Postoperative sexual functioning in total versus subtotal laparoscopic hysterectomy: what do women expect?

Purpose

To evaluate sexual functioning and expected changes in sexual functioning in women with planned total versus subtotal laparoscopic hysterectomy.

Methods

A total of 120 women undergoing laparoscopic hysterectomy were preoperatively enrolled in this study with a cross-sectional design. Full data sets were available for 112 patients, so that 56 patients with planned total laparoscopic hysterectomy (TLH) and 56 women with planned laparoscopic supracervical hysterectomy (LASH) were preoperatively assessed. Sexual functioning was evaluated using the female sexual function index (FSFI). Additionally, participants filled in a standardised questionnaire concerning expected changes on sexual function after the procedure. Demographic parameters, expectations concerning postoperative sexuality and FSFI scores were analysed and compared in women undergoing TLH and LASH.

Results

There were no significant differences concerning demographic parameters and FSFI scores comparing collectives. Sexuality in general was considered more important in women undergoing LASH (2.88 ± 0.83 vs. 2.48 ± 0.89; p = 0.011). Also, in 29 patients (52%) opting for LASH and 8 (14%) patients undergoing TLH a potential change in postoperative sexuality had an impact on their choice for a subtotal/total hysterectomy, respectively (p < 0.001).

Conclusion

Patients’ expectations concerning preservation of the cervix and postoperative sexuality appear to have the potential to bias investigations comparing total with subtotal hysterectomy. Hence, future research focusing on this issue should be accomplished incorporating patients’ expectations stratified by mode of intervention.

     

Sex-related differences in hematological values

Summary Hematological data known or supposed to be influenced by individual sex hormones were evaluated in 18 untreated transsexuals (TS) and in 20 castrated or non-castrated TS on androgen and estrogen treatment, respectively. Profiting from a situation of clinically controlled hormonal sex-transformation it was tested, whether the circulating erythrocyte and granulocyte mass and iron metabolism are linked to a male and female sex-hormone constellation. The erythrocyte and granulocyte counts were significantly higher in untreated males and treated female-to-male TS than in untreated females and treated male-to-female TS. The unexpected finding of sex hormone-dependent granulocyte fluctuations was corroborated by parallel concentration changes of lactoferrin, a granulocytederived plasma protein. Iron metabolism as judged from plasma iron, total iron-binding capacity and serum ferritin was unaffected by sexual transformation. Plasma iron and the total iron-binding capacity did not differ significantly in untreated and treated TS of either type. The serum ferritin concentration, however, was significantly lower in untreated as well as in virilized females than in untreated and in feminized males, but was not significantly changed by long-term androgen or estrogen treatment. The present study demonstrates the potential of human transsexualism as a model for the study of sex-related biological processes.     

Artificial intelligence in medicine: has the time come to hang up the stethoscope?

The question of whether the time has come to hang up the stethoscope is bound up in the promises of artificial intelligence (AI), promises that have so far proven difficult to deliver, perhaps because of the mismatch between the technical capability of AI and its use in real-world clinical settings. This perspective argues that it is time to move away from discussing the generalised promise of disembodied AI and focus on specifics. We need to focus on how the computational method underlying AI, i.e. machine learning (ML), is embedded into tools, how those tools contribute to clinical tasks and decisions and to what extent they can be relied on. Accordingly, we pose four questions that must be asked to make the discussion real and to understand how ML tools contribute to health care: (1) What does the ML algorithm do? (2) How is output of the ML algorithm used in clinical tools? (3) What does the ML tool contribute to clinical tasks or decisions? (4) Can clinicians act or rely on the ML tool? Two exemplar ML tools are examined to show how these questions can be used to better understand the role of ML in supporting clinical tasks and decisions. Ultimately, ML is just a fancy method of automation. We show that it is useful in automating specific and narrowly defined clinical tasks but likely incapable of automating the full gamut of decisions and tasks performed by clinicians.     

