This study aimed to identify factors influencing oncofertility and to explore the oncofertility experiences of patients with gynecological cancer using quantitative and qualitative methods, respectively. Methods: An explanatory sequential mixed-methods study was conducted. The quantitative study involved 222 patients with gynecological cancer recruited from online cafes and hospitals. Data were analyzed using IBM SPSS Statistics 28. For qualitative research, eight patients with gynecological cancer were interviewed. Data were analyzed using theme analysis method. Results: Oncofertility performance was quantitatively assessed in 40 patients (18.0%). Factors that significantly affected oncofertility were fertility preservation awareness (odds ratio [OR] = 14.97, 95% confidence interval [CI]: 4.22~53.08), number of children planned before cancer diagnosis (OR = 6.08, 95% CI: 1.89~19.62; OR = 5.04, 95% CI: 1.56~16.29), monthly income (OR = 3.29, 95% CI: 1.23~8.86), social support (OR = 1.08, 95% CI: 1.01~1.17), and anxiety (OR = 0.79, 95% CI: 0.66~0.95). Qualitative results showed three theme clusters and eight themes: (1) themes for determinant factors affecting oncofertility selection: ‘desire to have children’ and ‘special meaning of the uterus and ovaries;’ (2) themes for obstructive factors affecting oncofertility selection: ‘fertility preservation fall behind priorities,’ ‘confusion caused by inaccurate information,’ and ‘my choice was not supported;’ (3) themes for support factors affecting oncofertility selection: ‘provide accurate and reasonable information about oncofertility,’ ‘addressing the healthcare gap,’ and ‘need financial support for oncofertility.’ Conclusion: Financial support, sufficient information, social support, and anxiety-relief interventions are required for oncofertility in patients with gynecological cancer.

This study aimed to identify factors influencing oncofertility and to explore the oncofertility experiences of patients with gynecological cancer using quantitative and qualitative methods, respectively. Methods: An explanatory sequential mixed-methods study was conducted. The quantitative study involved 222 patients with gynecological cancer recruited from online cafes and hospitals. Data were analyzed using IBM SPSS Statistics 28. For qualitative research, eight patients with gynecological cancer were interviewed. Data were analyzed using theme analysis method. Results: Oncofertility performance was quantitatively assessed in 40 patients (18.0%). Factors that significantly affected oncofertility were fertility preservation awareness (odds ratio [OR] = 14.97, 95% confidence interval [CI]: 4.22~53.08), number of children planned before cancer diagnosis (OR = 6.08, 95% CI: 1.89~19.62; OR = 5.04, 95% CI: 1.56~16.29), monthly income (OR = 3.29, 95% CI: 1.23~8.86), social support (OR = 1.08, 95% CI: 1.01~1.17), and anxiety (OR = 0.79, 95% CI: 0.66~0.95). Qualitative results showed three theme clusters and eight themes: (1) themes for determinant factors affecting oncofertility selection: ‘desire to have children’ and ‘special meaning of the uterus and ovaries;’ (2) themes for obstructive factors affecting oncofertility selection: ‘fertility preservation fall behind priorities,’ ‘confusion caused by inaccurate information,’ and ‘my choice was not supported;’ (3) themes for support factors affecting oncofertility selection: ‘provide accurate and reasonable information about oncofertility,’ ‘addressing the healthcare gap,’ and ‘need financial support for oncofertility.’ Conclusion: Financial support, sufficient information, social support, and anxiety-relief interventions are required for oncofertility in patients with gynecological cancer.

This study aimed to identify factors influencing oncofertility and to explore the oncofertility experiences of patients with gynecological cancer using quantitative and qualitative methods, respectively. Methods: An explanatory sequential mixed-methods study was conducted. The quantitative study involved 222 patients with gynecological cancer recruited from online cafes and hospitals. Data were analyzed using IBM SPSS Statistics 28. For qualitative research, eight patients with gynecological cancer were interviewed. Data were analyzed using theme analysis method. Results: Oncofertility performance was quantitatively assessed in 40 patients (18.0%). Factors that significantly affected oncofertility were fertility preservation awareness (odds ratio [OR] = 14.97, 95% confidence interval [CI]: 4.22~53.08), number of children planned before cancer diagnosis (OR = 6.08, 95% CI: 1.89~19.62; OR = 5.04, 95% CI: 1.56~16.29), monthly income (OR = 3.29, 95% CI: 1.23~8.86), social support (OR = 1.08, 95% CI: 1.01~1.17), and anxiety (OR = 0.79, 95% CI: 0.66~0.95). Qualitative results showed three theme clusters and eight themes: (1) themes for determinant factors affecting oncofertility selection: ‘desire to have children’ and ‘special meaning of the uterus and ovaries;’ (2) themes for obstructive factors affecting oncofertility selection: ‘fertility preservation fall behind priorities,’ ‘confusion caused by inaccurate information,’ and ‘my choice was not supported;’ (3) themes for support factors affecting oncofertility selection: ‘provide accurate and reasonable information about oncofertility,’ ‘addressing the healthcare gap,’ and ‘need financial support for oncofertility.’ Conclusion: Financial support, sufficient information, social support, and anxiety-relief interventions are required for oncofertility in patients with gynecological cancer.

