Development and evaluation of a predictive nomogram for survival in heat stroke patients: a retrospective cohort study

doi:10.5847/wjem.j.1920-8642.2022.092

World Journal of Emergency Medicine ›› 2022, Vol. 13 ›› Issue (5): 355-360.doi: 10.5847/wjem.j.1920-8642.2022.092

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Development and evaluation of a predictive nomogram for survival in heat stroke patients: a retrospective cohort study

Fei Shao¹^,², Xian Shi³, Shu-hua Huo⁴, Qing-yu Liu², Ji-xue Shi⁵, Jian Kang⁶, Ping Gong⁶, Sheng-tao Yan⁷, Guo-xing Wang⁸, Li-jie Qin⁹, Fei Wang¹⁰, Ke Feng¹¹, Feng-ying Chen¹², Yong-jie Yin¹³, Tao Ma¹⁴, Yan Li¹⁵, Yang Wu¹, Hao Cui¹, Chang-xiao Yu¹, Song Yang³, Wei Gan¹⁶, Sai Wang¹⁶, Liu-ye-zi Du¹⁶, Ming-chen Zhao¹⁷, Zi-ren Tang¹^,¹⁸(), Shen Zhao¹⁹()

¹Department of Emergency Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
²Department of Emergency Medicine, Hebei Yanda Hospital, Langfang 065201, China
³Department of Emergency Medicine, Beijing Huairou Hospital, Beijing 101400, China
⁴Department of Emergency Medicine, the Second Hospital of Hebei Medical University, Shijiazhuang 050000, China
⁵Department of Emergency Medicine, the Second Affiliated Hospital of Shandong First Medical University, Tai’an 271000, China
⁶Department of Emergency Medicine, the First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
⁷Department of Emergency Medicine, China-Japan Friendship Hospital, Beijing 100029, China
⁸Department of Emergency Medicine, Beijing Friendship Hospital, Beijing 100050, China
⁹Department of Emergency Medicine, Henan Provincial People’s Hospital, Zhengzhou 450003, China
¹⁰Department of Emergency Medicine, Beijing Tsinghua Changung Hospital, Beijing 102218, China
¹¹Department of Emergency Medicine, General Hospital of Ningxia Medical University, Yinchuan 750004, China
¹²Department of Emergency Medicine, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010050, China
¹³Department of Emergency Medicine, the Second Hospital of Jilin University, Changchun 130021, China
¹⁴Department of Emergency Medicine, the First Hospital of China Medical University, Shenyang 110001, China
¹⁵Department of Emergency Medicine, the Second Hospital of Shanxi Medical University, Taiyuan 030001, China
¹⁶Department of Big Data Research, Goodwill Hessian Health Technology Co., Ltd., Beijing 100085, China
¹⁷School of Public Health, Peking University, Beijing 100083, China
¹⁸Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing 100020, China
¹⁹Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China

Received:2022-05-29 Accepted:2022-07-26 Online:2022-08-23 Published:2022-09-01
Contact: Zi-ren Tang,Shen Zhao E-mail:tangziren1970@163.com;jzkzhaoshen@163.com

1. Supplement tables and figures.zip(2969KB)

Abstract

Abstract:

BACKGROUND: This study aimed to establish an effective nomogram to predict the survival of heat stroke (HS) based on risk factors.

METHODS: This was a retrospective, observational multicenter cohort study. We analyzed patients diagnosed with HS, who were treated between May 1 and September 30, 2018 at 15 tertiary hospitals from 11 cities in Northern China.

RESULTS: Among the 175 patients, 32 patients (18.29%) died before hospital discharge. After the univariate analysis, mechanical ventilation, initial mean arterial pressure <70 mmHg, maximum heart rate, lab results on day 1 (white blood cell count, alanine aminotransferase, creatinine), and Glasgow admission prediction score were included in multivariate analysis. Multivariate Cox regression showed that invasive ventilation, initial mean arterial pressure <70 mmHg (1 mmHg=0.133 kPa), and Glasgow admission prediction score were independent risk factors for HS. The nomogram was established for predicting 7-d and 14-d survival in the training cohort. The nomogram exhibited a concordance index (C-index) of 0.880 (95% confidence interval [95% CI] 0.831-0.930) by bootstrapping validation (B=1,000). Furthermore, the nomogram performed better when predicting 14-d survival, compared to 7-d survival. The prognostic index cut-off value was set at 2.085, according to the operating characteristic curve for overall survival prediction. The model showed good calibration ability in the internal and external validation datasets.

