Ambient temperature and non-accidental mortality: a time series study

Diurnal temperature range and hospital admission due to cardiovascular and respiratory diseases in Dezful, a city with hot climate and high DTR fluctuation in Iran: an ecological time-series study

The results of previous studies have indicated the effects of temperature changes on health status. The present study was conducted to investigate the effects of diurnal temperature range (DTR) and hospital admission on cardiovascular and respiratory diseases in Dezful, in Iran. In this ecological time-series study, data related to hospital admissions based on ICD-10, meteorological, and climatological data were gathered over a period of six years from 2014 to 2019. A distributed lag nonlinear model combined with a quasi-Poisson regression was then used to assess the impact of DTR on cardiovascular and respiratory hospital admissions. Potential confounders, including wind speed, air pollution, seasonality, time trend, weekends and holidays, days of week, and humidity were controlled. In extreme low DTRs, the cumulative effects of cardiovascular admissions significantly increased in total, and in warm and cold seasons (Lag_0-21, P ≤ 0.05). In addition, in extreme high DTRs, the cumulative effects of cardiovascular significantly decreased in total (Lag_0-13 and Lag_0-21, P ≤ 0.05), and in warm (Lag_0-21, P ≤ 0.05) and cold seasons (Lag_0-21, P ≤ 0.05). Moreover, respiratory admissions significantly decreased in total (Lag_0-21, P ≤ 0.05) and in warm season (Lag_0-21, P ≤ 0.05).Our result indicates that extreme low DTRs could increase the risk of daily cardiovascular admissions, and extreme high DTRs may cause a protective effect on daily respiratory and cardiovascular admissions in some regions with high fluctuations in DTR.

Cold spells linked with respiratory disease hospitalization, length of hospital stay, and hospital expenses: Exploring cumulative and harvesting effects

BACKGROUND

Previous studies have revealed the relationship between cold spells and morbidity and mortality due to respiratory diseases, while the detrimental effects of cold spells on the length of hospital stay and hospitalization expenses remain largely unknown.

METHODS

We collected hospitalization data for respiratory diseases in 11 cities of Shanxi, China during 2017-2019. In each case, exposure to meteorological variables and air pollution was estimated by the bilinear interpolation approach and inverse distance weighting method, respectively, and then averaged at the city level. Cold spells were defined as the daily mean temperature below the 10^th, 7.5^th, or 5^th percentiles for at least 2 to 5 consecutive days. We applied distributed lag non-linear models combined with generalized additive models to assess cumulative effects and harvesting effects.

RESULTS

There were significant associations between cold spells and hospital admissions, length of hospital stay, and hospital expenses for respiratory diseases. Compared with the non-cold spell period, the overall (lag 0-21) cumulative risk of hospitalization for total respiratory diseases was 1.232 (95 % CI: 1.090, 1.394) on cold spell days, and the increased length of hospital stay and hospitalization expenses were 112.793 (95 % CI: 10.755, 214.830) days and 127.568 (95 % CI: 40.513, 214.624) thousand Chinese yuan. The overall cumulative risks of cold spells on total respiratory diseases and pneumonia were statistically significant. We further observed harvesting effects in the associations between cold spells and hospital admission, length of hospital stay, and hospitalization expenses for respiratory diseases.

CONCLUSIONS

Cumulative cold-spell exposure for up to three weeks is associated with hospitalization, length of hospital stay, and hospital expenses for respiratory diseases. The observed harmful effects of cold spells on respiratory diseases can be partly attributable to harvesting effects.

Effects of ambient temperature on mortality among elderly residents of Chengdu city in Southwest China, 2016-2020: a distributed-lag non-linear time series analysis

BACKGROUND

With complex changes in the global climate, it is critical to understand how ambient temperature affects health, especially in China. We aimed to assess the effects of temperature on daily mortality, including total non-accidental, cardiovascular disease (CVD), respiratory disease, cerebrovascular disease, and ischemic heart disease (IHD) mortality between 2016 and 2020 in Chengdu, China.

METHODS

We obtained daily temperature and mortality data for the period 2016-2020. A Poisson regression model combined with a distributed-lag nonlinear model was used to examine the association between temperature and daily mortality. We investigated the effects of individual characteristics by sex, age, education level, and marital status.