This study aimed to identify factors influencing oncofertility and to explore the oncofertility experiences of patients with gynecological cancer using quantitative and qualitative methods, respectively. Methods: An explanatory sequential mixed-methods study was conducted. The quantitative study involved 222 patients with gynecological cancer recruited from online cafes and hospitals. Data were analyzed using IBM SPSS Statistics 28. For qualitative research, eight patients with gynecological cancer were interviewed. Data were analyzed using theme analysis method. Results: Oncofertility performance was quantitatively assessed in 40 patients (18.0%). Factors that significantly affected oncofertility were fertility preservation awareness (odds ratio [OR] = 14.97, 95% confidence interval [CI]: 4.22~53.08), number of children planned before cancer diagnosis (OR = 6.08, 95% CI: 1.89~19.62; OR = 5.04, 95% CI: 1.56~16.29), monthly income (OR = 3.29, 95% CI: 1.23~8.86), social support (OR = 1.08, 95% CI: 1.01~1.17), and anxiety (OR = 0.79, 95% CI: 0.66~0.95). Qualitative results showed three theme clusters and eight themes: (1) themes for determinant factors affecting oncofertility selection: ‘desire to have children’ and ‘special meaning of the uterus and ovaries;’ (2) themes for obstructive factors affecting oncofertility selection: ‘fertility preservation fall behind priorities,’ ‘confusion caused by inaccurate information,’ and ‘my choice was not supported;’ (3) themes for support factors affecting oncofertility selection: ‘provide accurate and reasonable information about oncofertility,’ ‘addressing the healthcare gap,’ and ‘need financial support for oncofertility.’ Conclusion: Financial support, sufficient information, social support, and anxiety-relief interventions are required for oncofertility in patients with gynecological cancer.

Pregabalin is a gamma-aminobutyric acid analogue; it has been used clinically as an anticonvulsant and analgesic agent. Few documented reports exist of deaths resulting from pregabalin overdose. This report discusses a case of pregabalin intoxication in a 27-year-old male, who was found unconscious in a prison and later pronounced dead at a local hospital. An autopsy and toxicological analysis revealed the presence of pregabalin, alprazolam, diazepam, escitalopram, fluoxetine, lorazepam, bromazepam, flunitrazepam, zolpidem, and piroxicam. The concentrations of pregabalin and alprazolam were 10.3 mg/L and 0.10 mg/L in heart blood, and 11.4 mg/L and 0.08 mg/L in femoral blood, respectively. The other detected drugs were within therapeutic concentrations. Ethyl alcohol was not detected in the blood. Although the pregabalin concentration was within the therapeutic or toxic range, the concomitant use of other drugs, particularly benzodiazepines and zolpidem, likely enhanced its toxicity. Based on the autopsy findings and toxicological results, the cause of death was determined to be multidrug intoxication, including pregabalin. Although pregabalin is generally considered safe and deaths from its use alone are very rare, it can be fatal at relatively low blood concentrations when combined with opioids or other medications. The rising use of pregabalin in Korea increases the risk of overdose deaths, similar to this case. Therefore, in forensic practice, the possibility of such fatalities should be considered when pregabalin is detected.

Pregabalin is a gamma-aminobutyric acid analogue; it has been used clinically as an anticonvulsant and analgesic agent. Few documented reports exist of deaths resulting from pregabalin overdose. This report discusses a case of pregabalin intoxication in a 27-year-old male, who was found unconscious in a prison and later pronounced dead at a local hospital. An autopsy and toxicological analysis revealed the presence of pregabalin, alprazolam, diazepam, escitalopram, fluoxetine, lorazepam, bromazepam, flunitrazepam, zolpidem, and piroxicam. The concentrations of pregabalin and alprazolam were 10.3 mg/L and 0.10 mg/L in heart blood, and 11.4 mg/L and 0.08 mg/L in femoral blood, respectively. The other detected drugs were within therapeutic concentrations. Ethyl alcohol was not detected in the blood. Although the pregabalin concentration was within the therapeutic or toxic range, the concomitant use of other drugs, particularly benzodiazepines and zolpidem, likely enhanced its toxicity. Based on the autopsy findings and toxicological results, the cause of death was determined to be multidrug intoxication, including pregabalin. Although pregabalin is generally considered safe and deaths from its use alone are very rare, it can be fatal at relatively low blood concentrations when combined with opioids or other medications. The rising use of pregabalin in Korea increases the risk of overdose deaths, similar to this case. Therefore, in forensic practice, the possibility of such fatalities should be considered when pregabalin is detected.

