Senior citizens as rescuers: Is reduced knowledge the reason for omitted lay-resuscitation-attempts? Results from a representative survey with 2004 interviews.

OBJECTIVE: Resuscitation (CPR) provided by a bystander prior to the arrival of the emergency services is a beneficial factor for surviving a cardiac arrest (CA). Our registry-based data show, that older patients receive bystander-CPR less frequently. Little is known on possible reasons for this finding. We sought to investigate the hypothesis that awareness of CPR measures is lower in older laypersons being a possible reason for less CPR-attempts in senior citizens. METHODS: 1206 datasets on bystander resuscitations actually carried out were analyzed for age-dependent differences. Subsequently, we investigated whether the knowledge required carrying out bystander-CPR and the self-confidence to do so differ between younger and older citizens using computer-assisted telephone interviewing. 2004 interviews were performed and statistically analyzed. RESULTS: A lower level of knowledge to carry out bystander-CPR was seen in older individuals. For example, 82.4% of interviewees under 65 years of age, knew the correct emergency number. In this group, 66.6% named CPR as the relevant procedure in CA. Among older individuals these responses were only given by 75.1% and 49.5% (V = 0.082; P < 0.001 and V = 0.0157; P < 0.001). Additionally, a difference concerning participants' confidence in their own abilities was detectable. 58.0% of the persons younger than 65 years were confident that they would detect a CA in comparison to 44.6% of the participants older than 65 years (V = 0.120; P < 0.001). Similarly, 62.7% of the interviewees younger than 65 were certain to know what to do during CPR compared to 51.3% of the other group (V = 0.103; P < 0.001). CONCLUSIONS: Lower levels of older bystanders' knowledge and self-confidence might provide an explanation for why older patients receive bystander-CPR less frequently. Further investigation is necessary to identify causal connections and optimum ways to empower bystander resuscitation.

Comparison of an automatic analysis and a manual analysis of conjunctival microcirculation in a sheep model of haemorrhagic shock.

BACKGROUND: Life-threatening diseases of critically ill patients are known to derange microcirculation. Automatic analysis of microcirculation would provide a bedside diagnostic tool for microcirculatory disorders and allow immediate therapeutic decisions based upon microcirculation analysis. METHODS: After induction of general anaesthesia and instrumentation for haemodynamic monitoring, haemorrhagic shock was induced in ten female sheep by stepwise blood withdrawal of 3 × 10 mL per kilogram body weight. Before and after the induction of haemorrhagic shock, haemodynamic variables, samples for blood gas analysis, and videos of conjunctival microcirculation were obtained by incident dark field illumination microscopy. Microcirculatory videos were analysed (1) manually with AVA software version 3.2 by an experienced user and (2) automatically by AVA software version 4.2 for total vessel density (TVD), perfused vessel density (PVD) and proportion of perfused vessels (PPV). Correlation between the two analysis methods was examined by intraclass correlation coefficient and Bland-Altman analysis. RESULTS: The induction of haemorrhagic shock decreased the mean arterial pressure (from 87 ± 11 to 40 ± 7 mmHg; p < 0.001); stroke volume index (from 38 ± 14 to 20 ± 5 ml·m-2; p = 0.001) and cardiac index (from 2.9 ± 0.9 to 1.8 ± 0.5 L·min-1·m-2; p < 0.001) and increased the heart rate (from 72 ± 9 to 87 ± 11 bpm; p < 0.001) and lactate concentration (from 0.9 ± 0.3 to 2.0 ± 0.6 mmol·L-1; p = 0.001). Manual analysis showed no change in TVD (17.8 ± 4.2 to 17.8 ± 3.8 mm*mm-2; p = 0.993), whereas PVD (from 15.6 ± 4.6 to 11.5 ± 6.5 mm*mm-2; p = 0.041) and PPV (from 85.9 ± 11.8 to 62.7 ± 29.6%; p = 0.017) decreased significantly. Automatic analysis was not able to identify these changes. Correlation analysis showed a poor correlation between the analysis methods and a wide spread of values in Bland-Altman analysis. CONCLUSIONS: As characteristic changes in microcirculation during ovine haemorrhagic shock were not detected by automatic analysis and correlation between automatic and manual analyses (current gold standard) was poor, the use of the investigated software for automatic analysis of microcirculation cannot be recommended in its current version at least in the investigated model. Further improvements in automatic vessel detection are needed before its routine use.

Detection and distribution of opioid peptide receptors in porcine myocardial tissue.

There is growing evidence that opioid peptide receptors (OPRs) play an important role in cardiovascular function. Many studies have been conducted in swine, in view of their anatomic and physiologic similarities to humans. Until now, the presence and particularly distribution of OPRs has been unclear. Porcine myocardial tissue was obtained from both the left and right atria and ventricles. Expression of mRNA for µ-, δ- and κ-OPR was determined by reverse transcription PCR. OPR proteins were detected by Western blot, distribution and cellular location were identified using immunohistochemistry. Homogenous expression of mRNA and protein for δ- and κ-OPRs were demonstrated in all porcine myocardial tissue tested, whereas expression of µ-OPR mRNA was not demonstrated in any of the tissues tested. This study demonstrates the expression of δ- and κ-OPRs in porcine myocardial tissue. No differences in distribution of δ- and κ-OPRs were found between the four heart cavities. Modulation of cardiac function by δ- and κ-OPR agonists or antagonists is therefore possible, while µ-OPR-mediated direct cardiac effects appear unlikely, due to nonexpression of the receptor. This study demonstrates that porcine studies can further elucidate the role of OPRs in cardiac (patho-)physiology.