Learning from incident reports in the Australian medical imaging setting: handover and communication errors

Objective:

To determine the type and nature of incidents occurring within medical imaging settings in Australia and identify strategies that could be engaged to reduce the risk of their re-occurrence.

Methods:

71 search terms, related to clinical handover and communication, were applied to 3976 incidents in the Radiology Events Register. Detailed classification and thematic analysis of a subset of incidents that involved handover or communication (n=298) were undertaken to identify the most prevalent types of error and to make recommendations about patient safety initiatives in medical imaging.

Results:

Incidents occurred most frequently during patient preparation (34%), when requesting imaging (27%) and when communicating a diagnosis (23%). Frequent problems within each of these stages of the imaging cycle included: inadequate handover of patients (41%) or unsafe or inappropriate transfer of the patient to or from medical imaging (35%); incorrect information on the request form (52%); and delayed communication of a diagnosis (36%) or communication of a wrong diagnosis (36%).

Conclusion:

The handover of patients and clinical information to and from medical imaging is fraught with error, often compromising patient safety and resulting in communication of delayed or wrong diagnoses, unnecessary radiation exposure and a waste of limited resources. Corrective strategies to address safety concerns related to new information technologies, patient transfer and inadequate test result notification policies are relevant to all healthcare settings.

Advances in knowledge:

Handover and communication errors are prevalent in medical imaging. System-wide changes that facilitate effective communication are required.Problems involving the communication and handover of patient information are well documented [1–7], with inadequate communication identified as a contributing factor in up to 70% of hospital sentinel events [1,2]. Handover is a vulnerable time for patients, with an increased risk of discontinuity of care and adverse events [8–10]. Communication failures such as delayed, misplaced or forgotten results or inaccurate or inadequate handover of clinical information can result in adverse patient outcomes, including unnecessary delays in the diagnosis, treatment or communication of results and incorrect treatment [11,12]. Poor handover of information also results in considerable waste of limited resources [12].Medical imaging is not exempt from these types of errors. There is growing evidence that medical imaging is prone to failures in communication, particularly the communication of critical and non-critical test results [13–15] and inadequate communication of patient information on the request form [16,17]. With increasing complexities of care, technological advances in imaging and electronic communication systems have seen new types of errors emerging [18].Review of incident data informs patient safety and can improve the quality of care [19–21]. The Radiology Events Register (RaER) commenced in 2006 and it facilitates systematic data collection of incidents and discrepancies in all areas of medical imaging. In 2010, a multidisciplinary clinical interest group was convened to examine incidents involving handover and communication within the RaER database. The aim of this study was to identify where handover and communication incidents occurred within the imaging cycle [22], what human factors contributed to them and what strategies could be engaged to reduce the risk of their re-occurrence.     

Emergency caesarean section: risk factors for adverse neonatal outcome

Objective

Primary aim of the study was to identify risk factors for an adverse neonatal outcome in emergency caesarean deliveries (ECD). Secondary, the influence of the decision-to-delivery interval (DDI) on neonatal outcome was evaluated.

Methods

Study period of this retrospective investigation was 2001–2011, in which 336 ECD were evaluated. Main outcome measures were risk factors associated with an adverse neonatal outcome (umbilical cord arterial pH < 7.05, umbilical cord arterial base excess (BE) < ?12, Apgar score at 5 min <5 and the combination of umbilical cord arterial pH < 7.0, and umbilical cord arterial BE < ?12). Secondary, the influence of the DDI on neonatal outcome was assessed. These parameters were tested in univariate and multivariate analyses.

Results

Prematurity (<37 + 0 weeks of gestation) and silent cardiotocography (CTG) were identified as the major risk factors for an adverse neonatal outcome. Statistical analyses of the influence of the DDI on umbilical cord arterial pH and BE as well as the Apgar score at 5 min revealed no significant results.

Conclusion

Our results emphasize the necessity of attendance in a level-3 department of obstetrics in case of conceivable compromised neonatal conditions. Prematurity and silent CTG were identified as the major risk factors for an adverse neonatal outcome. As long as the DDI is under 20 min, it did not have an impact on neonatal outcome.