P2592Combining home monitoring temporal trends and baseline patient risk profile for predicting impending heart failure hospitalizations. Results from the SELENE HF (BIO.Detect HF IV) study

Background/Introduction

The lack of a validated method to efficiently combine information provided by Remote Monitoring (RM) of implantable defibrillators (ICD) and patient clinical profile has limited the use of RM in the prevention of worsening heart failure episodes.

Purpose

Our objective was to develop and validate an index combining RM temporal trends and a baseline risk score for predicting the first HF hospitalization after device implantation.

Methods

We prospectively enrolled 918 patients (81% male, median age 69, interquartile interval [QI], 61/76; Seattle Heart Failure Score [SHFS], 0.17, QI, −0.40/0.75) with indication to ICD (56%), or ICD with cardiac resynchronization therapy (44%). The Home Monitoring (HM) system was activated in all patients after implant to collect several technical and HF-related variables daily. Investigators were blinded to HM reports, and only received automatic alerts for critical technical issues. The primary endpoint was the first adjudicated HF hospitalization. The cohort was a posteriori 1:1 randomized in derivation and validation groups stratified by device type and primary endpoint occurrence. The SHFS was used for baseline risk assessment.

Results

During a median follow-up of 23 months (QI, 14/36), 62 first HF hospitalizations were adjudicated. In the derivation group, the index was constructed by combining the SHFS and temporal trends of 24-hour and rest mean heart rates, ventricular ectopic beat frequency, arrhythmic atrial burden, heart rate variability, physical exercise, and thoracic impedance. Variable selection was based on an automatic stepwise procedure, after applying appropriate transformations in variable-specific time frames to maximize the area under the receiver operating characteristics curve (AUC). The resulting index was associated to an AUC of 0.88 and an Odds Ratio of 2.72 (confidence interval [CI] 1.97–3.75, p<0.001) for index unitary increase. In the index validation test, first HF hospitalizations were predicted with a sensitivity of 73.3% (CI, 54.1%-87.7%), a median alerting time of 55 days (QI, 20/68), false alert rate of 0.75 (CI, 0.70–0.81) patient-year, and 95.1% false-alert-free days.

Conclusion

HM temporal trends of selected variables and the SHFS may be combined to timely and efficiently predict the first HF hospitalization after implant, with less than 1 expected per-patient false alert per year.

Acknowledgement/Funding

BIOTRONIK SE & Co. KG, Berlin, Germany

Distinct expression patterns of two zebrafish homologues of the human APP gene during embryonic development

The human amyloid protein precursor (APP) gene correlates with early onset of Alzheimer's disease in humans. We have identified two APP homologues in zebrafish, which we call appa and appb. They show a high degree of identity to human APP particularly in the beta APP42 and the transmembrane domain. Widespread expression of both appa and appb was detected from mid-gastrulation until the bud stage. During segmentation, the two genes diverged in their pattern of expression: at 14 h post-fertilisation (hpf) and 18 hpf both genes were expressed rostrally in the prospective CNS, but only appa was found caudally in the paraxial segmental plate and presomitic mesoderm, excluding the midline. In contrast, appb was found caudally in the neural rod at 14 hpf and the developing spinal cord at 18 hpf. Later, at 24 hpf both genes shared common expression domains, namely the telencephalon, the ventral diencephalon, the trigeminal ganglia, and the posterior lateral line ganglia. Unique expression domains for appa were the lens, the otic vesicles and the somites, while appb was expressed in a serially repeated set of nuclei within the hindbrain, the ventral mesencephalon and the motoneurones of the developing spinal cord.