Pregabalin is a gamma-aminobutyric acid analogue; it has been used clinically as an anticonvulsant and analgesic agent. Few documented reports exist of deaths resulting from pregabalin overdose. This report discusses a case of pregabalin intoxication in a 27-year-old male, who was found unconscious in a prison and later pronounced dead at a local hospital. An autopsy and toxicological analysis revealed the presence of pregabalin, alprazolam, diazepam, escitalopram, fluoxetine, lorazepam, bromazepam, flunitrazepam, zolpidem, and piroxicam. The concentrations of pregabalin and alprazolam were 10.3 mg/L and 0.10 mg/L in heart blood, and 11.4 mg/L and 0.08 mg/L in femoral blood, respectively. The other detected drugs were within therapeutic concentrations. Ethyl alcohol was not detected in the blood. Although the pregabalin concentration was within the therapeutic or toxic range, the concomitant use of other drugs, particularly benzodiazepines and zolpidem, likely enhanced its toxicity. Based on the autopsy findings and toxicological results, the cause of death was determined to be multidrug intoxication, including pregabalin. Although pregabalin is generally considered safe and deaths from its use alone are very rare, it can be fatal at relatively low blood concentrations when combined with opioids or other medications. The rising use of pregabalin in Korea increases the risk of overdose deaths, similar to this case. Therefore, in forensic practice, the possibility of such fatalities should be considered when pregabalin is detected.

Pregabalin is a gamma-aminobutyric acid analogue; it has been used clinically as an anticonvulsant and analgesic agent. Few documented reports exist of deaths resulting from pregabalin overdose. This report discusses a case of pregabalin intoxication in a 27-year-old male, who was found unconscious in a prison and later pronounced dead at a local hospital. An autopsy and toxicological analysis revealed the presence of pregabalin, alprazolam, diazepam, escitalopram, fluoxetine, lorazepam, bromazepam, flunitrazepam, zolpidem, and piroxicam. The concentrations of pregabalin and alprazolam were 10.3 mg/L and 0.10 mg/L in heart blood, and 11.4 mg/L and 0.08 mg/L in femoral blood, respectively. The other detected drugs were within therapeutic concentrations. Ethyl alcohol was not detected in the blood. Although the pregabalin concentration was within the therapeutic or toxic range, the concomitant use of other drugs, particularly benzodiazepines and zolpidem, likely enhanced its toxicity. Based on the autopsy findings and toxicological results, the cause of death was determined to be multidrug intoxication, including pregabalin. Although pregabalin is generally considered safe and deaths from its use alone are very rare, it can be fatal at relatively low blood concentrations when combined with opioids or other medications. The rising use of pregabalin in Korea increases the risk of overdose deaths, similar to this case. Therefore, in forensic practice, the possibility of such fatalities should be considered when pregabalin is detected.

Pickling salt, also known as curing salt, is a mixture of sodium chloride and sodium nitrite, which is used for color agent and a means to facilitate food preservation. Recently, online purchase of pure sodium nitrite has been restricted, and pickling salts have been used as replacements in cases of suicidal nitrite intoxication. From November 2020 to December 2021, there were four autopsy cases of nitrite poisoning caused by pickling salt, and 10 autopsy cases of nitrite poisoning by pure sodium nitrite. Due to the low nitrite concentration in pickling salts, serum nitrite and nitrate concentration, and methemoglobin levels were relatively low in pickling salts cases. Especially, low methemoglobin levels may cause confusion in the postmortem diagnosis of fatal nitrite intoxication, so caution is required.

This research proposes a safety strategy for coronavirus disease 2019 (COVID-19) walkthrough booths to optimize pandemic preparedness. These booths, designed for respiratory sample collection during the COVID-19 pandemic, effectively reduce infection risk and personal protective equipment-related fatigue among healthcare workers. However, inadequate disinfection and glove management could escalate infection transmission. Using computational fluid dynamics simulations, we analyzed droplet dispersion on booth surfaces and gloves under various wind conditions. Our findings suggest that when setting up COVID-19 walk-through booths, their location should be strategically chosen to minimize the effects of wind. All surfaces of booth gloves must be thoroughly disinfected with a certified disinfectant after nasopharyngeal swab collection. It is also recommended to wear disposable gloves over booth gloves when changing between patient examinations. In wind-affected areas, individuals nearby should not solely rely on the 2-meter distancing rule due to potential droplet spread from walk-through booths. We strongly recommend consistent and proper mask use for effective droplet blocking. Adherence to these guidelines can significantly enhance the safety and efficiency of walk-through booths, particularly in potential future pandemics.