RESULTS

We found significant non-linear effects of temperature on total non-accidental, CVD, respiratory, cerebrovascular, and IHD mortality. Heat effects were immediate and lasted for 0-3 days, whereas cold effects persisted for 7-10 days. The relative risks associated with extreme high temperatures (99th percentile of temperature, 28 °C) over lags of 0-3 days were 1.22 (95% confidence interval [CI]: 1.17, 1.28) for total non-accidental mortality, 1.40 (95% CI: 1.30, 1.50) for CVD morality, 1.34 (95% CI: 1.24, 1.46) for respiratory morality, 1.33 (95% CI: 1.20, 1.47) for cerebrovascular mortality, and 1.38 (95% CI: 1.20, 1.58) for IHD mortality. The relative risks associated with extreme cold temperature (1st percentile of temperature, 3.0 °C) over lags of 0-14 days were 1.32 (95% CI: 1.19, 1.46) for total mortality, 1.45 (95% CI: 1.24, 1.68) for CVD morality, 1.28 (95% CI: 1.09, 1.50) for respiratory morality, 1.36 (95% CI: 1.09, 1.70) for cerebrovascular mortality, and 1.26 (95% CI: 0.95, 1.68) for IHD morality. We found that hot and cold affects were greater in those over 85 years of age, and that women, individuals with low education levels, and those who were widowed, divorced, or never married, were more vulnerable.

CONCLUSIONS

This study showed that exposure to hot and cold temperatures in Chengdu was associated with increased mortality, with people over 85 years old, women, those with low education levels, and unmarried individuals being more affected by hot and cold temperatures.

Associations and burdens of relative humidity with cause-specific mortality in three Chinese cities

This study aimed to investigate the association between relative humidity (RH) and various cause of mortality, and then quantify the RH-related mortality fraction of low and high RH under the assumption that causal effects exist. Daily cause-specific mortality counts from 2008 to 2011, and contemporaneous meteorological data in three Chinese cities were collected. Distributed lag nonlinear models were adopted to quantify the nonlinear and delayed effects of RH on mortality risk. Low and high RH were defined as RH lower or higher than the minimum mortality risk RH (MMRH), respectively. Corresponding RH-related mortality fractions were calculated in the explanatory analysis. From the three cities, 736,301 deaths were collected. RH (mean ± standard deviation) were 50.9 ± 20.0 for Beijing, 75.5 ± 8.6 for Chengdu, and 70.8 ± 14.6 for Nanjing. We found that low RH in Beijing and high RH (about 80-90%) in Chengdu was associated with increased all-cause mortality risk. Both low and high RH may increase the CVD mortality risk in Beijing. Both low and high (about 80-85%) RH may increase the COPD mortality risk in Chengdu. Low RH (about < 45%) was associated with increased diabetes mortality risk in Nanjing. Effects of extreme low and extreme high RH were delayed in these cities, except that extreme low effects on COPD mortality appeared immediately in Chengdu. The effects of extreme low RH are higher than that of the extreme high RH in Beijing and Nanjing, while contrary in Chengdu. Finally, under the causal effect assumption, 6.80% (95% eCI: 2.90, 10.73) all-cause mortality and 12.48% (95% eCI: 7.17, 16.80) CVD deaths in Beijing, 9.59% (95% eCI: 1.38, 16.88) COPD deaths in Chengdu, and 23.79% (95% eCI: 0.92, 387.93) diabetes mortality in Nanjing were attributable to RH. Our study provided insights into RH-mortality risk, helped draw relative intervention policies, and is also significant for future predictions of climate change effects under different scenarios.

Effect of ambient temperature on daily hospital admissions for acute pancreatitis in Nanchang, China: A time-series analysis

The aim of this study was to evaluate the short-term effect of temperature on the risk of acute pancreatitis (AP) in southern China. We performed a time-series study of 2822 patients admitted with a first episode of AP in Nanchang between May 2014 and June 2017. A generalized additive model combined with a distributed lag non-linear model was applied to assess the association of temperature and AP. In subgroup analysis, according to different etiologies of pancreatitis, significant associations were found between daily average temperature and non-biliary pancreatitis hospitalization at lags of 0-7 days, but not for biliary pancreatitis or total AP. Higher daily average temperature tended to increase the occurrence of non-biliary pancreatitis at lags of 0-7 days. These findings suggest that high temperature is associated with higher non-biliary pancreatitis risk in Nanchang, China. In the context of global warming, the morbidity of non-biliary pancreatitis may increase.

