A new tool for the management of infection in patients with febrile neutropenia.

BACKGROUND: We describe a novel analytical technique for determining instantaneous trends in body temperature data, which may assist clinicians in optimizing antimicrobial therapy in patients with febrile neutropenia. The paper presents a new algorithm, based on a modified second backward difference (M2BD) matrix filter for monitoring temperature response to anti-microbial chemotherapies in neutropenic patients and develops techniques for extracting accurate, instantaneous trend data from clinical time series data. Such an algorithm is needed because it is difficult to assess patient wellbeing in those who are neutropenic. Temperature data, a key indicator of response to antimicrobial therapy, are typically very noisy, with many fluctuations, making it very difficult to identify underlying trends in real time. Clinicians are therefore forced to make important decisions concerning drug therapy on imperfect data. METHODS: In order to determine the underlying temperature trend, analysis of synthetic time series data (with a known underlying trend) was undertaken using both the CUSUM technique and the M2BD matrix filter. The CUSUM analysis was undertaken using four reference temperatures, 37.5 degrees C, 38.0 degrees C, 38.5 degrees C and 39.0 degrees C. A validation study was also undertaken using four sets of noisy synthetic temperature data to evaluate the performance of the M2BD filter. The M2BD filter was then used to analyse anonymized serial temperature data from a neutropenic patient undergoing chemotherapy. RESULTS: For all four reference temperatures the CUSUM analysis failed to predict the underlying temperature trend. By comparison, the M2BD filter extracted, in real time, the underlying temperature trend with great accuracy and no time lag. In the validation study, the M2BD filter accurately extracted the underlying temperature trend for all four of the synthetic datasets. With regard to the anonymized patient data, the M2BD filter again performed well, accurately determining the underlying trend. CONCLUSION: The study demonstrated that the M2BD filter is capable of instantaneously extracting underlying trends from clinical time series data. This finding suggests that this algorithm has great potential as a tool for assisting clinicians in the management of patients with febrile neutropenia.

Peripheral blood stem cell transplantation in myeloma using CD34 selected cells.

We have performed nine CD34 selection procedures on peripheral blood stem cells harvested from eight patients with myeloma using the Cellpro avidin-biotin immunoaffinity column (Ceprate). They all received CVAMP chemotherapy to maximum response prior to mobilisation. Six of the patients have been transplanted using these cells, one receiving successive autografts. Median absolute cell numbers processed and retrieved were: 31.1 x 10(9) pre-column, 2.07 x 10(8) in the final product and 30.4 x 10(9) in the column waste. Mean CD34 positivity in the product was 49% (range 18.4-98) with a median CD34+ yield of 31.4% (range 21-37.8). IgH PCR was performed and seven of the eight patients were amplifiable. Of these, two were positive in the pre-column product and both of these were successfully purged with a negative result in the final, post-column product. Patients were transplanted with a median of 2.0 x 10(6) CD34+ cells/kg (range 1.5-9.4) following conditioning with melphalan 200 mg/m2. The mean time to recovery of neutrophils to > 0.5 x 10(9)/l and platelets to > 20 x 10(9)/l was 16 and 17 days, respectively. At a mean follow-up of 9 months, four of the six patients transplanted are alive, three of them in complete remission and one in a clinically stable relapse. One has died of disease relapse and one of progressive neurological problems the aetiology of which was uncertain but there was no sign of progression of their myeloma. We conclude that PBSCT using CD34 selected cells is safe and practical in myeloma following remission induction with CVAMP chemotherapy.