Long-term screening for sleep apnoea in paced patients: preliminary assessment of a novel patient management flowchart by using automatic pacemaker indexes and sleep lab polygraphy.
BACKGROUND
The primary aim of this pilot study was to prospectively assess a flowchart to screen and diagnose paced patients (pts) affected by sleep apnoeas, by crosschecking indexes derived from pacemakers (minute ventilation sensor on-board) with Sleep-Lab Polygraphy (PG) outcomes. Secondarily, "smoothed" long-term pacemaker indexes (all the information between two consecutive follow-up visits) have been retrospectively compared vs. standard short-term pacemaker indexes (last 24h) at each follow-up (FU) visit, to test their correlation and diagnostic concordance.


METHODS
Data from long-term FU of 61 paced pts were collected. At each visit, the standard short-term apnoea+hypopnoea (PM_AHI) index was retrieved from the pacemaker memory. Patients showing PM_AHI ≥ 30 at least once during FU were proposed to undergo a PG for diagnostic confirmation. Smoothed pacemaker (PM_SAHI) indexes were calculated by averaging the overall number of apnoeas/hypopnoeas over the period between two FU visits, and retrospectively compared with standard PM_AHI.


RESULTS
Data were available from 609 consecutive visits (overall 4.64 ± 1.78 years FU). PM_AHI indexes were positive during FU in 40/61 pts (65.6%); 26/40 pts (65%) accepted to undergo a PG recording; Sleep-Lab confirmed positivity in 22/26 pts (84.6% positive predictive value for PM_AHI). A strong correlation (r=0.73) and a high level of concordance were found between smoothed and standard indexes (multivariate analysis, Cohen's-k and Z-score tests).


CONCLUSIONS
Pacemaker-derived indexes may help in screening paced pts potentially affected by sleep apnoeas. Long-term "smoothed" apnoea indexes could improve the accuracy of pacemaker screening capability, even though this hypothesis must be prospectively confirmed by larger studies.
Department of Cardiology, IRCCS Policlinico San Donato, San Donato (Milan), Italy. Electronic address: ezio.aime@grupposandonato.it.
Ezio
E
Aimé
Department of Cardiology, IRCCS Policlinico San Donato, San Donato (Milan), Italy.
Marina
M
Rovida
SORIN Group Italia S.r.l., Milan, Italy.
Danilo
D
Contardi
Universität Regensburg, Fakultät für Medizin, Institut für Epidemiologie und Präventivmedizin, Germany.
Cristian
C
Ricci
Unit of Biostatistic and Clinical Epidemiology, Department of Public Health and Neurosciences, University of Pavia, Italy.
Maddalena
M
Gaeta
Department of Cardiology, IRCCS Policlinico San Donato, San Donato (Milan), Italy.
Ester
E
Innocenti
Department of Cardiology, IRCCS Policlinico San Donato, San Donato (Milan), Italy.
Jacques
J
Cabral Tantchou-Tchoumi
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D010138:Pacemaker, Artificial; D010865:Pilot Projects; D017286:Polysomnography; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012189:Retrospective Studies; D012720:Severity of Illness Index; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis*; D013997:Time Factors
Apnoea and hypopnoea index; Artificial pacemaker; Minute ventilation sensor; Polysomnography; Screening; Sleep apnoea