The effect of ambient temperature on in-hospital mortality: a study in Nanjing, China

To reduce the inpatient mortality and improve the quality of hospital management, we explore the relationship between temperatures and in-hospital mortality in a large sample across 10 years in Nanjing, Jiangsu. We collected 10 years’ data on patient deaths from a large research hospital. Distributed lag non-linear model (DLNM) was used to find the association between daily mean temperatures and in-hospital mortality. A total of 6160 in-hospital deaths were documented. Overall, peak RR appeared at 8 °C, with the range of 1 to 20 °C having a significantly high mortality risk. In the elderly (age ≥ 65 years), peak RR appeared at 5 °C, with range − 3 to 21 °C having a significantly high mortality risk. In males, peak RR appeared at 8 °C, with the range 0 to 24 °C having a significantly high mortality risk. Moderate cold (define as 2.5th percentile of daily mean temperatures to the MT), not extreme temperatures (≤ 2.5th percentile or ≥ 97.5th percentile of daily mean temperatures), increased the risk of death in hospital patients, especially in elderly and male in-hospital patients.

Relationship between diurnal temperature range and emergency ambulance dispatches due to stroke in Guangzhou, China

BACKGROUND

The evidence between diurnal temperature range (DTR) and stroke remains controversial and sparse. We aimed to assess the relationship between DTR and emergency ambulance dispatches (EADs) due to stroke, and to explore whether there were effect modifications to the relationship.

METHODS

A Quasi-Poisson generalized linear regression combined with a distributed lag non-linear model was used to examine the relationship between DTR and EADs for stroke between January 1st 2011 and June 30th 2018 in Guangzhou, China. We estimated the effects of the low DTR and high DTR (defined as DTR below and above 10 °C respectively) on EADs. The effects of minimum, maximum, 5th, 25th, 50th, 75th, and 95th percentiles of DTR compared with the DTR of 10 °C were also analyzed.

RESULTS

A total of 20,275 EADs for stroke were included for analyses, among which 17,556 EADs were used in the model further adjusted for age and sex. A quasi-U-shaped relationship between DTR and EADs over lag0-2 days was observed. For the low DTR, per 1 °C decrease in DTR was significantly associated with an increase of 2.64% (RR = 1.03, 95% CI: 1.01-1.04) for EADs, while per 1 °C increase for the high DTR was non-significantly related with an increased risk of EADs (RR = 1.01, 95% CI: 0.90-1.13). Significant effects of the 5th and 25th percentiles of DTR on EADs were found when compared with the DTR of 10 °C. No significant effect modifications by age, sex or season were found to the association between DTR and EADs.

CONCLUSIONS

We found a quasi-U-shaped relationship between DTR and EADs due to stroke in this study, while age, sex or season did not significantly modify the association between DTR and EADs. More high-quality evidence is needed to further explore and validate the relationship between DTR and stroke.

Fluctuating temperature modifies heat-mortality association in the globe

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days’ minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: −0.33 to 1.69), 1.34% (95% CI: −0.14 to 2.73), 1.99% (95% CI: 0.29–3.57), and 2.73% (95% CI: 0.76–4.50) of total deaths for Q1–Q4 (first quartile–fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25–9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: −0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health.

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Increased temperature variability (TV) poses a greater mortality risk due to heat

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TV has a more profound modification effect on extreme heat-mortality association

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Strategies against heat and TV simultaneously would benefit public health

The association between diurnal temperature range and clinic visits for upper respiratory tract infection among college students in Wuhan, China

The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.

Effects of diurnal temperature range on cardiovascular disease hospital admissions in farmers in China's Western suburbs