CONCLUSION: A novel nomogram, integrated with prognostic factors, was proposed; it was highly predictive of the survival in HS patients.

Key words: Heat stroke, Nomogram, Survival, Prognosis

Fei Shao, Xian Shi, Shu-hua Huo, Qing-yu Liu, Ji-xue Shi, Jian Kang, Ping Gong, Sheng-tao Yan, Guo-xing Wang, Li-jie Qin, Fei Wang, Ke Feng, Feng-ying Chen, Yong-jie Yin, Tao Ma, Yan Li, Yang Wu, Hao Cui, Chang-xiao Yu, Song Yang, Wei Gan, Sai Wang, Liu-ye-zi Du, Ming-chen Zhao, Zi-ren Tang, Shen Zhao. Development and evaluation of a predictive nomogram for survival in heat stroke patients: a retrospective cohort study[J]. World Journal of Emergency Medicine, 2022, 13(5): 355-360.

Figures/Tables 3

Figure 1.

Table 1.

Demographic and clinical characteristics of the study population (n=175)

Characteristics	Overall (n=175)	Survivor (n=143)	Non-survivor (n=32)	P-value
Demographic data
Sex, n (%)
Female	61 (34.86)	49 (34.27)	12 (37.50)	0.887
Male	114 (65.14)	94 (65.73)	20 (62.50)
Age, years, median (interquartile range)	64 (51-75)	64 (50-75)	63 (53-71)	0.960
Condition of hospitalization
Initial mean arterial pressure, n (%)
70-105 mmHg	117 (66.86)	103 (72.03)	14 (43.75)	<0.001
<70 mmHg	29 (16.57)	14 (9.79)	15 (46.88)
>105 mmHg	29 (16.57)	26 (18.18)	3 (9.38)
Invasive ventilation, n (%)
No	111 (63.43)	107 (74.83)	4 (12.50)	<0.001
Yes	64 (36.57)	36 (25.17)	28 (87.50)
Core temperature, °C, median (interquartile range)	40.0 (38.1-41.0)	39.7 (37.5-41.0)	40.8 (40.0-42.0)	0.002
Maximum heart rate, n (%)
60-100 beats/min	52 (29.71)	49 (34.27)	3 (9.38)	0.010
>100 beats/min	123 (70.29)	94 (65.73)	29 (90.62)
Glasgow admission prediction score, median (interquartile range)	8 (5-12)	8 (6-14)	5 (3-7)	<0.001
Hemofiltration, n (%)
No	147 (84.00)	129 (90.21)	18 (56.25)	<0.001
Yes	28 (16.00)	14 (9.79)	14 (43.75)
Intravascular hypothermia, n (%)
No	164 (93.71)	133 (93.01)	31 (96.88)	0.692
Yes	11 (6.29)	10 (6.99)	1 (3.12)
Mild hypothermia in vitro, n (%)
No	106 (60.57)	90 (62.94)	16 (50.00)	0.249
Yes	69 (39.43)	53 (37.06)	16 (50.00)
Laboratory tests on day 1
White blood cell count (WBC), n (%)
(3.5-9.5)×10⁹/L	60 (34.29)	53 (37.06)	7 (21.88)	0.153
>9.5×10⁹/L	115 (65.71)	90 (62.94)	25 (78.12)
Red blood cell count (RBC), n (%)
(3.8-5.1)×10⁹/L	129 (73.71)	103 (72.03)	26 (81.25)	0.704
<3.8×10⁹/L	38 (21.71)	33 (23.08)	5 (15.62)
>5.1×10⁹/L	8 (4.57)	7 (4.90)	1 (3.12)
Hemoglobin count (HBG), n (%)
115-150 g/L	122 (69.71)	100 (69.93)	22 (68.75)	0.211
<115 g/L	34 (19.43)	30 (20.98)	4 (12.50)
