | 23.2% |
| 3280 | 3/30/20 | LR | Positive | 1273 | 844 | 66.3% | 264 | 20.8% | 165 | 12.9% |
| 3280 | 3/30/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 3/30/20 | RF | Positive | 685 | 408 | 59.6% | 146 | 21.2% | 131 | 19.2% |
Q Scout taken 4/6/2020
| 3280 | 4/6/20 | LF | Negative | 24 | <10 | 38.9% | <10 | 22.2% | <10 | 38.9% |
| 3280 | 4/6/20 | LR | Positive | 837 | 466 | 55.6% | 127 | 15.2% | 244 | 29.2% |
| 3280 | 4/6/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 4/6/20 | RF | Negative | 161 | 75 | 46.5% | 26 | 16.2% | 60 | 37.8% |
Q Scout taken 4/24/2020
| 3280 | 4/24/20 | LF | Negative | 29 | 13 | 43.2% | <10 | 9.1% | 14 | 47.7% |
| 3280 | 4/24/20 | LR | Positive | 971 | 616 | 63.4% | 80 | 8.2% | 275 | 28.3% |
| 3280 | 4/24/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 4/24/20 | RF | Negative | 313 | 170 | 54.1% | 36 | 11.5% | 108 | 34.4% |
Q Scout taken 5/14/2020
| 3280 | 5/14/20 | LF | Positive | 4983 | 3822 | 76.7% | 621 | 12.5% | 540 | 10.8% |
| 3280 | 5/14/20 | LR | Positive | 2159 | 1163 | 53.9% | 312 | 14.4% | 684 | 31.7% |
| 3280 | 5/14/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 5/14/20 | RF | Positive | 526 | 250 | 47.6% | 104 | 19.8% | 171 | 32.6% |
Taken 5/20/2020
| 3280 | 5/20/20 | LF | Positive | 15595 | >10000 | 86.1% | 1085 | 7% | 1089 | 7% |
| 3280 | 5/20/20 | LR | Positive | 3144 | 1998 | 63.5% | 525 | 16.7% | 621 | 19.8% |
| 3280 | 5/20/20 | RR | Disabled | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| 3280 | 5/20/20 | RF | Negative | 278 | 159 | 57.2% | 49 | 17.8% | 69 | 24.9% |
A lot is going on with this cow. To start, she is a three-teated animal and due to ongoing complications, may ultimately become a two-teated cow. This raises important questions: Do we want a two-teated cow in the herd? Should we even attempt to treat her?
Let’s focus on the mastitis infection in the right front (RF) teat and follow its progression over time. This is fascinating for me because nobody except a veterinarian will usually look at long-term results in such detail. Keep in mind that she was treated for Enterococcus sp. in her left rear (LR) teat and research shows that 40% of mastitis in cows resolves naturally without intervention.
It’s also helpful to interpret the data by understanding the SCC breakdown:
- The first number represents the total somatic cell count.
- The second number (from left to right) is Neutrophils, the white blood cells that are responsible for attacking bacteria during acute infections.
- The third number is Lymphocytes, which are white blood cells that trigger antibodies in an infection.
- Finally, the last group is Macrophages, present in high numbers during the clean-up phase of an infection.
By March 3rd, the total SCC in the right front quarter measured 389,000. The industry would say she had a subacute infection. Notice that Neutrophils are the highest portion of the cell count. By the following week, the cow was considered cured, as the Neutrophil count began to drop and the Macrophage count started to rise—an indication of the clean-up phase of infection.
Forward to March 30, and she faced reinfection in the same quarter, with the total SCC rising to over 685,000. At this point, neutrophils exceed 55% while macrophages are under 20%.
By April 6, however, she is cured again, with the total SCC dropping to 161,000, Neutrophils under 55%, and Macrophages over 20%.
A similar pattern repeated in May, with an infection detected on the 14th and cured by May 20. This proves to me that animals do fight and cure mastitis on their own. However, when the subclinical infection happens over and over again, it’s critical to evaluate the underlying problems, such as teat structure or the animal’s overall immune system function.
The Importance of Defining Success in Cow Treatment Plans
I want to point out that when measuring treatment success, it’s important to understand that the vast majority of cows treated with antibiotics in the hospital pen are already in the clean-up phase—which is when they are already going to self-heal.
From my perspective, a mastitis case can be considered cured when I see the Neutrophils drop and the Macrophages rise in a clean-up the debris stage. It’s also good to understand that the clean-up stage is when visible garget is seen in the milk. This is the aftermath of the immune system’s battle against the infection, not the battle itself.
If you’re interested in seeing an actual infection in the animal’s health data, review the data from the left front quarter of Cow 3280 between April 24 and May 20.
This is a great discussion to have with your veterinarian to ensure your cow protocol treatment strategies are effective. Define success, otherwise, you won’t know when you are improving or if an animal should be treated at all!