Cardiovascular disease (CVD), reported to relate with climate change, is the leading cause of global mortality and morbidity. Since the relevant information is quite limited from suburbs and countryside in developing and underdeveloped countries, there are no studies that focused on morbidity through diurnal temperature range (DTR) for these regions. This is the first study to evaluate the short-term effect of DTR on CVD hospital admission in suburban farmers, as well as to identify vulnerable subpopulations. Daily time series data of CVD hospital admissions on suburban farmers of Qingyang, China, and meteorological data from 2011 to 2015 were collected, and a distributed lag non-linear model (DLNM) combined with a quasi-Poisson generalized additive regression model (GAM) was used to examine the exposure-response relationship and delayed effect between DTR and CVD hospital admissions. Stratified analyses by age and gender were performed and extreme DTR effects were examined. Non-linear relation between DTR and CVD hospital admissions was observed, and whether DTR lower or higher than the reference (13 °C, 50^th percentile) had adverse effect while lower DTR have slightly higher impact. Also, both extreme low and extreme high DTR had adverse effect. Besides, adults (age < 65) and males were more vulnerable to the effects of DTR compared with the old (age ≥ 65) and females, respectively. This study provides evidence that not only high DTR but also low DTR had adverse effects on CVD which should be paid attention to. Adults and males were more vulnerable among suburban farmers. The results are inconsistent with the studies from urban and indicate differences between urban and suburban residents. Multiple factors such as occupations, risk awareness, and lifestyles could have a significant influence on CVD morbidity, and further study is needed to explore more evidence.

The association between temperature and cause-specific mortality in the Klang Valley, Malaysia

This study aims to examine the relationship between daily temperature and mortality in the Klang Valley, Malaysia, over the period 2006-2015. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM) was used to estimate the association between the mean temperature and mortality categories (natural n=69,542, cardiovascular n= 15,581, and respiratory disease n=10,119). Particulate matter with an aerodynamic diameter below 10 μm (PM₁₀) and surface ozone (O₃) was adjusted as a potential confounding factor. The relative risk (RR) of natural mortality associated with extreme cold temperature (1st percentile of temperature, 25.2 °C) over lags 0-28 days was 1.26 (95% confidence interval (CI): 1.00, 1.60), compared with the minimum mortality temperature (28.2 °C). The relative risk associated with extremely hot temperature (99th percentile of temperature, 30.2 °C) over lags 0-3 days was 1.09 (95% CI: 1.02, 1.17). Heat effects were immediate whereas cold effects were delayed and lasted longer. People with respiratory diseases, the elderly, and women were the most vulnerable groups when it came to the effects of extremely high temperatures. Extreme temperatures did not dramatically change the temperature-mortality risk estimates made before and after adjustments for air pollutant (PM₁₀ and O₃) levels.

An effect of 24-hour temperature change on outpatient and emergency and inpatient visits for cardiovascular diseases in northwest China

Some studies suggested that 24-h temperature change (TC24) was one of the potential risk factors for human health. However, evidence of the short-term effect of TC24 on outpatient and emergency department (O&ED) visits and hospitalizations for cause-specific cardiovascular diseases (CVDs) is still limited. The aim of this study is to explore the short-term effects of TC24 on O&ED visits and hospitalizations for CVDs in northwest China which is an area with large temperature variation. The O&ED visits records for CVDs of 3 general hospitals and the inpatient records for CVDs of 4 general hospitals were collected from January 1, 2013, to December 31, 2016, in Jinchang City, northwest China. Meteorological and air pollution data were also obtained during the same study period from local meteorological monitoring station and environmental monitoring station, respectively. A generalized additive model (GAM) with Poisson regression was employed to analyze the effects of TC24 on O&ED visits and hospitalizations for CVDs. V-shaped relationship were found between TC24 and O&ED visits and hospitalizations for CVDs, including total CVD, hypertension, coronary heart disease (CHD) and stroke. Stratified analysis showed that men and patients over 65 years old were more susceptible to temperature changes. The estimates in non-heating months were higher than in full year. TC24 can affect the O&ED visits and hospitalizations for CVDs in this study. This study provides useful data for policy makers to better prepare local responses to the impact of changes in temperature on population health.

Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.

Short-term effects of ambient temperature and pollutants on the mortality of respiratory diseases: A time-series analysis in Hefei, China

BACKGROUND

The air pollution has become an important environmental health problem due to its adverse health effect. The objective of this study was to investigate the effects of ambient temperature and pollutants on mortality of respiratory diseases (RD) in Hefei, China, a typical inland city.

METHODS

Nonlinear exposure-response dependencies and delayed effects of urban daily mean temperature (DMT) and pollutants were evaluated by distributed lag non-linear models (DLNM). To further explore this effect, different genders and ages were also examined by stratified analysis.