>150 g/L	19 (10.86)	13 (9.09)	6 (18.75)
Platelet count (PLT), n (%)
(125-350)×10⁹/L	92 (52.57)	80 (55.94)	12 (37.50)	0.086
<125×10⁹/L	81 (46.29)	61 (42.66)	20 (62.50)
>350×10⁹/L	2 (1.14)	2 (1.40)	0
Alanine aminotransferase (ALT), n (%)
7-40 U/L	72 (41.14)	67 (46.85)	5 (15.62)	0.002
>40 U/L	103 (58.86)	76 (53.15)	27 (84.38)
Creatine (CRE), n (%)
41.0-81.0 U/L	59 (33.71)	56 (39.16)	3 (9.38)	0.003
>81.0 U/L	116 (66.29)	87 (60.84)	29 (90.62)
Potassium, n (%)
3.5-5.3 m/L	92 (52.57)	71 (49.65)	21 (65.62)	0.053
<3.5 m/L	78 (44.57)	69 (48.25)	9 (28.12)
>5.3 m/L	5 (2.86)	3 (2.10)	2 (6.25)
Calcium, n (%)
2.11-2.52 m/L	57 (32.57)	46 (32.17)	11 (34.38)	0.440
<2.11 m/L	116 (66.29)	96 (67.13)	20 (62.50)
>2.52 m/L	2 (1.14)	1 (0.70)	1 (3.12)
Myoglobin (MYO), n (%)
0-107 μg/L	16 (9.14)	15 (10.49)	1 (3.12)	0.311
>107 μg/L	159 (90.86)	128 (89.51)	31 (96.88)
Brain natriuretic peptide (BNP), n (%)
0-100 pg/mL	39 (22.29)	33 (23.08)	6 (18.75)	0.767
>100 pg/mL	136 (77.71)	110 (76.92)	26 (81.25)
Laboratory tests on day 3
WBC, n (%)
(3.5-9.5)×10⁹/L	50 (28.57)	47 (32.87)	3 (9.38)	0.007
<3.5×10⁹/L	2 (1.14)	1 (0.70)	1 (3.12)
>9.5×10⁹/L	123 (70.29)	95 (66.43)	28 (87.50)
HBG, n (%)
(115-150)×10⁹/L	136 (77.71)	112 (78.32)	24 (75.00)	0.567
<115×10⁹/L	36 (20.57)	29 (20.28)	7 (21.88)
>150×10⁹/L	3 (1.71)	2 (1.40)	1 (3.12)
PLT, n (%)
(125-350)×10⁹/L	33 (18.86)	31 (21.68)	2 (6.25)	0.077
<125×10⁹/L	142 (81.14)	112 (78.32)	30 (93.75)
ALT, n (%)
7-40 U/L	21 (12.00)	21 (14.69)	0	0.015
>40 U/L	154 (88.00)	122 (85.31)	32 (100.00)
AST, n (%)
13-35 U/L	20 (11.43)	19 (13.29)	1 (3.12)	0.295
<13 U/L	1 (0.57)	1 (0.70)	0
>35 U/L	154 (88.00)	123 (86.01)	31 (96.88)
International normalized ratio (INR), n (%)
0.8-1.2	115 (65.71)	93 (65.03)	22 (68.75)	0.846
>1.2	60 (34.29)	50 (34.97)	10 (31.25)
CRE, n (%)
41.0-81.0 U/L	117 (66.86)	95 (66.43)	22 (68.75)	1
<41.0 U/L	4 (2.29)	4 (2.80)	0
>81.0 U/L	54 (30.86)	44 (30.77)	10 (31.25)
Potassium, n (%)
3.5-5.3 m/L	146 (83.43)	119 (83.22)	27 (84.38)	0.392
<3.5 m/L	27 (15.43)	23 (16.08)	4 (12.50)
>5.3 m/L	2 (1.14)	1 (0.70)	1 (3.12)
MYO, n (%)
0-107 μg/L	19 (10.86)	19 (13.29)	0
>107 μg/L	156 (89.14)	124 (86.71)	32 (100.00)	0.026
BNP, n (%)
0-100 pg/mL	4 (2.29)	4 (2.80)	0	1
>100 pg/mL	171 (97.71)	139 (97.20)	32 (100.00)

Table 1.

Figure 2.

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Development and evaluation of a predictive nomogram for survival in heat stroke patients: a retrospective cohort study

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