RESULTS

A total of 12876 deaths from RD were collected from January 1, 2014 to December 31, 2018 in Hefei, China. There was a U-shaped correlation between DMT and RD mortality, and the RD mortality rised by 11.6% (95% CI: 2.2-22.0%) when the DMT was 35.8 °C (reference temperature is 20 °C). The results show that risk of death with short-term exposure to elevated concentrations of PM₁₀ and SO₂ was not significant. The maximum hysteresis and cumulative relative risk (RR) of RD mortality were 1.012 (95% CI: 1.003 ~ 1.021, lag 0 day) and 1.072 (95% CI: 1.014 ~1.133, lag 10 days) for each 10 μg/m³ augment in NO₂; 1.005 (95% CI: 1.001-1.009, lag 0 day) and 1.027 (95% CI: 1.004-1.051, lag 10 days) for each 10 μg/m³ augment in O_3; a negative association between CO exposure and the cumulative risk of death was observed (RR = 0.964, 95% CI: 0.935-0.993, lag 07 days). Subgroup analysis showed the effect of high temperatures, NO_2, O₃ and CO exposure was still statistically significant for the elderly and male.

CONCLUSION

The present study found that short-term exposure to high temperature, NO_2, O₃ and CO were significantly associated with the risk of RD mortality and male as well as elderly are more susceptible to these factors.

Effect modification of the association between diurnal temperature range and hospitalisations for ischaemic stroke by temperature in Hefei, China

OBJECTIVES

Diurnal temperature range (DTR) is an important indicator of global climate change. Many epidemiological studies have reported the associations between high DTR and human health. This study investigated the association between DTR and hospitalisations for ischaemic stroke in Hefei, China.

STUDY DESIGN

This is an ecological study.

METHODS

Data of daily hospital admissions for ischaemic stroke and meteorological variables from 1 January 2009 to 31 December 2017 were collected in Hefei, China. A generalised additive model combined with distributed lag non-linear model was used to quantify the effects of DTR on ischaemic stroke. The interactive effect between DTR and temperature was explored with a non-parametric bivariate response surface model.

RESULTS

High DTR was associated with hospitalisations for ischaemic stroke. The adverse effect of extremely high DTR (99th percentile [17.1 °C]) occurred after 8 days (relative risk [RR] = 1.021, 95% confidence interval [CI] = 1.002, 1.041) and the maximum effect appeared after 12 days (RR = 1.029, 95% CI = 1.011, 1.046). The overall trend of the effect of DTR on ischaemic stroke was decreasing. In addition, there was a significant interactive effect of high DTR and low temperature on ischaemic stroke.

CONCLUSIONS

This study suggests that the impact of high DTR should be considered when formulating targeted measures to prevent ischaemic stroke, especially for those days with high DTR and low mean temperature.

Effect and Relationship of Seasons on the High Risk of Ovarian Hyperstimulation Syndrome After Oocyte Retrieval in Patients With Polycystic Ovary Syndrome

OBJECTIVE

To investigate the effect of seasons on the incidence of high risk of ovarian hyperstimulation syndrome (OHSS) after in oocyte retrieval in patients with polycystic ovarian syndrome (PCOS) and to establish a nomogram to predict the risk of OHSS.

DESIGN

Single-center, retrospective study.

SETTING

University-affiliated reproductive medicine center.

PATIENTS

A total of 2,030 infertility patients with PCOS underwent the follicular phase long-acting long protocol IVF/ICSI in the reproductive medicine center from January 2017 to December 2019.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Logistic regression analysis was used to analyze the factors associated with a high risk of OHSS. We established a nomogram to predict the risk of OHSS in infertility patients with PCOS after oocyte retrieval.

RESULTS

The incidence of patients at high risk of OHSS was significantly different from season-to-season and was especially higher in the summer and winter. Multivariate logistic analysis showed that gonadotropin dosage, number of retrieved oocytes, estradiol level, average bilateral ovarian diameter on the day human chorionic gonadotropin was administered, type of infertility, and average temperature were independent risk factors for OHSS after oocyte retrieval in PCOS patients. Based on the above independent risk factors, we constructed a prediction model for OHSS risk. To evaluate the efficiency of the prediction model, we calculated the C-index (0.849), area under the receiver operating characteristic curve (0.849), and internal validation C-index (0.846). Decision curve analysis suggested that the prediction model exhibited significant net benefits.

CONCLUSIONS

The incidence of PCOS patients at high risk for OHSS after oocyte retrieval fluctuated with seasonal temperature changes, and was significantly higher in extreme climates. The prediction model had favorable predictive performance and clinical application value.